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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
Published on: September 8, 2023
Energy-efficient secure routing in wireless sensor networks using fuzzy inference clustering and attention-based
M Ishwarya Niranjana1, N Kumareshan2
1Department of ECE, Sri Eshwar College of Engineering, Coimbatore, Tamilnadu, India. ishwaryaecephd@gmail.com.
Scientific Reports
|June 6, 2026
Summary
This study enhances Wireless Sensor Networks (WSNs) by optimizing cluster formation and secure routing using advanced algorithms. The new framework significantly improves energy efficiency, network lifetime, and intrusion detection capabilities.
Area of Science:
- Computer Science
- Network Engineering
- Cybersecurity
Background:
- Wireless Sensor Networks (WSNs) face challenges in energy efficiency, clustering, security, and intrusion detection.
- Existing WSN solutions often exhibit high energy consumption, routing overhead, poor scalability, and limited intrusion detection accuracy.
Purpose of the Study:
- To develop an integrated framework for WSNs that addresses energy constraints, enhances clustering stability, secures routing, and improves intrusion detection.
- To improve the overall performance, security, and lifetime of Wireless Sensor Networks.
Main Methods:
- Adaptive cluster formation using Mamdani-type Fuzzy Inference System (FIS).
- Cluster Head (CH) selection via Dynamic Adaptive Fig Tree-Wasp Symbiotic Coevolutionary Optimization (DA-FTWSCO) for energy efficiency.
- Secure communication using Adaptive Trust-Synchronized Packet Control Protocol (ATSPCP) and optimal path selection with Improved Grizzly Bear Fat Increase Optimizer (IGBFIO).
- Intrusion detection using Enhanced Multi-scale Dilated MobileNet with Attention Mechanism (EMSD-MobileNet-AM) for identifying DoS and zero-day attacks.
Main Results:
- Achieved low energy consumption (1.02 J), high throughput (0.93 Mbps), and low end-to-end delay (4.0 ms).
- Demonstrated a high attack detection rate of 98% for various network attacks.
- The proposed framework significantly outperformed existing methods in efficiency, security, and scalability.
Conclusions:
- The integrated framework effectively addresses key limitations in WSNs, offering substantial improvements in performance and security.
- The proposed optimization and detection mechanisms provide a robust solution for enhancing WSN reliability and longevity.
- This research contributes a scalable and secure WSN framework suitable for diverse applications.