Seminar: Samosličnost mreľnog prometa
Popis literature:
Uvodni članci - pojam samosličnosti:
Majid Ghaderi: Predicting Self-Similar Internet Traffic, 2002 - puno matematike.
Abstract: Self-similarity is one of the most important characteristics of the Internet trafic. In this paper, we look at the problem of trafic prediction in the presence of self-similarity and the research in this area. We first explain the concept of self-similarity and introduce short-range and long-range dependencies. Next, we briefly describe a number of short-memory and long-memory stochastic models. Finally, we discuss the problem of modeling the Internet trafic and explain our future study.
H.-D. J. Jeongy, D. McNicklez and K. Pawlikowskiy: A Generator of Pseudo-Random Self-Similar Sequences Based on SRA - puno matematike.
Abstract: It is generally accepted that self-similar (or fractal) processes may provide better models for teletraffic in modern computer networks than Poisson processes. If this is not taken into account, it can lead to inaccurate conclusions about performance of computer networks. Thus, an important requirement for conducting simulation studies of telecommunication networks is the ability to generate long synthetic stochastic self-similar sequences. A generator of pseudo-random self-similar sequences, based on the SRA method, is implemented and analysed in this report. Properties of this generator were experimentally studied in the sense of its statistical accuracy and the time required to produce sequences of a given (long) length. This generator shows acceptable level of accuracy of the output data (in the sense of relative accuracy of the Hurst parameter) and is fast. The theoretical algorithmic complexity is O(n).
Zafer Sahinoglu and Sirin Tekinay: Self-Similar Traffic and Network Performance - Uvod u tematiku samoslicnosti u mreznom prometu.
Abstract: The main objective in telecommunications network engineering is to have as many happy users as possible. In other words, the network engineer has to resolve the trade-off between capacity and QoS requirements. Accurate modeling of the offered traffic load is the first step in optimizing resource allocation algorithms such that provision of services complies with the QoS constraints while maintaining maximum capacity. In recent years, as broadband multimedia services became popular, they necessitated new traffic models with self-similar characteristics. In this article we present a survey of the self-similarity phenomenon observed in multimedia traffic and its implications on network performance. Our current research aims to fill the gap between this new traffic model and network engineering. An immediate consequence of this study is the demonstration of the limitations or validity of conventional resource allocation methods in the presence of self-similar traffic.
Mjerenja mreznog prometa:
D. R. Avresky and V. Shurbanov, R. Horst and P. Mehra: Performance Evaluation of the ServerNetR SAN under Self-Similar Traffic.
Abstract: Self-similar traffic distributions have been observed in a wide range of networking applications and models such as LANs, WANs, telnet, FTP, WWW, ISDN, SS7 and VBR traffic over ATM. Therefore, it has been suggested that many other theoretical protocols and systems need to be reevaluated under this different type of traffic before practical implementations potentially show their faults. The ServerNet SAN is a new core technology for server architectures that focuses on moving data. It is a wormholerouted, packet-switched, point-to-point network with special attention paid to reducing latency and assuring reliability.In this paper we investigate the implications of selfsimilar traffic distributions in the ServerNet SAN, and compare the results with those obtained on the basis of the Poisson assumption.
Savvas C. Nikiforou: Assignment #2 for Computer Networks.
Abstract: The purpose of this assignment is to compare the queueing behavior of real network traffic input to an infinite size queue versus the M/M/1. To simulate the real network a trace file was used, which was taken on the USF backbone 100-Mbps Ethernet connected to the router to the Internet. The results of the experiment show the difference between the real network simulation and the M/M/1 simulation, which grow bigger as the server utilization increases. The difference in the results between the two simulations is due to the assumption that the network traffic has a Poisson arrival time as well as packet length. It is clearly shown that it is not really the case but instead the packet size as well as the arrival time histograms is showing a very bursty behavior. Another thing that it is not taken into account for the M/M/1 model is the self-similarity of the data.
