Resource Management in Computational Grid with Economic Based Allocation Model Using Particle Swarm Optimization (pso)

Abstract

In grid environment, based on economic model, grid users who submit jobs and grid resource providers who provide resources have different motivations. Due to autonomy of both in gird users and resource providers, their objectives often conflict. This paper, review the Literature studies and techniques to solve the grid resource allocation problem. The problem of allocating resources in Grid environment requires the definition of a model that allows in considerable level in the code of allocating right resources to right jobs, poor economic model to communicate in order to achieve an efficient management of the resources themselves. Some of the drawbacks occur during grid resource allocation are low utilization, less economic reliability and increased waiting time of the jobs. Hence in this paper, the efficiency of the resource allocation mechanism is improved by proposing one allocation model. The allocation model technique which is presented in this paper has used the Particle Swarm Optimization (PSO) to overcome all the above mentioned drawbacks. This model also considers the economic reliability and this model overcomes the poor economic model drawback that is in the existing method. The economic based model is implemented and experimented with different number of jobs and resources. The proposed model has also been compared with the conventional resource allocation models in terms of utilization, cost factor, failure rate and make span.

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Cite this paper

@inproceedings{VENKATESAN2013ResourceMI, title={Resource Management in Computational Grid with Economic Based Allocation Model Using Particle Swarm Optimization (pso)}, author={R . VENKATESAN and K. Thanushkodi}, year={2013} }