Multi-agent framework for performance-based resource management in computational grid environment

Resource management is one of the focus areas in Grid computing research. One major objective of resource management in a computational Grid environment is to allocate jobs to make efficient use of the computational resources under different resource providers and, thereby, achieve high performance of the jobs. Therefore, performance analysis is also an important issue in Grid resource management. This paper aims at providing an integrated framework for performance-based resource management in computational Grid environment. The framework is supported by a multi-agent system (MAS) which has been developed using a firm software engineering approach based on Gaia methodology. The MAS provides adaptive execution facility either by rescheduling the jobs onto different resource providers or through application of local tuning techniques to jobs in case of any performance problem (may be due to some change in the resource availability or usage scenario). Thus it always guarantees to maintain the quality of service as desired by the client.