In the mobile edge computing (MEC) system, users’ offloading strategies will affect energy consumption and computing cost, which in turn affects the users’ benefit. However, most of the existing studies have not considered the impact of users’ offloading strategies and resource request strategies on the benefit in the random distribution of edge servers. Therefore, this study proposes a computing offloading and resource allocation strategy based on an improved double auction algorithm. Firstly, this strategy models the interaction process between users and edge servers as a Stackelberg game and proves that there is a unique Nash equilibrium point in the game. Secondly, the users’ willingness to offload different servers and the amount of computing resource requests are calculated, and then users and the optimal server are auctioned. Finally, the traversal method is employed to exchange some transactions in the previous auction for the optimal overall benefit of the system. Simulation results show that, compared with other benchmark algorithms, the proposed algorithm can improve the total benefit of system users by 33.4% in the scenario of random distribution of servers and effectively reduce system loss.