Adaptive Clustering Mechanism for Improved Energy Efficiency in WBANs

IPEM Journal Computer Applications > Adaptive Clustering Mechanism for Improved Energy Efficiency in WBANs

Adaptive Clustering Mechanism for Improved Energy Efficiency in WBANs

Ms. Anita Rani, Dr. Rakesh Kumar, Dr. Anant Ram

Vol 9 , Issue 1 , December 2024 | Pages: 30-37

Published Online: December, 2024

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Author Details

1. Ms. Anita Rani, Research Scholar, Computer Science of Engineering and Application, GLA University, Mathura, India
2. Dr. Rakesh Kumar, Associate Professor, Computer Science of Engineering and Application, GLA University, Mathura, India
3. Dr. Anant Ram, Associate Professor, Computer Science of Engineering and Application, Government Polytechnique College, Jalun, India

Wireless body area network (WBANs) plays an important role in monitoring and helps the patient to maintain the health surveillance system. The main aim of the research to design an energy efficient duty cycle technique apply with clustered in wireless body area network. In this research paper, a 60% duty cycle consist sleep and awake concept is introduced for clustered in WBANs. In the proposed approach, the network consists two phases as LEACH Protocol. first steady phase and second setup phase. Firstly, in set up phase apply the 60% duty cycle. And distance centroid has maximum energy of alive node is considered as initial cluster heads (CHs). The successive CHs are recognised on the basis of residual energy based on the threshold distance from the current cluster head (CH). After the formation of the clusters. Cluster head aggregate the emergency data depend on 60% duty cycle and send to the base station. This technique provides the more energy efficiency among the network. The performance evaluation of the proposed protocol Energy Efficient duty cycle-based cluster approach (EEDCCA) is doing using MATLAB tool and result are analysed. The simulation result validates that the proposed technique increases the overall lifetime of the network and also reduce the energy consumption of the network.

Keywords

Clusters, Sleep node, alive nodes, 60% duty Cycle, Regular data, Emergency data, Energy Efficiency.

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A. Rani, R. Kumar, and A. Ram, “Adaptive Clustering Mechanism for Improved Energy Efficiency in WBANs,” IPEM Journal of Computer Application & Research, vol. 9, pp. 30–37, Dec. 2024. DOI: