Network Reliability and Resilience [electronic resource] /by Ilya Gertsbakh, Yoseph Shpungin.
by Gertsbakh, Ilya [author.]; Shpungin, Yoseph [author.]; SpringerLink (Online service).
Material type:
BookSeries: SpringerBriefs in Electrical and Computer Engineering: Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2011.Description: X, 64p. 21 illus. online resource.ISBN: 9783642223747.Subject(s): Engineering | Computer network architectures | System safety | Telecommunication | Engineering | Communications Engineering, Networks | Computer Systems Organization and Communication Networks | Quality Control, Reliability, Safety and RiskDDC classification: 621.382 Online resources: Click here to access online
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Springer eBooksSummary: This book is devoted to the probabilistic description of a network in the process of its destruction, i.e. removal of its components (links, nodes) appearing as a result of technical failures, natural disasters or intentional attacks . It is focused on a practical approach to network reliability, based on application of Monte Carlo methodology to numerical evaluation of network most important structural parameters. This allows to obtain a probabilistic description of the network in the process of its destruction, to identify most important network components and to develop efficient heuristic algorithms for network optimal design. The methodology works with satisfactory accuracy and efficiency for small –to-medium size networks.
| Item type | Current location | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|
| MAIN LIBRARY | TK1-9971 (Browse shelf) | Available |
This book is devoted to the probabilistic description of a network in the process of its destruction, i.e. removal of its components (links, nodes) appearing as a result of technical failures, natural disasters or intentional attacks . It is focused on a practical approach to network reliability, based on application of Monte Carlo methodology to numerical evaluation of network most important structural parameters. This allows to obtain a probabilistic description of the network in the process of its destruction, to identify most important network components and to develop efficient heuristic algorithms for network optimal design. The methodology works with satisfactory accuracy and efficiency for small –to-medium size networks.
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