Computation Offloading Scheduling for Periodic Tasks in Mobile Edge Computing

Motivated by various delay sensitive applications, we address the problem of coordinating the offloading decisions of wireless devices that periodically generate computationally intensive tasks. We consider autonomous devices that aim at minimizing their own cost by choosing when to perform their tasks and whether or not to offload their tasks to an edge cloud through one of the multiple wireless links. We develop a game theoretical model of the problem, prove the existence of pure strategy Nash equilibria and propose a polynomial complexity algorithm for computing an equilibrium. Furthermore, we characterize the structure of the equilibria, and by providing an upper bound on the price of anarchy of the game we establish an asymptotically tight bound on the approximation ratio of the proposed algorithm. Our simulation results show that the proposed algorithm achieves significant performance gain compared to uncoordinated computation offloading at a computational complexity that is on average linear in the number of devices.