Time and message complexities of the generalized distributed mobility-adaptive clustering (GDMAC) algorithm in wireless multihop networks

C. Bettstetter, Bastian Friedrich
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引用次数: 21

Abstract

Distributed mobility-adaptive clustering algorithms are used in multihop ad hoc networks to separate the nodes into logical groups and build up a hierarchical network architecture. This paper studies the convergence time and message complexity of Basagni's generalized DMAC clustering algorithm. Our results show how many time steps and signaling messages are typically needed after a single topology change to re-achieve a stable and valid cluster structure. Furthermore, we discuss chain reactions that can occur along a path if certain conditions are fulfilled. Finally, we regard a mobile scenario in order to analyze (a) the number of signaling messages per node and time step and (b) the percentage of time steps in which the cluster structure is invalid. Our results give a qualitative insight on the behavior of clustering in ad hoc networks. In particular, they show that tuning the density of clusterheads and employing a hysteresis parameter for cluster changes can significantly improve the performance.
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在多跳自组织网络中,采用分布式自适应移动性聚类算法,将节点划分为逻辑组,形成分层的网络结构。本文研究了Basagni广义DMAC聚类算法的收敛时间和消息复杂度。我们的结果显示了在单个拓扑更改后,通常需要多少时间步长和信令消息才能重新实现稳定有效的集群结构。此外,我们还讨论了在满足某些条件的情况下沿一条路径可能发生的链式反应。最后,我们考虑一个移动场景,以分析(a)每个节点和时间步的信令消息数量,以及(b)集群结构无效的时间步的百分比。我们的结果对自组织网络中的聚类行为提供了定性的见解。特别是,他们表明,调优簇头的密度和为簇的变化使用迟滞参数可以显著提高性能。
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