00425nas a2200157   4500000000100000000000100001000000100002008004100003100001400044700002400058700002100082700001600103700001700119245012400136490000700260       2002                            d1 aA. Badrah1 aTadeusz Czachórski1 aJoanna Domańska1 aJ. Fourneau1 aF. Quessette00aPerformance evaluation of multistage interconnection networks with blocking - discrete and continuous time Markov model0 v1400383nas a2200133   4500000000100000000000100001008004100002260000800043100001300051700002400064700001600088700002200104245012300126       2007                            d  bACM1 aA. Busic1 aTadeusz Czachórski1 aJ. Fourneau1 aKrzysztof Grochla00aLevel Crossing Ordering of Markov Chains: Proving Convergence and Bounding End to End Delays in an All Optical Network01111nas a2200157   4500000000100000000000100001008004100002260003600043100001900079700002400098700002200122700002400144245007000168300001400238520070100252       2010                            d  bIITiS PANaGliwice, Bałtycka 51 aAdam Józefiok1 aTadeusz Czachórski1 aKrzysztof Grochla1 aTadeusz Czachórski00aPerformance evaluation of multiuser interactive networking system  a223–2313 aThe article presents a work in progress aiming at performance evaluation of a large database system at an assurance company. The system includes a server with a database and a local area network with a number of terminals where the company employees run applications that introduce documents or retrieve them from the database. We discuss a model of clients activities. Measurements were collected inside the working system: the phases at each users application were identified and their duration was measured. The collected data are used to construct a synthetic model of applications activities which is then applied to predict the system bahaviour in case of the growth of the number of users.00435nas a2200145   4500000000100000000000100001008004100002260005300043100001300096700001300109700002400122700002000146700002000166245010300186       2005                            d  bWydawnictwa Komunikacji i ŁącznościaWarszawa1 aP. Bazan1 aJ. Krzak1 aTadeusz Czachórski1 aAndrzej Grzywak1 aPiotr Pikiewicz00aNowe Technologie w Komputerowych Systemach Zarządzania. Internet w Społeczeństwie Informacyjnym00343nas a2200121   4500000000100000000000100001008004100002260004600043100001600089700002400105700002200129245007000151       2007                            d  c6bWydawnictwo Komunikacji i Łączności1 aA. Brachman1 aTadeusz Czachórski1 aKrzysztof Grochla00aAnaliza wydajności protokołu TCP-NCR w sieciach bezprzewodowych00437nas a2200169   4500000000100000000000100001008004100002260001800043100001400061700001400075700002400089700002100113700002000134700002500154700002400179245006400203       2004                            d  bWNTaWarszawa1 aB. Bylina1 aJ. Bylina1 aTadeusz Czachórski1 aJoanna Domańska1 aStefan Węgrzyn1 aBolesław Pochopień1 aTadeusz Czachórski00aWspółczesne problemy sieci komputerowych Nowe technologie00458nas a2200157   4500000000100000000000100001000000100002008004100003100001400044700001400058700002100072700002400093245016200117300001400279490000700293       2004                            d1 aB. Bylina1 aJ. Bylina1 aJoanna Domańska1 aTadeusz Czachórski00aThe use of vectorized and parallelized solutions to Markovian models in performance evaluation of communication networks: a case of leaky buckets with tokens  a153–1700 v1600306nas a2200109   4500000000100000000000100001008004100002260006200043100002400105700002000129245004700149       2003                            d  bWyższa Szkoła Biznesu i OrganizacjiaDąbrowa Górnicza1 aTadeusz Czachórski1 aAndrzej Grzywak00aInternet w społeczeństwie informatycznym00463nas a2200145   4500000000100000000000100001008004100002260008600043100002400129700001700153700002000170700001500190245010200205300001000307       2013                            d  c8bPracownia Komputerowa Jacka Skalmierskiegoa44-100 Gliwice, ul. Pszczyńska 441 aTadeusz Czachórski1 aV. Mityushev1 aŁ.A. Stępień1 aA. Budziak00aQueueing models: transient state analysis applied to performance evaluation of computer networks.  a5–601996nas a2200133   4500000000100000000000100001008004100002260005000043100002400093700001700117700001700134245005500151520165600206       2015                            d  bSpringer International Publishing Switzerland1 aTadeusz Czachórski1 aV. Mityushev1 aM. Ruzhansky00aAnalytic Methods in Interdisciplinary Applications3 aQueueing theory is a useful tool in design of computer networks and their performance evaluation. The literature concerning this subject is abundant. However, it is in general limited to the analysis of steady states. It means that flows of customers considered in models are constant and obtained solutions do not depend on time. It is in glaring contrast with the flows observed in real networks where the perpetual changes of traffic intensities are due to the nature of users, sending variable quantities of data, cf. multimedia traffic, and also due to the performance of traffic control algorithms which are trying to avoid congestion in networks, e.g. the algorithm of congestion window used in TCP protocol which is adapting the rate of the sent traffic to the observed losses or transmission delays. We discuss here the means used to analyse transient states in queueing models. In computer applications a mathematical model is useful only when it furnishes quantitative results. Therefore practical ussues related to numerical side of models are of importance and are here discussed. We present three approaches - Markov models solved numerically, fluid flow approximation and diffusion approximation. A particular importance is given to the latter as the author has here over 20year experience in development and application of this method. He is also convinced of the qualities of this approach - its flexibility to treat various variants of queueing models. Traffic intensity observed in computer networks have a complex stochastic nature that influences the network performances. We discuss also this side of implemented queueing models.00461nas a2200109   4500000000100000000000100001008004100002260017700043100002400220245009500244300001200339       2013                            d  c10bV.A.Trapeznikov Institute of Control Sciences Russian Academy of Sciences; Institute of Information and Communication technologies Bulgarian Academy of SciencesaMoscow1 aTadeusz Czachórski00aModelling transient states in queueing models of computer networks: a few practical issues  a27–2800211nas a2200085   4500000000100000000000100001008004100002100002400043245005800067       2013                            d1 aTadeusz Czachórski00aModelling and controlling dynamics of Internet flows.00239nas a2200085   4500000000100000000000100001008004100002100002400043245008600067       2013                            d1 aTadeusz Czachórski00aTransient queueing models applied to performance evaluation of computer networks.00289nas a2200109   4500000000100000000000100001008004100002100002400043245009200067300001300159490000700172       2003                            d1 aTadeusz Czachórski00aAnalityczne modele kolejkowe w ocenie efektywności pracy systemów i sieci kolejkowych  a90–1110 v1600343nas a2200133   4500000000100000000000100001008004100002100002400043700002100067700002400088700001600112245006700128300001400195       2004                            d1 aTadeusz Czachórski1 aJoanna Domańska1 aTadeusz Czachórski1 aN. Pekergin00aMarkovian models for long-range dependent traffic, new results  a213–22800333nas a2200133   4500000000100000000000100001000000100002008004100003100002400044700002100068245008900089300001400178490000700192       2002                            d1 aTadeusz Czachórski1 aJoanna Domańska00aWpływ samopodobnej natury ruchu na długości kolejek w przełącznikach sieciowych  a201–2120 v2300298nas a2200133   4500000000100000000000100001000000100002008004100003100002400044700002100068245005400089300001400143490000700157       2001                            d1 aTadeusz Czachórski1 aJoanna Domańska00aMarkovian models for long-range dependent traffic  a297–3080 v1300449nas a2200145   4500000000100000000000100001008004100002260005300043100002400096700002100120700001900141700002000160700002000180245010300200       2005                            d  bWydawnictwa Komunikacji i ŁącznościaWarszawa1 aTadeusz Czachórski1 aJoanna Domańska1 aAdam Domański1 aAndrzej Grzywak1 aPiotr Pikiewicz00aNowe Technologie w Komputerowych Systemach Zarządzania. Internet w Społeczeństwie Informacyjnym00441nas a2200157   4500000000100000000000100001008004100002260005300043100002400096700002100120700001900141700002000160700002500180700002400205245005400229       2005                            d  bWydawnictwa Komunikacji i ŁącznościaWarszawa1 aTadeusz Czachórski1 aJoanna Domańska1 aAdam Domański1 aStefan Węgrzyn1 aBolesław Pochopień1 aTadeusz Czachórski00aWysokowydajne sieci komputerowe. Nowe Technologie00359nas a2200121   4500000000100000000000100001008004100002260002600043100002400069700002100093700002200114245010100136       2006                            d  bPolitecnico de Torino1 aTadeusz Czachórski1 aJoanna Domańska1 aKrzysztof Grochla00aDynamics of TCP/IP flows in presence of various AQM algorithms, a fluid flow approximation model00338nas a2200121   4500000000100000000000100001008004100002260004200043100002400085700002100109700002200130245006400152       2006                            d  cVIbTechnical University of Catalonia1 aTadeusz Czachórski1 aJoanna Domańska1 aKrzysztof Grochla00aTCP/IP dynamics in wireless environment, a fluid-flow model00636nas a2200133   4500000000100000000000100001008004100002100002400043700002100067700002100088245006900109490000700178520031700185       2001                            d1 aTadeusz Czachórski1 aJoanna Domańska1 aArkadiusz Sochan00aSamopodobny charakter natężenia ruchu w sieciach komputerowych0 v223 aArtykuł przedstawia analizę natężenia ruchu pakietów w sieci Ethernet oraz ruchu ramek MPEG-2 w sieci ATM pod kątem występowania cechy zwanej samopodobieństwem. Zamieszczono krótką charakterystykę procesów samopodobnych oraz wnioski wypływające z samopodobnej natury ruchu w sieciach komputerowych.00324nas a2200133   4500000000100000000000100001008004100002260001800043100002400061700001900085700002100104700002000125245004500145       2004                            d  bWNTaWarszawa1 aTadeusz Czachórski1 aAdam Domański1 aJoanna Domańska1 aAndrzej Grzywak00aInternet w spoleczenstwie informatycznym00416nas a2200157   4500000000100000000000100001008004100002260001800043100002400061700001900085700002100104700002000125700002500145700002400170245006400194       2004                            d  bWNTaWarszawa1 aTadeusz Czachórski1 aAdam Domański1 aJoanna Domańska1 aStefan Węgrzyn1 aBolesław Pochopień1 aTadeusz Czachórski00aWspółczesne problemy sieci komputerowych Nowe technologie00314nas a2200121   4500000000100000000000100001008004100002100002400043700001600067700002000083700001700103245007200120       2002                            d1 aTadeusz Czachórski1 aJ. Fourneau1 aSławomir Nowak1 aF. Quessette00aPerformance of a mixed deflection and convergence routing algorithm00327nas a2200121   4500000000100000000000100001008004100002100002400043700002200067700001900089700001600108245008100124       2011                            d1 aTadeusz Czachórski1 aKrzysztof Grochla1 aAdam Józefiok1 aTomasz Nycz00aSimulation, Markov Chain and Diffusion Approximation Models – a Case Study00954nas a2200181   4500000000100000000000100001000000100002008004100003100002400044700002200068700001900090700001600109245009500125300001100220490000700231520052000238022001400758       2011                            d1 aTadeusz Czachórski1 aKrzysztof Grochla1 aAdam Józefiok1 aTomasz Nycz00aPorównanie metod analizy efektywności na przykładzie serwera aplikacji w sieci lokalnej  a7–200 v323 aW artykule przedstawiono model kolejkowy służący do oceny funkcjonowania dużego systemu sieciowego, w skład którego wchodzi rozbudowany system bazodanowy. Opisywany system jest systemem rzeczywistym. Zebrane wyniki pracy systemu posłużyły do budowy modelu działania aplikacji interakcyjnych, na podstawie łańcuchów Markova, aproksymacji dyfuzyjnej i symulacji zdarzeń dyskretnych. Porównanie ich z rzeczywistymi wynikami umożliwiło sprawdzenie przdatności użytych metod w rzeczywistych warunkach.  a1731-226401415nas a2200205   4500000000100000000000100001008004100002260001300043100002400056700002200080700001900102700001600121700002000137700001700157700001700174700002200191245010700213300001400320520087500334       2012                            d  bSpringer1 aTadeusz Czachórski1 aKrzysztof Grochla1 aAdam Józefiok1 aTomasz Nycz1 aFerhan Pekergin1 aErol Gelenbe1 aRicardo Lent1 aGeorgia Sakellari00aPerformance Evaluation of a Multiuser Interactive Networking System: A Comparison of Modelling Methods  a215–2223 aThis article presents a queueing model for performance evaluation of a large database system at an assurance company. The system includes a server with a database and a local area network with a number of terminals where the company employees run applications that introduce documents or retrieve them from the database. We discuss a model of clients activities. Measurements were collected inside the working system: the phases at each users application performance were identified and their duration was measured. The collected data are used to construct a synthetic model of applications activities which is then applied to predict the system behaviour in case of the growth of the number of users. We apply simulation, Markov and diffusion models-their comparison, based on real data, may better verify the utility of particular methods than usual academic examples.01580nas a2200169   4500000000100000000000100001008004100002260002100043100002400064700002200088700002000110700002000130700002100150245005200171300001400223520117300237       2007                            d  c5bSpringeVerlag1 aTadeusz Czachórski1 aKrzysztof Grochla1 aFerhan Pekergin1 aJ. Garcia-Vidal1 al. Cerda-Alabern00aStability and Dynamics of TCP-NCR(DCR) Protocol  a241–2543 aThe fluid-flow approximation models investigate with much success the dynamics and stability of TCP/RED connections. Their main assumption is that the fluctuations of variables characterizing the behaviour of the connections are relatively small, that enables the linearization of model and the use of traditional control analysis tools to obtain such measures as Bode gain, phase margins, tracking error or delay margin. In this article, preserving linear fluid-flow model, we propose its extension to the case when a network is composed of wired and wireless part. We consider a variant of TCP algorithm (TCP-DCR or its new version TCP-NCR) and fluid-flow differential equations representing the size of congestion window, mean queue at the bottleneck router and loss probability at a RED queue are supplemented with terms representing constant loss probability due to transmission in wireless part and probability that a fraction of these errors is recovered by a link level mechanism. The decrease of congestion window due to TCP mechanism is delayed to allow the link protocol to deal with the errors. The model considers the presence of uncontrollable UDP flows.00353nas a2200109   4500000000100000000000100001008004100002100002400043700002200067700002000089245013400109       2008                            d1 aTadeusz Czachórski1 aKrzysztof Grochla1 aFerhan Pekergin00aUn modele d’approximation de diffusion pour la distribution du temps d’acheminement des paquets dans les réseaux de senseurs00311nas a2200109   4500000000100000000000100001008004100002100002400043700002200067700002000089245009200109       2008                            d1 aTadeusz Czachórski1 aKrzysztof Grochla1 aFerhan Pekergin00aEstimation of packet transfer time at sensor networks, diffusion approximation approach00312nas a2200121   4500000000100000000000100001008004100002260000600043100002400049700002200073700002000095245007500115       2008                            d  c21 aTadeusz Czachórski1 aKrzysztof Grochla1 aFerhan Pekergin00aTCP performance for a wireless traffic, a diffusion approxiation model00321nas a2200121   4500000000100000000000100001008004100002260001700043100002400060700002200084700002000106245007300126       2007                            d  c9bIITiS PAN1 aTadeusz Czachórski1 aKrzysztof Grochla1 aFerhan Pekergin00aFluid-flow Approximation Model of TCP-NCR in wired-wireless networks00748nas a2200157   4500000000100000000000100001000000100002008004100003100002400044700002200068700002000090245003400110300001400144490000700158520042500165       2006                            d1 aTadeusz Czachórski1 aKrzysztof Grochla1 aFerhan Pekergin00aA model of TCP flows dynamics  a279–2920 v183 aThe fluid flow approximation models investigate with much success the dynamics and stability of TCP/RED connections. Their main assumption is that the fluctuations of variables characterizing the behaviour of the connections are relatively small, that enables the linearization of model and the use of traditional control analysis tools to obtain such measures as Bode gain, phase margins, tracking error or delay margin00354nas a2200121   4500000000100000000000100001008004100002260000600043100002400049700002200073700002000095245011700115       2006                            d  c91 aTadeusz Czachórski1 aKrzysztof Grochla1 aFerhan Pekergin00aSome contributions to the modelling the dynamics of (TCP,UDP)/RED flows over reliable and unreliable connections01771nas a2200169   4500000000100000000000100001008004100002260011200043100002400155700002200179700001200201700002000213700002400233245007800257300001400335520125200349       2010                            d  c1bInstitute of Theoretical and Applied Informatics of the Polish Academy of SciencesaGliwice, Bałtycka 51 aTadeusz Czachórski1 aKrzysztof Grochla1 aT. Nycz1 aFerhan Pekergin1 aTadeusz Czachórski00aModeling the IEEE 802.11 Networks MAC Layer Using Diffusion Approximation  a429–4423 aAbstract: The article presents an analytical model of wireless networks using the IEEE 802.11 protocol to access the transport medium. The model allows to determine such key factors of the quality of service as transmission delays and losses. The model is based on diffusion approximation approach which was proposed three decades ago to model wired networks. We show that it can be adapted to take into consideration the input streams with general interarrival time distributions and servers with general service time distributions. The diffusion approximation has been chosen because of fairly general assumptions of models based on it, hard to be represented in Markov models. A queueing network model can have an arbitrary topology, the intensity of