Novel Approach of Vehicular Cooperative Communication Based on Strategy of Interval Type-2 Fuzzy Logic and Cooperative Game
As an important branch of the Internet of Things (IoT), vehicular networks play a crucial role in the construction of intelligent transportation systems. However, due to the rapid movement of vehicles and signal obstruction, achieving high- quality and low-latency communication in vehicular networks remains a significant challenge. To address this issue, this paper proposes a novel data communication method based on interval type-2 fuzzy logic and cooperative game theory. Firstly, interval type-2 fuzzy logic is utilized to infer vehicle stability, thereby selecting high-quality backbone nodes. Concurrently, the memory and forgetfulness functions of the Gated Recurrent Unit are employed to retain critical data packets. Subsequently, a greedy algorithm and cooperative game theory model are used to describe the behavior of vehicles in Roadside-to-Vehicle (R2V) communication and Vehicle-to- Vehicle (V2V) communication, respectively. This approach encourages backbone nodes to cooperate and serve other vehicles based on a benefit function. Experimental results demonstrate that the proposed method excels in terms of transmission delay, coverage range, and data packet delivery success rate.
Authors
- Zhihao Zhang (ORCID: https://orcid.org/0000-0002-0252-4903)
- Ting Zhang (ORCID: https://orcid.org/0000-0003-0263-9679)
- Chen-hao Ni (ORCID: https://orcid.org/0000-0002-3528-968X)
- Degan Zhang
- Jie Zhang (ORCID: https://orcid.org/0000-0002-8496-6480)
- Xingru Jiang
Institutions
- Tianjin University of Technology (CN)
- Tianjin University of Sport (CN)
- University of Macau (MO)
- City University of Macau (MO)
- Beihang University (CN)
Publication Details
- Journal
- IEEE Transactions on Sustainable Computing
- Published
- 2024-11-21
- DOI
- https://doi.org/10.1109/tsusc.2024.3503580
- Citations
- 16
- Primary Topic
- Cognitive Computing and Networks
- Type
- article
- Field-Weighted Citation Impact
- 5.56