Topology and load aware - Grid scheduler for the computational grid environment

Computational Grid is a distributed computing paradigm that provides huge computational power for the large scale distributed application. One of the challenging issues in Grid Scheduling is dynamically choosing the best resource, by exploiting the topology and load information present at the time of scheduling. Here topology represents the delay or elapse time to reach the resource. In the proposed model, Grid Scheduling is done not only by considering topology and load information; in addition it also considers the type of job, such as data intensive or computation intensive. Moreover, we can realize the load balancing during the scheduling itself. This approach reduces the waiting time and elapse time of the job by submitting the job to the resource which is having less delay (Topology Cost) to reach and fewer loads. Moreover it increases the performance in the large scale application by maximize the utilization of the resources which are idle or least loaded.