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An optimization approach for decentralized QoS-based scheduling based on utility and pricing in Grid computing

机译:网格计算中基于效用和定价的基于QoS的分散式调度优化方法

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This paper presents an optimization approach for decentralized Quality of Service (QoS)-based scheduling based on utility and pricing in Grid computing. The paper assumes that the quality dimensions can be easily formulated as utility functions to express quality preferences for each task agent. The utility values are calculated by the user-supplied utility function that can be formulated with the task parameters. The QoS constraint Grid resource scheduling problem is formulated into a utility optimization problem. The QoS-based Grid resource scheduling optimization is decomposed into two subproblems by applying the Lagrangian method. In the Grid, a Grid task agent acts as a consumer paying for the Grid resource and the resource providers receive profits from task agents. A pricing-based QoS scheduling algorithm is used to perform optimally decentralized QoS-based resource scheduling. The experiments investigate the effect of the QoS metrics on the global utility and compare the performance of the proposed algorithm with other economical Grid resource scheduling algorithms.
机译:本文提出了一种在网格计算中基于效用和定价的基于分散服务质量(QoS)调度的优化方法。本文假设可以轻松地将质量维度表述为效用函数,以表达每个任务代理的质量偏好。效用值是由用户提供的效用函数计算的,可以用任务参数来表述。将QoS约束网格资源调度问题表述为效用优化问题。通过应用拉格朗日方法将基于QoS的网格资源调度优化分解为两个子问题。在网格中,网格任务代理充当消费者来为网格资源付款,资源提供者从任务代理那里获得利润。基于定价的QoS调度算法用于执行最佳分散的基于QoS的资源调度。实验研究了QoS指标对全球效用的影响,并将该算法与其他经济的网格资源调度算法的性能进行了比较。

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