Status Monitoring of Jobs in Heterogeneous Grid Environments

Computational grids are emerging as a computing paradigm for solving challenging applications in science, engineering and economics. Since the grid is a vast array of resources, monitoring of the grid is essential to improve debugging facilities and performance enhancement. Monitoring system must be able to provide information about the current state of various grid entities such as grid resources and running jobs as well as to provide notifications when certain important events occur. In this paper we provide a status monitoring system, which keeps track of the percentage of the job completed. It uses computational complexity and level of parallelism based algorithm for global scheduling and bottoms up heuristic for local scheduling the jobs. This heuristic technique efficiently maps tasks to resources so as to minimize the computing power consumed due to communication and computation