Optimal Offloading in Fog Computing Systems With Non-Orthogonal Multiple Access

Ziling Wei, Hai Jiang

Abstract: Fog computing has recently become a promising method to meet the increasing computation demands from mobile applications in the Internet of Things (IoT). In fog computing, the computation tasks of an IoT device can be offloaded to fog nodes. Due to the limited computation capacity of a fog node, the IoT device may try to offload its tasks to multiple fog nodes. In this paper, to improve the offloading efficiency, downlink non-orthogonal multiple access is applied in fog computing systems such that the IoT device can perform simultaneous offloading to multiple fog nodes. Then, to maximize the long-term average system utility, a task and power allocation problem for computation offloading is formulated subject to task delay and energy cost constraints. By the Lyapunov optimization method, the original problem is transformed to an online optimization problem in each time slot, which is non-convex. Accordingly, we propose an algorithm to solve the non-convex online optimization problem with polynomial complexity.