云计算中一种基于遗传算法与效益驱动的任务调度算法

A Benefit-driven Task Scheduling Algorithm Based on Genetic Algorithm in Cloud Computing

针对云计算的任务调度问题,提出了一种基于遗传算法与效益驱动的任务调度算法.在满足任务QoS约束的前提下,对计算开销、服务收益、延迟赔偿等因素进行了综合考虑,对任务调度问题进行了数学建模,同时采用遗传算法对目标函数进行求解.仿真表明,与Min-Min算法和QoS Min-Min算法相比,所提算法能够明显地减少任务调度完成时间,更好地均衡负载,提高单位计算开销效益.

To solve the benefit-driven task scheduling problem in clouding computing,a benefit-driven task scheduling algorithm based on genetic algorithm is proposed. Under the precondition of meeting the QoS constraints, the proposed algorithm takes computation overhead, service profit and delay compensation into account. And the mathematical model of the benefit-driven task scheduling problem is introduced. Meanwhile,genetic algorithm is used to solve the he benefit-driven task scheduling problem. Simulation demonstrates that compared with the Min-Min algorithm and QoS Min-Min algorithm, the proposed algorithm can significantly reduce the scheduling completion time, balance the load and improve the profit per unit computing cost.