The detection of new impact parameters for price adjusting and allocation in market-based grids

Abstract

A market-based computational grid is made up large sets of heterogeneous and geographically distributed resources that are gathered into virtual organizations for executing consumer's jobs or applications. One of the most important challenges in market-based grid is the management of grid users, such as provider nodes and consumers. The existing methods provide some alternative mechanisms for this problem, but they are not fully adequate. To address this problem, we propose an enhanced model by using new effective parameters for task management. We also present a cooperative method between low-level scheduler to accept jobs based on commodity or auction model. The evaluation of experimental results proofs an efficient performance of the proposed approach.