Traffic based clustering in wireless sensor network

V. Chaurasiya, S. Kumar, S. Verma, G. Nandi
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引用次数: 9

Abstract

To increase the lifetime and scalability of a wireless sensor network (WSN) it is necessary to have control over topology of the network. Dynamic clustering is one way for achieve the above defined objective. In this paper we are proposing a multi-level hierarchal clustering approach for WSN. Our proposed approach in this paper is to create a system which will adopt a topology (i.e. size of cluster and number of hierarchal level) in accordance with the traffic patterns and density of sensor nodes deployed in a given area of interest. Load on the cluster head near the base station will be more as compared to farther cluster heads as the proximity cluster head have to do the dual work of collecting data from its own cluster and also to forward (or relay) data from distant cluster heads. Therefore this situation may result in dying out of proximity cluster heads sooner than distant cluster heads. It will result in failure of network as a whole. In this situation a bottleneck will be created near the base station. In our approach, we are proposing an algorithm of hierarchical clustering with variable cluster size based on its distance from the base station. Variable cluster size is important for balancing inter-cluster and intra-cluster traffic.
无线传感器网络中基于流量的聚类
为了提高无线传感器网络的生存期和可扩展性,必须对网络的拓扑结构进行控制。动态聚类是实现上述目标的一种方法。本文提出了一种用于WSN的多级分层聚类方法。我们在本文中提出的方法是创建一个系统,该系统将采用拓扑结构(即集群的大小和层次层次的数量),根据在给定感兴趣的区域部署的流量模式和传感器节点的密度。与更远的簇头相比,靠近基站的簇头的负载更大,因为邻近簇头必须执行双重工作,即从自己的簇收集数据,并转发(或中继)来自遥远簇头的数据。因此,这种情况可能导致邻近簇头比远距簇头消亡得更快。这将导致整个网络的故障。在这种情况下,基站附近将产生瓶颈。在我们的方法中,我们提出了一种基于与基站距离的可变簇大小的分层聚类算法。可变集群大小对于平衡集群间和集群内的流量非常重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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