移动边缘计算中卸载策略与功率的联合优化

移动边缘计算卸载作为移动边缘计算的关键技术,主要功能是将移动设备的密集型计算任务迁移到边缘服务器上执行,实现低能耗和低时延的服务,但在计算任务卸载过程中产生的传输时延和能耗降低了用户的体验质量。为进一步降低延迟和能量消耗,针对移动边缘计算卸载系统,提出基于博弈论的功率分配算法。在服务器计算资源的约束条件下,采用二分搜索法优化传输功率降低传输时延和能耗,利用非合作博弈论解决多用户卸载决策问题降低系统开销。仿真结果表明,该算法可以获得较好的计算卸载性能,与单纯的博弈卸载算法和自适应顺序卸载博弈算法相比,卸载性能分别提高41%和12%。

Joint Optimization of Offloading Strategy and Power in Mobile-Edge Computing

The main function of Mobile-Edge Computing Offloading(MECO),which is a key technology for mobile edge computing,is to migrate the compute-intensive tasks of Mobile Devices(MD)to edge servers to implement low-energy and low-latency services.However,transmission delay and energy consumption in offloading of compute tasks still affect user experience.To further reduce the delay and energy consumption,this paper proposes a power distribution algorithm based on game theory for MECO system.Under the constraints of computing resources of a server,the binary search method is used to optimize the transmission power to reduce transmission delay and energy consumption,and the non-cooperative game theory is used to solve the multi-user offloading decision problem in order to reduce the system overhead.Simulation results show that the proposed algorithm can obtain better computation offloading performance,which is increased by 41%and 12%respectively compared with the original game-based offloading algorithm and adaptive sequential game-based offloading algorithm.