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Cluster Head Selection Method for Edge Computing WSN Based on Improved Sparrow Search Algorithm.

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Summary
This summary is machine-generated.

This study introduces an edge computing system for wireless sensor networks (WSNs) to reduce energy consumption and extend network life. The proposed method effectively lowers energy usage and prolongs operational duration.

Keywords:
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Area of Science:

  • Internet of Things (IoT)
  • Wireless Sensor Networks (WSNs)
  • Edge Computing

Background:

  • Wireless Sensor Networks (WSNs) are crucial in IoT but face limitations due to finite sensor node energy.
  • High energy consumption and short lifecycles in WSN data transmission hinder their widespread application.
  • Existing WSN systems struggle to balance resource allocation and network longevity effectively.

Purpose of the Study:

  • To propose a two-layer WSN system leveraging edge computing to address energy consumption and lifecycle issues.
  • To develop wireless energy consumption and distance optimization models tailored for sensor networks.
  • To establish an optimization objective focused on balancing load and distance factors for improved efficiency.

Main Methods:

  • Implementation of a two-layer WSN architecture incorporating edge computing principles.
  • Development of mathematical models for optimizing wireless energy consumption and node distance.
  • Utilization of an improved sparrow search algorithm for balanced distribution of sensor nodes.

Main Results:

  • The proposed edge computing approach significantly reduces overall network energy consumption.
  • Simulation experiments demonstrate a notable decrease in energy usage by 26.8%.
  • The optimized node distribution effectively prolongs the operational life cycle of the WSN.

Conclusions:

  • The two-layer WSN system based on edge computing offers a viable solution for energy efficiency.
  • Balancing load and distance factors through optimized node distribution enhances network performance.
  • The improved sparrow search algorithm contributes to reduced resource consumption and extended network lifespan.