Powered by OpenAIRE graph
Found an issue? Give us feedback
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 Networksarrow_drop_down
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
Networks
Article . 2013 . Peer-reviewed
License: Wiley Online Library User Agreement
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
zbMATH Open
Article . 2014
Data sources: zbMATH Open
DBLP
Article . 2014
Data sources: DBLP
versions View all 3 versions
addClaim

Nonexistence of optimal graphs for all terminal reliability

Authors: Jason I. Brown; Danielle Cox;

Nonexistence of optimal graphs for all terminal reliability

Abstract

AbstractSuppose that every edge of a graph G (finite and undirected) is independently operational with probability . The all terminal reliability of G is the probability that all vertices can communicate. It was conjectured that among all graphs with n vertices and m edges there always exists a most optimal graph, that is, one whose all terminal reliability is at least as large as any other such graph, no matter what the value of p. For each , a single value of m was found for which the restriction of the conjecture to simple graphs failed, but it remained open as to whether most optimal graphs exist when multiple edges are allowed. We show that in fact for a given , there are several values of m for which a most optimal simple graph does not exist. Moreover, we prove that including multiple edges still does not introduce a most optimal graph, disproving for the first time the conjecture for general graphs. In contrast, it will be shown that for a given n and m, there always exists a least optimal graph. © 2013 Wiley Periodicals, Inc. NETWORKS, Vol. 63(2), 146–153 2014

Related Organizations
Keywords

Graph theory, optimal, Combinatorial probability, reliability, semiregular graph, all terminal, Small world graphs, complex networks (graph-theoretic aspects)

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    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).
    33
    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.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
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!
33
Top 10%
Top 10%
Average
Upload OA version
Are you the author of this publication? Upload your Open Access version to Zenodo!
It’s fast and easy, just two clicks!