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Wireless sensor network routing optimization based on improved ant colony algorithm in the Internet of Things.

Hongzhang Han1, Jun Tang2, Zhengjun Jing1

  • 1School of Computer Engineering, Jiangsu University of Technology, Changzhou 213001, China.

Heliyon
|January 8, 2024
PubMed
Summary
This summary is machine-generated.

An improved ant colony algorithm optimizes routing in wireless sensor networks for the Internet of Things. This method enhances energy efficiency, reduces delay, and improves network throughput for smart city applications.

Keywords:
Improve ant colony algorithmNode positioningObjective functionRouting optimizationWireless sensor network

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Network Engineering

Background:

  • The Internet of Things (IoT) relies on wireless sensor networks (WSNs) for data collection and communication.
  • Optimizing routing in WSNs is crucial for efficient data transmission and network longevity.
  • Existing routing methods face challenges in balancing energy consumption, delay, and throughput.

Purpose of the Study:

  • To propose an improved ant colony algorithm for optimizing routing schemes in WSNs.
  • To enhance the performance of IoT networks through efficient WSN routing.
  • To address the limitations of traditional routing algorithms in terms of energy consumption and data transmission.

Main Methods:

  • Utilizing an improved ant colony algorithm inspired by ant foraging behavior.
  • Employing node positions as reference and anchor points for pathfinding.
  • Defining an objective function for WSN routing optimization.

Main Results:

  • The proposed method demonstrated significant improvements in energy consumption.
  • Reduced transmission delay was observed compared to existing methods.
  • The number of dead nodes decreased, and network throughput increased.

Conclusions:

  • The improved ant colony algorithm offers an effective solution for WSN routing optimization.
  • This approach supports the sustainable development and practical application of IoT.
  • The findings contribute to the advancement of the digital economy and smart city initiatives.