SCADS: Simultaneous Computing and Distribution Strategy for Task Offloading in Mobile-Edge Computing System

Mobile edge computing (MEC) has emerged as a prominent technique to improve the quality of computation experience for mobile devices in the fifth-generation (5G) networks. However, the design of computation task scheduling policies for MEC systems inevitably encounters a challenging latency optimization problem. Due to the limited radio and computational resources in communication system, a more efficient latency-optimal scheduling policy is urgently needed to meet the ever-increasing computation demands of many new mobile applications. In this paper, we formulate an optimization problem based on partial offloading strategy and transform it into a piecewise convex problem, getting the latency-optimal point by means of sub-gradient method. A simplified algorithm is further put forward to achieve close-to-optimal performance in polynomial time. Therefore, we conclude a simultaneous computing and distribution strategy called SCADS. Simulation results are provided to demonstrate the advantages of our proposed algorithms compared with other baseline strategies.