计算机与现代化 ›› 2022, Vol. 0 ›› Issue (11): 32-36.

• 算法设计与分析 • 上一篇    下一篇

基于粒子群算法的移动边缘计算任务分配方法

  

  1. (广州华商学院数据科学学院,广东广州511300)
  • 出版日期:2022-11-30 发布日期:2022-11-30
  • 作者简介:陈刚(1973—),男,湖南长沙人,讲师,硕士,研究方向:信息安全与云计算,E-mail: chengang_2022@126.com; 王志坚(1970—),男,湖南长沙人,教授,硕士生导师,博士,研究方向:控制理论与控制工程; 徐胜超(1980—),男,湖北武汉人,讲师,硕士,研究方向:并行分布式处理软件。
  • 基金资助:
    国家自然科学基金资助项目(61772221); 广州华商学院校内导师制科研资助项目(2022HSDS16)

Mobile Edge Computing Task Allocation Method Based on Particle Swarm Optimization

  1. (School of Data Science, Guangzhou Huashang College, Guangzhou 511300, China)
  • Online:2022-11-30 Published:2022-11-30

摘要: 为提高移动终端任务分配效率,降低计算能量损耗,提出基于粒子群算法的移动边缘计算任务分配方法。通过构建异构网络获取完整的需要分配的任务,明确任务分配时所需的特定条件,即分配消耗和时延等。将分配任务转化成寻找分配结果的最优解,构建最优解模型,利用粒子群算法对模型实施求解,经过不断迭代和更新,生成最优边缘计算任务的分配结果。实验结果表明,粒子群方法在分配任务数量为20~100之间时计算时间在1 s~3.3 s;当任务数量为100时,本文方法能耗仅为4107 J;粒子群方法在任务达到率达到100%时,其时延仅为12.5 ms;其任务分配计算时间短、能量消耗小和数据传输的时延短,能较好地满足实际应用需要。

关键词: 粒子群算法, 移动终端, 任务分配, 时间延时, 能量消耗

Abstract: In order to improve the task allocation efficiency of mobile terminals and reduce the computational energy consumption, a mobile edge computing task allocation method based on particle swarm algorithm is proposed. By building a heterogeneous network, we can obtain the complete tasks that need to be allocated, and clarify the specific conditions required for task allocation, that is, allocating consumption and delay. The assignment task is converted into finding the optimal solution of the assignment result, building the optimal solution model, solving the model with the help of the particle swarm algorithm, and generating the assignment result of the optimal edge computing task through continuous iteration and update. The experimental results show that the calculation time of the proposed method is between 1 and 3.3 s when the number of tasks assigned is between 20 and 100; when the number of tasks is 100, the energy consumption of the proposed method is only 4107 J; When it is 100%, its delay is only 12.5 ms; its task allocation calculation time is short, energy consumption is small and data transmission delay is short, which can satisfy the certain application requirement.

Key words: particle swarm algorithm, mobile terminal, task allocation, time delay, energy consumption