Stochastic Modeling and Analysis of Telecom Networks

Nonfiction, Science & Nature, Technology, Telecommunications
Cover of the book Stochastic Modeling and Analysis of Telecom Networks by Laurent Decreusefond, Pascal Moyal, Wiley
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Author: Laurent Decreusefond, Pascal Moyal ISBN: 9781118563014
Publisher: Wiley Publication: December 27, 2012
Imprint: Wiley-ISTE Language: English
Author: Laurent Decreusefond, Pascal Moyal
ISBN: 9781118563014
Publisher: Wiley
Publication: December 27, 2012
Imprint: Wiley-ISTE
Language: English

This book addresses the stochastic modeling of telecommunication networks, introducing the main mathematical tools for that purpose, such as Markov processes, real and spatial point processes and stochastic recursions, and presenting a wide list of results on stability, performances and comparison of systems.
The authors propose a comprehensive mathematical construction of the foundations of stochastic network theory: Markov chains, continuous time Markov chains are extensively studied using an original martingale-based approach. A complete presentation of stochastic recursions from an ergodic theoretical perspective is also provided, as well as spatial point processes.
Using these basic tools, stability criteria, performance measures and comparison principles are obtained for a wide class of models, from the canonical M/M/1 and G/G/1 queues to more sophisticated systems, including the current “hot topics” of spatial radio networking, OFDMA and real-time networks.

Contents

  1. Introduction.
    Part 1: Discrete-time Modeling
  2. Stochastic Recursive Sequences.
  3. Markov Chains.
  4. Stationary Queues.
  5. The M/GI/1 Queue.
    Part 2: Continuous-time Modeling
  6. Poisson Process.
  7. Markov Process.
  8. Systems with Delay.
  9. Loss Systems.
    Part 3: Spatial Modeling
  10. Spatial Point Processes.
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

This book addresses the stochastic modeling of telecommunication networks, introducing the main mathematical tools for that purpose, such as Markov processes, real and spatial point processes and stochastic recursions, and presenting a wide list of results on stability, performances and comparison of systems.
The authors propose a comprehensive mathematical construction of the foundations of stochastic network theory: Markov chains, continuous time Markov chains are extensively studied using an original martingale-based approach. A complete presentation of stochastic recursions from an ergodic theoretical perspective is also provided, as well as spatial point processes.
Using these basic tools, stability criteria, performance measures and comparison principles are obtained for a wide class of models, from the canonical M/M/1 and G/G/1 queues to more sophisticated systems, including the current “hot topics” of spatial radio networking, OFDMA and real-time networks.

Contents

  1. Introduction.
    Part 1: Discrete-time Modeling
  2. Stochastic Recursive Sequences.
  3. Markov Chains.
  4. Stationary Queues.
  5. The M/GI/1 Queue.
    Part 2: Continuous-time Modeling
  6. Poisson Process.
  7. Markov Process.
  8. Systems with Delay.
  9. Loss Systems.
    Part 3: Spatial Modeling
  10. Spatial Point Processes.

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