Journal of Computer Applications ›› 2021, Vol. 41 ›› Issue (5): 1392-1398.DOI: 10.11772/j.issn.1001-9081.2020071091

Special Issue: 先进计算

• Advanced computing • Previous Articles     Next Articles

Two-stage task offloading strategy based on game theory in cloud-edge environment

WANG Yijie1, FAN Jiafei2, WANG Chenyu1   

  1. 1. College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao Shandong 266000, China;
    2. The Third Military Representative Office of Air Force in Nanjing, Military Representative Office of Air Force in Shanghai, Nanjing Jiangsu 211100, China
  • Received:2020-07-27 Revised:2020-09-15 Online:2021-05-10 Published:2020-10-20
  • Supported by:
    This work is partially supported by the Aeronautical Fund of Chinese Aeronautical Establishment, AVIC Nanjing Engineering Institute of Aircraft Systems and Aviation Key Laboratory of Science and Technology on Aero Electromechanical System Integration (201928052006).


王艺洁1, 凡佳飞2, 王陈宇1   

  1. 1. 山东科技大学 计算机科学与工程学院, 山东 青岛 266000;
    2. 空装驻上海地区军事代表局 空装驻南京地区第三军事代表室, 南京 211100
  • 通讯作者: 王艺洁
  • 作者简介:王艺洁(1995-),女,江苏徐州人,硕士研究生,主要研究方向:云计算、移动边缘计算;凡佳飞(1991-),男,江苏扬州人,硕士研究生,主要研究方向:云计算、虚拟化、嵌入式系统;王陈宇(1995-),男,山东枣庄人,硕士研究生,CCF会员,主要研究方向:云计算、任务调度、进化计算。
  • 基金资助:

Abstract: Mobile Edge Computing (MEC) provides an effective solution to the conflict between computationally intensive applications and resource constrained mobile devices. However, most studies on the MEC offloading only consider the resource allocation between mobile devices and MEC servers, and ignore the huge computing resources in the cloud computing centers. In order to make full use of cloud and MEC resources, a task offloading strategy of cloud-edge collaboration was proposed. Firstly, the task offloading problem of the cloud-edge servers was transformed into a game problem. Then, the existence and uniqueness of Nash Equilibrium (NE) in this game were proved, and the solution to this game problem was obtained. Finally, a two-stage task offloading algorithm based on game theory was proposed to solve the task offloading scheme, and the performance of this algorithm was evaluated by performance indicators. The simulation results show that the total overhead of using the proposed algorithm is reduced by 72.8%, 47.9%, and 2.65% compared with those of local execution, cloud server execution and MEC server execution, respectively. The numerical results confirm that the proposed strategy can achieve higher energy efficiency and lower task offloading overhead, and extend scale well with the number of mobile devices increases.

Key words: Mobile Edge Computing (MEC), cloud-edge collaboration, task offloading, game theory, Nash Equilibrium (NE)

摘要: 移动边缘计算(MEC)为计算密集型应用和资源受限的移动设备之间的冲突提供了有效解决办法,但大多关于MEC迁移的研究仅考虑移动设备与MEC服务器之间的资源分配,忽略了云计算中心的巨大计算资源。为了充分利用云和MEC资源,提出一种云边协作的任务迁移策略。首先,将云边服务器的任务迁移问题转化为博弈问题;然后,证明该博弈中纳什均衡(NE)的存在以及唯一性,并获得博弈问题的解决方案;最后,提出了一种基于博弈论的两阶段任务迁移算法来求解任务迁移问题,并通过性能指标对该算法的性能进行了评估。仿真结果表明,采用所提算法所产生的总开销分别比本地执行、云中心服务器执行和MEC服务器执行的总开销降低了72.8%、47.9%和2.65%,数值结果证实了所提策略可以实现更高的能源效率和更低的任务迁移开销,并且随着移动设备数量的增加可以很好地扩展规模。

关键词: 移动边缘计算, 云边协作, 任务迁移, 博弈论, 纳什均衡

CLC Number: