Assessment of Clustering Constraints and Applications of Dense WSN
Assessment of Clustering Constraints and Applications of Dense WSN, (TROINDIA ISBN: 978-93-85225-92-5)
49 Pages Posted: 1 Nov 2017
Date Written: October 30, 2017
Wireless Sensor Network (WSN) is an emerging and very interesting technology applied to different applications. WSNs are networks in which thousands of small and battery powered nodes communicate with each other. A WSN consists of number of spatially distributed nodes which are interconnected without the use of wires. Each node is connected with one or more sensors. Each sensor node consists of a radio receiver, a microcontroller and a battery. The WSN is mainly used in area monitoring, environmental monitoring, industrial monitoring, waste water monitoring, structural monitoring, etc. The major advantages of these networks: they avoid wiring problems and it can be accessed through centralized control.
In order to reduce the data transmission time and energy consumption, the sensor nodes are grouped into a number of small groups called clusters. The grouping of sensor nodes is known as clustering. Every cluster has a leader which is known as cluster head (CH). A CH is also one of the sensor nodes which have higher capabilities than other sensor nodes. The cluster head is selected by the sensor nodes in the respective cluster. CHs may also be pre-assigned by the user. The advantages of clustering are that it transmits the aggregated data to the sink or base station. It provides scalability for large number of nodes and reduces energy consumption.
Clustering can be classified into three types: centralized clustering, distributed clustering and hybrid clustering. The centralized clustering is the one in which the cluster head is fixed. The remaining nodes in the cluster act as a member nodes. Distributed clustering is the one in which the cluster head is not fixed. The cluster head keeps on changing form node to node based n on some parameters. Hybrid clustering is the one which is formed by the combination of the centralized clustering and the distributed clustering.
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