Edge computing task offloading and resource allocation policies

Abstract

In moving edge computing system, the unloading strategy of users will affect the energy consumption and computing cost, and then affect the benefits of users. However, most studies do not consider the effect of user uninstallation strategy and resource request strategy on benefits in random distribution of edge servers. To solve this problem, a computational offloading and resource allocation strategy based on improved dual auction algorithm is proposed. First, the interaction process between users and edge servers is modeled as Stackelberg game, and it is proved that there is a unique Nash equilibrium point in this game. Secondly, the uninstallation intention of users for different servers and the amount of computing resource requests are calculated, and the users and the optimal server are auctioned. Finally, the traversal method is used to exchange users and servers in part of the last round of auction, so as to achieve the optimal overall benefit of the system. Simulation results show that the proposed algorithm can effectively reduce the system loss.