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A distributed decomposition policy for computational grid resource allocation optimization based on utility functions

机译:基于效用函数的计算网格资源分配优化的分布式分解策略

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This paper presents a market-oriented resource allocation strategy for grid resource. The proposed model uses the utility functions for calculating the utility of a resource allocation. This allows the integration of different optimization objectives into allocation process. This paper is targeted to solve the above issues by using utility-based optimization scheme. We decompose the optimization problem into two levels of sub problems so that the computational complexity is reduced. Two market levels converge to its optimal points; a globally optimal point is achieved. Total user benefit of the computational grid is maximized when the equilibrium prices are obtained through the service market level optimization and resource market level optimization. The economic model is the basis of an iterative algorithm that, given a finite set of requests, is used to perform optimal resource allocation. The experiments show that scheduling based on pricing directed resource allocation involves less overhead and leads to more efficient resource allocation than conventional Round-Robin scheduling.
机译:本文提出了一种面向市场的网格资源分配策略。所提出的模型使用效用函数来计算资源分配的效用。这允许将不同的优化目标集成到分配过程中。本文旨在通过使用基于效用的优化方案来解决上述问题。我们将优化问题分解为两个级别的子问题,从而降低了计算复杂度。两个市场水平趋同于最佳点。达到了全球最佳点。当通过服务市场水平优化和资源市场水平优化获得均衡价格时,计算网格的总用户收益将最大化。经济模型是迭代算法的基础,在给定有限请求集的情况下,该算法用于执行最佳资源分配。实验表明,与传统的轮询调度相比,基于定价的资源分配调度所涉及的开销更少,并且资源分配效率更高。

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