transmitted flows can be represented by non-Poisson (even self-similar) streams, the service times at nodes can be defined by general distributions. These assumptions are important: because of the CSMA/CA algorithm, the overall times needed to sent a packet are far from being exponentially distributed and therefore the flows between nodes are non-Poisson. Diffusion approximation allows us also to analyse the of transient behaviour of a network when traffic intensity is changing with time.00918nas a2200181   4500000000100000000000100001008004100002260001800043100002400061700002200085700001200107700002000119700002400139700001800163245003700181300001400218520050400232       2012                            d  c12bIITiS PAN1 aTadeusz Czachórski1 aKrzysztof Grochla1 aT. Nycz1 aFerhan Pekergin1 aTadeusz Czachórski1 aMateusz Nowak00aDuration of boot-up storm period  a145–1503 aThe simultaneous boot of multiple virtual machines or networking devices imposes heavy load on the networking infrastructure. In large network of virtual machines the coordination of the reboots and the device registration is required. In the paper we present a simple analytical model to compute the distribution of boot-up time. The model is verified by comparison to a simulation model, and may be used to check the influence of several parameters on the overall boot-up time during a boot storm.01701nas a2200181   4500000000100000000000100001000000100002008004100003100002400044700002200068700001200090700002000102245012000122300001400242490000700256520124200263022001401505       2010                            d1 aTadeusz Czachórski1 aKrzysztof Grochla1 aT. Nycz1 aFerhan Pekergin00aA diffusion approximation model for wireless networks based on IEEE 802.11 standard, Computer Communication Journal  aS86–S920 v333 aThe article presents an analytical model of wireless networks using the IEEE 802.11 protocol to access the transport medium. The model allows to determine such key factors of the quality of service as transmission delays and losses. The model is based on diffusion approximation approach which was proposed three decades ago to model wired networks. We show that it can be adapted to take into consideration the input streams with general interarrival time distributions and servers with general service time distributions. The diffusion approximation has been chosen because of fairly general assumptions of models based on it, hard to be represented in Markov models. A queueing network model can have an arbitrary topology, the intensity of transmitted flows can be represented by non-Poisson (even self-similar) streams, the service times at nodes can be defined by general distributions. These assumptions are important: because of the CSMA/CA algorithm, the overall times needed to sent a packet are far from being exponentially distributed and therefore the flows between nodes are non-Poisson. Diffusion approximation allows us also to analyse the of transient behaviour of a network when traffic intensity is changing with time.  a0140-366400418nas a2200157   4500000000100000000000100001008004100002260004000043100002400083700002400107700001800131700001600149700001400165700001400179245006700193       2002                            d  bIdea Group PublishingaHershey, USA1 aTadeusz Czachórski1 aStanisław Jędruś1 aM. Zakrzewicz1 aJ. Gozdecki1 aP. Pacyna1 aS. Rahman00aMultimedia Networking: Technology, Management and Applications00350nas a2200157   4500000000100000000000100001000000100002008004100003100002400044700001600068700002000084245005500104300001200159490000700171022001400178       2002                            d1 aTadeusz Czachórski1 aJ. Fourneau1 aSławomir Nowak00aSymulacyjne Badanie routingu w sieciach optycznych  a45–580 v2A  a0208-728601084nas a2200157   4500000000100000000000100001008004100002260005000043100002400093700001200117700001200129700001800141245009500159300001200254520066000266       2014                            d  bSpringer International Publishing Switzerland1 aTadeusz Czachórski1 aM. Nycz1 aT. Nycz1 aV. Vishnevsky00aModelling Transient States in Queueing Models of Computer Networks: A Few Practical Issues  a58–723 aThe article summarises author`s experience in two problems related to the use of queueing models in performance evaluation of computer networks: modelling transient states of queues and computations for queueing network models having large number of nodes. Both issues are not well represented in classical queuing theory, yet important to applications, because the observed traffic is time dependant and network topologies that should be considered become larger and larger. The article discusses two approaches: diffusion approximation and fluid-flow approximation that can cope with much larger models that are attainable with the use of Markov chains.00240nas a2200097   4500000000100000000000100001008004100002100002400043700001600067245005900083       2002                            d1 aTadeusz Czachórski1 aPiotr Pecka00aInternet and real-time performance: a web server model00323nas a2200109   4500000000100000000000100001008004100002100002400043700002000067700001900087245010700106       2004                            d1 aTadeusz Czachórski1 aFerhan Pekergin1 aD.D. Kouvatsos00aDiffusion Approximation as a modelling tool in congestion control and performance evaluation, tutorial00409nas a2200145   4500000000100000000000100001008004100002260005300043100002400096700002000120700002000140700002500160700002400185245005400209       2005                            d  bWydawnictwa Komunikacji i ŁącznościaWarszawa1 aTadeusz Czachórski1 aFerhan Pekergin1 aStefan Węgrzyn1 aBolesław Pochopień1 aTadeusz Czachórski00aWysokowydajne sieci komputerowe, Nowe Technologie01253nas a2200145   4500000000100000000000100001008004100002100002400043700002000067245017500087300001400262490000900276520080800285022001401093       2011                            d1 aTadeusz Czachórski1 aFerhan Pekergin00aDiffusion Approximation as a Modelling Tool, chapter in: Network Performance Engineering, A Handbook on Convergent Multi-Service Networks and Next Generation Internet, St  a447–4760 v52333 aDiffusion theory is already a vast domain of knowledge. This tutorial lecture does not cover all results: it presents in a coherent way an approach we have adopted and used in analysis of a series of models concerning evoluation of some traffic control mechanisms in computer, especially ATM, networks. Diffusion approximation is presented from engineer`s point of view, stressing its utility and commenting numerical problems of its implementation. Diffusion approximation is a method to model the behavior of a single queueing station or a network of stations. It allows one to include in the model general sevice times, general (also correlated)input streams and to investigate transient states, which, in presence of bursty streams (e.g. of multimedia transfers) in modern networks, are of interest.  a0302-974300290nas a2200121   4500000000100000000000100001000000100002008004100003100002400044700002000068245006600088300001400154       2005                            d1 aTadeusz Czachórski1 aFerhan Pekergin00aA diffusion approximation model of an electronic-optical node  a187–19900326nas a2200133   4500000000100000000000100001000000100002008004100003100002400044700002000068245008400088300001300172490000700185       2005                            d1 aTadeusz Czachórski1 aFerhan Pekergin00aA novel diffusion process with jumps to study an electronic-optical edge router  a87–1000 v1700272nas a2200097   4500000000100000000000100001008004100002100002400043700002000067245008700087       2003                            d1 aTadeusz Czachórski1 aFerhan Pekergin00aDiffusion approximation: modelling transient flows of multiclass queueing networks00236nas a2200097   4500000000100000000000100001008004100002100002400043700002000067245005100087       2002                            d1 aTadeusz Czachórski1 aFerhan Pekergin00aA diffusion approximation model of Web servers00259nas a2200097   4500000000100000000000100001008004100002100002400043700002000067245007400087       2001                            d1 aTadeusz Czachórski1 aFerhan Pekergin00aModelling New Congestion Control Mechanisms TCP/IP Internet Protocols00287nas a2200109   4500000000100000000000100001008004100002100002400043700002000067700001300087245007700100       2005                            d1 aTadeusz Czachórski1 aFerhan Pekergin1 aB. Szady00aForming optical packets, a diffusion approximation and simulation models00271nas a2200109   4500000000100000000000100001008004100002100002400043700002000067700001300087245006100100       2005                            d1 aTadeusz Czachórski1 aFerhan Pekergin1 aB. Szady00aForming optical packets, a diffusion approximation model00975nas a2200169   4500000000100000000000100001008004100002260005000043100002400093700001200117700001200129700002000141700002400161245008900185300001400274520051700288       2014                            d  bSpringer International Publishing Switzerland1 aTadeusz Czachórski1 aT. Nycz1 aM. Nycz1 aFerhan Pekergin1 aTadeusz Czachórski00aTraffic Engineering: Erlang and Engset Models Revisited with Diffusion Approximation  a249–2563 aClassical Erlang and Engset formulae determining the availability of channels, loss probability, and characteristics of overflow traffic are still use in telecommunications. Moreover, they are also interesting for traffic management in mobile networks and in Internet. They are based on the assumption of Poisson flows and exponentially distributed time of connections. By means of diffusion approximation queuing models, we extend these results to the case of general distributions and transient state analysis.00368nas a2200145   4500000000100000000000100001008004100002100001300043700001600056700002400072700001600096700001700112700001200129245008100141       2002                            d1 aD. Barth1 aP. Berthome1 aTadeusz Czachórski1 aJ. Fourneau1 aCh. Laforest1 aS. Vial00aA Mixed Deflection and Convergence Routing Algorithm: Design and Performance00325nas a2200133   4500000000100000000000100001000000100002008004100003100002100044700002400065245008100089300001400170490000700184       2003                            d1 aJoanna Domańska1 aTadeusz Czachórski00aWpływ samopodobnej natury ruchu na zachowanie mechanizmu cieknącego wiadra  a199–2120 v2400309nas a2200133   4500000000100000000000100001000000100002008004100003100002100044700002400065245006700089300001200156490000700168       2003                            d1 aJoanna Domańska1 aTadeusz Czachórski00aModel formowania pakietów w węźle brzegowym sieci optycznej  a51–610 v2400734nas a2200157   4500000000100000000000100001008004100002260003200043100002100075700001900096700002400115700001600139245005700155300001400212520035000226       2011                            d  bSpringeraBerlin Heidelberg1 aJoanna Domańska1 aAdam Domański1 aTadeusz Czachórski1 aS. Balandin00aInternet Traffic Source Vased on Hidden Markov Model  a395–4043 aThis article shows how to use Hidden Markov Models to generate self-similar traffic. The well-known Bellcore traces are used as a training sequence to learn HMM model parameters. Performance of trained model are tested on the remaining portions of the sequence. Then we can use the HMM trained with the Bellcore data as the traffic source model.01216nas a2200157   4500000000100000000000100001008004100002260005000043100002100093700001900114700002400133700002400157245006900181300001400250520079400264       2014                            d  bSpringer International Publishing Switzerland1 aJoanna Domańska1 aAdam Domański1 aTadeusz Czachórski1 aTadeusz Czachórski00aA few investigations of long-range dependence in network traffic  a137–1443 aThe paper presents measurements and analysis of a LAN long-range dependence traffic collected in IITiS PAN (The Institute of Theoretical and Applied Informatics of the Polish Academy of Sciences). Several methods of Hurst parameter estimation were used, the results obtained by the methods differ substantially. The analysis was made for the whole traffic and traffics generated by particular types of protocols. We seek for a dependence of Hurst parameter on a protocol type. Then, a MMPP(Markov-Modulated Poisson Process) model was applied to mimic the traces. It allows us to consider Markovian queueing models with long-range dependent and self-similar traffic, an important factor as we dispose an efficient software tool to solve numerically very large continuous-time Markov chains.00421nas a2200145   4500000000100000000000100001008004100002260005000043100002100093700001900114700002400133700001400157245009200171300001200263       2015                            d  bSpringer International Publishing Switzerland1 aJoanna Domańska1 aAdam Domański1 aTadeusz Czachórski1 aPiotr Gaj00aEstimating the intensity of long-range dependence in real and synthetic traffic traces.  a11–2200941nas a2200193   4500000000100000000000100001008004100002260001600043100002100059700001900080700002400099700002000123700002300143700002300166700001700189245007900206300001200285520045000297       2013                            d  c1bSpringer1 aJoanna Domańska1 aAdam Domański1 aTadeusz Czachórski1 aAlexander Dudin1 aValentina Klimenok1 aGennadiy Tsarenkov1 aSergey Dudin00aFluid Flow Analysis of RED Algorithm with Modified Weighted Moving Average  a50–583 aWe study with the use of fluid flow approximation the impact of a modified weighted moving average on the performance of RED mechanism. A model of TCP/UDP connection with RED implemented in an intermediate IP router is used, the weighted moving average is determined on the basis of a difference (recursive) equation. The fluid flow approximation technique is applied to model the interactions between the set of TCP/UDP flows and RED mechanism.00398nas a2200145   4500000000100000000000100001008004100002260005100043100002100094700001900115700002400134700002000158700001700178245005700195       2007                            d  bWyższa Szkoła Biznesu w Dąbrowie Górniczej1 aJoanna Domańska1 aAdam Domański1 aTadeusz Czachórski1 aAndrzej Grzywak1 aJerzy Klamka00aPodstawy Budowy i Oprogramowania Sieci Typu Internet00910nas a2200181   4500000000100000000000100001008004100002260005000043100002100093700001900114700002400133700002200157700001400179700001300193245007800206300001200284520043200296       2014                            d  bSpringer International Publishing Switzerland1 aJoanna Domańska1 aAdam Domański1 aTadeusz Czachórski1 aAndrzej Kwiecień1 aPiotr Gaj1 aP. Stera00aModeling Packet Traffic with the Use of Superpositions of Two-State MMPPs  a24–363 aThe aim of this paper is to use the superposition of two-state Markov Modulated Poisson Processes to replicate the statistical nature of internet traffic over several time scales. This paper characterizes of network traffic using Bellcore data and LAN traces collected in IITiS PAN. The fitting procedure for matching second-order self-similar properties of real data traces to that of two-state MMPP`s has also been described.00622nas a2200133   4500000000100000000000100001008004100002100002100043700001900064700002400083245003200107300001200139520033700151       2012                            d1 aJoanna Domańska1 aAdam Domański1 aTadeusz Czachórski00aA HMM network traffic model  a17–203 aThe article proposes a description of Internet traffic based on Hidden Markov Model. The model refers to packet level traffic and is validated with the use of real traffic collected in our laboratory. A part of the gathered traces is used as a training sequence to learn HMM model parameters an the rest serves as testing sequences.00327nas a2200145   4500000000100000000000100001000000100002008004100003260000700044100002100051700001900072700002400091245006000115490000600175       2008                            d  c031 aJoanna Domańska1 aAdam Domański1 aTadeusz Czachórski00aImplementation of modified AQM mechanisms in IP routers0 v400336nas a2200145   4500000000100000000000100001008004100002100002100043700001900064700002400083245004000107300001200147490000900159022002200168       2007                            d1 aJoanna Domańska1 aAdam Domański1 aTadeusz Czachórski00aThe Drop-From-Front Strategy in AQM  a61–720 v4712  a978-3-540-74832-800306nas a2200121   4500000000100000000000100001008004100002100002100043700001900064700002400083245006300107300001400170       2005                            d1 aJoanna Domańska1 aAdam Domański1 aTadeusz Czachórski00aThe influence of traffic self-similarity on QoS Mechanisms  a300–30300353nas a2200145   4500000000100000000000100001000000100002008004100003100002100044700001900065700002400084245007800108300001400186490000700200       2004                            d1 aJoanna Domańska1 aAdam Domański1 aTadeusz Czachórski00aSelf-similarity of network traffic and the performances of QoS mechanisms  a337–3490 v1600902nas a2200181   4500000000100000000000100001000000100002008004100003100002100044700001900065700002400084700001700108245006700125300001400192490000700206520049300213022001400706       2014                            d1 aJoanna Domańska1 aAdam Domański1 aTadeusz Czachórski1 aJerzy Klamka00aFlluid flow approximation of time-limited TCP/UDP/XCP streams.  a217–2250 v623 aThis article presents the use of fluid flow approximation to model interactions between a set of TCP, UDP and XCP flows in the enveronment of IP routers using AQM (Active Queue Management) algorithms to control traffic congestion. In contrast to other works, independent UDP and TCP streams are considered and the model allows to start and end data transmissions in TCP, UDP and XCP strams at any time moment. It incorporates several Active Queue Management mechanisms: RED, NLRED, CHOKe.  a0239-752800498nas a2200193   4500000000100000000000100001008004100002260004300043100002100086700002200107700002400129700001400153700002000167700002100187700002400208700002500232245004100257490000600298       2006                            d  bWydawnictwo Komunikacji i Łączności1 aJoanna Domańska1 aKrzysztof Grochla1 aTadeusz Czachórski1 aT. Atmaca1 aStefan Węgrzyn1 aLech Znamirowski1 aTadeusz Czachórski1 aStanisław Kozielski00aNowe Technologie Sieci Komputerowych0 v100293nas a2200133   4500000000100000000000100001008004100002100002100043700001600064700001400080700002400094245002700118300001400145       2003                            d1 aJoanna Domańska1 aI. Kotuliak1 aT. Atmaca1 aTadeusz Czachórski00aOptical packet filling  a419–42900918nas a2200181   4500000000100000000000100001008004100002260003500043100001900078700002100097700002400118700002200142700001400164700001300178245011300191300001400304520041800318       2013                            d  c6bSpringeraBerlin Heidelberg1 aAdam Domański1 aJoanna Domańska1 aTadeusz Czachórski1 aAndrzej Kwiecień1 aPiotr Gaj1 aP. Stera00aComparison of CHOKe and gCHOKe active queues managemant algirithms with the use of fluid flow approximation.  