A Hybrid Approach for Energy Consumption and Improvement in Sensor Network Lifespan in Wireless Sensor Networks

In this paper, we propose an improved clustering algorithm for wireless sensor networks (WSNs) that aims to increase network lifetime and efficiency. We introduce an enhanced fuzzy spider monkey optimization technique and a hidden Markov model-based clustering algorithm for selecting cluster heads....

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2024-02, Vol.24 (5), p.1353
Main Authors: Ullah, Arif, Khan, Fawad Salam, Mohy-Ud-Din, Zia, Hassany, Noman, Gul, Jahan Zeb, Khan, Maryam, Kim, Woo Young, Park, Youn Cheol, Rehman, Muhammad Muqeet
Format: Article
Language:English
Subjects:
Algorithms
Analysis
Clustering
Communication
Data mining
Electric power transmission
Energy consumption
Energy efficiency
Energy management systems
Energy use
Environmental monitoring
fuzzy spider monkey
hidden Markov model
hybrid routing protocol
Markov processes
Mathematical optimization
Methods
Military deployment
network lifetime
Optimization techniques
Privacy
Protocol
Quality of service
Sensors
Wireless sensor networks
Wireless telecommunications equipment
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Summary:In this paper, we propose an improved clustering algorithm for wireless sensor networks (WSNs) that aims to increase network lifetime and efficiency. We introduce an enhanced fuzzy spider monkey optimization technique and a hidden Markov model-based clustering algorithm for selecting cluster heads. Our approach considers factors such as network cluster head energy, cluster head density, and cluster head position. We also enhance the energy-efficient routing strategy for connecting cluster heads to the base station. Additionally, we introduce a polling control method to improve network performance while maintaining energy efficiency during steady transmission periods. Simulation results demonstrate a 1.2% improvement in network performance using our proposed model.
ISSN:1424-8220
1424-8220
DOI:10.3390/s24051353