Network Tomography: Identifiability, Measurement Design, and Network State Inference - Hardcover

He, Ting; Ma, Liang; Swami, Ananthram; Towsley, Don

 
9781108421485: Network Tomography: Identifiability, Measurement Design, and Network State Inference
Hardcover
ISBN 10: 1108421482 ISBN 13: 9781108421485
Publisher: Cambridge University Press, 2021

Synopsis

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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About the Authors

Ting He is an Associate Professor in the School of Electrical Engineering and Computer Science at The Pennsylvania State University. She is a Senior Member of the IEEE.

Liang Ma is a Research Scientist in the AI Group at Dataminr Inc.

Ananthram Swami is the Senior Research Scientist for Network Science at the US Army's CCDC Army Research Laboratory. He is an ARL Fellow and a Fellow of the IEEE.

Don Towsley is a Distinguished Professor of Computer Science at the University of Massachusetts, Amherst. He is a Fellow of the IEEE and ACM.

"About this title" may belong to another edition of this title.

Publisher
Cambridge University Press
Publication date
2021
Language
English
ISBN 10 
1108421482
ISBN 13 
9781108421485
Binding
Hardcover
Edition number
1
Number of pages
330