a363–3713 aIn the article we examine a model of TCP connection with Active Queue Managemanet in an intermediate IP router. We model a system where CHOKe or gCHOKe are the AQM policy. We use the fluid flow approximation technique to model the interactions between the set of TCP/UDP flows and two variants of the CHOKe algoithms. The obtained results confirm the superiority of these algorithms over a standard RED algorithm.00787nas a2200193   4500000000100000000000100001008004100002260003200043100001900075700002100094700002400115700002200139700001400161700001300175245002200188490000800210520035300218020002200571       2012                            d  bSpringeraBerlin Heidelberg1 aAdam Domański1 aJoanna Domańska1 aTadeusz Czachórski1 aAndrzej Kwiecień1 aPiotr Gaj1 aP. Stera00aComputer Networks0 v2913 aIn the article we study a model of TCP/UDP connection with Active Queue Management in an intermediate IP router. We use the fluid flow approximation technique to model the interactions between the set of TCP/UDP flows and AQM. We model a system where RED or NLRED are the AQM policy.The obtained results confirm the advantage of our NLRED algorithm  a978-3-642-31216-800819nas a2200169   4500000000100000000000100001008004100002260008800043100001900131700002100150700002400171700002000195700001800215245008300233520031100316020002200627       2013                            d  bAcademy od Business in Dabrowa Gorniczaa41-300 Dąbrowa Górnicza Cieplaka Str. 1c1 aAdam Domański1 aJoanna Domańska1 aTadeusz Czachórski1 aPiotr Pikiewicz1 aM. Rostański00aInternet in the Information Society Computer Systems Architecture and Security3 aIn the article we study a model of the TCP connection with Active Queue Management in the intermediate bottleneck IP router. The fluid flow approximation technique is used to model the interactions between the set of TCP flows and AQM algorithms. The numerical part of the model is run in CUDA environment.  a978-83-62897-40-700445nas a2200169   4500000000100000000000100001008004100002260004300043100001900086700002100105700002400126700002500150700002200175700002000197700001700217245004100234       2006                            d  bWydawnictwa Komunikacji i Łączności1 aAdam Domański1 aJoanna Domańska1 aTadeusz Czachórski1 aBolesław Pochopień1 aAndrzej Kwiecień1 aAndrzej Grzywak1 aJerzy Klamka00aNowe Technologie Sieci Komputerowych00432nas a2200169   4500000000100000000000100001008004100002260004300043100001900086700002100105700002400126700002000150700002100170700002400191245004100215490000600256       2006                            d  bWydawnictwa Komunikacji i Łączności1 aAdam Domański1 aJoanna Domańska1 aTadeusz Czachórski1 aStefan Węgrzyn1 aLech Znamirowski1 aTadeusz Czachórski00aNowe Technologie Sieci Komputerowych0 v100721nas a2200169   4500000000100000000000100001000000100002008004100003100001900044700002100063700002400084245008800108300001300196490000700209520032100216022001400537       2013                            d1 aAdam Domański1 aJoanna Domańska1 aTadeusz Czachórski00aGCU-Accelerated fluid flow approximation of the Active Queues Management algorithms  a93–1040 v253 aIn the article we study a model of TCP connection with Active Queue Management in an intermediate IP router. We use the fluid flow approximation technique to model the interactions between the set of TCP flows and AQM algorithms. Computations for fluid flow approximation model are performed in the CUDA environment.  a1896-533400286nas a2200109   4500000000100000000000100001008004100002100001900043700002100062700002400083245006900107       2008                            d1 aAdam Domański1 aJoanna Domańska1 aTadeusz Czachórski00aThe impact of self-similarity on traffic shaping in wireless LAN00307nas a2200121   4500000000100000000000100001008004100002260006000043100001900103700002100122700002400143245001800167       2005                            d  bOficyna Wydawnicza Politechniki WrocławskiejaWrocław1 aAdam Domański1 aJoanna Domańska1 aTadeusz Czachórski00aInternet 200500287nas a2200121   4500000000100000000000100001008004100002100001900043700002100062700002400083700001800107245004000125       2008                            d1 aAdam Domański1 aJoanna Domańska1 aTadeusz Czachórski1 aF. Kłębczyk00aSome aspects of QoS in wireless LAN00324nas a2200133   4500000000100000000000100001008004100002260004300043100001900086700002100105700002400126700001800150245002200168       2008                            d  bWydawnictwa Komunikacji i Łączności1 aAdam Domański1 aJoanna Domańska1 aTadeusz Czachórski1 aF. Kłębczyk00aSieci Komputerowe00354nas a2200133   4500000000100000000000100001008004100002100001900043700002100062700002000083700002400103245007000127022002300197       2010                            d1 aAdam Domański1 aJoanna Domańska1 aSławomir Nowak1 aTadeusz Czachórski00aA contribution to the fair scheduling for the TCP and UDP streams  aISBN 3-642-13860-800938nas a2200205   4500000000100000000000100001008004100002260003400043100001700077700002300094700002200117700002200139700002400161700002500185700002200210245005500232300001200287520041100299020002200710       2011                            d  bSpringeraBerlin / Heidelberg1 aPiotr Gawron1 aPrzemysław Głomb1 aJaroslaw Miszczak1 aZbigniew Puchała1 aTadeusz Czachórski1 aStanisław Kozielski1 aUrszula Stańczyk00aEigengestures for natural human computer interface  a49–563 aWe present the application of Principal Component Analysis for data acquired during the design of a natural gesture interface. We investigate the concept of an eigengesture for motion capture hand gesture data and present the visualisation of principal components obtained in the course of conducted experiments. We also show the influence of dimensionality reduction on reconstructed gesture data quality.  a978-3-642-23168-100332nas a2200121   4500000000100000000000100001008004100002260002300043100002200066700002400088700002100112245007700133       2001                            d  bIITiS PANaGliwice1 aKrzysztof Grochla1 aTadeusz Czachórski1 aArkadiusz Sochan00aA tool for network traffic generation and transmission delay measurement00328nas a2200133   4500000000100000000000100001008004100002260001700043100002200060700002400082700001300106700001600119245005900135       2007                            d  c9bIITiS PAN1 aKrzysztof Grochla1 aTadeusz Czachórski1 aA. Busic1 aJ. Fourneau00aSimulation Analysis of Deflection Routing in Hypercube00422nas a2200145   4500000000100000000000100001008004100002260004500043100002200088700002400110700002300134700002100157700002000178245007800198       2004                            d  bWydawnictwa Naukowo-TechniczneaWarszawa1 aKrzysztof Grochla1 aTadeusz Czachórski1 aPrzemysław Głomb1 aArkadiusz Sochan1 aAndrzej Grzywak00aInternet w społeczeństwie informacyjnym - Podstawowe problemy Internetu00293nas a2200109   4500000000100000000000100001008004100002100002200043700002400065700001700089245007700106       2011                            d1 aKrzysztof Grochla1 aTadeusz Czachórski1 aJerzy Klamka00aNumerical Model of Tcp in 802.16 Networks Using Fluid Flow Approximation00330nas a2200145   4500000000100000000000100001000000100002008004100003100001500044700001400059700002400073245006800097300001200165490000700177       2002                            d1 aH. Elbiaze1 aT. Atmaca1 aTadeusz Czachórski00aBlind shaping strategy of self-similar traffic: Markovian model  a13–250 v1401274nas a2200145   4500000000100000000000100001008004100002260003200043100001700075700002400092700002200116245007800138300001400216520089800230       2011                            d  bIEEE Computer Society Press1 aJerzy Klamka1 aTadeusz Czachórski1 aKrzysztof Grochla00aModelling TCP Connection in WIMAX Network Using Fluid Flow Approximation.  a502–5073 aThe fluid-flow approximation models have been during last few years to analyze the dynamics and stability of TCP/RED connections in wired networks. The model assumes that the fluctuations of parameters of the connections are relatively low. The fluid flow models base on the linearization and use of control theory analysis tools to verify the stability and behavior of the analyzed system. In this article we use some extensions of fluid flow approximation to support time division multiplexing used in WiMAX wireless networks. We describe the modification of fluid flow equations to incorporate the delivery of packets as an on-off source with on and off times modulated by the WiMAX scheduling algorithm. The results of the fluid flow model have been compared to the measurement in a small test bed. We also show how to analyze the stability of the connection using control theory approach.00973nas a2200145   4500000000100000000000100001008004100002260010800043100001700151700001600168700002400184245005700208300001200265520055000277       2010                            d  bInstitute of Theoretical and Applied Informatics of the Polish Academy o SciencesaGliwice, Bałtycka 51 aJerzy Klamka1 aJ. Tańcula1 aTadeusz Czachórski00aExamination of robust stability of computer networks  a75–873 aThe thesis presents a nonlinear mathematical model of a computer network with the RED algorithm. The model equations were linearized around the set operating point and next block diagrams of the system presented. Using the methods for examining stability known from the literature, the robust stability of the system has been analysed with slight changes in its parameters. An example of stability examination prepared on the basis of the data for a real computer network has been shown. The results generalise the results known in he literature00855nas a2200169   4500000000100000000000100001008004100002260013300043100002500176700001800201700002100219700002400240700002500264245005200289300001400341520033000355       2014                            d  bSilesian University of Technology, Gliwice, Institute of Theoretical and Applied Informatics, Polish Academy of Science, Gliwice1 aPrzemysław Kowalski1 aDariusz Pojda1 aAleksandra Gruca1 aTadeusz Czachórski1 aStanisław Kozielski00aVisualization of heterogenic images of 3D scene  a291–2973 a<p>The article presents a problem of 3D and 2D heterogenic data visualization. The data come from different devices installed on the robot platform. The data include 3D point cloud, 2D images, 3D and 2D occupancy grids, obtained from laser scanning device, stereocameras and calculated using data from laser 3D scanner.</p>
00889nas a2200157   4500000000100000000000100001008004100002260005000043100001200093700001200105700002400117700001400141245006600155300001400221520049600235       2015                            d  bSpringer International Publishing Switzerland1 aM. Nycz1 aT. Nycz1 aTadeusz Czachórski1 aPiotr Gaj00aAn analysis of the extracted parts of Opte Internet topology.  a371–3813 aThe paper defines a method to extract a part of a graph, which corresponding to a network (Internet) topology covering a certain area. The method refers to data gathered within Opte Project and describing the Internet topology. The extracted parts of graphs have been analyzed in terms of the number of neighbours, longest path length and existence of cycles. Then the resulting topologies are used to model transient behaviour of wide area networks with the use of fluid-flow approximation.00819nas a2200157   4500000000100000000000100001000000100002008004100003100001400044700002400058245007700082300001200159490000700171520046900178022001400647       2012                            d1 aM.M. Nycz1 aTadeusz Czachórski00aModelowanie dynamiki przesyłów TCP/IP z uwzględnieniem mechanizmu RED  a49–620 v333 aW pracy przedstawiono wyniki modelowania wybranych scenariuszy współczesnych sieci komputerowych. W badaniach zastosowano model matematyczny aproksymacji fluid flow, opisujący wpływ zmiennego w czasie natężenia ruchu pakietów na przełączniki sieciowe i generowanie strat pakietowych, zgodnie z założeniami mechanizmu RED stosowanego w routerach. Przeprowadzone doświadczenia obejmowały wpływ początkowych ustawień parametrów na zachowanie układu.  a0208-728600825nas a2200121   4500000000100000000000100001008004100002100001400043700002400057245009500081300001400176520051300190       2011                            d1 aM.M. Nycz1 aTadeusz Czachórski00aModelling transient TCP flows with the use of fluid flow approximation - a numerical study  a181–1843 aThis article presents the problem of modeling the basic elements of the transport system of the modern computer networks. The study of selected issues of the network topology uses a mathematical model of fluid flow approximations, which is based on mean value analysis. The model describes the effects of time varying packet traffic on the network switches and packet loss generation by the assumptions of active queue management mechanisms used in routers. The computations are due to our new software tool.00349nas a2200145   4500000000100000000000100001008004100002260001000043100001800053700002000071700002400091700002200115700002000137245004600157       2008                            d  bWKiŁ1 aMateusz Nowak1 aSławomir Nowak1 aTadeusz Czachórski1 aAndrzej Kwiecień1 aStefan Węgrzyn00aContemporary aspects of computer networks00888nas a2200145   4500000000100000000000100001008004100002260011200043100001800155700001600173700002400189245008300213300001400296520043200310       2010                            d  c1bInstitute of Theoretical and Applied Informatics of the Polish Academy of SciencesaGliwice, Bałtycka 51 aMateusz Nowak1 aPiotr Pecka1 aTadeusz Czachórski00aQoS management for multimedia traffic in synchronous slotted-ring OPS networks  a143–1523 aThe paper presents synchronous slotted-ring network with optical packet switching. The network is equipped with quality of service management, particularly considering multimedia transfers. Thanks to proposed mechanism of guarantees, multimedia data are delivered with guaranteed delay time, not greater than assumed, and in the case the delivery on time is impossible – they are removed, freeing place for remaining packets.00403nas a2200133   4500000000100000000000100001008004100002260003400043100002000077700002000097700002500117700002400142245010300166       2004                            d  bWydawnictwa Naukowo Technicze1 aSławomir Nowak1 aStefan Węgrzyn1 aBolesław Pochopień1 aTadeusz Czachórski00aNanotechnologi i nanoinformatyka, Rozdział w książce Współczesne problemy sieci komputerowych00318nas a2200121   4500000000100000000000100001008004100002100002000043700001900063700002100082700002400103245006900127       2010                            d1 aSławomir Nowak1 aAdam Domański1 aJoanna Domańska1 aTadeusz Czachórski00aSimulation models of fair scheduling for the TCP and UDP streams00297nas a2200121   4500000000100000000000100001008004100002260001700043100002000060700001800080700002400098245005300122       2007                            d  c9bIITiS PAN1 aSławomir Nowak1 aMateusz Nowak1 aTadeusz Czachórski00aParallel simulation of networks with packet loss00344nas a2200145   4500000000100000000000100001008004100002260001000043100002000053700002000073700002000093700002500113700002400138245003600162       2005                            d  bWKiŁ1 aSławomir Nowak1 aStefan Węgrzyn1 aStefan Węgrzyn1 aBolesław Pochopień1 aTadeusz Czachórski00aWysokowydajne sieci komputerowe01099nas a2200193   4500000000100000000000100001008004100002260003500043100002400078700001200102700001200114700002000126700002200146700001400168700001300182245008200195300001400277520061400291       2013                            d  c6bSpringeraBerlin Heidelberg1 aTadeusz Czachórski1 aM. Nycz1 aT. Nycz1 aFerhan Pekergin1 aAndrzej Kwiecień1 aPiotr Gaj1 aP. Stera00aAnalytical and numerical means to model transient states in computer networks  a426–4353 aTransient queue analysis is needed to model the influence of time-dependent flows on congestion in computer networks. It may be applied to the networks performance evaluation and the analysis of the transmissions quality of service. However, the exact queuing theory gives us only few practically useful results, concerning mainly M/M/1 and M/M/1/N queues. The article presents potentials of three approaches: Markovian queues solved numerically, the diffusion approximation, and fluid-flow approximation. We mention briefly a software we implemented to use these methods and summarise our experience with it.00930nas a2200193   4500000000100000000000100001008004100002260003300043100001600076700002400092700001800116700002400134700002500158700002200183245003000205490000800235520047100243020002200714       2011                            d  bSpringer Berlin / Heidelberg1 aPiotr Pecka1 aSebastian Deorowicz1 aMateusz Nowak1 aTadeusz Czachórski1 aStanisław Kozielski1 aUrszula Stańczyk00aMan-Machine Interaction 20 v1033 aMarkov chains are used in analysis in many fields. One of them is performance evaluation of computer systems, especially computer networks. For the analysis we use OLYMP object library that provides features to describe complex systems and find their statistical parameters. We present two compressed data structures for the most space-consuming parts of data processed by OLYMP. Then, we show how these improvements move the barrier of applicability of the utility.  