Conventional Resource Matching and Scheduling For Dependent and Independent Tasks in Grid

The tremendous potential of grid computing is efficient scheduling, to exploit the computationally intense problems. In the commonly used decentralized models, large scale scheduling implies time sequence constraints, which makes the models intractable. To resolve this constraint, disintegration and cyclic scheduling are often applied to such scheduling which is time consuming and introducing more complexities. The significance of this paper is marked by speed and efficiency. The task-resource mapping in such a non-deterministic computing environment leads to concerns over scheduling problems to identify suitable resources. Thereby we minimize the expected makespan and delay in allocation of tasks to reduce the turnaround time for tasks. The grid model is capable of handling applications with a combination of dependent and independent tasks. Our rigorous performance evaluation shows that our variant conventional resource matching algorithm generates schedules with smaller makespan and higher robustness compared with other existing approach gratuitous to the new enhancement.