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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Fuzzy-based cluster routing in wireless sensor network.

AliReza Naderloo1,2, Seyed Ali Fatemi Aghda3,4, Mahdi Mirfakhraei4,5

  • 1Iran University of Medical Sciences, Tehran, Iran.

Soft Computing
|April 24, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a fuzzy-based clustering routing protocol to enhance wireless sensor network lifetime. The proposed method significantly improves network longevity and energy efficiency compared to existing protocols.

Keywords:
ClusteringFuzzy logicNetwork lifetimeRoutingSelection of cluster head (CH)Wireless sensor network (WSN)

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Network Engineering

Background:

  • Wireless Sensor Networks (WSNs) face challenges with limited computational power and energy supply.
  • Hierarchical cluster routing is a key strategy to mitigate energy consumption and extend WSN operational lifespan.
  • Existing routing protocols often struggle to optimize energy distribution and network longevity effectively.

Purpose of the Study:

  • To propose a novel fuzzy-based clustering routing protocol for WSNs.
  • To enhance network lifetime and reduce energy consumption through intelligent cluster head selection.
  • To evaluate the proposed protocol's performance against established methods.

Main Methods:

  • A fuzzy-based clustering routing protocol was developed, utilizing network zoning and residual energy.
  • Key fuzzy inputs include node residual energy, distance to zone center, and angle to the base station.
  • The base station (BS) manages zone determination, node assignment, and calculates distances and angles for cluster head (CH) selection.

Main Results:

  • The proposed protocol demonstrated superior performance in network lifetime, stability period, CH selection, and average residual energy.
  • Network lifetime was improved by 50% over LEACH, 40% over Farahzadi, and 20% over MSCR.
  • The BS-centric approach for CH selection and parameter calculation effectively reduced overall network energy consumption.

Conclusions:

  • The fuzzy-based clustering routing protocol offers a significant advancement in WSN energy efficiency and longevity.
  • The proposed method provides a robust solution for optimizing resource management in energy-constrained WSNs.
  • Further research could explore adaptive fuzzy logic adjustments for dynamic network conditions.