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IEEE Transactions on Communications
Article . 1990 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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Least reliable networks and the reliability domination

Authors: A. Satyanarayana; Charles L. Suffel; F. T. Boesch;

Least reliable networks and the reliability domination

Abstract

Summary: A well-known model in communication network reliability consists of an undirected graph \(G\) whose edges operate independently with the same probability \(p\). Then the reliability, \(R(G,p)\) of \(G\), is the probability that \(G\) is connected. It is known that \(R(G,p)\) is a polynomial in \(p\) and its coefficients are invariants of \(G\). In particular, the coefficient of the least order term is the number of spanning trees \(t(G)\), while the coefficients of the highest order term is the reliability domination \(d(G)\) of \(G\). Presented is a complete characterization of graphs that achieve the minimum absolute value \(| d(G)|\) over the class \(n\)-node, \(e\)-edge connected graphs. Furthermore, the class of graphs that yield minimum \(t(G)\) is shown to minimize \(| d(G)|\). These results have applications in the synthesis of least reliable networks.

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Keywords

Graph theory, Reliability, availability, maintenance, inspection in operations research, communication, reliability domination, Applications of graph theory to circuits and networks, Communication networks in operations research, network reliability

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    influence
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
28
Top 10%
Top 10%
Average
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