DocumentCode :
2392221
Title :
Expected number of Cluster Members clustering algorithm in wireless sensor networks
Author :
Wei, Huiying ; Chen, Lijia ; Zhang, Yi
Author_Institution :
Dept. of Phys. & Electron., Henan Univ., Kaifeng, China
fYear :
2012
fDate :
19-20 May 2012
Firstpage :
1381
Lastpage :
1384
Abstract :
This paper proposes a protocol, ENCM (Expected Number of Cluster Members clustering algorithm), that´s designed for single-hop wireless sensor networks in which plain sensor nodes communicate directly with the CHs (Cluster Heads). All nodes are commonly resource constrained and have limited amount of energy. In wireless sensor networks, BS (Base Station) is generally set up away from the target area. When CHs transmit data directly to the BS, the CHs further away from the BS consume more energy related to distance and tend to die faster, leaving areas of the network uncovered and resulting in shortening the lifetime of the network. Aiming to prolong the network lifetime, we use ENCM to group the cluster members of different CHs and push the energy consumption of every CH to achieve the average value which is calculated in this paper. Simulation results comparing with previous protocols prove that our new algorithm is able to extend the network lifetime observably and moderately reduces the variance of energy consumption by the CHs.
Keywords :
pattern clustering; probability; routing protocols; wireless sensor networks; BS; CH; ENCM; WSN; base station; cluster heads; data transmission; energy consumption variance reduction; energy-efficient routing protocols; expected number-of-cluster members clustering algorithm; network lifetime; probability function; sensor nodes; single-hop wireless sensor networks; Educational institutions; Wireless sensor networks; clustering algorithm; energy consumption; network lifetime; wireless sensor networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems and Informatics (ICSAI), 2012 International Conference on
Conference_Location :
Yantai
Print_ISBN :
978-1-4673-0198-5
Type :
conf
DOI :
10.1109/ICSAI.2012.6223293
Filename :
6223293
Link To Document :
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