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ENERGY EFFICIENT DYNAMIC ADAPTIVE RECLUSTERING PROTOCOL FOR HETEROGENEOUS WIRELESS SENSOR NETWORKS

Wireless sensor networks are composed of a large number of sensor nodes with limited energy resources. One critical issue in wireless sensor networks is how to gather sensed information in an energy efficient way since the energy is limited. The clustering algorithm is a technique used to reduce ene...

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Bibliographic Details
Published in:ARPN journal of engineering and applied sciences 2015-03, Vol.10 (5), p.2244-2251
Main Authors: Subha, C P, Malarkkan, S
Format: Article
Language:English
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Summary:Wireless sensor networks are composed of a large number of sensor nodes with limited energy resources. One critical issue in wireless sensor networks is how to gather sensed information in an energy efficient way since the energy is limited. The clustering algorithm is a technique used to reduce energy consumption. It can improve the scalability and lifetime of wireless sensor network. In this paper, we introduce an adaptive clustering protocol for wireless sensor networks, which is called Adaptive Decentralized Re-Clustering Heterogeneous Protocol (ADRHP) for Wireless Sensor Networks. In ADRHP, the cluster heads and next heads are elected based on residual energy of each node and the average energy of each cluster. Clustering has been well received as an effective way to reduce the energy consumption of a wireless sensor network. Clustering is defined as the process of choosing a set of wireless sensor nodes to be cluster heads for a given wireless sensor network. Therefore, data traffic generated at each sensor node can be sent via cluster heads to the base station. The selection of cluster heads and next heads are weighted by the remaining energy of sensor nodes and the average energy of each cluster. ADRHP is an adaptive clustering protocol; cluster heads rotate over time to balance the energy dissipation of sensor nodes. The simulation results show that ADRHP achieves longer lifetime and more data message transmissions than current artificial neural network (ANN) based clustering protocol such as Residual Energy Based Clustering Self organizing map (R-EBCS ) in wireless sensor networks.
ISSN:1819-6608
1819-6608