Abstract
Computational grids have recently attracted considerable attention as cost‐effective platforms for parallel processing. Generally, a parallel program carried out on such a platform can be characterized as a directed acyclic graph (DAG). To take full advantage of available resources in grids and achieve high computational performance, an effective DAG scheduling algorithm is indispensable. This study presents a novel constructive algorithm based on the Fast Ant System (FANT). The proposed algorithm, namely, the Fast Ant System for Task Matching and Scheduling (FANT‐TMS) algorithm, determines the scheduling order of all tasks in a parallel program and, then, allocates these tasks to appropriate processing elements in a computational grid, thereby minimizing total completion time of the parallel program. Performance of the FANTTMS algorithm is demonstrated by comparison with a genetic algorithm (GA)‐based scheduling technique in terms of overall schedule length of randomly generated DAGs. Experimental results demonstrate that the proposed algorithm outperforms the conventional GA‐based approach. Additionally, a novel local search strategy is devised that further enhances solution quality obtained with the FANT‐TMS algorithm.
Published Version
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