LAUSR

This letter studies hierarchical Mobile Edge Computing (MEC) with multiple sources, multiple buffer-aided relays, and one Higher-level computing Node (HN). The relays may or may not have computation resources and therefore, they randomly decide to process the received tasks or to offload them to the HN. We consider the delay in the transmission and computation buffers, and propose a novel Fairness and Efficiency Cost Function (FECF) as the weighted sum of the maximum Average Response Time (ART) and the overall system ART. We formulate a novel problem to minimize the FECF while keeping the system queues stable, by jointly optimizing the offloading probabilities at the relays and the capacities of the virtual machines at the HN. We prove that the problem is a multi-convex optimization problem and propose an effective solution method by alternating optimization. Simulation results demonstrate the effectiveness of the different variants of the proposed scheme in the scenarios with server-less and server-empowered relays and provide important insights regarding the fairness and efficiency in terms of the ART.