a978-3-642-23168-100860nas a2200157   4500000000100000000000100001008004100002260011200043100001600155700001900171700002100190700002400211245007000235300001400305520038300319       2010                            d  c1bInstitute of Theoretical and Applied Informatics of the Polish Academy of SciencesaGliwice, Bałtycka 51 aD. Augustyn1 aAdam Domański1 aJoanna Domańska1 aTadeusz Czachórski00aActive Queue Management with non-linear packets dropping function  a133–1423 aAbstract: Algorithms of queue management in IP routers determine which packet should be deleted when necessary. The article investigates the influence of packet rejection probability function on the performance, i.e. response time for in case of RED and nRED queues. In particular, the self-similar traffic is considered. The quantitative analysis based on simulations is shown.00288nas a2200121   4500000000100000000000100001008004100002100001600043700002400059700002400083700001400107245004500121       2001                            d1 aR. Laalaoua1 aTadeusz Czachórski1 aStanisław Jędruś1 aT. Atmaca00aDiffusion Model of RED Control Mechanism00339nas a2200145   4500000000100000000000100001000000100002008004100003100001600044700002400060700001400084245007400098300001400172490000700186       2001                            d1 aR. Laalaoua1 aTadeusz Czachórski1 aT. Atmaca00aDiffusion approximation and markovian models of RED control mechanism  a343–3540 v1300244nas a2200109   4500000000100000000000100001008004100002100001600043700002400059700001400083245003700097       2001                            d1 aR. Laalaoua1 aTadeusz Czachórski1 aT. Atmaca00aMarkovian Model of RED Mechanism00901nas a2200169   4500000000100000000000100001008004100002260013300043100002100176700001600197700002100213700002400234700002500258245006500283300001400348520036900362       2014                            d  bSilesian University of Technology, Gliwice, Institute of Theoretical and Applied Informatics, Polish Academy of Science, Gliwice1 aKrzysztof Skabek1 aP. Płoszaj1 aAleksandra Gruca1 aTadeusz Czachórski1 aStanisław Kozielski00aImplementation of registration algorithms for multiple views  a315–3233 aThe article discusses the implementation of algorithms for registration and multiregistration of scans. The multiregistration strategies of mesh sequences for different scanning views were proposed and compared. The comparison criteria comprise parameters of the registration process such as: the accuracy of scan matching, performance, complexity of registration.00365nas a2200145   4500000000100000000000100001008004100002260001000043100002100053700002300074700002000097700002500117700002400142245005300166       2005                            d  bWKiŁ1 aKrzysztof Skabek1 aRyszard Winiarczyk1 aStefan Węgrzyn1 aBolesław Pochopień1 aTadeusz Czachórski00aWysokowydajne sieci komputerowe Nowe Technologie00271nas a2200097   4500000000100000000000100001008004100002100002500043700002400068245008100092       2005                            d1 aIreneusz Szcześniak1 aTadeusz Czachórski00aOPUS Software for Performance Evaluation of Optical Packet-Switched Networks00414nas a2200145   4500000000100000000000100001008004100002260005300043100002500096700002400121700002000145700002500165700002400190245005400214       2005                            d  bWydawnictwa Komunikacji i ŁącznościaWarszawa1 aIreneusz Szcześniak1 aTadeusz Czachórski1 aStefan Węgrzyn1 aBolesław Pochopień1 aTadeusz Czachórski00aWysokowydajne sieci komputerowe. Nowe Technologie00311nas a2200109   4500000000100000000000100001008004100002100002500043700002400068700001600092245009300108       2006                            d1 aIreneusz Szcześniak1 aTadeusz Czachórski1 aJ. Fourneau00aPacket Loss Analysis in Optical Packet-Switched Networks with Limited Deflection Routing00360nas a2200121   4500000000100000000000100001008004100002100002500043700001600068700002400084245011600108300001400224       2005                            d1 aIreneusz Szcześniak1 aJ. Fourneau1 aTadeusz Czachórski00aPreliminary results of packet loss analysis in optical packet-switched networks with limited deflection routing  a296–29900933nas a2200193   4500000000100000000000100001008004100002260002500043100001400068700002400082700002200106700001200128700002000140700001700160700001200177245003800189300001400227520049800241       2014                            d  c10bSpringeraLondon1 aT. Atmaca1 aTadeusz Czachórski1 aKrzysztof Grochla1 aT. Nycz1 aFerhan Pekergin1 aErol Gelenbe1 aR. Lent00aA model of boot-up storm dynamics  a371–3793 aThe simultaneous boot of multiple virtual machines or networking devices imposes heavy load on the networking infrastructure. In large network of many virtual machines the coordination of the reboots and device registration is required. In the paper we present a simple analytical model computing the distribution of boot-up time, which is verified by comparison to a simulation model and provide analysis of the influence of several parameters on the overall boot-up time during a boot storm.00300nas a2200145   4500000000100000000000100001000000100002008004100003100001400044700002400058700001600082245003500098300001400133490000700147       2002                            d1 aT. Atmaca1 aTadeusz Czachórski1 aR. Laalaoua00aBadanie dynamiki algorytmu RED  a223–2340 v2301389nas a2200157   4500000000100000000000100001000000100002008004100003100001200044700002400056245014600080300001200226490000700238520097200245022001401217       2012                            d1 aT. Nycz1 aTadeusz Czachórski00aBadanie skalowalności modeli sieci komputerowych wykorzystujących aproksymację dyfuzyjną wraz ze zwiększeniem rozmiaru modelowanej sieci  a63–780 v333 aZmienne natężenie ruchu generowanego przez aplikacje internetowe, np. multimedialne, a także przyjęta przez protokół TCP zasada regulacji natężenia transmisji w funkcji wykrytego obciążenia sieci, określanego na podstawie strat lub czasu transmisji, powodują, że natężenie transmisji internetowych jest permanentnie zmienne w czasie, a zmiany natężenia i dynamika tych zmian muszą być uwzględnione w ocenie algorytmów sterowania ruchem i unikania przeciążeń. Modelowanie struktur w Internecie wymaga z kolei dostosowania istniejących metod i modeli do analizy bardzo dużych konfiguracji sieciowych. Niniejsza praca bada pod kątem obliczeń numerycznych znany model matematyczny, umożliwiający analizę stanów nieustalonych w stanowisku obsługi i ich sieci, wykorzystujący metodę aproksymacji dyfuzyjnej. Zbadano wpływ poszczególnych parametrów modelu i rozmiaru sieci na całkowity czas obliczeń, a więc na skalowalność metody.  a0208-728600921nas a2200181   4500000000100000000000100001008004100002260005000043100001200093700001200105700002400117700002200141700001400163700001300177245012500190300001400315520041000329       2014                            d  bSpringer International Publishing Switzerland1 aT. Nycz1 aM. Nycz1 aTadeusz Czachórski1 aAndrzej Kwiecień1 aPiotr Gaj1 aP. Stera00aA Numerical Comparison of Diffusion and Fluid-Flow Approximations Used in Modelling Transient States of TCP/IP Networks.  a213–2223 aThe paper presents a comparison of two approaches to queuing models used in performance evaluation of computer networks: diffusion approximation and fluid-flow approximation. Both methods are well known and are used alternatively in similar problems but the differences between their results and the errors they introduce when applied to TCP driven time dependent flows were not sufficiently investigated.00389nas a2200133   4500000000100000000000100001008004100002260004300043100002000086700002000106700002500126700002400151245008000175       2005                            d  bWydawnictwa Komunikacji i Łączności1 aStefan Węgrzyn1 aStefan Węgrzyn1 aBolesław Pochopień1 aTadeusz Czachórski00aTechnologie molekularne realizowane przez molekularne systemy informatyczne00400nam a2200157   4500000000100000000000100001008004100002260005900043100002000102700001700122700002200139700002400161245003300185250000600218020001800224       2003                            d  bWydawnictwo Pracowni Komputerowej Jacka Skalmierskiego1 aStefan Węgrzyn1 aJerzy Klamka1 aJaroslaw Miszczak1 aTadeusz Czachórski00aKwantowe systemy informatyki  a2  a83-89105-46-201352nas a2200157   4500000000100000000000100001008004100002260005300043100002100096700002000117700002500137700002400162245005400186520093100240020002301171       2005                            d  bWydawnictwa Komunikacji i ŁącznościaWarszawa1 aLech Znamirowski1 aStefan Węgrzyn1 aBolesław Pochopień1 aTadeusz Czachórski00aWysokowydajne sieci komputerowe. Nowe technologie3 aW procesach budowy obiektów w dziedzinie informatycznej technologii wytwarzania, jedną z możliwych metod jest wykorzystanie molekularnego programu określającego budowę obiektu, który powstaje na bazie współdziałających, molekularnych narzędzi realizujących program. Analiza działania sieci współpracujących nanostruktur wymaga znajomości konformacji początkowych lub konformacji występujących w sieci w wyniku współdziałania z innymi nanostrukturami. W rozdziale rozpatruje się zagadnienie wyznaczania konformacji dla polipeptydu określonego jego kodem zapisanym w DNA w przypadku powstawania w rybosomie lub w wyniku współdziałania z tzw. białkiem opiekuńczym w fazie innej niż faza powstawania. Przedstawiony został bezgradientowy, dwufazowy algorytm wyznaczania konformacji poprzez obliczenie kątów torsyjnych dla łańcucha aminokwasów. Rozważania zilustrowano przykładem numerycznym.  aISBN 83-206-1573-900380nas a2200145   4500000000100000000000100001008004100002260001800043100002100061700002000082700002500102700002400127245006500151020001800216       2004                            d  bWNTaWarszawa1 aLech Znamirowski1 aStefan Węgrzyn1 aBolesław Pochopień1 aTadeusz Czachórski00aWspółczesne problemy sieci komputerowych. Nowe technologie  a83-204-3010-000856nas a2200145   4500000000100000000000100001008004100002260003500043100002400078700001700102700001200119245005300131520050400184020002200688       2014                            d  cXbISCIS 29th Annual Symposium1 aTadeusz Czachórski1 aErol Gelenbe1 aR. Lent00aQuantum Queuing Networks Throughput Optimisation3 aWe study models of quantum queues based on discrete time quantum walks with barriers. Our considerations refer to multi-servers queuing models. Input and output of jobs in the queue are realized by systems consisting of quantum coins and walkers. We show that presented models behave differently from the classical ones. We also present numerical methods for optimisation of jobs processed by the system. We simultaneously maximise jobs throughput in the system and minimise the number of jobs lost.  a978-3-319-09464-900342nas a2200121   4500000000100000000000100001008004100002260006800043100002400111700002100135245004600156020001800202       2001                            d  c09bInstytut Informatyki Teoretycznej i Stosowanej PANaGliwice1 aTadeusz Czachórski1 aArkadiusz Sochan00a8th Polish Teletraffic Symposium (Editor)  a83-86644-90-700430nas a2200157   4500000000100000000000100001008004100002260006700043100002400110700001900134700002100153700001600174245006200190300001200252490000800264       2016                            d  bSpringer International Publishing SwitzerlandaBrunów, Poland1 aTadeusz Czachórski1 aAdam Domański1 aJoanna Domańska1 aArtur Rataj00aA Study of IP Router Queues with the Use of Markov Models  a294-3050 v60800577nas a2200205   4500000000100000000000100001008004100002260004400043100001600087700001600103700002400119700002100143700001700164700001700181700001700198245006900215856005100284300001400335020002200349       2016                            d  bSpringer International PublishingaCham1 aMonika Nycz1 aTomasz Nycz1 aTadeusz Czachórski1 aOmer Abdelrahman1 aErol Gelenbe1 aGokce Gorbil1 aRicardo Lent00aModelling Dynamics of TCP Flows in Very Large Network Topologies  uhttp://dx.doi.org/10.1007/978-3-319-22635-4_23  a251–259  a978-3-319-22635-400644nas a2200229   4500000000100000000000100001008004100002260004400043100001700087700002400104700002100128700001800149700001600167700002100183700002300204700002500227700002400252245005500276856005000331300001100381020002200392       2016                            d  bSpringer International PublishingaCham1 aJohan Arcile1 aTadeusz Czachórski1 aJean-Yves Didier1 aHanna Klaudel1 aArtur Rataj1 aAleksandra Gruca1 aAgnieszka Brachman1 aStanisław Kozielski1 aTadeusz Czachórski00aModelling and Analysing Mixed Reality Applications  uhttp://dx.doi.org/10.1007/978-3-319-23437-3_1  a3–17  a978-3-319-23437-300519nas a2200169   4500000000100000000000100001008004100002260004400043100001900087700002100106700002400127245010300151856005100254300001400305490000800319020002200327       2016                            d  bSpringer International PublishingaCham1 aAdam Domański1 aJoanna Domańska1 aTadeusz Czachórski00aThe Impact of the Degree of Self-Similarity on the NLREDwM Mechanism with Drop from Front Strategy  uhttp://dx.doi.org/10.1007/978-3-319-39207-3_17  a192–2030 v608  a978-3-319-39207-300516nas a2200193   4500000000100000000000100001008004100002260004400043100002400087700001900111700002100130700001900151700001600170245004100186856005100227300001400278490000800292020002200300       2016                            d  bSpringer International PublishingaCham1 aTadeusz Czachórski1 aAdam Domański1 aJoanna Domańska1 aMichele Pagano1 aArtur Rataj00aDelays in IP Routers, a Markov Model  uhttp://dx.doi.org/10.1007/978-3-319-47217-1_20  a185–1920 v659  a978-3-319-47217-100535nas a2200181   4500000000100000000000100001008004100002260004400043100001900087700002100106700001900127700002400146245008800170856005100258300001400309490000800323020002200331       2016                            d  bSpringer International PublishingaCham1 aAdam Domański1 aJoanna Domańska1 aMichele Pagano1 aTadeusz Czachórski00aThe Fluid Flow Approximation of the TCP Vegas and Reno Congestion Control Mechanism  uhttp://dx.doi.org/10.1007/978-3-319-47217-1_21  a193–2000 v659  a978-3-319-47217-100634nas a2200217   4500000000100000000000100001008004100002260004400043100002000087700001800107700002200125700001600147700002400163700001700187700002200204700001700226245008600243856005100329300001400380020002200394       2016                            d  bSpringer International PublishingaCham1 aSławomir Nowak1 aMateusz Nowak1 aKrzysztof Grochla1 aPiotr Pecka1 aTadeusz Czachórski1 aErol Gelenbe1 aKrzysztof Grochla1 aRicardo Lent00aGlobal Queue Pruning Method for Efficient Broadcast in Multihop Wireless Networks  uhttp://dx.doi.org/10.1007/978-3-319-47217-1_23  a214–224  a978-3-319-47217-100372nam a2200169   4500000000100000000000100001000000100002008004100003100002400044700001700068700002200085700001700107245004900124250001300173300000800186490000800194       2016                            d1 aTadeusz Czachórski1 aErol Gelenbe1 aKrzysztof Grochla1 aRicardo Lent00aComputer and Information Sciences ISCIS 2016  aSpringer  a5000 v65901382nas a2200193   4500000000100000000000100001008004100002260003700043100002100080700001700101700002400118700002200142700002300164245009800187300001200285490000800297520086300305020002001168       2018                            d  bSpringeraLondon, United Kingdom1 aJoanna Domańska1 aErol Gelenbe1 aTadeusz Czachórski1 aAnastasios Drosou1 aDimitrios Tzovaras00aResearch and innovation action for the security of the internet of things: The SerIoT project  a101-1180 v8213 a<p>The Internet of Things (IoT) was born in the mid 2010’s, when the threshold of connecting more objects than people to the Internet, was crossed. Thus, attacks and threats on the content and quality of service of the IoT platforms can have economic, energetic and physical security consequences that go way beyond the traditional Internet’s lack of security, and way beyond the threats posed by attacks to mobile telephony. Thus, this paper describes the H2020 project “Secure and Safe Internet of Things” (SerIoT) which will optimize the information security in IoT platforms and networks in a holistic, cross-layered manner (i.e. IoT platforms and devices, honeypots, SDN routers and operator’s controller) in order to offer a secure SerIoT platform that can be used to implement secure IoT platforms and networks anywhere and everywhere.</p>
  a978-331995188-100916nas a2200193   4500000000100000000000100001008004100002260001200043100002100055700001800076700002000094700002400114245005900138856006700197300001200264490000800276520041600284022002200700       2018                            d  c08/20181 aJoanna Domańska1 aMateusz Nowak1 aSławomir Nowak1 aTadeusz Czachórski00aEuropean Cybersecurity Research and the SerIoT Project  uhttps://link.springer.com/chapter/10.1007/978-3-030-00840-6_19  a166-1730 v9353 a<p>This paper briefly reviews some recent research in Cybersecurity in Europe funded by the European Commission in areas such as mobile telephony, networked health systems, the Internet of Things. We then outline the objectives of the SerIoT Project which started in 2018 to address the security needs of fields such as Smart Cities, Smart Transportation Systems, Supply Chains and Industrial Informatics.</p>
  a978-3-030-00839-000416nas a2200157   4500000000100000000000100001008004100002100001900043700002100062700002400083700001700107700001900124245009700143300001000240490000800250       2019                            d1 aAdam Domański1 aJoanna Domańska1 aTadeusz Czachórski1 aJerzy Klamka1 aJakub Szyguła00aThe AQM Dropping Packet Probability Function Based on Non-integer Order PI^αD^β Controller  a36-480 v49600432nas a2200169   4500000000100000000000100001008004100002100001900043700002100062700002400083700001700107700001800124700001900142245008100161300001200242490000800254       2018                            d1 aAdam Domański1 aJoanna Domańska1 aTadeusz Czachórski1 aJerzy Klamka1 aDariusz Marek1 aJakub Szyguła00aGPU Accelerated Non-integer Order PI^αD^β Controller Used as AQM Mechanism  a286-2990 v86000465nas a2200169   4500000000100000000000100001008004100002100001900043700002100062700002400083700001700107700001800124700001900142245011600161300001000277490000800287       2018                            d1 aAdam Domański1 aJoanna Domańska1 aTadeusz Czachórski1 aJerzy Klamka1 aDariusz Marek1 aJakub Szyguła00aThe Influence of the Traffic Self-similarity on the Choice of the Non-integer Order PI^α Controller Parameters  a76-830 v93500373nas a2200145   4500000000100000000000100001008004100002260002200043100001700065700002100082700002400103700002100127700002300148245005600171       2018                            d  bIEEEaRome, Italy1 aErol Gelenbe1 aJoanna Domańska1 aTadeusz Czachórski1 aAnastasis Drosou1 aDimitrios Tzovaras00aSecurity for Internet of Things: The SerIoT Project00380nas a2200145   4500000000100000000000100001008004100002100001900043700002100062700002400083700001700107245009100124300001200215490000700227       2016                            d1 aAdam Domański1 aJoanna Domańska1 aTadeusz Czachórski1 aJerzy Klamka00aThe use of a non-integer order PI controller with an active queue management mechanism  a777-7890 v2600384nas a2200145   4500000000100000000000100001008004100002100001900043700002100062700002400083700001700107245009400124300001200218490000800230       2017                            d1 aAdam Domański1 aJoanna Domańska1 aTadeusz Czachórski1 aJerzy Klamka00aSelf-similarity Traffic and AQM Mechanism Based on Non-integer Order Pi^αD^β Controller  a336-3500 v71800327nas a2200133   4500000000100000000000100001008004100002100002100043700001900064700002400083245006800107300001000175490000800185       2017                            d1 aJoanna Domańska1 aAdam Domański1 aTadeusz Czachórski00aHidden Markov Models in Long Range Dependence Traffic Modelling  a75-860 v70001564nas a2200109   4500000000100000000000100001008004100002260005100043100002400094245007300118520126300191       2018                            d  c11/2018bRangsit UniversityaBangkok, Thailand1 aTadeusz Czachórski00aModels of traffic control in large Internet topologies, invited talk3 a<p><span style="font-family:times new roman,serif; font-size:12pt">Transient state queueing models help us to understand better the dynamics of Internet transmissions and the performance of traffic control algorithms. Fluid flow approximation, due its simplicity is popular and frequently used -- but even it, if applied to large topologies, is time and space consuming. The alternative approaches as Markov chains or diffusion approximation lead to much more complex computations. Fluid flow approximation is based on first-order differential equations, and its algorithm is based on iterative calculations on large mutually interdependent structures. In consequence, the bottleneck of the method lies not in numerical computations but in storing and selection of data. This is why we use an approach in which a database (SAP HANA) and its language are used to implement the method. The model logic is represented by ETL (Extract, Transform and Load) customizable and user-friendly processes. The numerical examples are based on a real topology having over 100 000 nodes. We may investigate and compare this way various TCP control algorithms as Vegas or Reno, as well as the influence of the introduction of energy aware algorithms to routers.</span></p>
