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Network tomography : identifiability, measurement design, and network state inference / Ting He, Liang Ma, Ananthram Swami, Don Towsley.

By: He, Ting (Associate professor of computer science and engineering) [author.].
Contributor(s): Ma, Liang (Research scientist) [author.] | Towsley, Don [author.] | Swami, Ananthram [author.].
Material type: materialTypeLabelBookPublisher: Cambridge : Cambridge University Press, 2021Description: 1 online resource (xi, 231 pages) : digital, PDF file(s).Content type: text Media type: computer Carrier type: online resourceISBN: 9781108377119 (ebook).Subject(s): Computer networks -- MonitoringAdditional physical formats: Print version: : No titleDDC classification: 004.6 Online resources: Click here to access online
Contents:
Preliminaries -- Fundamental conditions for additive network tomography -- Monitor placement for additive network tomography -- Measurement path construction for additive network tomography -- Fundamental conditions for Boolean network tomography -- Measurement design for Boolean network tomography -- Stochastic network tomography using unicast measurements -- Stochastic network tomography using multicast measurements -- Other applications and miscellaneous techniques.
Summary: 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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Title from publisher's bibliographic system (viewed on 28 May 2021).

Preliminaries -- Fundamental conditions for additive network tomography -- Monitor placement for additive network tomography -- Measurement path construction for additive network tomography -- Fundamental conditions for Boolean network tomography -- Measurement design for Boolean network tomography -- Stochastic network tomography using unicast measurements -- Stochastic network tomography using multicast measurements -- Other applications and miscellaneous techniques.

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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