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Title: An approach to data Aggregation in wireless sensor network using Voronoi fuzzy clustering algorithm
Authors: Nithyakalyani, S.
Kumar, S.Suresh
Keywords: Clustering algorithm;Fuzzy C-Means;Voronoi diagram;Data Aggregation;Residual energy;QOS
Issue Date: May-2013
Publisher: NISCAIR-CSIR, India
Abstract: Data collected through any sensor are needed to be processed for gaining some useful information. Wireless Sensor Network (WSN) is a subclass of sensor node which is evolving as an astonishing technique in wireless communication technology for monitoring large application domains such as weather forecasting, military surveillance, medical diagnosis, fire detection alarming systems, etc. Each sensor will not be able to process itself due to the primary issue of energy (battery power) curb in WSN. Still many investigators desire to find a solution to improve the lifespan of WSN. The best way is to select an optimum head node for data aggregation to reduce the energy of data transmission for the reason that energy required for computing is more than for data transmission. This prototype shifts the attention from the outmoded address-centric approaches to data-centric approach. Data centric techniques like data aggregation via energy efficient fuzzy clustering algorithm based on Voronoi diagram is proposed in this paper. The proposed novel algorithm is a combination of Voronoi and modified Fuzzy C-Means clustering algorithm called as Voronoi Fuzzy (VF) algorithm.Cluster head (CH) for VF clustering algorithm is nominated by considering node's residual energy, distance between CH and its neighbor’s sensor node and Quality of service. Furthermore, data aggregation is employed in each cluster’s CH to reduce the amount of data transmission which effectively extends the network lifetime. Simulation result reveals that this method achieves agreeable performance in extending the network lifetime compared to the existing ones.
Page(s): 287-293
ISSN: 0975-1084 (Online); 0022-4456 (Print)
Appears in Collections:JSIR Vol.72(05) [May 2013]

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