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Related Experiment Video

Updated: May 27, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Research on rechargeable agricultural wireless sensor network based on ZigBee immune routing repair algorithm.

Ruipeng Tang1, Yinhe Wu2, Jun Tan3

  • 1Faculty of Engineering, University of Malaya, 50603, Kuala Lumpur, Malaysia. 22057874@siswa.um.edu.my.

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|February 17, 2025
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Summary

The ZIRRA algorithm enhances agricultural wireless sensor networks by repairing abnormal nodes using an immune system approach. This leads to reduced energy consumption, lower data transmission delays, and extended node survival times for improved network stability.

Keywords:
Agricultural environment monitoringImmune systemIndustryRepair algorithmRouting energy lossSensorWireless sensor networkinnovation and infrastructure

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Area of Science:

  • Agricultural Technology
  • Wireless Sensor Networks
  • Network Reliability

Background:

  • Wireless Sensor Networks (WSN) are crucial for agricultural environment monitoring but face challenges with unstable power supplies affecting node reliability.
  • Environmental factors can cause node abnormalities in outdoor WSNs, impacting monitoring accuracy and data transmission.
  • Existing power supply methods and repair algorithms struggle to ensure consistent performance in long-term agricultural monitoring.

Purpose of the Study:

  • To propose the ZigBee Immune Routing Repair Algorithm (ZIRRA) for rechargeable agricultural WSNs to address node abnormalities.
  • To enhance network stability, energy efficiency, and data transmission reliability in agricultural WSNs.
  • To improve the optimization ability of routing paths and extend the operational lifespan of network nodes.

Main Methods:

  • Developed the ZIRRA algorithm, simulating the immune system with identification, processing, cloning, and storage modules for abnormal node repair.
  • Implemented an improved clone tracking algorithm within the learning module, enhancing cloning and mutation mechanisms for optimal node repair.
  • Integrated an adaptive energy management strategy to prioritize critical data transmission and manage energy fluctuations.

Main Results:

  • ZIRRA demonstrated significant advantages over LFRA, AR-TORA, and ICCO algorithms, reducing average routing energy consumption by 35.33%–58.37%.
  • Data transmission delay was reduced by 16.28%–36.74%, and average node survival time extended by 25.08%–33.55%.
  • Increased maximum communication time by 44.49% and network throughput by 13.03% for networks with 1000–2000 nodes.

Conclusions:

  • The ZIRRA algorithm effectively improves energy efficiency, transmission reliability, and network stability in agricultural WSNs.
  • The immune system-inspired approach provides higher efficiency and accuracy in identifying and repairing abnormal nodes compared to traditional methods.
  • ZIRRA's adaptive energy management and optimized repair mechanisms ensure robust performance and extended network lifespan in challenging environments.