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A NEW HEURISTIC APPROACH FOR RELIABILITY OPTIMIZATION OF DISTRIBUTED COMPUTING SYSTEMS SUBJECT TO CAPACITY CONSTRAINTS

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Distributed Computing Systems (DCS) have become a major trend in computer system design today, because of their high speed and reliable performance. Reliability is an important performance parameter in DCS design. In the reliability analysis of a DCS, the term of K-Node Reliability (KNR) is defined as the probability that all nodes in K (a subset of all processing elements) are connected. In this paper, we propose a simple, easily programmed heuristic method for obtaining the optimal design of a DCS in terms of maximizing reliability subject to a capacity constraint. The first part of this paper presents a heuristic algorithm which selects an optimal set of K-nodes that maximizes the KNR in a DCS subject to the capacity constraint. The second part of the paper describes a new approach that uses a K-tree disjoint reduction method to speed up the KNR evaluation. Compared with existing algorithms on various DCS topologies, the proposed algorithm finds a suboptimal design much more efficiently in terms of both execution time and space than an exact and exhaustive method for a large DCS.

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