云计算任务调度的混合遗传蚁群算法研究

Research on Cloud Computing Task Scheduling Based on Hybrid Genetic Ant Algorithm

针对云计算任务调度效率与负载均衡问题,提出一种基于混合蚁群遗传算法的任务调度方法。该算法通过分析云计算任务调度特点,以最小任务调度完成时间为优化目标,通过任务分组、重新设计变异算子和信息素挥发系数,实现任务到资源调度的完成时间最小。通过CloudSim平台仿真,并与Max-Min、Min-Min、GA和AIGA算法对比,结果表明,所提出的算法有效缩短了任务调度的完成时间,降低了运营成本,具有优越的综合性能。

Aiming at the efficiency and loadbalance of cloud computing task scheduling,a task scheduling method based on hybrid genetic ant algorithm is proposed.The algorithm analyzes the characteristics of cloud computing task scheduling,takes the minimum task scheduling completion time as the optimization goal,and achieves the minimum completion time from tasks to resource scheduling through task grouping,redesigning mutation operators and pheromone volatility coefficients.And compared with Max-Min,Min-Min,GA and AIGA algorithms.The simulation results show that the proposed algorithm effectively shortens the completion time of task scheduling,reduces operating costs,and has excellent comprehensive performance.