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A Context-Aware Edge-Based VANET Communication Scheme for ITS.
Chang An1, Celimuge Wu2, Tsutomu Yoshinaga3
1Inner Mongolia Normal University, Hohhot 010010, China. 20060623@imnu.edu.cn.
Sensors (Basel, Switzerland)
|June 26, 2018
Summary
This study introduces a smart packet forwarding system for vehicular networks using fuzzy logic and reinforcement learning to optimize data delivery. The context-aware approach enhances wireless resource efficiency and communication route adaptiveness.
Area of Science:
- Vehicular Networks
- Wireless Communication
- Edge Computing
Background:
- Vehicular networks require efficient packet forwarding.
- Existing protocols face challenges in resource utilization and adaptiveness.
Purpose of the Study:
- To propose a context-aware, edge-based packet forwarding scheme for vehicular networks.
- To enhance wireless resource efficiency and communication route adaptiveness.
Main Methods:
- Fuzzy logic-based edge node selection for decentralized forwarding.
- Reinforcement learning to optimize last two-hop communications.
- Context-aware selection based on connection-dependency, communication type, and payload size.
Main Results:
- The proposed scheme demonstrates efficient wireless resource utilization.
- Improved adaptiveness of communication routes compared to existing protocols.
- Effective packet forwarding through selected edge nodes.
Conclusions:
- The context-aware edge-based scheme offers an efficient solution for vehicular networks.
- Fuzzy logic and reinforcement learning effectively optimize packet forwarding.
- The scheme adapts to various communication contexts and network conditions.
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