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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Fuzzy-Logic Based Distributed Energy-Efficient Clustering Algorithm for Wireless Sensor Networks.

Ying Zhang1,2, Jun Wang3, Dezhi Han4

  • 1College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China. yingzhang@shmtu.edu.cn.

Sensors (Basel, Switzerland)
|July 4, 2017
PubMed
Summary

Wireless sensor networks (WSNs) face energy imbalance issues with clustering routing. Our fuzzy logic approach (EEDCF) improves energy efficiency and network lifetime by optimizing cluster head selection.

Keywords:
TSK fuzzy modeldistributed clusteringload balanceneighbor nodes’ energynon-uniform distribution

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Network Engineering

Background:

  • Clustering routing algorithms are vital for energy efficiency and scalability in wireless sensor networks (WSNs).
  • Multi-hop communication in WSNs leads to excessive energy consumption in relay nodes near cluster heads, causing load imbalance.
  • Existing methods struggle to effectively balance energy consumption and prolong network lifespan.

Purpose of the Study:

  • To propose an energy-efficient distributed clustering algorithm (EEDCF) for wireless sensor networks.
  • To address the issue of uneven energy consumption and improve load balancing in WSNs.
  • To enhance the overall network lifetime and data transmission efficiency.

Main Methods:

  • Developed an energy-efficient distributed clustering algorithm (EEDCF) utilizing a fuzzy approach with non-uniform distribution.
  • Incorporated node energies, node degree, and neighbor node residual energies as input parameters for cluster head election.
  • Employed the Takagi, Sugeno, and Kang (TSK) fuzzy model for quantitative analysis and distributed probability calculation for cluster head selection.

Main Results:

  • The EEDCF algorithm demonstrated superior performance compared to existing representative methods.
  • Significant improvements were observed in data transmission efficiency.
  • Reduced overall energy consumption and extended network lifetime were achieved.

Conclusions:

  • The proposed EEDCF algorithm effectively balances energy consumption in wireless sensor networks.
  • The fuzzy-based approach enhances the performance of clustering routing protocols.
  • EEDCF offers a promising solution for improving the longevity and efficiency of WSNs.