DocumentCode :
1118907
Title :
A Heuristic Algorithm for Reliability Modeling and Analysis of Grid Systems
Author :
Dai, Yuan-Shun ; Xie, Min ; Wang, Xiaolong
Author_Institution :
Dept. of Comput. & Inf. Sci., Indiana Univ.-Purdue Univ., Indianapolis, IN
Volume :
37
Issue :
2
fYear :
2007
fDate :
3/1/2007 12:00:00 AM
Firstpage :
189
Lastpage :
200
Abstract :
Grid computing focuses on large-scale resource sharing. Using a general reliability model for grid computing to relax some impractical assumptions, a heuristic algorithm is presented to evaluate grid program/service reliability. The heuristic algorithm is based on two heuristic criteria that determine the significance of an entity and prune those insignificant ones. Through algorithm analysis, the heuristic algorithm is shown to have a linear complexity. This is much better than the previous algorithms, which are of exponential complexity. Another advantage of the heuristic algorithm is that the running time is controllable by adjusting the parameter of significant level (SL) and significant rate. A regression method is proposed to adjust the SL and predict the running time. Two examples are given
Keywords :
Bayes methods; computational complexity; grid computing; reliability theory; Bayesian analysis; distributed computing; exponential complexity; grid computing; grid systems analysis; heuristic algorithm; large-scale resource sharing; regression method; reliability modeling; service reliability; significant level; Algorithm design and analysis; Application software; Collaborative software; Distributed computing; Graph theory; Grid computing; Heuristic algorithms; Large-scale systems; Reliability theory; Resource management; Bayesian analysis; distributed computing; graph theory; grid program/service reliability; heuristic algorithm;
fLanguage :
English
Journal_Title :
Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on
Publisher :
ieee
ISSN :
1083-4427
Type :
jour
DOI :
10.1109/TSMCA.2006.889479
Filename :
4100774
Link To Document :
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