03310nas a2200109   4500000000100000000000100001008004100002260007300043100002400116245011000140520295000250       2018                            d  c11/2018bXi'an University of Science Technology, ChinaaXi'an, China1 aTadeusz Czachórski00aQueueing Models for Performance Evaluation of Computer Networks - Transient State Analysis, invited talk 3 a<p>Queueing theory is a useful tool in design of computer networks and their performance evaluation. The literature concerning this subject is abundant. However, it is in general limited to the analysis of steady states. It means that flows considered in models are constant and obtained solutions do not depend on time. It is in glaring contrast with the flows observed in real networks where the perpetual changes of traffic intensities are due to the nature of users, sending variable quantities of data, cf. multimedia traffic, and also due to the performance of traffic control algorithms which are trying to avoid congestion in networks, e.g. the algorithm of congestion window used in TCP protocol which is adapting the rate of the sent traffic to the observed losses or transmission delays. The quality of Internet transmission services depends on current load of links and not on its average value. Also modelling and understanding the performance of traffic control mechanisms, control stability and its impact on quality of service needs transient state analysis.</p>

<p>We discuss mathematical and computational means used to analyse transient states in queueing models. In computer applications a mathematical model is useful only when it furnishes quantitative results. Therefore practical issues related to numerical side of models are of importance. &nbsp;We present three approaches - Markov models solved numerically, fluid flow approximation and diffusion approximation. A particular importance is given to the latter which is describing the evolution of queues and waiting times in terms of partial differential equations. The author has over 20 year experience in development and application of this method and is also convinced of the qualities of this approach, its flexibility to treat various variants of queueing models.</p>

<p>Fluid flow approximation, due its simplicity is popular and frequently used -- but even it, if applied to large topologies, is time and space consuming. &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Fluid flow approximation is based on first-order differential equations, and its algorithm needs iterative calculations on large mutually interdependent structures. In consequence, the bottleneck of the method lies not in numerical computations but in storing and selection of data. This is why we use an approach in which a database and its language are used to implement the method. The numerical examples are based on a real topology having over 100 000 nodes. We may investigate and compare this way various TCP control algorithms as Vegas or Reno, as well as the influence of the introduction of energy aware algorithms to routers.</p>

<p>Traffic intensity observed in computer networks have a complex stochastic nature (self-similarity and long-range dependence) that influences the network performances. We discuss also this side of implemented queueing models.</p>
01579nas a2200109   4500000000100000000000100001008004100002260009000043100002400133245011000157520120200267       2018                            d  c09/2018b Lviv Polytechnic National Universitya Lviv Polytechnic National University1 aTadeusz Czachórski00aQueueing models of traffic control and performance evaluation in large Internet topologies, key-note talk3 a<p>Transient state queueing models help us to understand better the dynamics of internet transmissions and the performance of traffic control algorithms. Fluid flow approximation, due its simplicity is popular and frequently used -- but even it, if applied to large topologies, is time and space consuming. The alternative approaches as Markov chains or diffusion approximation lead to much more complex computations. Fluid flow approximation is based on first-order differential equations, and its algorithm is based on iterative calculations on large mutually interdependent structures. In consequence, the bottleneck of the method lies not in numerical computations but in storing and selection of data. This is why we use an approach in which a database (SAP HANA) and its language are used to implement the method.</p>

<p>The model logic is represented by ETL (Extract, Transform and Load) customizable and user-friendly processes. The numerical examples are based on a real topology having over 100 000 nodes. We may investigate and compare this way various TCP control algorithms as Vegas or Reno, as well as the influence of the introduction of energy aware algorithms to routers.</p>
00284nas a2200097   4500000000100000000000100001008004100002260004500043100002400088245007400112       2018                            d  c09/2018bPolitechnika ŚląskaaZakopane1 aTadeusz Czachórski00aMetoda sterowania natężeniem ruchu w Internecie, referat zaproszony00452nas a2200133   4500000000100000000000100001008004100002260009400043100001800137700002000155700002400175700001600199245010300215       2018                            d  c09/2018bCommunications in Computer and Information Science , vol. 935, SpringeraPoznań1 aGodlove Suila1 aEdelqueen Anyam1 aTadeusz Czachórski1 aArtur Rataj00aPerformance of a buffer between electronic and all-optical networks, diffusion approximation model00385nas a2200121   4500000000100000000000100001008004100002260009300043100001700136700002400153700001600177245007000193       2018                            d  c06/2018bSpringer, Communications in Computer and Information Science, vol. 860aGliwice1 aKuaban Suila1 aTadeusz Czachórski1 aArtur Rataj00aA Queueing Model of the Edge Node in IP over All-Optical Networks00457nas a2200133   4500000000100000000000100001008004100002260010100043100001900144700002400163700001600187245009800203020002200301       2017                            d  c10/2017bSpringer, Advances in Intelligent Systems and Computing, vol. 659, pp. 525-531aKraków1 aAdam Józefiok1 aTadeusz Czachórski1 aArtur Rataj00aA Queueing Model of an Insurance Database Interactive System, Comparison of Modelling Methods  a978-3-319-67791-000448nas a2200133   4500000000100000000000100001008004100002260011100043100001600154700001600170700002400186245007600210020002800286       2017                            d  c09/2017bSpringer, Communications in Computer and Information Science, vol. 700, pp. 49-62aMoscow, Russia1 aMonika Nycz1 aTomasz Nycz1 aTadeusz Czachórski00aPerformance Modelling of Transmissions in Very Large Network Topologies  aISBN: 978-3-319-66835-202624nas a2200157   4500000000100000000000100001000000100002008004100003260006500044100001500109700002400124245011500148250001300263300001200276520217800288       2019                            d  bSpringer, Communications in Computer and Information Science1 aMarek Fiuk1 aTadeusz Czachórski00aA Queueing Model and Performance Analysis of UPnP/HTTP client server interactions in Networked Control Systems  aSpringer  a366-3863 a<div>HTTP based communication protocols are ubiquitous in modern distributed control/supervision systems, therefore it becomes important to understand the performance of the HTTP protocol working with this type of applications and to develop techniques to investigate the impact of the protocol on the overall performance of these systems. A distributed control/supervision system based on HTTP usually consists of multiple nodes sending control requests or measurements to one or more recipient nodes; these data are used to perform control functions, and are stored or presented to supervising personnel. Typically multiple, concurrent flows of data are carried over HTTP to a given recipient. The stochastic characteristics of these flows are often different from the bursty nature of the ordinary Web Browser – Web Server interactions. Furthermore, in order to efficiently carry the randomly arriving data, the number of overlapping (concurrent) HTTP request/response sessions utilized by a sending node is higher than in typical Web Browser -- Web Server communications.</div>

<div>We investigate how the characteristics of nodes participating in the distributed control system communications (number of nodes, service times, number of service stations, queue lengths) influence performance of the employed HTTP protocol. The main focus is on&nbsp; end-to-end delays in transmissions, the most important factor in control. The presented approach can be used to select configuration parameters for the nodes of a realistic control/supervision system having in mind the best communication related performance of such system.</div>

<div>In this work we propose a queuing model of HTTP client/server interactions which we subsequently simplify to be represented by a numerically solvable Markov chain. We compare the results obtained with the simplified model with the output of a discrete event simulation based on the original full model.</div>

<div>The initial motivation for this research came from a study of UPnP based remote PTZ camera control mechanism used by a leading manufacturer of large scale video monitoring systems.</div>

<div>&nbsp;</div>
00439nas a2200157   4500000000100000000000100001008004100002260002000043100001800063700002000081700002100101700002400122245006400146856004900210020002200259       2019                            d  aAarhus, Denmark1 aMateusz Nowak1 aSławomir Nowak1 aJoanna Domańska1 aTadeusz Czachórski00aCognitive Packet Networks for the Secure Internet of Things  uhttps://ieeexplore.ieee.org/document/8766380  a978-1-7281-2171-002334nas a2200853   4500000000100000000000100001008004100002260002100043100001900064700002100083700002300104700002100127700002400148700002500172700002500197700002800222700002700250700002000277700002100297700002500318700001800343700002500361700002100386700002200407700001800429700001300447700001800460700001900478700002100497700001600518700002100534700001800555700002100573700001900594700001900613700002200632700001900654700001900673700001700692700002100709700002300730700001600753700001800769700002300787700002500810700002200835700001900857700002400876700002400900700001900924700001800943700001800961700002000979700002400999700002001023700002201043700002301065700001501088700001701103700002001120700001801140700002401158700002101182700002101203700002301224700001401247700002401261700002001285700001801305700002401323700001901347245009601366020001801462       2018                            d  bRiver Publishers1 aEnrico Ferrera1 aClaudio Pastrone1 aPaul-Emmanuel Brun1 aRemi De Besombes1 aKonstantinos Loupos1 aGerasimos Kouloumpis1 aPatrick O’Sullivan1 aAlexandros Papageorgiou1 aPanayiotis Katsoulakos1 aBill Karakostas1 aAntonis Mygiakis1 aChristina Stratigaki1 aBora Caglayan1 aBasile Starynkevitch1 aChristos Skoufis1 aStelios Christofi1 aNicolas Ferry1 aHui Song1 aArnor Solberg1 aPeter Matthews1 aAntonio Skarmeta1 aJosé Santa1 aMichail Beliatis1 aMirko Presser1 aJosiane Parreira1 aJuan Martínez1 aPayam Barnaghi1 aShirin Enshaeifar1 aThorben Iggena1 aMarten Fischer1 aRalf Tönjes1 aMartin Strohbach1 aAlessandro Sforzin1 aHien Truong1 aJohn Soldatos1 aSofoklis Efremidis1 aGeorgios Koutalieris1 aPanagiotis Gouvas1 aJuergen Neises1 aGeorge Hatzivasilis1 aIoannis Askoxylakis1 aVivek Kulkarni1 aArne Broering1 aDariusz Dober1 aKostas Ramantas1 aChristos Verikoukis1 aJoachim Posegga1 aDomenico Presenza1 aGeorge Spanoudakis1 aDanilo Pau1 aErol Gelenbe1 aSławomir Nowak1 aMateusz Nowak1 aTadeusz Czachórski1 aJoanna Domańska1 aAnastasis Drosou1 aDimitrios Tzovaras1 aTommi Elo1 aSanteri Paavolainen1 aDmitrij Lagutin1 aHelen Leligou1 aPanagiotis Trakadas1 aGeorge Polyzos00aIoT European Security and Privacy Projects: Integration, Architectures and Interoperability  a978877022007100430nas a2200157   4500000000100000000000100001008004100002100001900043700002100062700002400083700001700107700001800124700001900142245010200161490000900263       2019                            d1 aAdam Domański1 aJoanna Domańska1 aTadeusz Czachórski1 aJerzy Klamka1 aDariusz Marek1 aJakub Szyguła00aAQM Mechanism with the Dropping Packet Function Based on the Answer of Several  PIα  Controllers0 v103900357nas a2200121   4500000000100000000000100001008004100002260000900043100002400052700002200076245007900098856005800177       2019                            d  bIEEE1 aTadeusz Czachórski1 aKrzysztof Grochla00aDiffusion Approximation Models for Cloud Computations with Task Migrations  uhttps://ieeexplore.ieee.org/abstract/document/882182400385nas a2200145   4500000000100000000000100001008004100002100001900043700002100062700002400083700001700107700001900124700001800143245007800161       2020                            d1 aAdam Domański1 aJoanna Domańska1 aTadeusz Czachórski1 aJerzy Klamka1 aJakub Szyguła1 aDariusz Marek00aDiffusion Approximation Model of TCP NewReno Congestion Control Mechanism00389nas a2200157   4500000000100000000000100001008004100002260002100043100001900064700001900083700002100102700002400123700001800147700001700165245004900182       2020                            d  c23-26 March 20201 aJakub Szyguła1 aAdam Domański1 aJoanna Domańska1 aTadeusz Czachórski1 aDariusz Marek1 aJerzy Klamka00a AQM mechanism with neuron tuning parameters00977nas a2200349   4500000000100000000000100001008004100002260001300043100002200056700001700078700002800095700002200123700003000145700002400175700001700199700002300216700002300239700001500262700002100277700001900298700001600317700001300333700001700346700002100363700002400384700002200408700002000430700001700450700002300467245008900490856004800579       2018                            d  bSpringer1 aAnastasija Collen1 aNiels Nijdam1 aJavier Augusto-Gonzalez1 aSokratis Katsikas1 aKonstantinos Giannoutakis1 aGeorgios Spathoulas1 aErol Gelenbe1 aKonstantinos Votis1 aDimitrios Tzovaras1 aN. Ghavami1 aMelanie Volkamer1 aPiroska Haller1 aA. Sánchez1 aM. Dimas1 aErol Gelenbe1 aPaolo Campegiani1 aTadeusz Czachórski1 aSokratis Katsikas1 aIoannis Komnios1 aLuigi Romano1 aDimitrios Tzovaras00aGHOST - Safe-Guarding Home IoT Environments with Personalised Real-Time Risk Control  uhttps://doi.org/10.1007/978-3-319-95189-8_700480nas a2200169   4500000000100000000000100001008004100002260001300043100002200056700001700078700002400095700001700119700002200136700001700158245008600175856004900261       2018                            d  bSpringer1 aOlumide Akinwande1 aErol Gelenbe1 aTadeusz Czachórski1 aErol Gelenbe1 aKrzysztof Grochla1 aRicardo Lent00aA Reinforcement Learning Approach to Adaptive Forwarding in Named Data Networking  uhttps://doi.org/10.1007/978-3-030-00840-6_2300662nas a2200205   4500000000100000000000100001008004100002260001300043100001700056700002100073700002400094700002200118700002000140700001700160700002300177245018000200856004600380490000800426020002200434       2018                            d  bSpringer1 aErol Gelenbe1 aPaolo Campegiani1 aTadeusz Czachórski1 aSokratis Katsikas1 aIoannis Komnios1 aLuigi Romano1 aDimitrios Tzovaras00aSecurity in Computer and Information Sciences - First International ISCIS Security Workshop 2018, Euro-CYBERSEC 2018, London, UK, February 26-27, 2018, Revised Selected Papers  uhttps://doi.org/10.1007/978-3-319-95189-80 v821  a978-3-319-95188-100514nas a2200157   4500000000100000000000100001008004100002260001300043100002400056700001700080700002200097700001700119245019000136490000800326020002200334       2018                            d  bSpringer1 aTadeusz Czachórski1 aErol Gelenbe1 aKrzysztof Grochla1 aRicardo Lent00aComputer and Information Sciences - 32nd International Symposium, ISCIS 2018, Held at the 24th IFIP World Computer Congress, WCC 2018, Poznan, Poland, September 20-21, 2018, Proceedings0 v935  a978-3-030-00839-001382nas a2200145   4500000000100000000000100001008004100002260002400043100002400067700001700091700001900108700001800127245004400145520104700189       2020                            d  bIEEEaMilano, Italy1 aTadeusz Czachórski1 aErol Gelenbe1 aGodlove Kuaban1 aDariusz Marek00aTransient Behaviour of a Network Router3 a<p>The broader use of Software Defined Network (SDN) controllers creates periodic changes in topology and traffic rates at routers that adapt the network to changes in network conditions.&nbsp;<br />
Thus the transient behaviour of network components, and in particular routers, is becoming of great interest.<br />
Since standard queueing models are difficult to analyze under time-varying conditions, we propose a tractable diffusion approximation for both the transient and steady-state behaviour of a network router. In particular, the analysis provides the steady-state and transient delay and packet loss probability as a function of traffic load and other characteristics. Using these results, we show that when SDN routers change the paths of flows frequently, the network's behaviour may often be far from its steady-state behaviour. Therefore any network optimization conducted with the help of SDN should not be based on&nbsp;steady-state behaviour, but rather on some metric reated to the network time dependent behaviour.</p>
