In the running process of cloud computing system, the idle compute nodes will generate a large amount of idle energy consumption. Furthermore, the unmatching task scheduling strategy will also cause a great waste of energy consumption. This paper presents a policy of energy optimal management for cloud computing system based on task scheduling strategy. First, use queueing system to model the cloud computing system for analyzing the mean response time, mean power consumption of cloud computing system, and constructing the energy consumption model of cloud computing system. In order to reduce waste of energy, a high service utilization task scheduling and a low execution energy task scheduling strategy are propsed, which are used to reduce idle energy and "luxury" energy respectively. Based on the idea of the strategies, an algorithm is designed which is called minimum expectation execution energy with performance constraints (ME3PC). Repeated experiments show that this energy management strategy can reduce the energy consumption considerably while meeting performance constraints.%针对云计算系统在运行过程中由于计算节点空闲而产生大量空闲能耗,以及由于不匹配任务调度而产生大量“奢侈”能耗的能耗浪费问题,提出一种通过任务调度方式的能耗优化管理方法.首先,用排队模型对云计算系统进行建模,分析云计算系统的平均响应时间和平均功率,建立云计算系统的能耗模型.然后提出基于大服务强度和小执行能耗的任务调度策略,分别针对空闲能耗和“奢侈”能耗进行优化控制.基于该调度策略,设计满足性能约束的最小期望执行能耗调度算法ME3PC(minimum expectation execution energy with performance constraints).实验结果表明,该算法在保证执行性能的前提下,可大幅度降低云计算系统的能耗开销.
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