Multi economic agent interaction for optimizing the aggregate utility of grid users in computational grid
Multi economic agent interaction for optimizing the aggregate utility of grid users in computational grid
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DOI：
10.1007/s10489-006-9651-8
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发表时间：
2006-10
影响因子：
5.3
通讯作者：
Chunlin Li;La-yuan Li
中科院分区：
文献类型：
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作者：
Chunlin Li;La-yuan Li
本文研究了代表网格用户的代理与网格资源提供者之间的交互，以最大化计算网格中所有网格用户的总效用。它提出了一种基于价格的资源分配模型，以实现计算网格中网格用户和提供者效用的最大化。现有的分布式资源分配方案假设资源提供者能够测量用户的资源需求、计算和传达价格，但这些在现实中都不存在。本文解决了这些挑战如下。首先，网格用户效用被定义为网格用户分配的资源单位的函数。我们使用非线性优化理论将资源分配形式化，该理论结合了网格资源容量约束和作业完成时间。最佳解决方案最大化所有电网用户的总效用。其次，本文提出了一种新的基于优化的网格资源定价算法，用于将资源分配给网格用户，同时最大化网格提供商的收入。仿真结果表明，我们提出的算法比对比分配方案更有效。
This paper investigates the interactions between agents representing grid users and the providers of grid resources to maximize the aggregate utilities of all grid users in computational grid. It proposes a price-based resource allocation model to achieve maximized utility of grid users and providers in computational grid. Existing distributed resource allocation schemes assume the resource provider to be capable of measuring user’s resource demand, calculating and communicating price, none of which actually exists in reality. This paper addresses these challenges as follows. First, the grid user utility is defined as a function of the grid user’s the resource units allocated. We formalize resource allocation using nonlinear optimization theory, which incorporates both grid resource capacity constraint and the job complete times. An optimal solution maximizes the aggregate utilities of all grid users. Second, this paper proposes a new optimization-based grid resource pricing algorithm for allocating resources to grid users while maximizing the revenue of grid providers. Simulation results show that our proposed algorithm is more efficient than compared allocation scheme.