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To support multimedia applications, high-speed networks must be able to provide quality-of-service (QoS) guarantees for connections with drastically different traf®c characteristics. Some of the characteristics fall beyond the conventional framework of Markov traf®c modeling. For instance, recent studies have demonstrated convincingly that there exists long-range dependence or self-similarity in packet video, which is an important traf®c component in high-speed networks. Essentially, longrange dependence cannot be captured by Markov. | Self-Similar Network Traffic and Performance Evaluation Edited by Kihong Park and Walter Wi 1 linger Copyright 2000 by John Wiley Sons Inc. Print ISBN 0-471-31974-0 Electronic ISBN 0-471-20644-X 13 ANALYSIS OF TRANSIENT LOSS PERFORMANCE IMPACT OF LONG-RANGE DEPENDENCE IN NETWORK TRAFFIC Guang-Liang Li and Victor O. K. Li Department of Electrical Electronic Engineering The University of Hong Kong Pokfulam Hong Kong China INTRODUCTION To support multimedia applications high-speed networks must be able to provide quality-of-service QoS guarantees for connections with drastically different traffic characteristics. Some of the characteristics fall beyond the conventional framework of Markov traffic modeling. For instance recent studies have demonstrated convincingly that there exists long-range dependence or self-similarity in packet video which is an important traffic component in high-speed networks. Essentially long-range dependence cannot be captured by Markov traffic models. Although long-range dependence in network traffic has been widely recognized 1 2 4 8 11 15 17 18 QoS impact of long-range dependence is still an open issue. For example there are different opinions regarding whether Markov traffic models can still be used to predict loss performance in the presence of long-range dependence. This and other related issues are also discussed in Chapter 12 of this book. QoS guarantee for long-range dependent LRD traffic is the topic of Chapters 16 and 19 as well. The issue of congestion control for self-similar traffic is addressed in Chapter 18. 319 320 TRANSIENT LOSS PERFORMANCE IMPACT OF LRD IN NETWORK TRAFFIC In this chapter we present an analysis of transient loss performance impact of long-range dependence in network traffic. This work is only the first step of our exploration. But we hope that it will still be helpful for understanding loss performance impact of long-range dependence in the transient state although much farther work needs to be done in

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