A Quantum Ant Colony Multi-Objective Routing Algorithm in WSN and Its Application in a Manufacturing Environment.

Area of Science:

• Computer Science
• Electrical Engineering
• Industrial Engineering

Background:

• Wireless Sensor Networks (WSNs) are crucial for monitoring equipment in complex manufacturing environments.
• Existing routing algorithms like Basic Ant-Based Routing (BABR) suffer from slow convergence and local optima, limiting WSN performance.
• WSNs require long service lifetimes and efficient data transmission for effective equipment monitoring.

Purpose of the Study:

• To develop an improved routing algorithm for WSNs in manufacturing environments.
• To address the limitations of traditional routing algorithms in terms of speed, optimization, and network longevity.
• To enhance the reliability and efficiency of equipment monitoring data transmission.

Main Methods:

• Introduced a novel Quantum Ant Colony Multi-Objective Routing (QACMOR) algorithm.
• Utilized quantum bits to represent and update node pheromones via quantum gate rotations.
• Implemented a multi-objective fitness function considering energy consumption, transmission delay, and network load balancing.

Main Results:

• QACMOR demonstrated improved performance compared to traditional routing algorithms.
• The algorithm effectively balances energy consumption, transmission delay, and network load.
• Simulation analysis and real-world manufacturing tests validated the enhanced performance of QACMOR.

Conclusions:

• QACMOR offers a significant advancement in WSN routing for manufacturing applications.
• The integration of quantum computation and multi-objective optimization enhances WSN efficiency and lifespan.
• The proposed algorithm provides a robust solution for real-time equipment monitoring in industrial settings.