2011
DOI: 10.1109/tr.2011.2170250
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Polynomial-Time Topological Reductions That Preserve the Diameter Constrained Reliability of a Communication Network

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Cited by 21 publications
(18 citation statements)
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“…The above researches on network reliability do not restrict the length of the path. Petingi et al [26] proposed a polynomial-time algorithm for detecting and deleting irrelevant edges that make no difference to the source-to-terminal diameter constrained network reliability. They integrated this algorithm within an exact recursive factorization approach based upon Moskowitz's edge decomposition, conducted on different real-world topologies and confirmed a substantial computational gain.…”
Section: Background and Related Workmentioning
confidence: 99%
“…The above researches on network reliability do not restrict the length of the path. Petingi et al [26] proposed a polynomial-time algorithm for detecting and deleting irrelevant edges that make no difference to the source-to-terminal diameter constrained network reliability. They integrated this algorithm within an exact recursive factorization approach based upon Moskowitz's edge decomposition, conducted on different real-world topologies and confirmed a substantial computational gain.…”
Section: Background and Related Workmentioning
confidence: 99%
“…If we are given a graph, a terminal set (i.e., a node subset), and a positive integer d (called diameter), we want all pairs to be connected by d hops or less, in a hostile environment where link failures occur. We invite the reader to see [3] for a rich discussion on diameter-constrained reliability and its applications, ranging from FTTH to peer-to-peer networks and floodingbased systems.…”
Section: Motivationmentioning
confidence: 99%
“…In Definition 3, the expected s,t-path is different from (1). For the expected path with diameter constraint can be rewritten as:…”
Section: The Expected Path For Diameter Constraintmentioning
confidence: 99%
“…Two terminals normally mean source node s, and target node t in V. Lecture [1] consider the model that nodes are perfect, but each edge of G is assigned an independent probability, and called the edge probability. The states of edges are supposed to be independent random variables with either operational state or failed state in network.…”
Section: Introductionmentioning
confidence: 99%