WACA:一种针对移动混合网络优化的分层加权聚类算法

Matthias R. Brust, A. Andronache, S. Rothkugel
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引用次数: 40

摘要

集群技术在平面网络上创建层次网络结构,称为集群。在动态环境中(就节点移动性以及稳定变化的设备参数而言),必须根据合适的更新策略重新调用簇头选举过程。集群重组会导致额外的消息交换和计算复杂性,并且必须对其执行进行优化。我们的研究集中在考虑稳定性标准的最小化簇头重选问题上。这些标准是基于拓扑特征以及器件参数。提出了一种加权聚类算法,该算法对移动自组网中稳定簇避免不必要的簇头重选进行了优化。提出的局部化算法处理移动性,但不需要地理、速度或距离信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
WACA: A Hierarchical Weighted Clustering Algorithm Optimized for Mobile Hybrid Networks
Clustering techniques create hierarchal network structures, called clusters, on an otherwise flat network. In a dynamic environment-in terms of node mobility as well as in terms of steadily changing device parameters-the clusterhead election process has to be re-invoked according to a suitable update policy. Cluster re-organization causes additional message exchanges and computational complexity and it execution has to be optimized. Our investigations focus on the problem of minimizing clusterhead re-elections by considering stability criteria. These criteria are based on topological characteristics as well as on device parameters. This paper presents a weighted clustering algorithm optimized to avoid needless clusterhead re- elections for stable clusters in mobile ad-hoc networks. The proposed localized algorithm deals with mobility, but does not require geographical, speed or distances information.
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