Mobility-Aware Multi-Hop Task Offloading for Autonomous Driving in Vehicular Edge Computing and Networks

Vehicular Edge Computing (VEC) has gained increasing interest due to its potential to provide low latency and reduce the load in backhaul networks. In order to meet drastically increasing computation demands from emerging ever-growing vehicular applications, e.g., autonomous driving, abundant computation resources of individual vehicles can play a crucial role in task execution in a VEC scenario, that can further contribute in considerably improving user experience. This is however an extremely challenging task due to high mobility of vehicles that can easily lead to intermittent connectivity, thereby disrupting on-going task processing. In this paper, we propose a task offloading scheme by exploiting…

• CP
  China Postdoctoral Science Foundation

  Award: 2021M692501
• NS
  Natural Science Foundation of Hebei Province

  Award: F2020501037
• FR
  Fundamental Research Funds for the Central Universities

  Awards: XJS210105, XJS210107
• BA
  Basic and Applied Basic Research Foundation of Guangdong Province

  Awards: 2020A1515110079, 2020A1515110496