| 基于连通概率感知的车联网资源优化技术研究 |
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| 引用本文： | 赵海涛 朱洪波 张晖 刘南杰. 基于连通概率感知的车联网资源优化技术研究[J]. 仪器仪表学报, 2015, 36(8): 1724-1734 |
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| 作者姓名： | 赵海涛 朱洪波 张晖 刘南杰 |
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| 作者单位： | 1. 南京邮电大学通信与信息工程学院南京210003；2.东南大学移动通信国家重点实验室南京210096 |
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| 基金项目： | 国家“973”计划（2013CB329005）、国家自然科学基金（61302100,61471203,61201162）、中国博士后研究基金（2013M531391）、教育部博士点基金（20133223120002）、江苏省基础研究计划—重点研究专项基金（BK2011027）项目资助 |
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| 摘 要： | 研究一种自由连通状态下基于车辆速度的多车道连通概率分析模型。该模型主要关注各个路段的连通概率,基于随机过程统计分析理论推导出多车道的道路连通概率。其次,针对单播或多播的端到端的消息分发场景,提出一种基于连通度概率感知的资源优化选择算法。该算法通过考虑车辆速度及方向特征,宏观层次上选择连通度概率高的路段作为数据包转发的路径;微观层次上针对每一路段进行基于邻居信息的多跳广播,快速地将数据包从路段入口传输到路段出口,提高数据分发效率。NS2仿真结果表明,提出的资源优化算法提高了分组转发的有效性,降低了车载网络的分组传输时延。
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| 关 键 词： | 车联网；连通概率；环境感知；资源优化 |
Research on resource optimization technique based on connectivityprobability perception for internet of vehicle |
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| Zhao Haitao,Zhu Hongbo,Zhang Hui,Liu Nanjie. Research on resource optimization technique based on connectivityprobability perception for internet of vehicle[J]. Chinese Journal of Scientific Instrument, 2015, 36(8): 1724-1734 |
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| Authors: | Zhao Haitao Zhu Hongbo Zhang Hui Liu Nanjie |
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| Affiliation: | 1. College of Communication and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China; 2. National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China |
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| Abstract: | This paper presents a multi lane connectivity probability analysis model based on vehicle speed under free connection state, which focuses on the connectivity probabilities for various road segments, and calculates multilane connectivity probability based on stochastic process statistical analysis theory. Aiming at the unicast/multicast end to end packet delivery scenario, a resource optimization selection algorithm based on connectivity probability perception is proposed. In the proposed algorithm, the effect of vehicle speed and direction is described as the stochastic process of probability prediction in vehicular network. The best road segment with high connectivity probability is selected to forward packet on a macro level. On the other hand, in order to improve the packet successful delivery percentage, the neighbor information based multi hop broadcasting is proceeded to quickly transmit packets from the selected segment to another one on a micro level. NS2 simulation results show that the proposed resource optimization algorithm improves the effectiveness of packet delivery and reduces the end to end delay of packet transmission in internet of vehicle. |
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| Keywords: | internet of vehicle connectivity probability environment perception resource optimization |
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