Network Reliability and Resilience
Nonfiction, Computers, Computer Hardware, Input-Output Equipment, Science & Nature, Technology, Telecommunications
| Author: | Ilya Gertsbakh, Yoseph Shpungin | ISBN: | 9783642223747 |
| Publisher: | Springer Berlin Heidelberg | Publication: | September 5, 2011 |
| Imprint: | Springer | Language: | English |
| Author: | Ilya Gertsbakh, Yoseph Shpungin |
| ISBN: | 9783642223747 |
| Publisher: | Springer Berlin Heidelberg |
| Publication: | September 5, 2011 |
| Imprint: | Springer |
| Language: | English |
This book is devoted to the probabilistic description of the behavior of a network in the process of random 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 and resilience evaluation, based on applications of Monte Carlo methodology to numerical approximation of network combinatorial invariants, including so-called multidimensional destruction spectra. This allows to develop a probabilistic follow-up analysis of the network in the process of its gradual destruction, to identify most important network components and to develop efficient heuristic algorithms for network optimal design. Our methodology works with satisfactory accuracy and efficiency for most applications of reliability theory to real –life problems in networks.
This book is devoted to the probabilistic description of the behavior of a network in the process of random 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 and resilience evaluation, based on applications of Monte Carlo methodology to numerical approximation of network combinatorial invariants, including so-called multidimensional destruction spectra. This allows to develop a probabilistic follow-up analysis of the network in the process of its gradual destruction, to identify most important network components and to develop efficient heuristic algorithms for network optimal design. Our methodology works with satisfactory accuracy and efficiency for most applications of reliability theory to real –life problems in networks.
