Energy Efficient Data Aggregation using Voronoi based Genetic Clustering Algorithm in WSN

Abstract

Wireless Sensor Network is an major emerging technique in wireless communication technology for application across a wide array of domains such as the military surveillance, medical diagnosis, weather forecasting, fire detection alarming systems, etc. One of the main challenges of wireless sensor network (WSN) is how to improve its time of livelihood due to the restricted energy of sensor nodes. Data must be aggregated in order to avoid amounts of traffic in the network, limit the recourses and energy. To solve the above dilemmas , data mining process such as clustering and data aggregation is used .clustering is used to group the nodes where as data aggregation function like MIN,MAX,AVG is used for swabbing redundant data transmission and improves the life span of energy in wireless sensor network. In this paper a new approach related to Voronoi based Genetic clustering (VBGC) Algorithm is proposed for energy efficient data aggregation. Our algorithm achieves energy efficiency by reducing the number of data transmission in each round to cluster head and from it to Base station (BS) .The Base Station periodically executes the proposed algorithm to select new Cluster-Heads after a certain period of time. Simulation results reveal that our algorithm outperforms basic GA.

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“…The experimental results demonstrated capabilities of the projected method. Nithya et al [21] proposed Voronoi Based Genetic Clustering (VBGC) for energy efficient data aggregation. It reduces number of bits for data transmission.…”

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