Joint Task Offloading and Resource Allocation for Vehicular Edge Computing Based on V2I and V2V Modes

In an internet of vehicle (IoV) scenario, vehicular edge computing (VEC) exploits the computing capabilities of the vehicles and roadside unit (RSU) to enhance the task processing capabilities of the vehicles. Resource management is essential to the performance improvement of the VEC system. In this paper, we propose a joint task offloading and resource allocation scheme to minimize the total task processing delay of all the vehicles through task scheduling, channel allocation, and computing resource allocation for the vehicles and RSU. Different from the existing works, our scheme: 1) considers task diversity by profiling the tasks of the vehicles by multiple attributes including data size, computation…

• NN
  National Natural Science Foundation of China

  Awards: 62271086, 61821001
• NS
  Natural Science Foundation of Beijing Municipality

  Award: JQ21036
• SK
  State Key Laboratory of Information Photonics and Optical Communications