VANETs覆盖选择模型中的热点发现算法

Huang Cheng, Xin Fei, A. Boukerche, M. Almulla
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引用次数: 0

摘要

覆盖感兴趣区域的RSU部署算法已成为车载自组织网络中有前景的研究领域。然而,关于兴趣区发现的研究却很少。此外,通常针对连续覆盖和稀疏覆盖提出部署算法。模型选择的智慧很少被提及。本文提出了一种新的兴趣区域发现算法。提出了一种预算约束下的覆盖选择算法,帮助网络设计者选择合适的覆盖模型来满足预算和质量要求。这些算法是在Ns2之上实现的,并使用SUMO和OpenStreet Maps进行了仿真。通过与其他两种聚类算法的性能比较,证明本文算法在稀疏覆盖和持续覆盖的接触时间方面都具有更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hotspot discovery algorithms in coverage selection model over VANETs
The RSU deployment algorithms to cover interest regions have emerged as promising areas of research in vehicular ad hoc networks. However, there is few research on the discovery of the interest regions. Besides, the deployment algorithms are usually proposed for either continuous coverage or sparse coverage. The wisdom of the model selection are rarely addressed. In this paper, we proposed a new algorithm to discover interest regions. A budget-constrained coverage selection algorithm is also presented to help network designers choose suitable coverage models to meet the budget and quality requirements. The algorithms are implemented on top of Ns2 and the simulations are carried out using SUMO and OpenStreet Maps. The performance comparison between our algorithm and other two clustering algorithms prove that our algorithm has a better performance in terms of contact time for both sparse coverage and continue coverage.
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