Joint Optimization Offloading and Resource Allocation in Vehicular Edge Cloud Computing Networks with Delay Constraints
Xueying Liu, Guanglin Zhang · 2020
The development of 5G technology has led to the rapid construction of the Internet of Vehicles (IOV). The emergences of various IOV applications like autonomous driving require unlimited low-latency computation resources, which can be provided by Mobile edge computing (MEC) technique. In this paper, we study a framework of IOV with a cloud computing center that supports edge computing, aiming at improving the quality of service (QoS) for vehicles. We consider delay-sensitive tasks and non-delay-sensitive tasks, which are classified according to their task processing delay constraints. We formulate the optimization problem as a system utility maximization problem, searching for the optimal QoS. Based on the distribution method and the ant colony algorithm (ACO), we propose an optimization approach with joint offloading selection strategy and computing resource distribution strategy. Lastly, we show the simulation results, which demonstrates the effectiveness and high-efficiency of the proposed algorithm.