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基于蚁群算法的任务调度会遇到负载不均衡与收敛速度变慢的问题,针对蚁群算法应用于任务调度机制时存在的缺陷,通过赋予权重的方法对该算法的信息素更新规则进行改进,加快求解速度,利用动态更新挥发系数优化算法的综合性能,并在局部信息素的更新过程中,引入虚拟机负载权重系数。实验结果表明,基于改进算法的任务调度策略在保证任务得到合理分配的同时,算法的收敛速度与总执行时间得到了优化。
Task scheduling based on ant colony algorithm will encounter the problem of unbalanced load and slower convergence speed. Aiming at the shortcomings of ant colony algorithm applied to task scheduling mechanism, the algorithm of pheromone updating is improved by giving weight , Speeding up the solution, using the comprehensive performance of the dynamic update volatility optimization algorithm, and introducing virtual machine load weight coefficient in the process of updating the local pheromone. The experimental results show that the task scheduling strategy based on the improved algorithm can optimize the task convergence rate and the total execution time while ensuring the task assignment.