self-similar network traffic and performance evaluation.

SELF-SIMILAR NETWORK TRAFFIC AND PERFORMANCE EVALUATION Self-Similar Network Traffic and Performance Evaluation Edited by Kihong Park, Walter Willinger Copyright  2000 John Wiley & Sons, Inc. ISBNs: 0-471-31974-0 (Hardback); 0-471-20644-X (Electronic) SELF-SIMILAR NETWORK TRAFFIC AND PERFORMANCE EVALUATION Edited by KIHONG PARK Purdue University WALTER WILLINGER AT&T Labs-Research A Wiley-Interscience Publication JOHN WILEY & SONS, INC. New York  Chichester  Weinheim  Brisbane  Singapore  Toronto Designations used by companies to distinguish their products are often claimed as trademarks. In all instances where John Wiley & Sons, Inc., is aware of a claim, the product names appear in initial capital or ALL CAPITAL LETTERS. Readers, however, should contact the appropriate companies for more complete information regarding trademarks and registration. 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ISBN 0-471-20644-X This title is also available in print as ISBN 0-471-31974-0. For more information about Wiley products, visit our web site at www.Wiley.com. Copyright#2000byJohnWiley&Sons,Inc.Allrightsreserved. CONTRIBUTORS Abdelnaser Adas, Conexant, Inc., Newport Beach, California, USA P. Abry, CNRS UMR 5672, E  cole Normale Supe  rieure de Lyon, Laboratoire de Physique, Lyon, France O. J. Boxma, Eindhoven University of Technology, Eindhoven, The Netherlands and CWI, Amsterdam, The Netherlands F. Brichet, France Te  le  com, CNET, Issy-Moulineaux, France J. W. Cohen, CWI, Amsterdam, The Netherlands Mark E. Crovella, Boston University, Boston, Massachusetts, USA N. G. Duf®eld, AT&T Labs±Research, Florham Park, New Jersey, USA Anja Feldmann, University of SaarbruÈcken, SaarbruÈ cken, Germany P. Flandrin, CNRS UMR 5672, E  cole Normale Supe  rieure de Lyon, Laboratoire de Physique, Lyon, France Daniel P. Heyman, AT&T Labs, Middleton, New Jersey, USA Philippe Jacquet, INRIA, Le Chesnay, France P. R. Jelenkovic  , Columbia University, New York, New York, USA Gitae Kim, Boston University, Boston, Massachusetts, USA T. V. Lakshman, Bell Laboratories, Lucent Technologies, Holmdel, New Jersey, USA v Guang-Liang Li, The University of Hong Kong, Hong Kong, China Victor O.K. Li, The University of Hong Kong, Hong Kong, China N. Likhanov, Institute for Problems of Information Transmission, Russian Acad- emy of Science, Moscow, Russia Lester Lipsky, University of Connecticut, Storrs, Connecticut, USA Armand M. Makowski, University of Maryland, College Park, Maryland, USA L. MassoulieÂ, Microscoft Research Ltd., Cambridge, United Kingdom Amarnath Mukherjee, Knoltex Corporation, San Jose, California, USA Ilkka Norros, VTT Information Technology, Espoo, Finland Kihong Park, Purdue University, West Lafayette, Indiana, USA Minothi Parulekar, University of Maryland, College Park, Maryland, USA R. H. Riedi, Rice University, Houston, Texas, USA Sidney Resnick, Cornell University, Ithaca, New York, USA J. W. Roberts, France Te  le  com, CNET, Issy-Moulineaux, France Gennady Samorodnitsky, Cornell University, Ithaca, New York, USA A. Simonian, France Te  le  com, CNET, Issy-Moulineaux, France M. S. Taqqu, Boston University, Boston, Massachusetts, USA Tsunyi Tuan, Purdue University, West Lafayette, Indiana, USA D. Veitch, Software Engineering Research Centre, Carlton, Victoria, Australia W. Whitt, AT&T Labs±Research, Florham Park, New Jersey, USA Walter Willinger, AT&T Labs±Research, Florham Park, New Jersey, USA vi CONTRIBUTORS CONTENTS Preface xi 1 Self-Similar Network Traf®c: An Overview 1 Kihong Park and Walter Willinger 2 Wavelets for the Analysis, Estimation, and Synthesis of Scaling Data 39 P. Abry, P. Flandrin, M. S. Taqqu, and D. Veitch 3 Simulations with Heavy-Tailed Workloads 89 Mark E. Crovella and Lester Lipsky 4 Queueing Behavior Under Fractional Brownian Traf®c 101 Ilkka Norros 5 Heavy Load Queueing Analysis with LRD OnaOff Sources 115 F. Brichet, A. Simonian, L. MassoulieÂ, and D. Veitch 6 The Single Server Queue: Heavy Tails and Heavy Traf®c 143 O. J. Boxma and J. W. Cohen 7 Fluid Queues, OnaOff Processes, and Teletraf®c Modeling with Highly Variable and Correlated Inputs 171 Sidney Resnick and Gennady Samorodnitsky vii 8 Bounds on the Buffer Occupancy Probability with Self-Similar Input Traf®c 193 N. Likhanov 9 Buffer Asymptotics for MaGa11 Input Processes 215 Armand M. Makowski and Minothi Parulekar 10 Asymptotic Analysis of Queues with Subexponential Arrival Processes 249 P. R. Jelenkovic  11 Traf®c and Queueing from an Unbounded Set of Independent Memoryless OnaOff Sources 269 Philippe Jacquet 12 Long-Range Dependence and Queueing Effects for VBR Video 285 Daniel P. Heyman and T. V. Lakshman 13 Analysis of Transient Loss Performance Impact of Long-Range Dependence in Network Traf®c 319 Guang-Liang Li and Victor O.K. Li 14 The Protocol Stack and