Code-based Computation Offloading in Vehicular Fog Networks

Abstract

With the number of in-vehicle infotainment applications exponentially increasing, offloading several subtasks divided from computation-intensive application to different fog nodes is convinced as a promising paradigm to satisfy the offloading requirements. However, failure transmission of subtask in any fog node will increase execution latency and energy consumption in Vehicular Fog Networks (VeFNs). In this paper, we leverage the code technology to produce extra subtasks and exchange the redundancy of computing resources for reliability, which improve the robustness of vehicle to vehicle (V2V) communication and decrease the overhead of computation offloading. Furthermore, we adopt a code-based computation offloading algorithm based on simulated annealing (CBSA) that finds the optimal coding scheme and resources allocation strategy. The numerical results are illustrated to demonstrate effectiveness of proposed algorithm.