L. Wang, J. Gui, X. Deng, F. Zeng and Z. Kuang, "Routing Algorithm Based on Vehicle Position Analysis for Internet of Vehicles," in IEEE Internet of Things Journal, vol. 7, no. 12, pp. 11701-11712, Dec. 2020, doi: 10.1109/JIOT.2020.2999469. (中科院 1区)
发布时间:2024-03-13
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发表刊物:IEEE Internet of Things Journal
摘要:Abstract—Geographic routing is a research hotspot of the Internet of Vehicles (IoV) and intelligent traffic system (ITS). In practice, the vehicle movement is not only affected by its characteristics and the relationship between the vehicle and position but also affected by some implicit factors. Pointing to this problem, we combine the vehicle moving position probability matrix, the vehicle position association matrix, and the implicit factors to study the influence of vehicle position potential features and vehicle association potential features and propose a routing algorithm based on vehicle position (RAVP) analysis, which can obtain the more accurate vehicle prediction trajectory. Then, the vehicle distance is obtained based on the vehicle prediction trajectory. By the normalization of vehicle distance and cache, the vehicle data forwarding capability is obtained and the transmission decision is made. Simulation results show that the proposed algorithm outperforms the other three routing algorithms in terms of packet delivery ratio, average end-to-end delay, and routing overhead ratio.
备注:http://faculty.csu.edu.cn/dengxiaoheng/zh_CN/lwcg/10445/content/49280.htm
是否译文:否
附件:
29-Routing_Algorithm_Based_on_Vehicle_Position_Analysis_for_Internet_of_Vehicles.pdf
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