Genetic Algorithm Based Optimized Adaptive Teen Routing for WSN
G.R. Annusha Kumar1, V. Padmathilagam2, K.Devarajan3
1G.R. AnnushaKumar, Assistant professor in Electronics and Communication Engineering, Government College of Engineering, Thanjavur, Tamil Nadu, India.
2V. Padmathilagam, Assistant Professor in Electrical and Electronics Engineering, FEAT, Annamalai University, Chidambaram, Tamil Nadu, India.
3K. Devarajan, Assistant Professor in Electronics and Communication Engineering, FEAT, Annamalai University, Chidambaram, Tamil Nadu, India.

Manuscript received on November 19, 2019. | Revised Manuscript received on November 29 2019. | Manuscript published on 30 November, 2019. | PP: 9838-9843 | Volume-8 Issue-4, November 2019. | Retrieval Number: F2345037619/2019©BEIESP | DOI: 10.35940/ijrte.F2345.118419

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Abstract: A sensor network with wireless communication channel and often termed as WSN comprises of a set of such as nodes with different computing power, and different energy levels. Clustering is an approach to increase the availability of the nodes in the network in terms of lifetime. But an efficient and an optimal to increase the remaining life period of the network is to use an efficient routing approach with hierarchical architecture where at different levels of clusters are formed. Efficient cluster formation in terms of energy and reliable routing are two widely analyzed challenges in WSN. Despite various clustering approaches developed by so many researchers still the design of optimal clustering strategy is remaining as an open challenge. This paper focuses on the design and evaluation of an energy-efficient hierarchical clustering approach of integrating an evolutionary algorithm and the Adaptive Threshold sensitive Energy Efficient routing protocol. Genetic Algorithm (GA) is used to optimize the energy exhaustion in the network.
Keywords: Hierarchical Routing, Adaptive TEEN, Evolutionary Algorithm, and Genetic Algorithm.
Scope of the Article: Parallel and Distributed Algorithms.