Will E. Leland, Murad S. Taqqu, Walter Willinger and Daniel V. Wilson: On the Self-Similar Nature of Ethernet Traffic.
Abstract: We demonstrate that Ethernet local area network (LAN) traffic is statistically self-similar, that none of the commonly used traffic models is able to capture this fractal behavior, that such behavior has serious implications for the design, control, and analysis of high-speed, cell-based (B-ISDN) networks, and that aggregating streams of such traffic typically intensifies the selfsimilarity ("burstiness") instead of smoothing it. Intuitively, the critical characteristic of this self-similar traffic is that there is no natural length of a "burst": at every time scale ranging from a few milliseconds to minutes and hours, similar-looking traffic bursts are evident. Our conclusions are supported by a rigorous statistical analysis of hundreds of millions of high quality Ethernet traffic measurements collected between 1989 and 1992, coupled with a discussion of the underlying mathematical and statistical properties of self-similarity and their relationship with actual network behavior. We also consider some implications for congestion control in B-ISDN and present traffic models based on self-similar stochastic processes. Selfsimilar traffic models provide simple, accurate, and realistic descriptions of traffic scenarios encountered during B-ISDN deployment.
Will E. Leland, Murad S. Taqqu, Walter Willinger and Daniel V. Wilson: On the Self-Similar Nature of Ethernet Traffic - skracena verzija.
Abstract: We demonstrate that Ethernet local area network (LAN) traffic is statistically self-similar, that none of the commonly used traffic models is able to capture this fractal behavior, and that such behavior has serious implications for the design, control, and analysis of high-speed, cell-based networks. Intuitively, the critical characteristic of this self-similar traffic is that there is no natural length of a "burst": at every time scale ranging from a few milliseconds to minutes and hours, similar-looking traffic bursts are evident; we find that aggregating streams of such traffic typically intensifies the self-similarity ("burstiness") instead of smoothing it. Our conclusions are supported by a rigorous statistical analysis of hundreds of millions of high quality Ethernet traffic measurements collected between 1989 and 1992, coupled with a discussion of the underlying mathematical and statistical properties of self-similarity and their relationship with actual network behavior. We also consider some implications for congestion control in high-bandwidth networks and present traffic models based on self-similar stochastic processes that are simple, accurate, and realistic for aggregate traffic.
Marcus Brenner, Dietmar Tutsch and G¨unter Hommel: Measuring Transient Performance of a Multistage Interconnection Network Using Ethernet Networking Equipment - usporedba samoslicnosti i Poissonove razdiobe.
Abstract: Multistage interconnection networks (Banyan networks, MINs) are frequently proposed as connections in multiprocessor systems or in highbandwidth network switches. Using off-the-shelf Ethernet networking components, a small multistage interconnection network was re-created and several measurements concerning delay times and throughput were conducted on this setup using Poisson as well as selfsimilar input traffic. The analysis of the transient measurements reveals a dependency of the delays’ variance on the offered input load.
Matthew T. Lucas, Dallas E. Wrege, Bert J. Dempsey and Alfred C. Weaver: Statistical Characterization of Wide-Area IP Traffic - statisticka karakterizacija IP prometa.
Abstract: Background traffic models are fundamental to packet-level network simulation since the background traffic impacts packet drop rates, queuing delays, end-to-end delay variation, and also determines available network bandwidth. In this paper, we present a statistical characterization of widearea IP traffic based on 90-minute traces taken from a weeklong trace of packets exchanged between a large campus network, a state-wide educational network, and a large Internet service provider. The results of this analysis can be used to provide a basis for modeling background load in simulations of wide-area packet-switched networks such as the Internet, contribute to understanding the fractal behavior of widearea network utilization, and provide a benchmark to evaluate the accuracy of existing traffic models. The key findings of our study include the following: (1) both the aggregate packet stream and its component substreams exhibit significant long-range dependencies in agreement with other recent traffic studies, (2) the empirical probability distributions of packet arrivals are log-normally distributed, (3) packet sizes exhibit only short-term correlations, and (4) the packet size distribution and correlation structure are independent from both network utilization and time of day.
