Abstract
Green Vehicular Ad-hoc Network (VANET) is a newly-emerged research area that focuses on reducing harmful impacts of vehicular communication equipment on the natural environment. Recent studies have shown that grouping vehicles into clusters for green communications in VANETs can significantly improve networking efficiency and reduce infrastructure costs. As a dynamic network system, maintaining the network connectivity and reducing the communication overlap are two critical challenges for green VANET clustering. However, most existing work studies connectivity and overlap separately, lacking a deep understanding of the relationship between them. To address this issue, we present a comprehensive analysis that jointly considers the two critical factors in one model. Specifically, we first design a state resemblance prediction (SRP) model based on the historical trajectory feature relevance between vehicles; Combined with the SRP model, we propose the region-based collaborative management scheme (RCMS) to establish the dynamic clustering; Lastly, we take extensive experiments to verify the region-based collaborative management scheme for dynamic clustering. The results demonstrate that the proposed clustering algorithm can achieve high networking efficiency and better communication stability.
Original language | English |
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Pages (from-to) | 1276-1287 |
Number of pages | 12 |
Journal | IEEE Transactions on Green Communications and Networking |
Volume | 6 |
Issue number | 3 |
DOIs | |
Publication status | Published - Sept 2022 |
Externally published | Yes |
Keywords
- Clustering algorithms
- Collaboration
- Communication overlap
- Dynamic clustering.
- Green communication
- Green products
- Heuristic algorithms
- Network connectivity
- Prediction algorithms
- VANETs
- Vehicle dynamics
- Vehicular ad hoc networks
- communication overlap
- network connectivity
- dynamic clustering
- green communication