Abstract: Edge computing is to migrate terminal tasks to the edge server for execution, and reduce task execution delay and terminal energy consumption through reasonable migration decision. In view of the fact that a large number of literatures only consider the unloading decision of multi-task single server and ignore the balance of computing tasks between servers, a multi-task multi-server joint optimization strategy based on particle swarm optimization (PSO) is proposed. Taking the delay and energy consumption as the optimization objectives, considering the queuing delay and the balance of the amount of computation of the edge computing server (MEC), the global computing resources were fully utilized, which further reduced energy consumption and time delay. Simulation results show that, compared with other algorithms, the average task cost of the proposed algorithm is the smallest, which proves the feasibility and high efficiency of the method.