基于免疫遗传算法的网格任务调度

Task Scheduling in Grid Environment Based on Immune Genetic Algorithm

研究了网格环境下任务调度问题,提出了一个任务调度机制:基于任务图将每一个可能的任务调度方案表示成一个任务-资源分配图,将网格任务调度问题转化为任务-资源分配图优化选取问题.提出了一种基于免疫遗传算法的、实现任务-资源分配图优化选取的任务调度算法.该算法将任务-资源分配图的最长路径作为抗原,每一个任务-资源分配图对应一个抗体.实验结果表明这个算法在全局优化能力及收敛速度上均有显著提高.

Studies the task scheduling in grid environment and proposes a task scheduling mechanism, i.e. each and every possible task scheduling scheme is expressed as a task-resource assignment graph, thus converting the task scheduling problem into a graphically optimal selection problem. Then, to find the optimal solution quickly and accurately, a task scheduling algorithm based on immune genetic algorithm is proposed to implement the optimal selection. This algorithm takes the longest path in the task-resource assignment graph as an antigen and every task-resource assignment as a corresponding antibody. Experimental results show that the approach proposed is effective in the capability of global optimization and significantly improves the convergence rate.