Performance Modeling, Stochastic Networks, and Statistical Multiplexing

Released on by Ravi R. Mazumdar
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  • Performance Modeling, Stochastic Networks, and Statistical Multiplexing Book Detail

  • Author : Ravi R. Mazumdar
  • Release Date : 2013-06-01
  • Publisher : Morgan & Claypool Publishers
  • Genre : Computers
  • Pages : 213
  • ISBN 13 : 1627051732
  • File Size : 6,6 MB
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Performance Modeling, Stochastic Networks, and Statistical Multiplexing by Ravi R. Mazumdar PDF Summary

Book Description: This monograph presents a concise mathematical approach for modeling and analyzing the performance of communication networks with the aim of introducing an appropriate mathematical framework for modeling and analysis as well as understanding the phenomenon of statistical multiplexing. The models, techniques, and results presented form the core of traffic engineering methods used to design, control and allocate resources in communication networks.The novelty of the monograph is the fresh approach and insights provided by a sample-path methodology for queueing models that highlights the important ideas of Palm distributions associated with traffic models and their role in computing performance measures. The monograph also covers stochastic network theory including Markovian networks. Recent results on network utility optimization and connections to stochastic insensitivity are discussed. Also presented are ideas of large buffer, and many sources asymptotics that play an important role in understanding statistical multiplexing. In particular, the important concept of effective bandwidths as mappings from queueing level phenomena to loss network models is clearly presented along with a detailed discussion of accurate approximations for large networks. Table of Contents: Introduction to Traffic Models and Analysis / Queues and Performance Analysis / Loss Models for Networks / Stochastic Networks and Insensitivity / Statistical Multiplexing

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Network Connectivity

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Networks naturally appear in many high-impact domains, ranging from social network analysis to disease dissemination studies to infrastructure system design. Wi