云工作流系统中能耗感知的任务调度算法*

云工作流系统研究集中在工作流任务执行的时间效率优化，然而时间最优的任务调度方案可能存在不同能耗，因此，文中求解满足时间约束时能耗最优的调度方案。首先改进任务执行能耗模型，设计适用于评价任务调度方案执行能耗的适应度计算方法。然后基于精准调整粒子速度的自适应权重，提出解决任务调度能耗优化问题的自适应粒子群算法。实验表明，文中算法收敛稳定，调度方案执行能耗较低。

Energy Aware Task Scheduling Algorithm in Cloud Workflow System

In the research on cloud workflow systems, the time efficiency optimization of the task execution is the emphasis. The energy consumption optimization of the task execution is often ignored. However, time-optimal task scheduling plans have different energy consumption. Therefore, how to solve energy-optimal task scheduling plans with time constraint are discussed in this paper. Firstly, the energy model of task execution is improved. Then, the fitness computation method of the task plan is designed to evaluate energy consumption. Finally, an adaptive inertia weight computation method is applied to adjust particle velocity accurately and a particle swarm optimization (PSO) algorithm is presented to solve the energy consumption optimization problem of task scheduling in cloud workflow systems. Experimental results show that the proposed algorithm has a stable convergence speed with low energy consumption.