Joint Computing and Caching in 5G-Envisioned Internet of Vehicles: A Deep Reinforcement Learning-Based Traffic Control System

Zhaolong Ning, Kaiyuan Zhang, Xiaojie Wang*, Mohammad S. Obaidat, Lei Guo*, Xiping Hu*, Bin Hu*, Yi Guo*, Balqies Sadoun, Ricky Y.K. Kwok

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

187 Citations (Scopus)

Abstract

Recent developments of edge computing and content caching in wireless networks enable the Intelligent Transportation System (ITS) to provide high-quality services for vehicles. However, a variety of vehicular applications and time-varying network status make it challenging for ITS to allocate resources efficiently. Artificial intelligence algorithms, owning the cognitive capability for diverse and time-varying features of Internet of Connected Vehicles (IoCVs), enable an intent-based networking for ITS to tackle the above-mentioned challenges. In this paper, we develop an intent-based traffic control system by investigating Deep Reinforcement Learning (DRL) for 5G-envisioned IoCVs, which can dynamically orchestrate edge computing and content caching to improve the profits of Mobile Network Operator (MNO). By jointly analyzing MNO's revenue and users' quality of experience, we define a profit function to calculate the MNO's profits. After that, we formulate a joint optimization problem to maximize MNO's profits, and develop an intelligent traffic control scheme by investigating DRL, which can improve system profits of the MNO and allocate network resources effectively. Experimental results based on real traffic data demonstrate our designed system is efficient and well-performed.

Original languageEnglish
Article number8984310
Pages (from-to)5201-5212
Number of pages12
JournalIEEE Transactions on Intelligent Transportation Systems
Volume22
Issue number8
DOIs
Publication statusPublished - Aug 2021
Externally publishedYes

Keywords

  • 5G
  • Internet of connected vehicles
  • content caching
  • deep reinforcement learning
  • edge computing
  • traffic control system

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