Joint edge caching and computation offloading for heterogeneous tasks in MEC-enabled vehicular networks

Abstract

Edge caching is an effective paradigm that can significantly reduce the computation task offloading latency for mobile edge computing (MEC) in vehicular networks, while also alleviating the backhaul transmission pressure for retrieving content data from the cloud server. However, most existing works fail to address how to handle heterogeneous tasks generated by vehicle terminals (VTs), especially in complex scenarios where both computation and content tasks are generated simultaneously. In this paper, we consider a mobility-aware vehicular network model where VTs simultaneously generate heterogeneous task requests, i.e., a computation task and a content task, and investigate joint optimization of caching for heterogeneous tasks data, computation offloading, and computing resource allocation. In order to optimize the latency for processing the heterogeneous tasks, an average execution latency minimization problem with sojourn time and caching capacity constraints is formulated. We decompose this problem into two tractable subproblems, i.e., caching optimization subproblem, and computation offloading and resource allocation optimization subproblem. We first develop a dynamic programming (DP) algorithm to obtain the optimal caching strategies for heterogeneous tasks data. We compare the obtained content retrieval latency with the local computing latency, and derive the optimal computation offloading and edge computing resource allocation solutions. On this basis, we propose a joint computation offloading and resource allocation (JCORA) algorithm to determine the computing resources allocated to each VT and corresponding computation offloading strategy. Numerical results indicate that the proposed algorithm, which integrates DP algorithm and JCORA algorithm, can achieve lower execution latency for heterogeneous tasks compared to the benchmark schemes. Additionally, for task loss scenarios where the sojourn time constraint cannot be met, the impact of VT mobility on the task loss probability is also revealed.