Clustering sensor networks using growing self-organising map

被引：0

作者：

Guru, SM ^{[1
]}

Hsu, A ^{[1
]}

Halgamuge, S ^{[1
]}

Fernando, S ^{[1
]}

机构：

[1] Univ Melbourne, Parkville, Vic 3010, Australia

来源：

PROCEEDINGS OF THE 2004 INTELLIGENT SENSORS, SENSOR NETWORKS & INFORMATION PROCESSING CONFERENCE | 2004年

关键词：

energy optimization; Self-Organising Map; k-mean; sensor networks;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Sensor networks consist of wireless enabled sensor nodes with limited energy. As sensors could be deployed in a large area, data transmitting and receiving are energy consuming operations. One of the methods to save energy is to reduce the transmission distance of each node by grouping them to clusters. Each cluster will have a cluster-head (CH), which will communicate with all the other nodes of that cluster and transmit the data to the remote base station. In this paper we describe the adaptation of Growing Self-Organising map (GSOM) to cluster the wireless sensor nodes and to identify the cluster-heads. We compare the results with a well-known clustering algorithm. We also describe the energy minimization criterion for clustering.

引用

页码：91 / 96

页数：6

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