Mjerenje sveucilista u Budinpesti
Simulacije i modeli:
Vern Paxson and Sally Floyd: WHY WE DON'T KNOW HOW TO SIMULATE THE INTERNET, 1997.
Abstract: Simulating how the global Internet data network behaves is an immensely challenging undertaking because of the network's great heterogeneity and rapid change. The heterogeneity ranges fromthe individual links that carry the network's trafic, to the protocols that interoperate over the links, to the \mix" of different applications used at a site and the levels of congestion (load) seen on diferent links. We discuss two key strategies for developing meaningful simulations in the face of these dificulties: searching for invariants and judiciously exploring the simulation parameter space. We finish with a look at a collaborative efort to build a common simulation environment for conducting Internet studies.
Kriteriji za dizajniranje samoslicnog prometa, jako puno matematike, Abstract:
Modeliranje uz pomoc Markovljevog pristupa, jako puno matematike, Abstract:
JAMES H. COWIE, DAVID M. NICOL and ANDY T. OGIELSKI: MODELING THE GLOBAL INTERNET, 1999 - opceniti uvod.
David A. Nash and Daniel J. Ragsdale: Simulation of self-similarity in network utilization patterns as a precursor to automated testing of intrusion detection systems.
Abstract: The behavior of a certain class of automatic intrusion detection systems (IDS) may be characterized as sensing patterns of network activity which are indicative of hostile intent. An obvious technique to test such a system is to engage the IDS of interest, and then use human actors to introduce the activities of a would-be intruder. While having the advantage of realism, such an approach is difficult to scale to large numbers of intrusive behaviors. Instead it would be preferable to generate traffic which includes these manifestations of intrusive activity automatically. While such traffic would be difficult to produce in a totally general way, there are some aspects of network utilization which may be reproducible without excessive investment of resources. In particular, real network loading often exhibits patterns of self-similarity, which may be seen at various levels of time scaling. These patterns should be replicated in simulated network traffic as closely as is feasible, given the computational ability of the simulator. This motivates interest in an efficient way to detect multi-scale phenomena in network traffic, as well as a means to create simulated traffic that exhibits the desired characteristics. We propose the use of multiresolution wavelet analysis as a technique which may be used to accomplish the desired detection, and subsequent construction of self-similarity in the simulated traffic. Following a multiresolution decomposition of the traffic using an orthogonal filter bank, the resulting wavelet coef- ficients may be filtered according to their magnitude. Some of the coeficients may be discarded, yielding an efficient representation. We investigate the effect of compression upon the reconstructed signal’s selfsimilarity, as measured by its estimated Hurst parameter.
L.G. Samuel, J.M.Pitts, R.J. Mondragón: FAST SELF-SIMILAR TRAFFIC GENERATION, 1997.
Abstract: Recent measurements of high speed network traffic suggest that the traffic in such a network is self-similar. Follow-up research has been conducted in order to obtain realistic traffic models for self-similar traffic. Most of these are stochastic models based on Fractional Brownian Motion. Alternative models exist based on dynamics rather than statistics in the form of chaotic maps. If self-similar traffic can be generated quickly online then this leads to the concept of on-line modelling of networks. This paper presents the results of an accelerated single map interpretation of a chaotic map which can be used to model aggregate traffic. This approach yields a fast generator of self-similar traffic.
Vern Paxson and Sally Floyd: Wide-Area Traffic: The Failure of Poisson Modeling, 1995.