Its Modulating Effect on Self-Similar Traf®c 349 Kihong Park, Gitae Kim, and Mark E. Crovella 15 Characteristics of TCP Connection Arrivals 367 Anja Feldmann 16 Engineering for Quality of Service 401 J. W. Roberts 17 Network Design and Control Using OnaOff and Multilevel Source Traf®c Models with Heavy-Tailed Distributions 421 N. G. Duf®eld and W. Whitt 18 Congestion Control for Self-Similar Network Traf®c 446 Tsunyi Tuan and Kihong Park 19 Quality of Service Provisioning for Long-Range-Dependent Real-Time Traf®c 481 Abdelnaser Adas and Amarnath Mukherjhee viii CONTENTS 20 Toward an Improved Understanding of Network Traf®c Dynamics 507 R. H. Riedi and Walter Willinger 21 Future Directions and Open Problems in Performance Evaluation and Control of Self-Similar Network Traf®c 531 Kihong Park Index 555 CONTENTS ix [...]... AT&T Labs May 2000 KIHONG PARK WALTER WILLINGER SELF-SIMILAR NETWORK TRAFFIC AND PERFORMANCE EVALUATION Self-Similar Network Traf®c and Performance Evaluation, Edited by Kihong Park and Walter Willinger Copyright # 2000 by John Wiley & Sons, Inc Print ISBN 0-471-31974-0 Electronic ISBN 0-471-20644-X 1 SELF-SIMILAR NETWORK TRAFFIC: AN OVERVIEW KIHONG PARK Network Systems Lab, Department of Computer Sciences,... of the self-similar nature of network traf®c, including parallel efforts and important follow-up work, we refer the reader to Willinger [71] An extended list of references that includes works related to self-similar network traf®c and performance modeling up to about 1995 can be found in the bibliographical guide [75] Self-Similar Network Traf®c and Performance Evaluation, Edited by Kihong Park and Walter... diverse contexts, from local-area and wide-area networks to IP and ATM protocol stacks to copper and ®ber optic transmission media In particular, Leland et al [41] demonstrated self-similarity in a LAN environment (Ethernet), Paxson and Floyd [56] showed self-similar burstiness manifesting itself in pre-World Wide Web WAN IP traf®c, and Crovella and Bestavros [13] showed self-similarity for WWW traf®c... require more concentrated focus on revolutionary ideas and approaches to networking research and practice, especially as far as network performance analysis and traf®c control are concerned The chapter contributions have been organized into three parts: (i) estimation and simulation, (ii) queueing with self-similar input, and (iii) traf®c control and resource provisioning The threefold categorization... the seminal study of Leland, Taqqu, Willinger, and Wilson [41], which set the groundwork for considering self-similarity an important notion in the understanding of network traf®c including the modeling and analysis of network performance, an explosion of work has ensued investigating the multifaceted nature of this phenomenon.1 The long-held paradigm in the communication and performance communities... productive and timely occasion, and a delightful experience for us We are con®dent that despite the rapidly changing conditions that have become a trademark of modern communication networks, this book contains insights and lessons that are less transient and will withstand the test of time We hope the book will be of service as a comprehensive, in-depth, and up-to-date reference on self-similar network. .. endowed on the networking domain: the physics and causal mechanisms underlying network phenomena including traf®c characteristics Since network architectureÐeither by implementation or simulationÐis con®gurable, from a network engineering perspective physical traf®c models that trace back the roots of self-similarity and long-range dependence to architectural properties such as network protocols and ®le size... empirically observed network traf®c and an important notion in the understanding of the traf®c'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... 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... range of network environments Accompanying the traf®c characterization efforts has been work in the area of statistical and scienti®c inference that has been essential to the detection and quanti®cation of self-similarity or long-range dependence.2 This work has speci®cally been geared toward network traf®c self-similarity [28, 64] and has focused on exploiting the immense volume, high quality, and diversity . SELF-SIMILAR NETWORK TRAFFIC AND PERFORMANCE EVALUATION Self-Similar Network Traffic and Performance Evaluation Edited by Kihong Park, Walter Willinger Copyright . University AT&T Labs May 2000 xiv PREFACE SELF-SIMILAR NETWORK TRAFFIC AND PERFORMANCE EVALUATION 1 SELF-SIMILAR NETWORK TRAFFIC: AN OVERVIEW KIHONG PARK Network Systems Lab, Department of Computer. works related to self-similar network traf®c and performance modeling up to about 1995 can be found in the bibliographical guide [75]. Self-Similar Network Traf®c and Performance Evaluation, Edited