Far East Journal of Experimental and Theoretical Artificial Intelligence
Volume 2, Issue 2 (Special Issue on Hybrid Intelligent Systems), Pages 129 - 140
(November 2008)
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PARTICLE SWARM OPTIMIZATION FOR DISTRIBUTED SYSTEM RELIABILITY
Chin-Ching Chiu (Taiwan)
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Abstract: The reliability optimization of a distributed system is generally an NP-hard problem. The reliability of a k-node set with capacity constraint is defined as the probability that a subset of the set of processing elements in system is connected and possesses sufficient node capacity. In this work, a particle swarm optimization is presented to reduce the computational time and the absolute error from the exact solution for obtaining the reliability of a k-node set with capacity constraint. The method uses an efficient objective function to evaluate the chosen nodes when a particle derives its k-node set process. Reliability computation is performed only once, thereby spending less time to compute the reliability. Moreover, the absolute error of proposed algorithm from exact solution is smaller than that of k-tree reduction method. Computational results demonstrate that the proposed algorithm is a more efficient solution for a large distributed system than conventional ones. |
Keywords and phrases: particle swarm optimization, distributed systems, reliability optimization. |
Communicated by Zne-Jung Lee |
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