Network Tomography
Identifiability, Measurement Design, and Network State Inference
Published on 26. May 2021
978-1-108-38378-3 (ISBN)
Description
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.
More details
Language
English
Place of publication
Cambridge
United Kingdom
Target group
Professional and scholarly
Illustrations
Worked examples or Exercises
File size
12,10 MB
ISBN-13
978-1-108-38378-3 (9781108383783)
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Schweitzer Classification
Other editions
Additional editions
Ting He | Liang Ma | Ananthram Swami
Network Tomography
Identifiability, Measurement Design, and Network State Inference
Book
05/2021
Cambridge University Press
€113.90
Shipment within 15-20 days
Persons
Content
Introduction; 1. Preliminaries; 2. Fundamental conditions for additive network tomography; 3. Monitor placement for additive network tomography; 4. Measurement path construction for additive network tomography; 5. Fundamental conditions for Boolean network tomography; 6. Measurement design for Boolean network tomography; 7. Stochastic network tomography using unicast measurements; 8. Stochastic network tomography using multicast measurements; 9. Other applications and miscellaneous techniques; Appendix datasets for evaluations; Index.
