A major challenge in traffic modeling and performance analysis for the Transmission Control Protocol (TCP) stems from the fact that the incoming traffic is not independent of the congestion level in the network. This paper investigates a queueing model where the traffic essentially shows ON/OFF characteristics, i.e. the number of active TCP connections of finite (probabilistic) duration varies as described by a stochastic process. The essential behavior of TCP-like flow-control mechanisms is captured in the analytic model by the feature that the packet-rate of active connections can be throttled in order to avoid that the overall packet-stream exceeds the output-bandwidth of the bottleneck router. By appropriate adjustment of the connection duration, the number of packets in the connections remains unaffected. However, since TCP reacts to existing congestion, the throttling mechanism is only activated when the buffer-occupancy at the bottleneck router exceeds a certain threshold. The impact of such a flowcontrol mechanism on the characteristics of the incoming traffic as well as on the performance behavior at the bottleneck router is discussed and illustrated by numerical results of the analytic model. In particular, the use of (truncated) Power-Tail distributions for the ON periods leads to conclusions about the behavior of long-range dependent traffic under the influence of TCP's flow-control mechanism. Keywords--- TCP flow-control, ON/OFF models, Markov Modulated Poisson Processes, Long-Range Dependence, Truncated Power-Tail Distributions I.

The N-Burst model describes traffic in telecommunication systems as the superposition of N packet (or cell) streams of ON/OFF type, i.e., during its ON-time each source generates packets according to a Poisson Process with intra-burst packet rate p . As such, the N-Burst is an analytic Point-Process modeling network traffic on the packet level. When using Power-Tail Distributions for the duration of the ON periods, self-similar properties are observed. A variety of widely used approximate traffic models are shown to be limiting cases of N-Burst/G/1 queues. For very low intra-burst packet rates, the N-Burst/G/1 model reduces to an M/G/1 queue. For p ! 1 all packets in a burst arrive simultaneously and the model reduces to a Bulk arrival, or M (X) =G=1, queue. In the same limit, the packet-based model can be compared to a model on the burst level, an M/G/1 queue where the individual customers represent complete bursts rather than individual packets. Thus the mean system time describes ...

The inclusion of Transmission Control Protocol (TCP) is necessary for the realistic simulation of data networks. However, the operation of HTTP-TCP sources puts a heavy tax on the simulations leading to two major scalability problems: the computing resources required by each source put a limit on the total number of sources that can be simulated, and the number of events generated by every simulated connection leads to long simulation times. The problems while addressable for the present day networks become major obstacles for realistic simulations of optical networks. In this paper we present an open-loop traffic source that generates traffic statistically similar to the traffic produced by a number of HTTP-TCP sources. The source is based upon an integrated packet-session levels model that captures the web user-behavior as well as the TCP characteristics. The gain against the scalability problems comes by reducing the required number of sources, and by simulating only the slow-start mechanism of TCP. By comparing key traffic statistics we show that the source qualifies as a good candidate for generating network traffic.

Let = n be the first time a queueing process like the queue length or workload exceeds a level n. For the M/M/1 queue length process, the mean IE and the Laplace transform IEe \Gammas is derived in closed form using a martingale introduced in Kella & Whitt (1992). For workload processes and more general systems like MAP/PH/1, we use a Markov additive extension given in Asmussen & Kella (2000) to derive sets of linear equations determining the same quantities. Numerical illustrations are presented in the framework of M/M/1 and MMPP/M/1 with an application to performance evaluation of telecommunication systems with long--range dependent properties in the packet arrival process. Different approximations that are obtained from asymptotic theory are compared with exact numerical results.

This paper discusses potential drawbacks of steady-state parameters, in particular of the steady-state buffer-overflow or cell-loss probability. The importance of transient performance analysis is demonstrated for long-range dependent (multiplexed) ON/OFF traffic. A transient parameter pair is proposed as replacement for the steady-state overflow or loss probabilities. The in-depth discussion of the behavior of those transient parameters reveals surprising results that allow for characterization and understanding of the fluctuations that are being observed in actual network behavior under traffic loads with long-range dependent properties.

Hagit, there are so many things that I want to thank you for. You always left your door open for me. You always welcomed me with a big smile and endless patience. With one hand, you gave me academic freedom to choose the subjects and with the other hand you escorted, supported and guided me. How can I thank you for the infinite time you spent reading, commenting, and improving this research? In fact, you where the one who taught me what the meaning of an academic research is. I would like to thank Hadas Shachnai, whom I used to bother asking her to referee and discuss most of the results reached in this thesis. She was always kind and her comments were always relevant and helped me to improve the research. The final exam was conducted by Hagit, Hadas and Yuval Shavit in both a friendly atmosphere and on high intellectual level. Thank you. In the beginning of my research I had some useful discussions with Roy Friedman, Danny Raz and Roman Vitenberg which widened my horizons. I would like to thank my family for their support. My mother, Dina Teplixke, who could not care less about my grades except for the one in mathematics... My husband, Nir, who

The impact of the now widely acknowledged self-similar property of network traffic on buffer overflows in a single server queueing model is investigated. The analytic traffic model, called N-Burst, uses the superposition of N independent cell streams of ON/OFF type with Power-Tail distributed ON periods. Due to the high correlation of overflow events for queueing models with self-similar arrival processes, the steady-state buffer overflow probabilities can be misleading, especially when they are rather low. Several transient overflow parameters are introduced to capture the implications of the correlation in the overflow events. A discussion and analysis of those transient parameters for the given aggregated ON/OFF traffic model reveals that the self-similar property leads to a very peculiar behavior, namely that the so-called conditional overflow ratio increases asymptotically with increasing buffer-size. The derivation of the asymptotic behavior provides additional insight into the ...