Comparison between Genetic Algorithm and PSO for Wireless Sensor Networks

  • Pritee ParwekarEmail author
  • Sireesha Rodda
  • S. Vani Mounika
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 77)


One of the most promising algorithms for network optimization is the particle swarm optimization (PSO) and genetic algorithm (GA). The paper is about comparing these two as applied to wireless sensor networks. If a sink is placed at a longer distance from the sensors then the battery life (energy) drains faster, and it reduces the life of the network. Our analysis shows that optimized clustering technique of sensors can minimize the communication distance and can help to increase the network stability. GA and PSO can optimize the cluster formation of sensors. Simulation results have shown us that PSO performs better than GA for clustering algorithms in wireless sensor networks.


Wireless sensors Network Ad hoc networks Clustering Genetic algorithm Particle swarm optimization 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Pritee Parwekar
    • 1
    Email author
  • Sireesha Rodda
    • 2
  • S. Vani Mounika
    • 1
  1. 1.Anil Neerukonda Institute of Technology and SciencesVisakhapatnamIndia
  2. 2.GITAM UniversityVisakhapatnamIndia

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