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A survey on clustering algorithms for vehicular ad-hoc networks

机译:车载自组织网络的聚类算法研究

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In the past few years we are witnessing increased interest in the research of inter-vehicle communications. Due to vehicle specific movement patterns new algorithms and solutions have to be developed. Clustering is a technique for grouping nodes in geographical vicinity together, making the network more robust and scalable. This article presents an overview of proposed clustering algorithms for use in vehicular ad-hoc network (VANET). We survey different clustering algorithms and highlight their objectives, features, specialties and possible limitations. Varieties of different approaches have been observed whereby typically each one focuses on different performance metric. Diverse are also complexities of algorithms and the input data they use and relay on. With this article, readers can have a more thorough and delicate understanding of ad hoc clustering and the research trends in this area. The most promising solutions show the significance of reused concepts from the field of social network analysis.
机译:在过去的几年中,我们目睹了对车辆间通信研究的浓厚兴趣。由于车辆特定的运动模式,必须开发新的算法和解决方案。群集是一种将地理位置附近的节点分组在一起的技术,使网络更加健壮和可扩展。本文概述了用于车辆自组织网络(VANET)的建议聚类算法。我们调查了不同的聚类算法,并重点介绍了它们的目标,功能,特长和可能的局限性。已经观察到各种不同的方法,从而通常每个方法都专注于不同的性能指标。算法及其使用和中继的输入数据的复杂性也很多种。通过本文,读者可以对临时聚类和该领域的研究趋势有更透彻和细致的理解。最有前途的解决方案显示了社交网络分析领域中重用概念的重要性。

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