00508nas a2200169   4500000000100000000000100001008004100002260001300043100002400056700001900080700001600099700002500115700002500140700001900165245010600184856004800290       2019                            d  bSpringer1 aTadeusz Czachórski1 aGodlove Kuaban1 aTomasz Nycz1 aVladimir Vishnevskiy1 aKonstantin Samouylov1 aDmitry Kozyrev00aMultichannel Diffusion Approximation Models for the Evaluation of Multichannel Communication Networks  uhttps://doi.org/10.1007/978-3-030-36614-8_400569nas a2200181   4500000000100000000000100001008004100002260001300043100002100056700002400077700002400101700002300125700002500148245013700173856004600310490000900356020002200365       2020                            d  bSpringer1 aAleksandra Gruca1 aTadeusz Czachórski1 aSebastian Deorowicz1 aKatarzyna Harezlak1 aAgnieszka Piotrowska00aMan-Machine Interactions 6 - 6th International Conference on Man-Machine Interactions, ICMMI 2019, Cracow, Poland, October 2-3, 2019  uhttps://doi.org/10.1007/978-3-030-31964-90 v1061  a978-3-030-31963-202537nas a2200097   4500000000100000000000100001008004100002100002400043245023500067520213700302       2019                            d1 aTadeusz Czachórski00aDiffusion approximation as a tool in computer networks performance evaluation, invited talk,  The 9th International Conference on  Electronics, Communications and Networks, CECNet 2019, October 18-21, 2019   Kitakyushu City, Japan3 a<p>Performance of computer networks is frequently investigated with the use of queueing theory. Its models represent the queues of packets waiting in routers to be sent further and evaluate queueing delays, loss probabilities in routers and then the overall transmission quality of service. There is a constant effort &nbsp;to develop models reflecting as exactly as possible the stochastic nature of the transmission intensity, its variability, the distribution of the size of packets, &nbsp;and the rules of traffic management applied by protocols to avoid network congestion. The article describes one of the approaches: diffusion approximation where the size of queues is described by a diffusion process. The method was introduced in 1970-ties by Hisashi Kobayashi and Erol Gelenbe and is still being developed by the author to fit various models of Internet, Internet of Things, Software Defined Networks, Cloud and Fog computing, edge computing. The method is based on the solution of a system of differential partial equations giving&nbsp; an approximation of the queue lengths distribution at any considered time moment. The features that are in favour of the method are:</p>

<ul>
	<li>diffusion model of a single server assumes general&nbsp; interarrival and service time distributions this way going beyond Markov models,</li>
	<li>network models may have any topology, also hierarchical, and any number of nodes (are easy scalable)</li>
	<li>the results are obtained in form of queue distributions and waiting time distributions that makes easier to analyse&nbsp; QoS of paths, e.g. jitter,</li>
	<li>&nbsp;easy separation of each node within a network model,</li>
	<li>the transient state model is solved step-by-stem in small time intervals with parameters specific to these intervals; any decision of a controller concerning&nbsp; dynamic routing of packets,&nbsp; as well as changes of flows due to attacks and control mechanisms may be easily reflected in time-dependent and state-dependent diffusion parameters&nbsp; and time-depended routing probabilities in equations determining the flows.</li>
</ul>
00338nas a2200145   4500000000100000000000100001008004100002100001900043700002100062700002000083700001900103700002400122245003900146490000700185       2020                            d1 aAdam Domański1 aJoanna Domańska1 aKatarzyna Filus1 aJakub Szyguła1 aTadeusz Czachórski00aThe self-similar markovian sources0 v1000358nas a2200133   4500000000100000000000100001008004100002260003000043100001900073700002400092700001600116245007100132020002100203       2018                            d  bSpringeraGliwice, Poland1 aGodlove Kuaban1 aTadeusz Czachórski1 aArtur Rataj00aA Queueing Model of the Edge Node in IP over  All-Optical Networks  a978-3-3199-249-500425nas a2200145   4500000000100000000000100001008004100002260003000043100001900073700002000092700002400112700001600136245010400152020002300256       2018                            d  bSpringeraPoznań, Poland1 aGodlove Kuaban1 aEdelqueen Anyam1 aTadeusz Czachórski1 aArtur Rataj00aPerformance of a buffer between  electronic and all-optical networks, diffusion approximation model  a 978-3-0300-0839-000445nas a2200169   4500000000100000000000100001008004100002100001900043700001900062700002100081700002400102700001700126700001800143245004900161856005800210490000700268       2021                            d1 aJakub Szyguła1 aAdam Domański1 aJoanna Domańska1 aTadeusz Czachórski1 aJerzy Klamka1 aDariusz Marek00aThe IoT Gateway with Active Queue Management  uhttps://www.amcs.uz.zgora.pl/?action=paper&paper=15980 v3101417nas a2200205   4500000000100000000000100001008004100002260001200043100001800055700001900073700002100092700002400113700001700137700001900154245008700173856007100260490000800331520085800339022001401197       2021                            d  c01/20211 aDariusz Marek1 aAdam Domański1 aJoanna Domańska1 aTadeusz Czachórski1 aJerzy Klamka1 aJakub Szyguła00aCombined diffusion approximation - simulation model of AQM’s transient behaviour  uhttp://www.sciencedirect.com/science/article/pii/S01403664203199400 v1663 a<p>The article introduces an approach combining diffusion approximation and simulation ones. Furthermore, it describes how it can be used to evaluate active queue management (AQM) mechanisms. Based on the obtained queue distributions, the simulation part of the model decides on package losses and modifies the flow intensity sent by the transmitter. The diffusion is used to estimate queue distributions and the goal of the simulation part of the model is to represent the AQM mechanism. On the one hand, the use of the diffusion part considerably accelerates the performance of the whole model. On the other hand, the simulation increases the accuracy of the diffusion part. We apply the model to compare the performance of fractional order PIη controller used in AQM with the performance of RED, a well known active queue management mechanism.</p>
  a0140-366401554nas a2200193   4500000000100000000000100001008004100002260005600043100002400099700001700123700001900140700001800159245008100177250003000258856003300288300001000321490000900331520102000340       2020                            d  c12/2020bCEUR-WS.orgaPetrozavodsk, Karelia, Russia1 aTadeusz Czachórski1 aErol Gelenbe1 aGodlove Kuaban1 aDariusz Marek00aTime Dependent Diffusion Model for Security Driven Software Defined Networks  aCEUR Workshop Proceedings  uhttp://ceur-ws.org/Vol-2792/  a38-560 v27923 a<p>We present a model of a Software Defined Network (SDN) where frequent changes in routing and traffic rates at routers are needed to respond to the security, quality of service (QoS), and energy savings requirements of applications such as the Internet of Things.<br />
Such frequent path and traffic changes introduce time-dependent network behaviours, and standard queueing models are not well adapted to analyse the transient regime, we propose a tractable diffusion approximation for both the transient and steady-state behaviour.<br />
Our model can represent any network topology transmitting time-dependent flows with routing changes, and computes queue length and delay distributions at each network node and along&nbsp;complete paths between senders and receivers.&nbsp;<br />
Using realistic router parameters, we show that transients occupy a significant fraction of system time, so that the optimisation conducted with SDN controllers needs to include the effect of time-dependent behaviours.</p>
02557nas a2200181   4500000000100000000000100001008004100002260005600043100001700099700001600116700001900132700002400151245009600175250006500271490001000336520200700346020002202353       2020                            d  c12/2020bSpringer International Publishingaon-line1 aTulin Atmaca1 aAmira Kamli1 aGodlove Kuaban1 aTadeusz Czachórski00aPerformance Evaluation of the Packet Aggregation Mechanism of an N-GREEN Metro Network Node  aComputer Communication Networks and Telecommunications, LNCS0 v125273 a<p>Today's telecommunication network infrastructure and services are dramatically changing due partially to the rapid increase in the amount of traffic generation and its transportation. This rapid change is also caused by the increased demand for a high quality of services and the recent interest in green networking strengthened by cutting down carbon emission and operation cost. Access networks generate short electronic packets of different sizes, which are aggregated into larger optical packets at the ingress edge nodes of the optical backbone network. It is transported transparently in the optical domain, reconverted into the electronic domain at the egress edge nodes, and delivered to the destination access networks. Packet aggregation provides many benefits at the level of MAN, and core networks such as, increased spectral efficiency, energy efficiency, optimal resource utilisation, simplified traffic management which significantly reduces protocol and signalling overhead. However, packet aggregation introduces performance bottleneck at the edge node as the packets from the access networks are temporarily stored in the aggregation buffers during the packet aggregation process. In this article, we apply the diffusion approximation model and other stochastic modelling methods to analytically evaluate the performance of a new packet aggregation mechanism which was developed specifically for an N-GREEN (Next Generation of Routers for Energy &nbsp;Efficiency) metro network. We obtain the distribution of the packets' queue in the aggregation buffer, which influences the distribution of the waiting time (delay) experienced by packets in the aggregation buffer. We then, demonstrate the influence of the probability $p$ of successfully inserting the packet data units from the aggregation queue to the optical ring within a defined timeslot $\Delta$. We also discuss the performance evaluation of the complete ring by deriving the utilisation of each link.<br />
&nbsp;</p>
  a978-3-030-68110-401417nas a2200181   4500000000100000000000100001008004100002260005600043100002400099700001700123700001800140245005300158250006500211856005100276490001000327520087600337020002201213       2020                            d  c12/2020bSpringer International Publishingaon-line1 aTadeusz Czachórski1 aErol Gelenbe1 aDariusz Marek00aSoftware Defined Network Dynamics via Diffusions  aComputer Communication Networks and Telecommunications, LNCS  uhttps://www.springer.com/gp/book/97830306810980 v125273 a<p>Software-Defined Networks (SDN) dynamically modify the paths of Internet flows in response to the quality of service or security needs, and hence frequently modify traffic levels at network routers. Thus network routers often operate in the transient regime, rather than at steady-state, with significant impact on packet loss probabilities and delay. We, therefore, investigate the time-dependent performance of a small network of routers, modelled as G/G/1/N queueing stations. &nbsp;A diffusion approximation is developed to predict the quality of service of the routers in the transient regime. Numerical examples show that&nbsp;the results in the transient regime can differ very significantly from the steady-state results, and therefore that the&nbsp;transient analysis must be taken into account in evaluating the performance of routers in a SDN network.</p>
  a978-3-030-68110-401378nas a2200157   4500000000100000000000100001008004100002100002400043700001700067700001900084700001800103245008100121300001400202490000900216520099500225       2020                            d1 aTadeusz Czachórski1 aErol Gelenbe1 aGodlove Kuaban1 aDariusz Marek00aTime Dependent Diffusion Model for Security Driven Software Defined Networks  app. 38-560 v27923 a<p>We present a model of a Software Defined Network (SDN) where frequent changes in routing and traffic rates at routers are needed<br />
to respond to the security, quality of service (QoS), and energy savings requirements of applications such as the Internet of Things. Such frequent path and traffic changes introduce time-dependent network behaviours, and standard queueing models are not well adapted to analyse the transient regime, we propose a tractable diffusion approximation for both the transient and steady-state behaviour. Our model can represent any network topology transmitting time-dependent flows with routing changes, and computes queue length and delay distributions at each network node and along complete paths between senders and receivers. Using realistic router parameters, we show that transients occupy a significant fraction of system time, so that the optimisation conducted with SDN controllers needs to include the effect of time-dependent behaviours.</p>
01671nas a2200169   4500000000100000000000100001008004100002260001200043100002400055700001700079700001900096700001800115245007100133856004100204490000700245520124900252       2021                            d  c03/20211 aTadeusz Czachórski1 aErol Gelenbe1 aGodlove Kuaban1 aDariusz Marek00aTime-Dependent Performance of a Multi-Hop Software Defined Network  uhttps://www.mdpi.com/journal/applsci0 v113 a<p>It has been recently observed that Software Defined Networks (SDN) can change the<br />
paths of different connections in the network at a relatively frequent pace to improve the overall<br />
network performance, including delay and packet loss, or to respond to other needs such as security.<br />
These changes mean that a network that SDN controls will seldom operate in steady state; rather,<br />
the network may often be in transient mode, especially when the network is heavily loaded and<br />
path changes are critically important. Hence, we propose a transient analysis of such networks to<br />
better understand how frequent changes in paths and the switches’ workloads may affect multi-hop<br />
networks’ performance. Since conventional queueing models are difficult to solve for transient<br />
behaviour and simulations take excessive computation time due to the need for statistical accuracy,<br />
we use a diffusion approximation to study a multi-hop network controlled by SDN. The results show<br />
that network optimization should consider the transient effects of SDN and that transients need to be<br />
included in the design of algorithms for SDN controllers that optimize network performance.</p>
00431nas a2200169   4500000000100000000000100001008004100002260001200043100001800055700001900073700002100092700001900113700002400132700001700156245008100173490000700254       2021                            d  c05/20211 aDariusz Marek1 aAdam Domański1 aJoanna Domańska1 aJakub Szyguła1 aTadeusz Czachórski1 aJerzy Klamka00aDiffusion model of a non-integer order PIγ controller with TCP/UDP  streams0 v2301535nas a2200145   4500000000100000000000100001008004100002260003900043100001700082700001500099700001800114700002400132245009800156520113500254       2021                            d  c11/2021bIEEEaHouston, Texas, USA1 aErol Gelenbe1 aMert Nakip1 aDariusz Marek1 aTadeusz Czachórski00aDiffusion Analysis Improves Scalability of IoTNetworks to Mitigate the Massive Access Problem3 a<p>A significant challenge of IoT networks is to offer Quality of Service (QoS) and meet deadline requirements when packets from a massive number of IoT devices are forwarded to an IoT gateway. Many IoT devices tend to report their data to their wired or wireless network gateways at closely correlated instants of time, leading to congestion known as the MassiveAccess Problem (MAP), which increases the probability that the IoT data will not meet its required deadlines. Since IoT data loses much of its value if it arrives to destination beyond a required deadline, MAP has been extensively studied in the literature. Thus we first take a queueing theoretic view of the problem, and also use a Diffusion Approximation to gain insight into the IoT traffic statistics that affect MAP. Then we introduce the Quasi-Deterministic Transmission Policy (QDTP) which significantly alleviates MAP when the average traffic rate grows beyond a given level and substantially reduces the probability that IoT data deadlines are missed. The results are validated using real IoT data which has been placed in IP packets for transmission.</p>
01085nas a2200145   4500000000100000000000100001008004100002260001200043100001600055700002400071700001600095245012100111490000700232520070000239       2021                            d  c07/20211 aTomasz Nycz1 aTadeusz Czachórski1 aMonika Nycz00aDiffusion Model of Preemptive-Resume Priority Systems and Its Application to Performance Evaluation of SDN Switches.0 v213 a<p>The increasing use of Software-Defined Networks brings the need for their performance analysis and detailed analytical and numerical models of them. The primary element of such research is a model of a SDN switch. This model should take into account non-Poisson traffic and general distributions of service times. Because of frequent changes in SDN flows, it should also analyze transient states of the queues. The method of diffusion approximation can meet these requirements. We present here a diffusion approximation of priority queues and apply it to build a more detailed model of SDN switch where packets returned by the central controller have higher priority than other packets.</p>
01800nas a2200169   4500000000100000000000100001008004100002260001200043100001900055700001700074700001600091700002400107700002000131245014200151490000700293520133000300       2021                            d  c06/20211 aGodlove Kuaban1 aTulin Atmaca1 aAmira Kamli1 aTadeusz Czachórski1 aPiotr Czekalski00aPerformance Analysis of Packet Aggregation Mechanisms and Their Applications in Access (e.g., IoT, 4G/5G), Core, and Data Centre Networks0 v213 aThe transmission of massive amounts of small packets generated by access networks
through high-speed Internet core networks to other access networks or cloud computing data centres has introduced several challenges such as poor throughput, underutilisation of network resources,  and higher energy consumption. Therefore, it is essential to develop strategies to deal with these challenges. 
One of them is to aggregate smaller packets into a larger payload packet, and these groups of aggregated packets will share the same header, hence increasing throughput, improving resource utilisation, and reduction in energy consumption. This paper presents a review of the packet aggregation applications in access networks (e.g., IoT and 4G/5G mobile networks), optical core networks, and cloud computing data centre networks. 
Then we propose new analytical models based on diffusion approximation for the evaluation of the performance of packet aggregation mechanisms. We demonstrate the use of measured traffic from real networks to evaluate the performance of packet aggregation mechanisms analytically. The use of diffusion approximation allows us to consider time-dependent queueing models with general interarrival and service time distributions. Therefore these models are more general than others presented till now.
