Performance Analysis of Queuing and Computer Networks

Performance Analysis of Queuing and Computer Networks

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Performance Analysis of Queuing and Computer Networks develops simple models and analytical methods from first principles to evaluate performance metrics of various configurations of computer systems and networks. It presents many concepts and results of probability theory and stochastic processes. After an introduction to queues in computer networks, this self-contained book covers important random variables, such as Pareto and Poisson, that constitute models for arrival and service disciplines. It then deals with the equilibrium M/M/1/â queue, which is the simplest queue that is amenable for analysis. Subsequent chapters explore applications of continuous time, state-dependent single Markovian queues, the M/G/1 system, and discrete time queues in computer networks. The author then proceeds to study networks of queues with exponential servers and Poisson external arrivals as well as the G/M/1 queue and Pareto interarrival times in a G/M/1 queue. The last two chapters analyze bursty, self-similar traffic, and fluid flow models and their effects on more

Product details

  • Electronic book text | 472 pages
  • Taylor & Francis Ltd
  • Chapman & Hall/CRC
  • London, United Kingdom
  • 6 Tables, black and white; 80 Illustrations, black and white
  • 158488987X
  • 9781584889878

Table of contents

Introduction Background Queues in Computers and Computer Networks Queuing Models Conclusion Characterization of Data Traffic The Pareto Random Variable The Poisson Random Variable Simulation Elements of Parameter Estimation Sequences of Random Variables Elements of Digital Communication and Data Link Performance The M/M/1/â Queue Derivation of Equilibrium State Probabilities Simple Performance Figures Response Time and Its Distribution More Performance Figures for M/M/1/â System Waiting Time Distribution Departures from Equilibrium M/M/1/â System Analysis of ON-OFF Model of Packet Departures Round Robin Operating System Examples Analysis of Busy Times Forward Data Link Performance and Optimization State-Dependent Markovian Queues Stochastic Processes Continuous Parameter Markov Chains Markov Chains for State-Dependent Queues Intuitive Approach for Time Averages Statistical Analysis of Markov Chains' Sample Functions Little's Result Application Systems Medium Access in Local Area Networks The M/G/1 Queue Imbedded Processes Equilibrium and Long-Term Operation of M/G/1/â Queue Derivation of the Pollaczek-Khinchin Mean Value Formula Application Examples Special Cases Discrete Time Queues Timing and Synchronization State Transitions and Their Probabilities Discrete Parameter Markov Chains Classification of States Analysis of Equilibrium Markov Chains Performance Evaluation of Discrete Time Queues Applications Conclusion Continuous Time Queuing Networks Model and Notation for Open Networks Global Balance Equations Traffic Equations The Product Form Solution Validity of Product Form Solution Development of Product Form Solution for Closed Networks Convolution Algorithm Performance Figures from the g(n,m) Matrix Mean Value Analysis Conclusion The G/M/1 Queue The Imbedded Markov Chain for G/M/1/â Queue Analysis of the Parameter α Performance Figures in G/M/1/â Queue Finite Buffer G/M/1/k Queue Pareto Arrivals in a G/M/1/â Queue Queues with Bursty, MMPP, and Self-Similar Traffic Distinction between Smooth and Bursty Traffic Self-Similar Processes Hyperexponential Approximation to Shifted Pareto Interarrival Times Characterization of Merged Packet Sources Product Form Solution for the Traffic Source Markov Chain Joint Markov Chain for the Traffic Source and Queue Length Evaluation of Equilibrium State Probabilities Queues with MMPP Traffic and Their Performance Performance Figures Conclusion Analysis of Fluid Flow Models Leaky Bucket with Two State ON-OFF Input Little's Result for Fluid Flow Systems Output Process of Buffer Fed by Two State ON-OFF Chain General Fluid Flow Model and Its Analysis Leaky Bucket Fed by M/M/1/â Queue Output Appendix: Review of Probability Theory Index An Introduction and Exercises appear in each more