On the performance of a dual-objective optimization model for workflow applications on grid platforms

In attempts to exploit a diverse set of resources in grids efficiently, numerous assays in resource management, particularly scheduling, have been made. The primary objective of these efforts is the minimization of application completion time; however, they tend to achieve this objective at the expense of redundant resource usage. This paper investigates the problem of scheduling workflow applications on grids and presents a novel scheduling algorithm for the solution of this problem. Our algorithm performs the scheduling by accounting for both completion time and resource usage - dual objectives. Since the performance of grid resources changes dynamically and the accurate estimation of their performance is very difficult, our algorithm incorporates rescheduling to deal with unforeseen performance fluctuations effectively. The paper provides a comparative evaluation study conducted by using an extensive set of experiments. The study demonstrates that the proposed algorithm delivers promising performance in three respects: completion time, resource utilization, and robustness to resource-performance fluctuations.