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

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.