WSN ENERGY OPTIMIZATION WITH ENHANCEMENT OF THROUGHOUT USING CLUSTRING ALGORITHM

Authors: Nikita Sharma, Ass.Prof. Mohit Jain

Published in: IJRRETAS, Volume 8, Issue 8, pp. 1-8 (01 Aug 2022)

Impact Factor: 6.80 (2022)

License: CC BY 4.0 CC BY 4.0 (Open Access)

Certificate: View Certificate

Abstract

The main concern in Wireless Sensor Networks is how to handle with their limited energy resources. The performance of Wireless Sensor Networks strongly depends on their lifetime. As a result, Dynamic Power Management approaches with the purpose of reduction of energy consumption in sensor nodes, after deployment and designing of the network, have drawn attentions of many research studies. Recently, there have been a strong interest to use intelligent tools especially Neural Networks in energy efficient approaches of Wireless Sensor Networks, due to their simple parallel distributed computation, distributed storage, data robustness, autoclassification of sensor nodes and sensor reading. Dimensionality reduction and prediction of sensor data obtained simply from the outputs of the neural-networks algorithms can lead to lower communication costs and energy conservation. All these characteristics show great analogy and compatibility between wireless sensor networks and neural networks. This paper aims to present the most important

Keywords
  • Wireless Sensor Networks
  • Energy Efficiency & Neural Networks
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How to Cite
APA: Sharma, N., & Jain, A. P. M. (2022). WSN ENERGY OPTIMIZATION WITH ENHANCEMENT OF THROUGHOUT USING CLUSTRING ALGORITHM. International Journal for Rapid Research in Engineering Technology & Applied Science, 8(8), 1–8. https://ijrretas.com/research-paper/wsn-energy-optimization-with-enhancement-of-throughout-using-clustring-algorithm
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