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Efficient computation offloading for Internet of Vehicles in edge computing-assisted 5G networks

  • Shaohua Wan
  • Xiang Li
  • Yuan Xue
  • Wenmin Lin
  • Xiaolong XuEmail author
Article
  • 27 Downloads

Abstract

The Internet of Vehicles (IoV) is employed to gather real-time traffic information for drivers, and base stations in 5G systems are used to assist in traffic data transmission. For rapid implementation, the applications in vehicles are available to be offloaded to edge nodes (ENs) which are enhanced from micro base stations. Despite the benefits of IoV and ENs, the explosive growth of offloaded vehicle applications exceeds the capacity of ENs, causing the overload of fractional ENs. Therefore, it is necessary to offload the computing applications in overloaded ENs to other idle ENs, while it is a challenge to select appropriate offloading destination ENs. In this paper, we first consider edge computing framework for computation offloading in IoV under the architecture of 5G networks. We then formulate a multi-objective optimization problem to select suitable destination ENs, which aims to minimize the vehicle application offloading delay and offloading cost as well as realizing the load balance of ENs. Moreover, a computation offloading method for IoV, named COV, is designed to solve the multi-objective optimization problem. Finally, various simulation analyses demonstrate the effectiveness and efficiency of COV.

Keywords

IoV 5G networks Edge computing Computation offloading Delay Offloading cost Load balance 

Notes

Acknowledgements

This research is supported by the National Natural Science Foundation of China under Grant No. 61702277.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Information and Safety EngineeringZhongnan University of Economics and LawWuhanChina
  2. 2.School of Computer and SoftwareNanjing University of Information Science and TechnologyNanjingChina
  3. 3.School of ComputerHangzhou Dianzi UniversityHangzhouChina
  4. 4.Key Laboratory of Complex Systems Modeling and SimulationMinistry of EducationHangzhouChina

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