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Intelligent Deployment Strategy for Heterogeneous Nodes to Increase the Network Lifetime of Wireless Sensor Networks
Sidhartha Sankar Dora1, Prasanta Kumar Swain2

1Sidhartha Sankar Dora, Ph.D. (Pursuing), Sriram Chandra Bhanja Deo University, Baripada (Odisha), India.
2Dr. P.K.Swain, Assistant Professor, Department of Computer Application, North Orissa University, India.
Manuscript received on 27 June 2022 | Revised Manuscript received on 02 July 2022 | Manuscript Accepted on 15 July 2022 | Manuscript published on 30 July 2022 | PP: 159-164 | Volume-11 Issue-2, July 2022 | Retrieval Number: 100.1/ijrte.B71820711222 | DOI: 10.35940/ijrte.B7182.0711222
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: The applications of wireless sensor networks are increased day by day for different applications. Heterogeneous wireless sensor networks offer limitless possibilities because to their expandable capabilities, such as diverse computing power and sensing range, but they also represent significant issues due to the scarcity of energy, which is typically non-renewable. The node deployment, coverage area, connectivity, power depletion and network life time are major issues in wireless sensor networks. We have deployed heterogeneous sensor nodes on the basis of energy to design a heterogeneous network model and applied intelligent node deployment techniques by using metaheuristic algorithms such as genetic algorithm (GA) and particle swarm optimization (PSO) algorithm to minimize the power depletion of sensor nodes for enhancing network life time using multi-hop transmission in this paper. The benefits of heterogeneity have been revealed by our experimental findings. 
Keywords: Index Terms: Wireless Sensor Networks, Genetic Algorithm, Particle Swarm Optimization, Power Depletion, Network Lifetime
Scope of the Article: Wireless Sensor Networks