Abstract: Network arrivals are often modeled as Poisson processes for analytic simplicity, even though a number of traffic studies have shown that packet interarrivals are not exponentially distributed. We evaluate 24 wide-area traces, investigating a number of wide-area TCP arrival processes (session and connection arrivals, FTP data connection arrivals within FTP sessions, and TELNET packet arrivals) to determine the error introduced by modeling them using Poisson processes. We find that user-initiated TCP session arrivals, such as remote-login and file-transfer, are well-modeled as Poisson processes with fixed hourly rates, but that other connection arrivals deviate considerably from Poisson; that modeling TELNET packet interarrivals as exponential grievously underestimates the burstiness of TELNET traffic, but using the empirical Tcplib [Danzig et al, 1992] interarrivals preserves burstiness over many time scales; and that FTP data connection arrivals within FTP sessions come bunched into “connection bursts,” the largest of which are so large that they completely dominate FTP data traffic. Finally, we offer some results regarding how our findings relate to the possible self-similarity of wide-area traffic.
Modeliranje samoslicnog prometa
Novi modeli samoslicnog prometa
Fraktalno modeliranje mreznog prometa
Alexander Ost and Boudewijn R. Haverkort: Modeling and Evaluation of Pseudo Self-Similar Traffic with Infinite-State Stochastic Petri Nets
Abstract: We address the suitability of a recently suggested approach for approximating self-similar traffic with a Markovian model. The phasetype nature of the proposed approach is identified and used to transform it from the discrete-time to the continuous-time domain. We then investigate the performance of a simple queueing system subject to self-similar arrival traffic, thereby comparing the results of trace-driven simulation with a measured self-similar trace to those derived from a numerical analysis of the suggested model. The numerical investigations are performed using a special class of stochastic Petri nets which is particularly suited for analyzing queueing-model like situations. Our results indicate that the suggested Markovian traffic model needs still to be improved, even though the properties of self-similarity per se are well approximated.
Razmatranja:
LIANG GUO, MARK CROVELLA and IBRAHIM MATTA: How does TCP generate Pseudo-self-similarity.
Abstract: Long-range dependence has been observed in many recent Internet traffic measurements. In addition, some recent studies have shown that under certain network conditions, TCP itself can produce traffic that exhibits dependence over limited timescales, even in the absence of higher-level variability. In this paper, we use a simple Markovian model to argue that when the loss rate is relatively high, TCP’s adaptive congestion control mechanism indeed generates traffic with OFF periods exhibiting power-law shape over several timescales and thus introduces pseudo-long-range dependence into the overall traffic. Moreover, we observe that more variable initial retransmission timeout values for different packets introduces more variable packet inter-arrival times, which increases the burstiness of the overall traffic. We can thus explain why a single TCP connection can produce a time-series that can be misidentified as self-similar using standard tests.
Dr. Martin J. Fischer and Dr. Thomas B. Fowler: Fractals, Heavy-Tails, and the Internet, 2001.
Napomena: Nije cijeli.
Jon M. Peha: Protocols Can Make Traffic Appear Self-Similar, 1997.
Abstract: Empirical studies have shown that self-similar traffic models may better describe traffic in many of today's computer networks than traditional Markovian models. The causes of this apparent self-similar behavior must be identified to determine how widely applicable these models are, and how network designers should respond. While some researchers have argued self similarity is an inherent property of traffic as generated by the typical applications, it is also possible that the network's own protocols may cause or at least contribute to this phenomenon. In this paper, it is shown that even if packets were to arrive according to the wellbehaved Poisson process, simple retransmission mechanisms can make traffic appear self similar over time scales of engineering interest. Moreover, some techniques intended to decrease the likelihood of congestion also have the effect of prolonging congestion when it does occur. This increases burstiness over large time-scales, reinforcing the appearance of self-similarity.
Mark E. Crovell and Azer Bestavros: Self-Similarity in World Wide Web Traffic: Evidence and Possible Causes, 1997.
