Distributed task offloading strategy to low load base stations in mobile edge computing environment

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.