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010   $a9783031142567$b(electronic bk.)
010   $z9783031142550
024 7 $a10.1007/978-3-031-14256-7
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035   $a(DE-He213)978-3-031-14256-7
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100   $a20220831d2022      u|         0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aRegional Failure Events in Communication Networks $eModels, Algorithms and Applications /$fby Balázs Vass
205   $a1st ed. 2022.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2022.
215   $a1 online resource (130 pages)
225 1 $aSpringer Theses, Recognizing Outstanding Ph.D. Research,$x2190-5061
311 08$aPrint version: Vass, Balázs Regional Failure Events in Communication Networks Cham : Springer International Publishing AG,c2022 9783031142550 
327   $aIntroduction -- Formal Problem Statement -- RelatedWork -- Algorithmic Background.
330   $aThis book presents a comprehensive study covering the design and application of models and algorithms for assessing the joint device failures of telecommunication backbone networks caused by large-scale regional disasters. At first, failure models are developed to make use of the best data available; in turn, a set of fast algorithms for determining the resulting failure lists are described; further, a theoretical analysis of the complexity of the algorithms and the properties of the failure lists is presented, and relevant practical case studies are investigated. Merging concepts and tools from complexity theory, combinatorial and computational geometry, and probability theory, a comprehensive set of models is developed for translating the disaster hazard in informative yet concise data structures. The information available on the network topology and the disaster hazard is then used to calculate the possible (probabilistic) network failures. The resulting sets of resources that are expected to break down simultaneously are modeled as a collection of Shared Risk Link Groups (SRLGs), or Probabilistic SRLGs. Overall, this book presents improved theoretical methods that can help predicting disaster-caused network malfunctions, identifying vulnerable regions, and assessing precisely the availability of internet services, among other applications.
410  0$aSpringer Theses, Recognizing Outstanding Ph.D. Research,$x2190-5061
606   $aComputer Networks
606   $aComputer science
606   $aGeometry
606   $aStatistics
606   $aSystem theory
606   $aComputer Networks
606   $aComputational Geometry
606   $aStatistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences
606   $aComplex Systems
615  0$aComputer Networks.
615  0$aComputer science.
615  0$aGeometry.
615  0$aStatistics.
615  0$aSystem theory.
615 14$aComputer Networks.
615 24$aComputational Geometry.
615 24$aStatistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
615 24$aComplex Systems.
676   $a363.348
676   $a621.3820113
700   $aVass$b Bala?zs$00
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
912   $a9910590044903321
996   $aRegional Failure Events in Communication Networks$92908185
997   $aUNINA