Soft Computing Paradigms Based Clustering in Wireless Sensor Networks: A Survey

  • Richa SharmaEmail author
  • Vasudha Vashisht
  • Umang Singh
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 612)


Energy conservation is one of the critical design issues in Wireless Sensor Networks (WSNs). WSN comprises of a huge collection of resource-restricted devices called sensor nodes (SNs). These nodes are deployed in network dimensions to sense and predict hazardous environmental conditions. Being dispersed randomly in unattended areas, these SNs face different challenges like rapid energy drainage, stability period, node localization, node deployment, clustering, etc. This study presents the potential of different soft computing paradigms namely Fuzzy Logic (FL), Evolutionary Algorithms (EA), Artificial Neural Networks (ANN), and Swarm Intelligence (SI) optimization in tackling with the issue of energy efficiency in WSNs.


Evolutionary technique Fuzzy logic Network stability Neural networks Soft computing 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Amity Institute of Information TechnologyAmity UniversityNoidaIndia
  2. 2.Amity School of Engineering and TechnologyAmity UniversityNoidaIndia
  3. 3.Institute of Technology & ScienceGhaziabadIndia

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