Due to the limited computing resources and battery capacity of existing mobile devices, it cannot meet the requirements of low load base station group for computing capacity and delay, and the emergence of mobile edge computing (MEC) technology provides the possibility for it. Therefore, a distributed task unloading strategy to low load base station group under MEC environment is proposed. Firstly, the communication resource, computing resource and task queue of low load base station group are modeled to quantify the energy cost in the process of task unloading. Then, the game theory is introduced, and the potential game model is used to solve the problem of distributed task unloading. The target function of energy optimization based on delay limitation is transformed into the potential game equation, and the mobile device selects MEC nodes according to the game results to calculate the unloading. Finally, based on the MATLAB platform, the algorithm is simulated, and the results show that the proposed potential game equation can converge to the Nash equilibrium. Compared with other algorithms, the proposed distributed task unloading algorithm can effectively save the energy consumption of task unloading.

由于现有移动设备的计算资源和电池容量有限，它不能满足低负载基站群对计算能力和时延的要求，而移动边缘计算技术的出现为它提供了可能性。因此，提出了一种MEC环境下低负荷基站群的分布式任务卸载策略。首先，对低负荷基站群的通信资源，计算资源和任务队列进行建模，以量化任务卸载过程中的能源成本。然后介绍了博弈论，并用潜在的博弈模型解决了分布式任务卸载的问题。基于延迟限制的能量优化目标函数转化为潜在博弈方程，然后移动设备根据游戏结果选择MEC节点进行卸载。最后，在MATLAB平台上对该算法进行了仿真，结果表明所提出的潜在博弈方程可以收敛到纳什均衡。与其他算法相比，本文提出的分布式任务卸载算法可以有效地节省任务卸载的能耗。