基于混合蚁群优化的边缘计算细粒度任务调度方法

Method of Fine Grained Task Scheduling for Edge Computing Based on Hybrid Ant Colony Optimization

为缓解中心服务器的压力,制定合理的调度方案,基于混合蚁群优化算法提出了边缘计算细粒度任务调度方法;描述边缘计算任务调度问题,并设置假设条件,简化调度求解难度;通过计算任务的优先指数,按照从大到小的顺序排列后组成任务队列;分析边缘服务器性能特征,明确边缘服务器处理能力;构建能耗以及时延多目标函数,并设置约束条件,利用混合蚁群优化算法求解多目标函数,完成边缘计算细粒度任务调度方案设计;仿真结果表明:在5000 m×5000 m的仿真区域内,该方法应用下的任务调度能耗可以控制在150 kW/h以内,任务调度时延在5 s以内,说明该方法性能更优,所获得的调度方案更合理。

In order to alleviate the pressure of the central server and formulate a reasonable scheduling scheme,a fine-grained task scheduling method based on edge computing is proposed based on hybrid ant colony optimization algorithm.The scheduling problem of edge computing tasks is described,and the assumptions are set to simplify the difficulty of scheduling.By calculating the priority index of tasks,the task queue is formed after being arranged in the order from large to small.The performance characteristics of edge server are analyzed,and the processing capacity of edge server is clarified.The multi-objective function of energy consumption and delay is constructed,and some constraints are set.The multi-objective function is solved by the hybrid ant colony optimization algorithm to complete the design of fine-grained task scheduling scheme for edge computing.In a simulation area of 5000 m×5000 m,the experimental results show that the task scheduling energy consumption of the method may control within 160 Kw/h,the delay of task scheduling is 4 s,which shows that the performance of the proposed method is better,and the scheduling scheme is more reasonable.