Abstract: Recently, the notion of self-similarity has been shown to apply to wide-area and local-area network traffic. In this paper, we show evidence that the subset of network traffic that is due to World Wide Web (WWW) transfers can show characteristics that are consistent with self-similarity, and we present a hypothesized explanation for that self-similarity. Using a set of traces of actual user executions of NCSA Mosaic, we examine the dependence structure of WWW traffic. First, we show evidence that WWW traffic exhibits behavior that is consistent with self-similar traftic models. Then we show that the self-shnilarity in such traftic can be explained based an the underlying distributions of WWW document sizes, the effects of caching and user preference in tile transfer, the effect of user “think time,” and the superimposition of many such transfers in a local-area network. To do this, we rely on empirically measured distributions both from client traces and from data independently collected at WWW servers.
KIHONG PARK and TSUNYI TUAN: Performance Evaluation of Multiple Time Scale TCP Under Self-Similar Traffic Conditions, 2000.
Abstract: Measurements of network traffic have shown that self-similarity is a ubiquitous phenomenon spanning across diverse network environments. In previous work, we have explored the feasibility of exploiting long-range correlation structure in self-similar traffic for congestion control. We have advanced the framework of multiple time scale congestion control and shown its effectiveness at enhancing performance for rate-based feedback control. In this article, we extend the multiple time scale control framework to window-based congestion control, in particular, TCP. This is performed by interfacing TCP with a large time scale control module that adjusts the aggressiveness of bandwidth consumption behavior exhibited by TCP as a function of “large time scale” network state, that is, information that exceeds the time horizon of the feedback loop as determined by RTT. How to effectively utilize such information - due to its probabilistic nature, dispersion over multiple time scales, and realization on top of existing window-based congestion controls - is a nontrivial problem. First, we define a modular extension of TCP (a function call with a simple interface that applies to various flavors of TCP, e.g., Tahoe, Reno, and Vegas) and show that it significantly improves performance. Second, we show that multiple time scale TCP endows the underlying feedback control with proactivity by bridging the uncertainty gap associated with reactive controls which is exacerbated by the high delay-bandwidth product in broadband wide area networks. Third, we investigate the influence of three traffic control dimensions - tracking ability, connection duration, and fairness - on performance. Performance evaluation of multiple time scale TCP is facilitated by a simulation benchmark environment based on physical modeling of self-similar traffic. We explicate our methodology for discerning and evaluating the impact of changes in transport protocols in the protocol stack under self-similar traffic conditions and discuss issues arising in comparative performance evaluation under heavy-tailed workloads.
S.A Kalim, Dr Lionel Sacks: An Investigation Using Wavelet Analysis to Detect A Change In The Characteristics Of Self-Similar Traffic
Abstract: At present threshold values are based on the mean and standard deviation of link utilisation are used as trigger to find more stable route in the network. The Aim of this paper is to use a technique based on the wavelet method (of Abry and Veitch 1998 ) to detect a real time change in the characteristics of self-similar traffic and this can be used as a threshold trigger to provide optimum path selection for routing protocols such as OSPF (Open Shortest Path First).
Gotovi simulatori:
simATM , win2000 platforma, izvorna lokacija
nam, novije verzije win2000 platforma, služi za praćenje mrežnog prometa, izvorna lokacija sa uputama i ns simulatorom ; francuska stranica o Ns-nam simulatoru, primjer za nam su ovdje. Sorce code nam-a je ovdje ili na izvornoj lokaciji
NS pocetna stranica, uputstva, simulator i mnostvo linkova; upute za instalciju.
NS 2 simulator, Unix verzija.
Popis simulatora moze se pronaci na ovoj stranici.
Generator of Self-Similar Network Traffic - verzija 1, Windows verzija, upute i kod, izvorna lokacija - po Pareto razdiobi sa ON-OFF paketima, primjer izlaza - primjer.txt.
Generator of Self-Similar Network Traffic - verzija 2, Windows verzija, upute i kod, izvorna lokacija - ima gresaka u kodu
Arnold W. Bragg: GENERATING SELF-SIMILAR TRAFFIC FOR OPNET SIMULATIONS, 1999 - opis simulatora i njegovog koristenja, link na code i upute simulatora.
