DocumentCode :
1315917
Title :
A coherent model for reliability of multiprocessor networks
Author :
Boesch, F. ; Gross, D. ; Suffel, G.
Author_Institution :
Dept. of Electr. Eng., Stevens Inst. of Technol., Hoboken, NJ, USA
Volume :
45
Issue :
4
fYear :
1996
fDate :
12/1/1996 12:00:00 AM
Firstpage :
678
Lastpage :
684
Abstract :
Graph G has perfectly reliable nodes and edges that are subject to stochastic failure. The network reliability R is the probability that the surviving edges induce a spanning connected subgraph of G. Analysis problems concern determining efficient algorithms to calculate R, which is known to be NP-hard for general graphs. Synthesis problems concern determining graphs that are, according to some definition, the most reliable in the class of all graphs having a given number of edges and nodes. In applications where the edges are perfectly reliable and the nodes are subject to failure, another measure (residual node connectedness reliability) is defined as the probability that the surviving nodes induce a connected subgraph of G. Referring to such a subset as an operating state, the measure is not coherent because a superset of an operating state need not be an operating state. This paper proposes a new definition of network reliability that handles the case of node failures; it is coherent. We determine many of its properties, and present several analysis and synthesis results
Keywords :
computational complexity; computer network reliability; graph theory; multiprocessor interconnection networks; NP-hard; coherent model; failure; multiprocessor networks reliability; network reliability; probability; residual node connectedness reliability; spanning connected subgraph; stochastic failure; surviving edges; synthesis problems; Bipartite graph; Computer network reliability; Network synthesis; Network topology; Tree graphs;
fLanguage :
English
Journal_Title :
Reliability, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9529
Type :
jour
DOI :
10.1109/24.556593
Filename :
556593
Link To Document :
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