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Related Concept Videos

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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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An intelligent algorithm based optimized clustering method for energy harvesting WSN.

Sanjai Prasada Rao Banoth1, Biswa Mohan Sahoo2, Anil Kumr Gankotiya3

  • 1School of Technology, Woxsen University, Hyderabad, India.

Scientific Reports
|December 8, 2025
PubMed
Summary
This summary is machine-generated.

Energy-harvesting wireless sensor networks (EH-WSNs) benefit from MCSOC clustering, which optimizes energy, communication costs, and node distances. This approach significantly enhances network lifetime and throughput for practical applications.

Keywords:
Energy harvestingIntra-clusterIoT, EH-WSNMCSOC algorithmOptimized clustering

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Area of Science:

  • Wireless Sensor Networks
  • Optimization Algorithms
  • Energy Harvesting

Background:

  • Energy-harvesting wireless sensor networks (EH-WSNs) face challenges in balancing sensing, energy dynamics, and communication costs.
  • Efficient clustering is crucial for maximizing the operational lifespan and performance of EH-WSNs.

Purpose of the Study:

  • To introduce MCSOC (Modified Cat-Swarm-Optimization based clustering) for EH-WSNs.
  • To co-optimize cluster-head selection based on residual energy, intra-cluster distance, inter-cluster transmission cost, and node-to-sink distances.

Main Methods:

  • Developed a domain-aware, multi-objective fitness function for cluster-head selection.
  • Utilized a modified Cat Swarm Optimization algorithm.
  • Evaluated MCSOC on two deployment scenarios (200x200m2 and 500x500m2 with 200 nodes) using a first-order radio energy model.

Main Results:

  • MCSOC demonstrated superior network lifetime, throughput, and stability compared to benchmark methods (NEHCP, ROTEE, SMEOR, GAPSO-H).
  • Achieved significant performance enhancements: up to 42.13% in network performance, 45.57% in stability, and 48.48% in throughput over GAPSO-H.
  • Showcased a higher saving proportion of early dead nodes, indicating improved energy management.

Conclusions:

  • MCSOC provides a practical and effective solution for long-lifetime sensing in EH-WSNs.
  • The proposed method is suitable for precision agriculture, smart-city environmental monitoring, and industrial health monitoring.