Network Reliability and Resilience [electronic resource] / by Ilya Gertsbakh, Yoseph Shpungin.
Tipo de material: TextoSeries SpringerBriefs in Electrical and Computer EngineeringDescripción: X, 64p. 21 illus. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resource ISBN: 9783642223747 99783642223747Tema(s): Engineering | Computer network architectures | System safety | Telecommunication | Engineering | Communications Engineering, Networks | Computer Systems Organization and Communication Networks | Quality Control, Reliability, Safety and RiskClasificación CDD: 621.382 Clasificación LoC:TK1-9971Recursos en línea: ir a documento En: 0# Springer eBooksResumen: 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.Tipo de ítem | Ubicación actual | Colección | Signatura | Info Vol | Copia número | Estado | Fecha de vencimiento | Código de barras | Reserva de ítems |
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DOCUMENTOS DIGITALES | Biblioteca Jorge Álvarez Lleras | Digital | 621.382 223 (Navegar estantería) | Ej. 1 | 1 | Disponible | D000578 |
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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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