Stochastic Networks
1st Edition
Published on 31. January 2014
978-1-107-72308-5 (ISBN)
Description
Communication networks underpin our modern world, and provide fascinating and challenging examples of large-scale stochastic systems. Randomness arises in communication systems at many levels: for example, the initiation and termination times of calls in a telephone network, or the statistical structure of the arrival streams of packets at routers in the Internet. How can routing, flow control and connection acceptance algorithms be designed to work well in uncertain and random environments? This compact introduction illustrates how stochastic models can be used to shed light on important issues in the design and control of communication networks. It will appeal to readers with a mathematical background wishing to understand this important area of application, and to those with an engineering background who want to grasp the underlying mathematical theory. Each chapter ends with exercises and suggestions for further reading.
More details
Series
Language
English
Place of publication
Cambridge
United Kingdom
Target group
Professional and scholarly
College/higher education
Illustrations
Worked examples or Exercises; 60 Line drawings, unspecified
File size
4,84 MB
ISBN-13
978-1-107-72308-5 (9781107723085)
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Schweitzer Classification
Other editions
Additional editions
Frank Kelly | Elena Yudovina
Stochastic Networks
Book
02/2014
Cambridge University Press
€94.20
Shipment within 15-20 days
Frank Kelly | Elena Yudovina
Stochastic Networks
Book
02/2014
Cambridge University Press
€54.40
Shipment within 15-20 days
Persons
Frank Kelly is Professor of the Mathematics of Systems at the University of Cambridge. His main research interests are in random processes, networks and optimization. He is especially interested in applications to the design and control of networks and to the understanding of self-regulation in large-scale systems. Elena Yudovina is a postdoctoral research fellow at the University of Michigan. Her research interests are in applications of queueing theory. She received her PhD from the University of Cambridge, where her interest in the subject was sparked by a course on stochastic networks taught by Frank Kelly.
Content
Overview; Part I: 1. Markov chains; 2. Queueing networks; 3. Loss networks; Part II: 4. Decentralized optimization; 5. Random access networks; 6. Effective bandwidth; Part III: 7. Internet congestion control; 8. Flow level internet models; Appendix A. Continuous time Markov processes; Appendix B. Little's law; Appendix C. Lagrange multipliers; Appendix D. Foster-Lyapunov criteria; References; Index.
