A combined algorithm of potential game and particle swarm optimization for multi-user edge computing task offloading

For the scenario of edge computing tasks’ offloading between multi-user and multi-server, the number of offloading strategies increases exponentially with the number of users which makes it difficult to find the optimal solution through brute force search. The task offloading model for this scenario is established, and a combined algorithm using potential game method to avoid the premature convergence of the particle swarm optimization is proposed in this paper. The simulation results have shown the proposed algorithm outcomes have lower system cost and better quality of service.