Network Tomography
eBook - PDF

Network Tomography

Identifiability, Measurement Design, and Network State Inference

  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

Network Tomography

Identifiability, Measurement Design, and Network State Inference

About this book

Providing the first truly comprehensive overview of Network Tomography - a novel network monitoring approach that makes use of inference techniques to reconstruct the internal network state from external vantage points - this rigorous yet accessible treatment of the fundamental theory and algorithms of network tomography covers the most prominent results demonstrated on real-world data, including identifiability conditions, measurement design algorithms, and network state inference algorithms, alongside practical tools for applying these techniques to real-world network management. It describes the main types of mathematical problems, along with their solutions and properties, and emphasizes the actions that can be taken to improve the accuracy of network tomography. With proofs and derivations introduced in an accessible language for easy understanding, this is an essential resource for professional engineers, academic researchers, and graduate students in network management and network science.

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Yes, you can access Network Tomography by Ting He,Liang Ma,Ananthram Swami,Don Towsley in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Signals & Signal Processing. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half-title
  3. Title page
  4. Copyright information
  5. Contents
  6. Notation
  7. Introduction
  8. 1 Preliminaries
  9. 2 Fundamental Conditions for Additive Network Tomography
  10. 3 Monitor Placement for Additive Network Tomography
  11. 4 Measurement Path Construction for Additive Network Tomography
  12. 5 Fundamental Conditions for Boolean Network Tomography
  13. 6 Measurement Design for Boolean Network Tomography
  14. 7 Stochastic Network Tomography Using Unicast Measurements
  15. 8 Stochastic Network Tomography Using Multicast Measurements
  16. 9 Other Applications and Miscellaneous Techniques
  17. Appendix: Datasets for Evaluations
  18. Index