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Modeling, Simulation and Optimization pp 213–229Cite as

MLGARTC: Machine Learning Based Genetic Approach in RSSI Tree Climbing Path Improvisation of the Mobile Anchor’s Using K-Means Clustering of Wireless Sensor Network

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Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 206))

Abstract

WSN is an emerging trend in real-time applications where the most sensitive information matters. Since this sensitive information collected through sensor nodes and routed to sink in a specified manner. The routing information in a proper route is more essential than collecting the data. Mostly sensor networks are deflation in nature due to its many external factors. Though the rapid deflation, the WSN needs replaceable redesign for proper routing. This is achieved by introducing machine_learning (ML) techniques to mobile anchor’s (MA) path selection. This paper enhances the RTC path by adopting the genetic algorithm (GA) approach in artificial intelligence to identify the best path and to react dynamically and also these machine learning-based genetic approach in RSSI tree climbing) characteristics analyzed through the cluster formation and path exists between them.

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Author information

Authors and Affiliations

  1. Department of Information Technology, Jerusalem College of Engineering, Chennai, 600100, India

    P. Thilagavathi

  2. Department of Electronics Communication Engineering, St. Joseph’s College of Engineering, Chennai, 600119, India

    J. Martin Leo Manickam

Authors
  1. P. Thilagavathi
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  2. J. Martin Leo Manickam
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Corresponding author

Correspondence to P. Thilagavathi .

Editor information

Editors and Affiliations

  1. Department of Mechanical Engineering, National Institute of Technology, Silchar, Assam, India

    Biplab Das

  2. Department of Computer Science and Engineering, National Institute of Technology Silchar, Silchar, Assam, India

    Ripon Patgiri

  3. National Institute of Technology Silchar, Silchar, India

    Sivaji Bandyopadhyay

  4. Aurel Vlaicu University of Arad, Arad, Romania

    Valentina Emilia Balas

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Thilagavathi, P., Martin Leo Manickam, J. (2021). MLGARTC: Machine Learning Based Genetic Approach in RSSI Tree Climbing Path Improvisation of the Mobile Anchor’s Using K-Means Clustering of Wireless Sensor Network. In: Das, B., Patgiri, R., Bandyopadhyay, S., Balas, V.E. (eds) Modeling, Simulation and Optimization. Smart Innovation, Systems and Technologies, vol 206. Springer, Singapore. https://doi.org/10.1007/978-981-15-9829-6_17

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