Abstract: Self-similar (s-s) arrival processes are realistic models for many types of network traffic. Unfortunately, generating synthetic s-s arrivals and interarrival times for simulations is rather involved. This paper discusses six issues related to s-s traffic generation for discrete-event simulations: (i) what s-s processes are, and why they are important to network modelers; (ii) where to find a fast s-s generator; (iii) how to install the generator and synthesize s-s arrivals; (iv) how to convert s-s arrival counts to interarrival times; (v) how to build a simple OPNET process model for generating interarrivals; and (vi) how traffic from simulated s-s arrival processes compares with traffic from simulated bursty and Poisson arrival processes.
Na adresama http://www.networkinstruments.com/downloads/obs_success.html, http://www.networkinstruments.com/downloads/la_success.html i http://www.networkinstruments.com/ se moze pronaci softver i hardver za analizu i pracenje mreznog prometa, stranica ne nudi slobodan softver, ali postoje neki demo programi.
Simulator Selfis, nekoliko nerazvrstanih .PDF-a, par peferenci i 3 veryije nam-a.
Teski redovi:
Modeliranje distribucije teskih redova.
Xiaoyun Zhu, Jie Yu and John Doyle: Heavy Tails, Generalized Coding and OptimalWeb Layout
Abstract:This paper considers Web layout design in the spirit of source coding for data compression and rate distortion theory, with the aim of minimizing the average size of files downloaded during Web browsing sessions. The novel aspect here is that the object of design is layout rather than codeword selection, and is subject to navigability constraints. This produces statistics for file transfers that are heavy tailed, completely unlike standard Shannon theory, and provides a natural and plausible explanation for the origin of observed power laws in Web traffic. We introduce a series of theoretical and simulation models for optimal Web layout design with varying levels of analytic tractability and realism with respect to modeling of structure, hyperlinks, and user behavior. All models produce power laws which are striking both for their consistency with each other and with observed data, and their robustness to modeling assumptions. These results suggest that heavy tails are a permanent and ubiquitous feature of Internet traffic, and not an artifice of current applications or user behavior. They also suggest new ways of thinking about protocol design that combines insights from information and control theory with traditional networking.
Nevezano za seminar, ali vrlo slicne tematike:
Tatsuya Hagiwara, Hiroshi Majima, Takahiro Matsuda and Miki Yamamoto: Impact of Round Trip Delay Self-Similarity on TCP Performance - po principu samoslicnosti.
Abstract: Recent measurement showed that self-similar nature is found not only in network traffic volume but also round trip packet delay. In this paper, we discuss three issues of the self-similarity of round trip time (RTT), which is one of the most important parameters to determine TCPthroughput performance. First, we discuss the origin of the packet delay self-similarity. A recent study anticipated that the queueing delay of self-similar traffic is the reason for packet delay self-similarity. With computer simulation, we evaluate the correlation between traffic and RTT self-similarity. Next, we investigate the impact of RTT self-similarity on TCPthroughput performance. Computer simulation results show that RTT self-similarity gives high variability to file transfer time. Finally, we investigate the impact of RTT self-similarity on RTO (Retransmission Time Out). We discover that the bigger the Hurst parameter of RTT is, the more frequent unnecessary timeouts occurs. Furthermore, we propose a new RTO calculation algorithm to improve these unnecessary timeouts.
Bruce A. Mah: An Empirical Model of HTTP Network Traffic, 1997.
Abstract: The workload of the global Internet is dominated by the Hypertext Transfer Protocol (HTTP), an application protocol used by World Wide Web clients and servers. Simulation studies of IP networks will require a model of the traffic patterns of the World Wide Web, in order to investigate the effects of this increasingly popular application. We have developed an empirical model of network traffic produced by HTTP. Instead of relying on server or client logs, our approach is based on packet traces of HTTP conversations. Through traffic analysis, we have determined statistics and distributions for higher-level quantities such as the size of HTTP files, the number of files per “Web page”, and user browsing behavior. These quantities form a model can then be used by simulations to mimic World Wide Web network applications.