02934nas a2200145   4500000000100000000000100001008004100002260004200043100001700085700001600102700001900118700002400137245009600161520253100257       2021                            d  c January 2021bSpringeraNice, France1 aTulin Atmaca1 aAmira Kamli1 aGodlove Kuaban1 aTadeusz Czachórski00aPerformance Evaluation of the Packet Aggregation Mechanism of an N-GREEN Metro Network Node3 a<p><span style="background-color:rgb(255, 255, 255); color:rgb(51, 51, 51); font-family:hind,arial,sans-serif; font-size:15px">Today’s telecommunication network infrastructure and services are dramatically changing due partially to the rapid increase in the amount of traffic generation and its transportation. This rapid change is also caused by the increased demand for a high quality of services and the recent interest in green networking strengthened by cutting down carbon emission and operation cost. Access networks generate short electronic packets of different sizes, which are aggregated into larger optical packets at the ingress edge nodes of the optical backbone network. It is transported transparently in the optical domain, reconverted into the electronic domain at the egress edge nodes, and delivered to the destination access networks. Packet aggregation provides many benefits at the level of MAN, and core networks such as, increased spectral efficiency, energy efficiency, optimal resource utilisation, simplified traffic management which significantly reduces protocol and signalling overhead. However, packet aggregation introduces performance bottleneck at the edge node as the packets from the access networks are temporarily stored in the aggregation buffers during the packet aggregation process. In this article, we apply the diffusion approximation model and other stochastic modelling methods to analytically evaluate the performance of a new packet aggregation mechanism which was developed specifically for an N-GREEN (Next Generation of Routers for Energy Efficiency) metro network. We obtain the distribution of the packets’ queue in the aggregation buffer, which influences the distribution of the waiting time (delay) experienced by packets in the aggregation buffer. We then, demonstrate the influence of the probability&nbsp;</span><em>p</em><span style="background-color:rgb(255, 255, 255); color:rgb(51, 51, 51); font-family:hind,arial,sans-serif; font-size:15px">&nbsp;of successfully inserting the packet data units from the aggregation queue to the optical ring within a defined timeslot&nbsp;</span><span style="background-color:rgb(255, 255, 255); color:rgb(51, 51, 51); font-family:hind,arial,sans-serif; font-size:15px">Δ</span><span style="background-color:rgb(255, 255, 255); color:rgb(51, 51, 51); font-family:hind,arial,sans-serif; font-size:15px">. We also discuss the performance evaluation of the complete ring by deriving the utilisation of each link.</span></p>
00491nas a2200193   4500000000100000000000100001000000100002008004100003260004800044100002200092700002400114700001700138700002200155700001800177245006400195300000800259490000800267020002200275       2021                            d  bSpringeraVirtual Event, June 28–29, 20211 aAleksander Byrski1 aTadeusz Czachórski1 aErol Gelenbe1 aKrzysztof Grochla1 aYuko Murayama00aComputer Science Protecting Human Society Against Epidemics  a1250 v616  a978-3-030-86582-501329nas a2200169   4500000000100000000000100001008004100002260001200043100001600055700001600071700002400087245007500111856004500186490000600231520090800237022001401145       2021                            d  c12/20211 aMonika Nycz1 aTomasz Nycz1 aTadeusz Czachórski00aFluid-Flow Approximation in the Analysis of Vast Energy-Aware Networks  uhttps://www.mdpi.com/2227-7390/9/24/32790 v93 a<p>The paper addresses two issues: (i) modeling dynamic flows transmitted in vast TCP/IP networks and (ii) modeling the impact of energy-saving algorithms. The approach is based on the fluid-flow approximation, which applies first-order differential equations to analyze the evolution of queues and flows. We demonstrate that the effective implementation of this method overcomes the constraints of storing large data in numerical solutions of transient problems in vast network topologies. The model is implemented and executed directly in a database system. It can analyze transient states in topologies of more than 100,000 nodes, i.e., the size which was not considered until now. We use it to investigate the impact of an energy-saving algorithm on the performance of a vast network. We find that it reduces network congestion and save energy costs but significantly lower network throughput.</p>
  a2227-739000511nas a2200181   4500000000100000000000100001008004100002100001800043700001900061700002100080700001900101700002400120700001700144700002000161245006400181856007700245490000700322       2022                            d1 aDariusz Marek1 aAdam Domański1 aJoanna Domańska1 aJakub Szyguła1 aTadeusz Czachórski1 aJerzy Klamka1 aKatarzyna Filus00aApproximation Models for the Evaluation of TCP/AQM Networks  uhttps://journals.pan.pl/dlibra/publication/141986/edition/123961/content0 v7001328nas a2200145   4500000000100000000000100001008004100002260002700043100001700070700001500087700001800102700002400120245006800144520097000212       2022                            d  bSpringeraNice, France1 aErol Gelenbe1 aMert Nakip1 aDariusz Marek1 aTadeusz Czachórski00aMitigating the Massive Access Problem in the Internet of Things3 a<p>The traffic from the large number of IoT devices connected to the IoT is a source of congestion known as the Massive Access Problem (MAP), that results in packet losses, delays and missed deadlines for realtime data. This paper reviews the literature on MAP and summarizes recent results on two approaches that have been designed to mitigate MAP. One approach is based on randomizing the packet arrival instants to IoT gateways within a given time interval that is chosen so that packet arrivals do not exceed their deadlines, but also so that they do not constitute bulk arrivals. The second approach is a novel traffic shaping policy named the Quasi-Deterministic-Transmission-Policy (QDTP) which has been proved to drastically reduce queue formation at the receiving gateway by delaying packet departures from the IoT devices in a judicious manner. Both analytical and experimental results are summarized, that describe the benefits of these techniques.</p>
00999nas a2200133   4500000000100000000000100001008004100002260001200043100001700055700001500072700002400087245004500111520070900156       2022                            d  c08/20221 aErol Gelenbe1 aMert Nakip1 aTadeusz Czachórski00aImproving Massive Access to IoT Gateways3 a<p>IoT networks handle incoming packets from large numbers of IoT Devices (IoTDs) to IoT Gateways. This can lead to the IoT Massive Access Problem that causes buffer overflow, large end-to-end delays and missed deadlines. This paper analyzes a novel traffic shaping method named the Quasi-Deterministic Traffic Policy (QDTP) that mitigates this problem by shaping the incoming traffic without increasing the end-to-end delay or dropping packets. Using queueing theoretic techniques and extensive data driven simulations with real IoT datasets, the value of QDTP is shown as a means to considerably reduce congestion at the Gateway, and significantly improve the IoT network’s overall performance.</p>
01281nas a2200157   4500000000100000000000100001008004100002260002700043100002400070700001700094700001900111700001800130245005000148490000900198520091600207       2022                            d  bSpringeraNice, France1 aTadeusz Czachórski1 aErol Gelenbe1 aGodlove Kuaban1 aDariusz Marek00aOptimizing Energy Usage for an Electric Drone0 v15963 a<p>Unmanned Aerial Vehicles (UAVs) are rapidly gaining popu-<br />
larity in a wide variety of applications, e.g., agriculture, health care, envi-<br />
ronmental management, supply chains, law enforcement, surveillance,<br />
and photography. Dones are often powered by batteries, making energy<br />
a critical resource that must be optimised during the mission of the<br />
drone. The duration of a done’s mission depends on the amount of energy<br />
required to perform some manoeuvering actions (takeoff, level flight, hov-<br />
ering, and landing), the energy required to power the ICT modules in<br />
the drone, the drone’s speed, payload, and the wind. In this paper, we<br />
present a model that minimizes the energy consumption of a low power<br />
drone and maximizes the time required to completely drain the drone’s<br />
battery and ensure the safe landing of the drone.</p>
01364nas a2200133   4500000000100000000000100001008004100002260002300043100002400066700001700090700001900107245007900126520102500205       2022                            d  bIEEEaNice, France1 aTadeusz Czachórski1 aErol Gelenbe1 aGodlove Kuaban00aModelling energy changes in the energy harvesting battery of an IoT device3 a<p>The complexity of battery-powered autonomous de-<br />
vices such as Internet of Things (IoT) nodes or Unmanned Aerial<br />
Vehicles (UAV) and the necessity to ensure an acceptable quality<br />
of service, reliability, and security, have significantly increased<br />
their energy demand. In this paper, we discuss using a diffusion<br />
approximation process to approximate the dynamic changes in<br />
the energy content of a battery. We consider the case when<br />
energy harvesting sources are constantly charging the battery.<br />
The model assumes a probabilistic consumption and delivery of<br />
energy, giving the time-dependent distributions of the energy at<br />
the battery, of the time remaining until it becomes empty, the<br />
time required to charge the battery to its total capacity, or the<br />
time it is operational between two moments of complete depletion.<br />
When possible, we compare the diffusion approximation results<br />
with corresponding Markovian models.</p>
01293nas a2200133   4500000000100000000000100001008004100002260003900043100002400082700001700106700001900123245007900142520093800221       2023                            d  c03/2023bIEEE XploreaNice, France1 aTadeusz Czachórski1 aErol Gelenbe1 aGodlove Kuaban00aModelling energy changes in the energy harvesting battery of an IoT device3 a<p>The complexity of battery-powered autonomous devices such as Internet of Things (IoT) nodes or Unmanned Aerial Vehicles (UAV) and the necessity to ensure an acceptable quality of service, reliability, and security have significantly increased their energy demand. In this paper, we discuss using a diffusion approximation process to approximate the dynamic changes in the energy content of a battery. We consider the case when energy harvesting sources are constantly charging the battery. The model assumes a probabilistic consumption and delivery of energy, giving the time-dependent distributions of the energy at the battery, of the time remaining until it becomes empty, the<br />
time required to charge the battery to its total capacity, or the time it is operational between two moments of complete depletion.<br />
When possible, we compare the diffusion approximation results with corresponding Markovian models.</p>
01276nas a2200193   4500000000100000000000100001000000100002008004100003260002700044100002400071700001700095700001900112700001800131245005000149300001200199490000900211520084000220020002201060       2022                            d  bSpringeraNice, France1 aTadeusz Czachórski1 aErol Gelenbe1 aGodlove Kuaban1 aDariusz Marek00aOptimizing Energy Usage for an Electric Drone  a61–750 v15963 a<p>Unmanned Aerial Vehicles (UAVs) are rapidly gaining popularity in a wide variety of applications, e.g., agriculture, health care, environmental management, supply chains, law enforcement, surveillance, and photography. Dones are often powered by batteries, making energy<br />
a critical resource that must be optimised during the mission of the drone. The duration of a done’s mission depends on the amount of energy required to perform some manoeuvering actions (takeoff, level flight, hovering, and landing), the energy required to power the ICT modules in the drone, the drone’s speed, payload, and the wind. In this paper, we present a model that minimizes the energy consumption of a low-power drone and maximizes the time required to completely drain the drone’s battery and ensure the safe landing of the drone.</p>
  a978-3-031-09357-902144nas a2200169   4500000000100000000000100001008004100002260001200043100001900055700001700074700002400091700002000115700001800135245012900153490000700282520168500289       2023                            d  c07/20231 aGodlove Kuaban1 aErol Gelenbe1 aTadeusz Czachórski1 aPiotr Czekalski1 aJulius Tangka00aModelling of the Energy Depletion Process and Battery Depletion Attacks for Battery-Powered Internet of Things (IoT) Devices0 v233 a<pre>
The Internet of Things (IoT) is transforming almost every industry, including agriculture, food processing, health care, oil and gas, environmental protection, transportation and logistics, manufacturing, home automation, and safety. Cost-effective, small-sized batteries are often used to power IoT devices being deployed with limited energy capacity. The limited energy capacity of IoT devices makes them vulnerable to battery depletion attacks designed to exhaust the energy stored in the battery rapidly and eventually shut down the device. In designing and deploying IoT devices, the battery and device specifications should be chosen in such a way as to ensure a long lifetime of the device. This paper proposes diffusion approximation as a mathematical framework for modelling the energy depletion process in IoT batteries. We applied diffusion or Brownian motion processes to model the energy depletion of a battery of an IoT device. We used this model to obtain the probability density function, mean, variance, and probability of the lifetime of an IoT device. Furthermore, we studied the influence of active power consumption, sleep time, and battery capacity on the probability density function, mean, and probability of the lifetime of an IoT device. We modelled ghost energy depletion attacks and their impact on the lifetime of IoT devices. We used numerical examples to study the influence of battery depletion attacks on the distribution of the lifetime of an IoT device. We also introduced an energy threshold after which the device's battery should be replaced in order to ensure that the battery is not completely drained before it is replaced. </pre>
01685nas a2200145   4500000000100000000000100001008004100002260004300043100001900086700001700105700002400122700002000146245009000166520128300256       2024                            d  c16/01/2024bIEEEaStony Brook, NY, USA1 aGodlove Kuaban1 aErol Gelenbe1 aTadeusz Czachórski1 aPiotr Czekalski00aModelling the Energy Performance of Off-Grid Sustainable Green Cellular Base Stations3 a<pre>
There is a growing awareness of the need to reduce carbon emissions from the operation of mobile networks. The massive deployment of ultra-dense 5G and IoT networks will significantly increase energy demand and put the electricity grid under stress while also driving up operational costs. In this paper, we model the energy performance of an off-grid sustainable green cellular base station site which consists of a solar power system, Battery Energy Storage (BESS) and Hydrogen Energy Storage (HESS) system, and various types of macrocells, microcells, picocells, or femtocells, with broadband optical or microwave transmission systems, and other electrical and electronic systems (air conditioner, power converters, and controllers. We propose diffusion-based models of the charging and discharging processes of the energy storage systems, and obtain the probability of charging them to their full capacities during the day and completely discharging them at the end of each day. We also investigate the impact of design parameters such as the mean charging rate and the mean discharging rate on the probability densities of charging BESS and HESS to their full capacities during the day and of completely discharging them before the end of each night period. </pre>
01666nas a2200169   4500000000100000000000100001008004100002260000900043100001900052700002400071700001700095700001800112700002000130245009500150520122900245020002201474       2024                            d  bIEEE1 aGodlove Kuaban1 aTadeusz Czachórski1 aErol Gelenbe1 aSapana Sharma1 aPiotr Czekalski00aA Markov model for a Self-Powered Green IoT Device with State-Dependent Energy Consumption3 a<pre>
The growing concerns about the resource sustainability and environmental impact of deploying billions or trillions of IoT devices in the various sectors of society or economy have given rise to an energy research field known as Green-IoT (G-IoT). G-IoT emphasises the need to prioritise energy efficiency and the reduction of pollution in the IoT ecosystem. This paper presents a Markov model for a self-powered Green IoT device with state-dependent energy consumption. The model evaluates the energy performance of a self-powered Green IoT device. We derive the probability distribution of the energy content of the battery, including the probability that the energy stored in the battery is completely depleted and the density of the lifetime of the IoT device. We investigate the influence of some design parameters on the results. Introducing the threshold at which the device is forced to enter an energy-saving regime significantly increases a G-IoT device's lifetime. Apart from deploying energy-efficient mechanisms to increase the lifetime of a G-IoT device, integrating an efficient energy harvesting system into the device will increase its lifetime and reduce the frequency of battery replacement.</pre>
  a979-8-3503-3691-702099nas a2200181   4500000000100000000000100001008004100002260004000043100001900083700002400102700001700126700001600143700001900159700002000178245008400198520161300282020002201895       2024                            d  c17/07/2024bIEEEaAyia Napa, Cyprus1 aGodlove Kuaban1 aTadeusz Czachórski1 aErol Gelenbe1 aPiotr Pecka1 aValery Nkemeni1 aPiotr Czekalski00aEnergy performance of Internet of Things (IoT) networks for pipeline monitoring3 a<pre>
Pipelines are the most convenient ways to transport fluids (e.g., water, oil, and gas). However, leakage of fluids into the environment results in resource wastage (especially water, which is becoming a scarce resource) and environmental pollution (in the case of leakage of toxic fluids like oil and gas). Emerging technologies like the Internet of Things (IoT), Wireless Sensor Networks (WSNs), Artificial Intelligence (AI), distributed computing, and cloud computing enable continuous monitoring of pipelines to detect leakages and corrosion on the pipeline. The main challenge with using battery-powered sensor nodes to monitor pipelines is the energy constraint, necessitating frequent battery replacement. Thus, there is a need to develop energy-saving mechanisms to prolong the lifetime of these sensor nodes. In this paper, we use the diffusion approximation modelling framework in which the data from the experimental testbed are used to model the dynamics of the battery's energy content and to estimate the mean and variance of the device's lifetime. The novelty in the proposed diffusion model of the battery of an IoT node is the introduction of multiple energy thresholds that split the energy state-space of the battery into multiple energy-saving regimes. As the battery discharges, the node gradually transitions into energy-saving regimes by reconfiguring some of its parameters to reduce energy consumption (sometimes at the cost of trading off some performance metrics). We investigate the impact of energy-saving regimes or the number of thresholds on the node's lifetime.</pre>
  a979-8-3503-6126-101486nas a2200169   4500000000100000000000100001008004100002260001500043100001900058700001700077700002400094700002000118700001900138245006400157490000800221520108700229       2024                            d  c10/07/20241 aGodlove Kuaban1 aErol Gelenbe1 aTadeusz Czachórski1 aPiotr Czekalski1 aValery Nkemeni00aEnergy Performance of Off-Grid Green Cellular Base Stations0 v1653 a<pre>
The most energy-hungry parts of mobile networks are the base station sites, which consume around $60-80\%$ of their total energy. One of the approaches for relieving this energy pressure on the electricity grid infrastructure and reducing the Operational Expenditures (OPEX) is to power base stations with renewable energy. However, the design of a green mobile network requires the dimensioning of the energy harvesting and storage systems through the estimation of the network's energy demand. Therefore, this paper develops a diffusion-based modelling framework for solar-powered green off-grid base station sites. We apply this framework to evaluate the energy performance of homogeneous and hybrid energy storage systems supplied by harvested solar energy. We present the complete analysis, with numerical examples, to study the relationship between the design parameters and the energy performance metrics. The numerical computations demonstrate how the proposed framework can be applied to evaluate homogeneous and unconventional hybrid energy storage systems.</pre>
