Latency-Energy Optimization For Joint Wifi And Cellular Offloading In Mobile Edge Computing Networks

Mobile terminals (MTs) within the coverage of both the WiFi and cellular network can offload computation tasks via the WiFi access point to efficiently release the cellular network congestion and reduce the load on base stations. In this paper, a novel scheme of joint WiFi and cellular offloading is proposed to optimally reduce the latency and energy consumption of MTs in task processing. Based on the statistical characteristics of MTs' task generation, our scheme serves as strategic guidance for computation offloading without frequent execution of the optimization algorithm. MTs with the different channel access priorities are also considered in our scheme. A balance factor is introduced to flexibly adjust the minimization between the energy consumption of MT and the processing latency of its tasks. We design an iterative algorithm combining the linear programming with the Alternating Optimization technique to efficiently solve the non-convex problem for computation tasks offloading decision. The numerical results demonstrate that our scheme can largely improve the system performance, and the superiority of our scheme is shown in all scenarios.