Decentralized Scheduling for Offloading of Periodic Tasks in Mobile Edge Computing

Motivated by various surveillance applications, we consider wireless devices that periodically generate computationally intensive tasks. The devices aim at maximizing their performance by choosing when to perform the computations and whether or not to offload their computations to a cloud resource via one of multiple wireless access points. We propose a game theoretic model of the problem, give insight into the structure of equilibrium allocations and provide an efficient algorithm for computing pure strategy Nash equilibria. Extensive simulation results show that the performance in equilibrium is significantly better than in a system without coordination of the timing of the tasks’ execution, and the proposed algorithm has an average computational complexity that is linear in the number of devices.