Multi-Objective Ant Colony Optimization for Task Scheduling in Grid Computing

Abstract

Resource Management in Grid computing system is a fundamental issue in achieving high performance due to the distributed and heterogeneous nature of the resources. The efficiency and effectiveness of Grid resource management greatly depend on the scheduling algorithm. In this paper, the problem of scheduling is represented by a weighted directed acyclic graph (DAG). Ant Colony Optimization is used for scheduling tasks on resources in Grid which simultaneously pay attention to two objectives of makespan (schedule length) and the failure probability (reliability). These objectives are conflicting and it is not possible to minimize both objectives at the same time. With the help of concept of non-dominance, we are able to choose a trade-off between makespan minimization and reliability maximization. For evaluating the algorithm, ACO is compared with NSGA-II. The metrics for evaluating the convergence and diversity of the obtained non-dominated solutions by the two algorithms are reported. The results of simulation using JAVA programming language manifest that proposed approach can be used more efficiently for allocating the tasks as compared to NSGA-II.