Self-Similar Network Traffic and Performance Evaluation (Wiley-Interscience) - Hardcover

 
9780471319740: Self-Similar Network Traffic and Performance Evaluation (Wiley-Interscience)

Inhaltsangabe

A collection of work from top researchers in the field, this book covers all aspects of self-similar network traffic. Readers will gain a better understanding of these networks through a broad introduction to the topic, as well as suggestions for future research.

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Über die Autorin bzw. den Autor

Kihong Park is the editor of Self-Similar Network Traffic and Performance Evaluation, published by Wiley.

Walter Willinger is the editor of Self-Similar Network Traffic and Performance Evaluation, published by Wiley.

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Self-Similar Network Traffic and Performance Evaluation

John Wiley & Sons

Copyright © 2000 Kihong Park
All right reserved.

ISBN: 978-0-471-31974-0

Contents

Preface.....................................................................................................................................................................................xi1 Self-Similar Network Traffic: An Overview Kihong Park and Walter Willinger...............................................................................................................12 Wavelets for the Analysis, Estimation, and Synthesis of Scaling Data P. Abry, P. Flandrin, M. S. Taqqu, and D. Veitch....................................................................393 Simulations with Heavy-Tailed Workloads Mark E. Crovella and Lester Lipsky...............................................................................................................894 Queueing Behavior Under Fractional Brownian Traffic Ilkka Norros.........................................................................................................................1015 Heavy Load Queueing Analysis with LRD On/Off Sources F. Brichet, A. Simonian, L. Massouli, and D. Veitch...............................................................................1156 The Single Server Queue: Heavy Tails and Heavy Traffic O. J. Boxma and J. W. Cohen.......................................................................................................1437 Fluid Queues, On/Off Processes, and Teletraffic Modeling with Highly Variable and Correlated Inputs Sidney Resnick and Gennady Samorodnitsky.....................1718 Bounds on the Buffer Occupancy Probability with Self-Similar Input Traffic N. Likhanov...................................................................................................1939 Buffer Asymptotics for M/G/[infinity] Input Processes Armand M. Makowski and Minothi Parulekar...........................................................................................21510 Asymptotic Analysis of Queues with Subexponential Arrival Processes P. R. Jelenkovic....................................................................................................24911 Traffic and Queueing from an Unbounded Set of Independent Memoryless On/Off Sources Philippe Jacquet....................................................................................26912 Long-Range Dependence and Queueing Effects for VBR Video Daniel P. Heyman and T. V. Lakshman............................................................................................28513 Analysis of Transient Loss Performance Impact of Long-Range Dependence in Network Traffic Guang-Liang Li and Victor O.K. Li...........................................................31914 The Protocol Stack and Its Modulating Effect on Self-Similar Traffic Kihong Park, Gitae Kim, and Mark E. Crovella.............................................34915 Characteristics of TCP Connection Arrivals Anja Feldmann................................................................................................................................36716 Engineering for Quality of Service J. W. Roberts........................................................................................................................................40117 Network Design and Control Using On/Off and Multilevel Source Traffic Models with Heavy-Tailed Distributions N. G. Duffield and W. Whitt................................................42118 Congestion Control for Self-Similar Network Traffic Tsunyi Tuan and Kihong Park.........................................................................................................44619 Quality of Service Provisioning for Long-Range-Dependent Real-Time Traffic Abdelnaser Adas and Amarnath Mukherjhee......................................................................48120 Toward an Improved Understanding of Network Traffic Dynamics R. H. Riedi and Walter Willinger...........................................................................................50721 Future Directions and Open Problems in Performance Evaluation and Control of Self-Similar Network Traffic Kihong Park...................................................................531Index.......................................................................................................................................................................................555

Preface

The recent discovery of scaling phenomena in modern communication networks involving self-similarity or fractals and power-law or heavy-tailed distributions is yet another realization of Benoit Mandelbrot's vision of order in physical, social, and engineered systems characterized by scaling laws. Since the seminal paper by Leland, Taqqu, Willinger and Wilson in 1993 which set the groundwork for considering self-similarity an ubiquitous feature of empirically observed network traffic and an important notion in the understanding of the traffic's dynamic nature for modeling analysis and control of network performance, an explosion of work has ensued investigating the multifaceted nature of this phenomenon.

Despite the fact that data networks such as the Internet are drastically different from legacy public switched telephone networks, the long held paradigm in the communication and networking research community has been that data traffic-analogous to voice traffic-is adequately described by certain Markovian models which are amenable to accurate analysis and efficient control. This supposition has been instrumental in shaping the optimism permeating the late 1980s and early 1990s regarding the ability of achieving efficient traffic control for quality of service provisioning in modern high-speed communication networks. The discovery and, more importantly, succinct formulation and recognition that actual data traffic may, in fact, be fundamentally different in nature from the hereto accustomed telephony traffic has significantly influenced the networking research landscape, necessitating a reexamination and revamping of some of its basic premises.

This book is a collection of chapter contributions which brings together relevant past works spanning a cross-section of topics covering traffic measurement, modeling, performance analysis, and traffic control for self similar network traffic. The primary objective of the book is to present a comprehensive yet cohesive account of some of the principal developments and results concerning self-similar network traffic across its various facets, with the aim of serving as a reflective milestone that captures the state-of-the-art in the field. The book is organized around three main subtopics-traffic modeling, queueing-based performance analysis, and traffic control. By and large, the chapters reflect how research in these areas has reacted when faced with the new scientific discoveries involving self similarity and ubiquitous presence of heavy-tailed phenomena in networked systems.

The spectrum of reactions ranges from evolutionary-holding on to traditional frameworks and tested concepts, and trying to extend, generalize them in the presence of unfamiliar characteristics that, in many ways, contradict conventional wisdom-all the way to revolutionary, which embrace the novel and, at times, surprising features giving rise to new questions, research problems, and challenges both on theoretical and practical fronts of relevance to the future Internet. Overall, the reader may find the majority of book chapters to be of an evolutionary rather than revolutionary nature: Many of...

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