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GAHCT:Genetic Algorithm Based Hierarchical Cooperative Technique for Energy Efficient Topology Control in Wireless Sensor Networks


Affiliations
1 Sathyabama University, India
2 Department of E & C, Sathyabama University, India
     

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Topology control plays a vital role in maximizing the network lifetime and in increasing the network capacity of a Wireless Sensor Network (WSN). In this paper, a two tier architecture based topology control algorithm which increases the overall energy efficiency of WSN is presented. The lower tier involves clustering of sensor nodes which forms cluster slaves for the purpose of data gathering. The upper tier forms a communication network, where data forwarding between the cluster heads destined to the sink node, takes place. Cluster head selection is a critical process in this two tier architecture. So a new methodology based on genetic algorithm, for cluster head selection in a hierarchical cooperative approach which takes care of the nodes bandwidth, residual energy and memory capacity is proposed and implemented. Simulation results prove the effectiveness of our algorithm.

Keywords

Bandwidth, Clustering, Genetic Algorithm, Memory Capacity, Residual Energy, Topology Control, Wireless Sensor Network.
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  • GAHCT:Genetic Algorithm Based Hierarchical Cooperative Technique for Energy Efficient Topology Control in Wireless Sensor Networks

Abstract Views: 208  |  PDF Views: 1

Authors

S. Emalda Roslin
Sathyabama University, India
C. Gomathy
Department of E & C, Sathyabama University, India

Abstract


Topology control plays a vital role in maximizing the network lifetime and in increasing the network capacity of a Wireless Sensor Network (WSN). In this paper, a two tier architecture based topology control algorithm which increases the overall energy efficiency of WSN is presented. The lower tier involves clustering of sensor nodes which forms cluster slaves for the purpose of data gathering. The upper tier forms a communication network, where data forwarding between the cluster heads destined to the sink node, takes place. Cluster head selection is a critical process in this two tier architecture. So a new methodology based on genetic algorithm, for cluster head selection in a hierarchical cooperative approach which takes care of the nodes bandwidth, residual energy and memory capacity is proposed and implemented. Simulation results prove the effectiveness of our algorithm.

Keywords


Bandwidth, Clustering, Genetic Algorithm, Memory Capacity, Residual Energy, Topology Control, Wireless Sensor Network.