DocumentCode :
1058510
Title :
An analysis of edge fault tolerance in recursively decomposable regular networks
Author :
Lagman, Annette ; Najjar, Walid A. ; Srimani, Pradip K.
Author_Institution :
Dept. of Comput. Sci., Colorado State Univ., Fort Collins, CO, USA
Volume :
43
Issue :
4
fYear :
1994
fDate :
4/1/1994 12:00:00 AM
Firstpage :
470
Lastpage :
475
Abstract :
Fault tolerance of interconnection networks is one of the major considerations in evaluating the reliability of large scale multiprocessor systems. In the paper, the reliability of a family of regular networks with respect to edge failures is investigated using four different fault tolerance measures. Two probabilistic measures, resilience and restricted resilience, are developed, used to evaluate disconnection likelihoods using two different failure models, and compared with corresponding deterministic measures. The network topologies chosen for the present study all have the recursive decomposition property, where larger networks can be decomposed into copies of smaller networks of the same topology. This family of graphs includes the k-ary n-cube, star and cube connected cycle graphs, which have optimal deterministic connectivities. The probabilistic fault tolerance measures, however, are found to depend on topological properties such as network size and degree
Keywords :
fault tolerant computing; multiprocessor interconnection networks; network topology; edge failures; edge fault tolerance; fault tolerance measures; interconnection networks; large scale multiprocessor; network topologies; probabilistic fault tolerance measures; probabilistic measures; recursively decomposable; regular networks; reliability; resilience; restricted resilience; topological properties; Character generation; Computer science; Failure analysis; Fault tolerance; Intelligent networks; Large-scale systems; Multiprocessor interconnection networks; Network topology; Resilience; Size measurement;
fLanguage :
English
Journal_Title :
Computers, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9340
Type :
jour
DOI :
10.1109/12.278484
Filename :
278484
Link To Document :
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