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An Optimization Routing Algorithm for Green Communication in Underground Mines.

Heng Xu1, Qiyue Li2, Jianping Wang3

  • 1School of Electrical Engineering and Automation, Hefei University of Technology, Hefei 230009, China. neosonny@163.com.

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Summary
This summary is machine-generated.

This study introduces an optimization routing algorithm for green communication in underground mines. It effectively reduces network energy consumption and extends network lifetimes by balancing sensor node energy usage.

Keywords:
DCMSTGAgreen communicationheterogeneous networkunderground mine

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Mining Engineering

Background:

  • Underground mining relies on sensor networks for safety and efficiency.
  • Mobile sensor nodes in these networks are often battery-powered, necessitating energy conservation.
  • Current networks face challenges in energy consumption and limited operational longevity.

Purpose of the Study:

  • To develop an energy-efficient routing algorithm for underground mine sensor networks.
  • To enhance the longevity of sensor networks through green communication strategies.
  • To address heterogeneous factors impacting network performance and energy usage.

Main Methods:

  • Utilized the Degree Constraint Minimum Spanning Tree (DCMST) to model network constraints and assign weights.
  • Implemented a Genetic Algorithm (GA) for sensor node clustering and energy balancing.
  • Integrated DCMST routing paths with GA for optimized network operation.

Main Results:

  • The proposed optimization routing algorithm significantly reduces network energy consumption.
  • Demonstrated an extension of network lifetimes in simulated underground mining environments.
  • Validated the effectiveness of the green communication approach in reducing energy demands.

Conclusions:

  • The developed algorithm offers an effective solution for energy-efficient sensor networks in hazardous underground mining settings.
  • Green communication strategies are crucial for sustainable and long-lasting underground mining operations.
  • The integration of DCMST and GA provides a robust framework for optimizing network performance and energy efficiency.