A context-aware edge-based VANET communication scheme for ITS

Chang An (Corresponding Author), Celimuge Wu (Corresponding Author), Tsutomu Yoshinaga, Xianfu Chen, Yusheng Ji

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)

Abstract

We propose a context-aware edge-based packet forwarding scheme for vehicular networks. The proposed scheme employs a fuzzy logic-based edge node selection protocol to find the best edge nodes in a decentralized manner, which can achieve an efficient use of wireless resources by conducting packet forwarding through edges. A reinforcement learning algorithm is used to optimize the last two-hop communications in order to improve the adaptiveness of the communication routes. The proposed scheme selects different edge nodes for different types of communications with different context information such as connection-dependency (connection-dependent or connection-independent), communication type (unicast or broadcast), and packet payload size. We launch extensive simulations to evaluate the proposed scheme by comparing with existing broadcast protocols and unicast protocols for various network conditions and traffic patterns.

Original languageEnglish
Article number2022
JournalSensors
Volume18
Issue number7
DOIs
Publication statusPublished - 1 Jul 2018
MoE publication typeA1 Journal article-refereed

Fingerprint

communication
Communication
Network protocols
Fuzzy Logic
Humulus
Reinforcement learning
Learning algorithms
Fuzzy logic
reinforcement
payloads
learning
traffic
Learning
logic
resources
routes
conduction
simulation

Keywords

  • Broadcast communications
  • Context-aware communications
  • Edge computing
  • Intelligent transportation systems
  • Unicast communications
  • VANET
  • Vehicular networks

Cite this

An, Chang ; Wu, Celimuge ; Yoshinaga, Tsutomu ; Chen, Xianfu ; Ji, Yusheng. / A context-aware edge-based VANET communication scheme for ITS. In: Sensors. 2018 ; Vol. 18, No. 7.
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A context-aware edge-based VANET communication scheme for ITS. / An, Chang (Corresponding Author); Wu, Celimuge (Corresponding Author); Yoshinaga, Tsutomu; Chen, Xianfu; Ji, Yusheng.

In: Sensors, Vol. 18, No. 7, 2022, 01.07.2018.

Research output: Contribution to journalArticleScientificpeer-review

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AU - An, Chang

AU - Wu, Celimuge

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AU - Chen, Xianfu

AU - Ji, Yusheng

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AB - We propose a context-aware edge-based packet forwarding scheme for vehicular networks. The proposed scheme employs a fuzzy logic-based edge node selection protocol to find the best edge nodes in a decentralized manner, which can achieve an efficient use of wireless resources by conducting packet forwarding through edges. A reinforcement learning algorithm is used to optimize the last two-hop communications in order to improve the adaptiveness of the communication routes. The proposed scheme selects different edge nodes for different types of communications with different context information such as connection-dependency (connection-dependent or connection-independent), communication type (unicast or broadcast), and packet payload size. We launch extensive simulations to evaluate the proposed scheme by comparing with existing broadcast protocols and unicast protocols for various network conditions and traffic patterns.

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