基于延迟接受的多用户任务卸载策略

随着人工智能的应用对计算资源的要求越来越高,移动设备由于计算能力和存储能量有限而无法处理这类有实时性需求的计算密集型应用。移动边缘计算(Mobile Edge Computing,MEC)可以在无线网络边缘提供计算卸载服务,达到缩短时延和节约能源的目的。针对多用户依赖任务卸载问题,在综合考虑时延与能耗的基础上建立用户依赖任务模型,提出了基于延迟接受的多用户任务卸载策略(Multi-User Task Offloading Based on Delayed Acceptance,MUTODA),用于解决时延约束下最小化能耗的任务卸载问题。该策略通过非支配的单用户最优卸载策略和解决资源竞争的调整策略两个步骤的不断迭代,来解决多用户任务卸载问题。实验结果表明,相比基准策略和启发式策略,基于延迟接受的多用户任务卸载策略能够提高约8%的用户满意度,节约30%~50%的移动终端能耗。

Multi-user Task Offloading Based on Delayed Acceptance

With the application of artificial intelligence,the demand for computing resources is higher and higher.Due to the limi-ted computing power and energy storage,mobile devices can not deal with this kind of computing intensive applications with real-time requirements.Mobile edge computing(MEC)can provide computing offload service at the edge of wireless network,so as to reduce the delay and save energy.Aiming at the problem of multi-user dependent task offloading,a user dependent task model is established based on the comprehensive consideration of delay and energy consumption.The multi-user task offloading strategy based on delay acceptance(MUTODA)is proposed to solve the problem of minimizing energy consumption under delay constraints.MUTODA solves the problem of multi-user task offloading through two steps of non dominated single user optimal offloading strategy and adjustment strategy to solve resource competition.The experimental results show that compared with the benchmark strategy and heuristic strategy,the multi-user task offloading strategy based on delayed acceptance can improve about 8%user satisfaction and save 30%~50%of the energy consumption of mobile terminals.