Grid task scheduling using mutation particle swarm algorithm

Computing grids utilize Internet or special networks to access computing resources which are geographically widespread, in order to solve complex problems more effectively. Task scheduling in grid plays an important role in grid system. This paper introduces mutation into particle swarm algorithm. The method makes the algorithm jump out local optimization and search for the global optimal solution in other areas. To some extent, it overcomes the inherent flaw of PSO that falling into local optimization. Using this method in grid task scheduling can not only generate relevant scheme dynamically, and also make the complete time minimum. The experiment shows that the algorithm achieves a better result in task scheduling.