FlexEdge: Digital Twin-Enabled Task Offloading for UAV-Aided Vehicular Edge Computing

Bin Li, Wancheng Xie, Yinghui Ye, Lei Liu, Zesong Fei*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)

Abstract

Integrating unmanned aerial vehicles (UAVs) into vehicular networks have shown high potentials in affording intensive computing tasks. In this paper, we study the digital twin driven vehicular edge computing networks for adaptively computing resource management where an unmanned aerial vehicle (UAV) named FlexEdge acts as a flying server. In particular, we first formulate an energy consumption minimization problem by jointly optimizing UAV trajectory and computation resource under the practical constraints. To address such a challenging problem, we then build the computation offloading process as a Markov decision process and propose a deep reinforcement learning-based proximal policy optimization algorithm to dynamically learn the computation offloading strategy and trajectory design policy. Numerical results indicate that our proposed algorithm can achieve quick convergence rate and significantly reduce the system energy consumption.

Original languageEnglish
Pages (from-to)11086-11091
Number of pages6
JournalIEEE Transactions on Vehicular Technology
Volume72
Issue number8
DOIs
Publication statusPublished - 1 Aug 2023

Keywords

  • Digital twin
  • UAV
  • proximal policy optimization
  • vehicular edge computing

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