Michael Jiang, Milan Nikolic, Stephen Hardy and Ljiljana Trajkovic: IMPACT OF SELF-SIMILARITY ON WIRELESS DATA NETWORK PERFORMANCE.
Abstract: In this paper we investigate the impact of traffic patterns on wireless data networks. Modeling and simulation of the Cellular Digital Packet Data (CDPD) network of Telus Mobility (a commercial service provider) were performed using the OPNET tool. We use trace-driven simulations with genuine traffic trace collected from the CDPD network to evaluate the performance of CDPD protocol. This trace tends to exhibit longrange dependent behavior. Our simulation results indicate that genuine traffic traces, compared to traditional traffic models such as the Poisson model, produce longer queues and, thus, require larger buffers in the deployed network's elements.
Jakob Carlström and Ernst Nordström: Reinforcement Learning for Control of Self-Similar Call Traffic in Broadband Networks.
Abstract: Reinforcement learning is applied to admission control of self-similar call traffic in broadband networks. The reinforcement learning method solves a Markov Decision Problem without the need for a model of the dynamics of the controlled system. A state descriptor containing continuous-valued running averages of the call inter-arrival times is employed. Radial-basis function neural networks approximate the value function. In simulations, the proposed method yields higher throughput than methods that do not exploit the self-similarity of the call arrival process.
B. Sikdar, K. Chandrayana, K. S. Vastola and S. Kalyanaraman: Queue Management Algorithms and Network Traffic Self-Similarity.
Abstract: The self-similarity of network traffic has been established in a variety of environments and it is well known that self-similar traffic can lead to larger queueing delays, higher drop rates and extended periods of congestion. In this paper, we investigate the impact of various buffer management algorithms on the self-similarity of network traffic. In this paper we investigate the impact of active and passive queue management policies used at the routers on the self-similarity of TCP traffic. We also propose a modification to the RED algorithm, aimed at reducing the timeouts and exponential backoffs in TCP flows, and show that it can lead to significant reductions in the traffic self-similarity under a wide range of network conditions, as compared to the currently implemented active and passive buffer management policies. We also show that though our techniques are aimed at TCP related causes, it is also effective in reducing the degree of self-similarity in traffic even when application and user level causes are also present, as long as TCP is used as the underlying transport protocol.
Jin Cao, Kavita Ramanan: A Poisson Limit for Buffer Overflow Probabilities.
Abstract: A key criterion in the design of high-speed networks is the probability that the buffer content exceeds a given threshold. We consider n independent identical traffic sources modelled as point processes, which are fed into a link with speed proportional to n. Under fairly general assumptions on the input processes we show that the steady state probability of the buffer content exceeding a thresholdb > 0 tends to the corresponding probability assuming Poisson input processes. We verify the assumptions for a large class of long-range dependent sources commonly used to model data traffic. Our results show that with superposition, significant multiplexing gains can be achieved for even smaller buffers than suggested by previous results, which consider O(n) buffer size. Moreover, simulations show that for realistic values of the exceedance probability and moderate utilisations, convergence to the Poisson limit takes place at reasonable values of the number of sources superposed. This is particularly relevant for high-speed networks in which the cost of high-speed memory is significant.
Utjecaj samoslicnosti na teoriju redova.
Homayoun Yousefi’zadeh: A Neural-Based Technique for Estimating Self-Similar Traffic Average Queuing Delay
Abstract: Estimating buffer latency is one of the most important challenges in the analysis and design of traffic control algorithms. In this paper a novel approach for estimating average queuing delay in multiple source queuing systems is introduced. The approach relies on the modeling power of neural networks in predicting self-similar traffic patterns in order to determine the arrival rate and the packet latency of low loss, moderately loaded queuing systems accommodating such traffic patterns.
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Autor: Tomislav Tandarić 0036377349
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