A genetic algorithm perspective to distributed systems design

Proceedings of the IEEE SoutheastCon 2000. 'Preparing for The New Millennium' (Cat. No.00CH37105) Pub Date : 2000-04-07 DOI:10.1109/SECON.2000.845430

Sanjay P. Ahuja

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引用次数: 6

Abstract

Distributed computing systems (DCSs) have the potential for high reliability. When the topology of a DCS is fixed, the DCS's reliability depends mainly on the allocation of various resources. One of the important resources to be allocated in a DCS are various files. In this paper, a genetic algorithm (GA) based file allocation and design scheme has been developed for distributed systems. In this scheme, files are allocated to the nodes of the DCS such that the overall effectiveness of executing a program, which requires files from remote nodes, is maximized. Different topologies are considered to illustrate the GA-based solution approach. The effectiveness of the GA-based approach is demonstrated by comparing the results obtained using the GA with the results obtained by an exhaustive search of the problem state space. A timing study that was carried out also illustrates the effectiveness of the GA-based approach. This paper also studies the impact of the probability of crossover (Pc) and the probability of mutation (Pm) on the results obtained using the GA.

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分布式系统设计的遗传算法视角

分布式计算系统(dcs)具有高可靠性的潜力。当DCS的拓扑结构固定时，DCS的可靠性主要取决于各种资源的分配。要在DCS中分配的重要资源之一是各种文件。本文提出了一种基于遗传算法的分布式系统文件分配与设计方案。在这种方案中，文件被分配给DCS的节点，这样执行需要远程节点提供文件的程序的总体效率就得到了最大化。考虑不同的拓扑来说明基于遗传算法的解决方案方法。通过将遗传算法得到的结果与穷举搜索问题状态空间得到的结果进行比较，证明了基于遗传算法的方法的有效性。进行的时序研究也说明了基于遗传算法的方法的有效性。本文还研究了交叉概率(Pc)和突变概率(Pm)对遗传算法所得结果的影响。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Proceedings of the IEEE SoutheastCon 2000. 'Preparing for The New Millennium' (Cat. No.00CH37105)

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