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Hybrid Mexican axolotl and bitterling fish optimization algorithm-based spectrum sensing multi‑hop clustering routing
C Balasubramanian1, G Sathya2, R Praveen3
1Department of Computer Science and Engineering, P.S.R. Engineering College, Sivakasi, Tamil Nadu, 626140, India.
Scientific Reports
|December 27, 2024
Summary
A new hybrid optimization algorithm improves cognitive radio sensor networks by enhancing spectrum sensing and energy efficiency. This approach extends network lifetime and optimizes data routing for better performance.
Area of Science:
- Computer Science
- Electrical Engineering
- Wireless Communication
Background:
- Clustered cognitive radio sensor networks (CRSNs) require efficient spectrum sensing and energy management for fair data traffic.
- Existing multi-hop routing protocols often assume perfect spectrum sensing, which is unrealistic in practical CRSNs.
- Imbalanced residual energy among cluster heads (CHs) degrades data packet delivery.
Purpose of the Study:
- To propose a hybrid optimization algorithm for imperfect spectrum sensing in CRSNs.
- To enhance downlink energy harvesting utilization and node energy levels.
- To extend network lifetime and maintain surveillance capabilities.
Main Methods:
- Developed a hybrid Mexican axolotl and bitterling fish optimization algorithm (HMABFOA) for spectrum sensing and multi-hop clustering routing.
- Implemented imperfect spectrum sensing to address real-world network conditions.
- Utilized Mexican axolotl optimization algorithm (MAOA) for CH selection and cluster formation, ensuring energy stability.
- Employed bitterling fish optimization algorithm (BFOA) for optimized multi-hop routing, minimizing energy consumption and maximizing spectrum sensing.
Main Results:
- Achieved a maximized network lifetime increase of 24.38%.
- Improved spectrum utilization rate by 24.58%.
- Reduced energy utilization by 25.62% compared to baseline approaches.
Conclusions:
- The proposed HMABFOA effectively addresses imperfect spectrum sensing challenges in CRSNs.
- The algorithm enhances energy efficiency, network lifetime, and spectrum utilization.
- HMABFOA offers a robust solution for sustainable network surveillance and data transmission.