01587nas a2200145   4500000000100000000000100001008004100002100001900043700002400062700002000086245014600106856012400252520104300376020002201419       2024                            d1 aGodlove Kuaban1 aTadeusz Czachórski1 aPiotr Czekalski00aMarkov Models for Dimensioning and Provisioning of Battery Energy Storage Systems (BESS) for Off-Grid Green Mobile Network Base Station Sites  uchrome-extehttps://icmss.nust.na/sites/default/files/ICMSS-1%20Conference%20Proceedings_1st%20Edition_Final-11apr24.pdf3 a<pre>
There is a growing desire by mobile network operators and other stakeholders to reduce carbon emissions from the operation of mobile networks. The widespread adoption of ultra-dense 5G and Internet of Things (IoT) networks will likely increase the energy demand from these networks significantly. In this paper, we model the density of the time required to charge BESS to its full capacity when the renewable energy sources can generate enough energy to meet the needs of the base station site and the density of the time required to completely deplete the energy stored in BESS when the renewable energy sources cannot generate a sufficient amount of energy to meet the demand of the site. We also investigate the influence of the design parameters, such as the energy supply-demand ratio, on the distribution of the time required to charge BESS to its full capacity (for a supply-demand ratio greater than one) and the time required to completely deplete the energy stored in BESS (for supply-demand ratio less than one).</pre>
  a978-99916-55-80-200430nas a2200145   4500000000100000000000100001008004100002260001200043100001600055700001600071700002400087245009400111856007200205490000700277       2024                            d  c09/20241 aMonika Nycz1 aTomasz Nycz1 aTadeusz Czachórski00aDropping or Marking: a Review and Evaluation of  Existing Fluid-Flow Approximation Models  uhttp://journals.pan.pl/Content/131546/PDF/BPASTS_2024_72_5_4300.pdf0 v7202260nas a2200205   4500000000100000000000100001008004100002260001500043100001900058700002400077700001700101700001600118700001800134700001800152700001900170700002000189245005500209490000700264520178300271       2024                            d  c07/11/20241 aGodlove Kuaban1 aTadeusz Czachórski1 aErol Gelenbe1 aPiotr Pecka1 aSapana Sharma1 aPradeep Singh1 aValery Nkemeni1 aPiotr Czekalski00aEnergy performance of self-powered Green IoT nodes0 v123 a<p>The widespread adoption of the Internet of Things (IoT) partly depends on the successful design and deployment of IoT nodes that can operate for several years without any service outage and the need to replace their energy storage systems (e.g., battery, capacitor, or supercapacitor) when all the stored energy is depleted or when the cycle life of the Energy Storage Systems (ESS) is reached. Replacing batteries in the case of large-scale IoT networks and nodes located in places that are hard to reach is very challenging and costly, requiring the design of IoT nodes that can operate for several years without the need for human intervention. One such example is the deployment of IoT nodes in large agricultural fields (for soil or crop monitoring) or a long-distance pipeline (for pipeline monitoring). This paper investigates the practical implications of imposing energy-saving thresholds on the energy performance metrics of green IoT nodes. We propose an energy packet-based model for the evaluation of the energy performance of a green IoT node with the possibility of switching the node to energy-saving regimes on the fly when the energy content of the ESS reaches defined thresholds. Configuring single or multiple thresholds improves the energy performance of the node significantly (e.g., increases the lifetime of the node and reduces the probability of service outage and energy wastage), and the value of the threshold(s) should be carefully chosen. The energy performance of the IoT node can also be improved by dimensioning the energy harvesting system to ensure that the node operates for several years without running out of energy (e.g., maximizing the lifetime of the nodes and minimising the probability of service outage and energy wastage).</p>
01664nas a2200181   4500000000100000000000100001008004100002260002500043100001900068700002400087700001700111700001600128700001900144700002000163245007400183856005100257520117400308       2024                            d  bIEEEaKrakow, Poland1 aGodlove Kuaban1 aTadeusz Czachórski1 aErol Gelenbe1 aPiotr Pecka1 aValery Nkemeni1 aPiotr Czekalski00aImpact of energy leakage on the energy performance of green IoT nodes  uhttps://ieeexplore.ieee.org/document/10786519 3 a<p>In the present paper, we investigate the impact of imperfections (non-idealities) of the energy storage system (e.g., batteries, capacitors, or supercapacitors) on the energy performance of green IoT nodes. In particular, we investigate the impact of energy leakage from the Energy Storage System (ESS) on important energy performance metrics, such as service outage probability, the density of the lifetime of the node, and the time-dependent mean number of energy packets (EPs) in the ESS. Also, we explore various strategies that can be employed to compensate for the impact of energy losses due to energy leakage on the energy performance metrics. Specifically, we examine two potential strategies for improving the energy performance of the IoT nodes: (i) through increasing the energy generation rate of the energy harvesters (e.g., by adding additional solar panels or replacing the existing solar panels with more efficient ones that can produce more energy), and (ii) through reducing the energy consumption rate of the IoT node (e.g., by configuring ESS energy thresholds below which the nodes are forced to operate in low energy consumption states).</p>
01697nas a2200157   4500000000100000000000100001008004100002260001300043100001900056700001900075700002400094700002000118700001800138245008300156520130000239                                       d  bSpringer1 aGodlove Kuaban1 aValery Nkemeni1 aTadeusz Czachórski1 aPiotr Czekalski1 aEric Djomadji00aDimensioning the renewable energy system of a Green Cellular Base Station Site3 a<p>The demand for mobile communication services has experienced astronomical growth in the past few decades and continues to grow steadily at a brisk rate. This is due partly to falling prices of user devices, the evolution of mobile applications, the widespread adoption of social media, and the recent advances in modern technologies such as the Internet of Things (IoT), cloud/fog computing, and Artificial Intelligence (AI). An expansion of mobile communication infrastructure to accommodate the rapidly growing demand and to migrate to new technologies (e.g., 4G/5G) have also resulted in a significant increase in the energy consumption of mobile networks. An attractive solution to reduce the carbon footprint of mobile networks and to reduce the energy bills of network operators is to deploy renewable energy systems(e.g., solar energy systems) to power base station sites. In this paper, we present a practical approach for dimensioning and evaluating renewable generation and storage systems for cellular base station sites. We use data collected from a base station site in Banda (North region of Cameroon) as input to the analytical model; we estimate the probability of service outage (when all the stored energy is consumed and the PV system is not able to generate energy).</p>
01866nas a2200169   4500000000100000000000100001008004100002260003900043100001900082700001600101700001600117700002400133700002000157245010800177520138900285020002201674       2025                            d  c07/2025bSpringer, ChamaSingapore1 aGodlove Kuaban1 aTomasz Nycz1 aMonika Nycz1 aTadeusz Czachórski1 aPiotr Czekalski00aModelling the Transient Evolution of Queues in Plugged-in Electric Vehicles(PEV) Fast Charging Stations3 a<p>The transportation sector is responsible for approximately 23% of global greenhouse gas (GHG) emissions, with road transportation contributing nearly 70% of these emissions. The widespread adoption of electric vehicles (EVs) is transforming this sector by reducing emissions and decreasing reliance on fossil fuels. However, the growing number of EVs presents significant challenges for charging infrastructure, particularly in managing long queues, extended wait times, and limited station capacity. Most existing studies on the performance of electric vehicle charging stations assume Poisson arrivals and exponential charging times, simplifications that often overlook real-world variability. This paper introduces a generalized queueing model that leverages empirical interarrival and charging duration data for more accurate performance evaluation. A transient analysis is conducted, examining two operational optimization strategies aimed at minimizing queue sizes during peak demand: (1) a queue management policy that encourages charging only up to a predefined state-of-charge (SoC) threshold instead of the typical 80–100%, and (2) dynamic control of the number of active charging ports based on demand. The results show that these operational optimization policies improve the efficiency of the charging station and significantly improve the customer experience.</p>
  a978-3-031-97635-302085nas a2200133   4500000000100000000000100001008004100002100001900043700002400062700001700086700002000103245013100123520169700254       2025                            d1 aGodlove Kuaban1 aTadeusz Czachórski1 aErol Gelenbe1 aPiotr Czekalski00aTime-Dependent Analysis of the Interaction Between Energy Harvesting, Leakage, and Consumption Processes in a Green IoT Device3 a<p>The Internet of Things (IoT) is transforming industries by enhancing productivity and efficiency; however, energy availability remains a significant challenge due to the limited capacity of batteries and supercapacitors powering IoT devices. The emergence of Green IoT (G-IoT) frameworks, which prioritize energy efficiency and renewable energy integration, offers a promising solution to address this challenge. Despite these advancements, energy storage systems (ESSs) face issues such as capacity degradation, leakage, and charge redistribution, which can lead to energy depletion and service disruptions. Traditional models often assume constant energy harvesting rates, overlooking the time-varying nature of environmental conditions that influence energy availability. In this paper, we propose a novel mathematical framework that incorporates time-dependent fluctuations in the energy harvesting rate to analyse the dynamic interactions between energy harvesting, leakage, and consumption in green IoT systems. Our approach includes an Energy Packet Network (EPN) model to represent transient energy dynamics and a Markov model to capture fluctuations in the energy harvesting rate. Through numerical simulations, we evaluate the impact of key design parameters, such as ESS capacity, mean energy consumption rate, energy leakage, and energy harvesting rate variations, on critical performance metrics including the probability of energy depletion and the transient mean number of stored energy packets. The results highlight the importance of considering time-varying energy harvesting in the design and optimization of IoT systems for long-term operation and sustainability.</p>
02041nas a2200157   4500000000100000000000100001008004100002260004100043100001900084700001700103700001800120700002400138700002000162245010800182520159300290       2025                            d  c02/12/2025bIEEEaMarrakech, Morocco1 aGodlove Kuaban1 aTulin Atmaca1 aZeynep Turgut1 aTadeusz Czachórski1 aPiotr Czekalski00aLeveraging Packet Aggregation to Optimise QoS and Energy Trade-offs in 5G/6G Optical Fronthaul Networks3 a<p>The growing demands of 5G and emerging 6G mobile networks—driven by the proliferation of IoT devices, immersive applications, and high-throughput services—necessitate more efficient and scalable fronthaul solutions. Open Radio Access Networks and cloud-RAN architectures offer promising frameworks by decoupling hardware and software and enabling centralised processing. However, the fronthaul segment still faces challenges related to bandwidth inefficiency, signalling overhead, and relatively high energy consumption, particularly due to the transmission of vast numbers of small packets. Packet aggregation emerges as a viable strategy to mitigate these challenges by grouping multiple small packets into larger payloads, thereby reducing protocol overhead, improving throughput efficiency, and lowering energy consumption in the network as a whole. This paper investigates the impact of packet aggregation on both quality of service (QoS) and energy efficiency in the fronthaul of 5G/6G mobile networks. While prior studies have examined its effects on throughput and latency, the implications for energy consumption remain underexplored. We evaluate how aggregation design parameters—such as time thresholds, size thresholds, and traffic intensity—influence performance metrics such as throughput and latency. We also propose ways to achieve an optimal trade-off between QoS and energy efficiency.&nbsp;Our findings offer insights into the design of energy-aware, delay-sensitive packet aggregation schemes tailored for next-generation mobile network architectures.</p>
02212nas a2200157   4500000000100000000000100001008004100002260003300043100001900076700002400095700001700119700001600136700002000152245011000172520177200282       2025                            d  c12/2025bIEEEaParis, France1 aGodlove Kuaban1 aTadeusz Czachórski1 aErol Gelenbe1 aPiotr Pecka1 aPiotr Czekalski00aEnergy Dynamics of Green IoT Nodes with Time-Varying Energy Harvesting, Leakage, and Consumption Patterns3 a<p>The growing proliferation of Internet of Things (IoT) devices has intensified the need for sustainable energy solutions, particularly in resource-constrained deployments where non-rechargeable batteries and supercapacitors are the primary energy sources. Green IoT (G-IoT) frameworks address this challenge by combining energy-saving techniques with energy harvesting from ambient sources such as solar power. However, the intermittent nature of renewable energy and the non-ideal behavior of energy storage systems—such as energy leakage and capacity degradation—complicate reliable energy provisioning. This paper presents a novel Markovian framework for modelling the coupled dynamics of time-varying solar energy harvesting, time-dependent energy consumption, and state-dependent energy leakage in G-IoT systems. Unlike traditional steady-state models, our approach uses Discrete-Time Markov Chains (DTMCs) to capture the stochastic variability in both energy harvesting and consumption processes. We also introduce a refined leakage model in which the leakage rate is dynamically dependent on the stored energy level, enabling a more realistic characterization of energy losses due to energy leakage. Through extensive analytical evaluation, we examine how key parameters—such as storage capacity, leakage rate coefficient, and energy harvesting and consumption patterns—affect critical performance metrics, including the mean stored energy and energy-related service outage probability. Furthermore, we propose a parameter tuning strategy to optimize energy reliability and storage efficiency. The proposed model provides valuable insights for the design and optimization of robust, energy-aware IoT systems powered by renewable energy sources.</p>
01648nas a2200145   4500000000100000000000100001008004100002260003300043100001900076700002400095700001700119700002000136245007700156520126900233       2025                            d  c12/2025bIEEEaParis, France1 aGodlove Kuaban1 aTadeusz Czachórski1 aTulin Atmaca1 aPiotr Czekalski00aAnalytical Power Efficiency Models for Open Radio Access Network (O-RAN)3 a<p>The rapid deployment of 5G and the anticipated evolution to 6G have intensified the need for energy-efficient radio access networks, driven by rapidly growing power demands, rising energy costs, and environmental concerns. Open Radio Access Networks (O-RAN) offer a flexible and scalable architecture; however, their disaggregated nature requires accurate power modelling to optimise energy consumption. This paper proposes enhanced power consumption models for O-RAN that account for power efficiency gains from resource sharing across multiple radio units (O-RUs) and the offloading of highly parallel baseband processing tasks to specialised energy-efficient hardware accelerators such as ASICs, FPGAs, or GPUs. The models are used to analyse the scaling behavior of O-RUs, distributed units (O-DUs), and centralized units (O-CUs) under varying deployment scenarios. Results show that O-RUs dominate the total network power budget, while O-DUs benefit from sublinear growth due to statistical multiplexing, and O-CUs scale the slowest owing to centralised control-plane sharing. Furthermore, the study identifies optimal ranges of RU-to-DU aggregation and accelerator utilization for maximising energy efficiency in large-scale 5G/6G O-RAN deployments.</p>
01617nas a2200145   4500000000100000000000100001008004100002260002900043100001900072700002400091700001700115700002000132245005800152520126100210                                       d  bIEEEaLas Vegas, NV, USA1 aGodlove Kuaban1 aTadeusz Czachórski1 aTulin Atmaca1 aPiotr Czekalski00aPower models for O-RAN O-DU planning and optimisation3 a<p>The transition from 5G to 6G networks is driving an unprecedented densification of Radio Access Networks (RANs), resulting in increased energy demand and operational costs. Open RAN (O-RAN) architectures, which disaggregate baseband processing across commercial off-the-shelf (COTS) servers, further amplify these challenges due to the power sensitivity of the Distributed Unit (O-DU) to traffic load variations.&nbsp;This paper develops a nonlinear O-DU power model that captures load-dependent efficiency effects and integrates it into a dynamic core management framework, which activates or deactivates CPU cores based on instantaneous traffic demand. The effectiveness of the proposed dynamic core management framework is investigated in multi-RU O-RAN scenarios, comparing the proposed dynamic approach with a static baseline. Simulation results show that the dynamic scheme reduces energy consumption by up to $59.42\%$ on average under light traffic, with instantaneous savings exceeding $70\%$ during off-peak periods, while maintaining performance. These findings demonstrate that workload-aware core provisioning can deliver substantial energy efficiency gains in O-RAN deployments, particularly in lightly to moderately loaded networks.</p>
01208nas a2200217   4500000000100000000000100001008004100002260003300043653000900076100002400085700002200109700001600131700001700147700001600164700001700180700001600197700001600213245007200229856005000301520063900351       2026                            d  c02/2026bIEEEaLas Vegas USA10aLoRa1 aTadeusz Czachórski1 aKrzysztof Grochla1 aPiotr Pecka1 aAnna Strzoda1 aJ. Fourneau1 aLynda Mokdad1 aMonika Nycz1 aTomasz Nycz00aThe impact of CSMA on LoRaWAN gateways' performance in IoT networks  uhttps://ieeexplore.ieee.org/document/113665363 a<p>The CSMA mode of operation was recently added to the LoRaWAN standard. We investigate, using a queueing model, how the introduction of CSMA in the communication between devices and the gate in LoRaWan may increase the probability of successful transmission. &nbsp;In the proposed model, customers (transmissions) are served by a multichannel station (gate), and the number of channels corresponds to the number of transmissions that can be performed in parallel. We introduce a queueing model with multiple attempts to find a free channel and investigate their impact on transmission throughput and reliability.<br />
&nbsp;</p>
00237nas a2200085   4500000000100000008004100001260001200042100002400054245007300078       2026                            d  c05/20261 aTadeusz Czachórski00a Queueing Theory and Diffusion Approximation with their Applications00529nas a2200181   4500000000100000008004100001260002600042653004100068100002400109700002200133700001600155700001700171700001800188700001700206700001600223700001600239245009200255       2026                            d  bIEEEaAvignon, France10aDiffusion approximation; LPWAN; CSMA1 aTadeusz Czachórski1 aKrzysztof Grochla1 aPiotr Pecka1 aAnna Strzoda1 aJean Fourneau1 aLynda Mokdad1 aMonika Nycz1 aTomasz Nycz00aThe Impact of CSMA on LoRaWAN Communication Efficiency: A Diffusion Approximation Model