A Task Offloading and Resource Allocation Strategy Based on Improved WSO for Internet of Vehicles

In this paper, we investigate a task offloading and resource allocation strategy concerning multi-access edge computing (MEC) servers and multi-vehicles in the Internet of Vehicles (IoV). Aiming at dealing with resource allocation issues involved with the task offloading procedure, we first formulate the task offloading problem to minimize the average cost. Next, the improved War Strategy optimization (WSO) algorithm is introduced to solve the resource allocation issue. In particular, combined with stringent delay and energy requirements, the improved WSO algorithm is employed in several iterations processes to achieve optimal offloading decisions and resource allocation policies. Simulation results further demonstrate that the proposed strategy significantly reduces the average cost and improves the task offloading efficiency in the IoV compared with benchmark schemes.