000 03043nam a22003735i 4500
001 393867
003 ES-MaUEC
005 20230102123033.0
007 cr nn 008mamaa
008 220831s2022 sz | s |||| 0|eng d
020 _a9783031142567
024 7 _a10.1007/978-3-031-14256-7
_2doi
040 _aES-MaUEC
_bspa
_cES-MaUEC
100 1 _aVass, Balázs
_eautor
_0(orcid)0000-0002-8589-7165
_1https://orcid.org/0000-0002-8589-7165
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aRegional Failure Events in Communication Networks
_bModels, Algorithms and Applications
_cby Balázs Vass
250 _a1st edition 2022
264 1 _aCham
_bSpringer International Publishing
_c2022
300 _a1 recurso en línea (XIV, 119 páginas)
_b38 ilustraciones, 28 ilustraciones a color
336 _atexto
_btxt
_2rdacontent
337 _aelectrónico
_bc
_2rdamedia
338 _arecurso electrónico
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
490 0 _aSpringer Theses Recognizing Outstanding Ph.D. Research
_x2190-5061
505 0 _aIntroduction -- Formal Problem Statement -- RelatedWork -- Algorithmic Background.
520 _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.
776 0 8 _iPrinted edition:
_z9783031142550
776 0 8 _iPrinted edition:
_z9783031142574
776 0 8 _iPrinted edition:
_z9783031142581
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-14256-7
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942 _2lcc
_cLE
988 _aSpringer_Computer_2022
999 _c393867
_d393867