Enhance Network Life Time and Efficiency of Wireless Sensor Networks via Hybrid Deep Learning Based Clustering Head Selection with Metaheuristics Optimization Algorithm
Aug 2026· Wireless personal communications· Vol 146, pp. 5483 - 5507· 0 citations· 31 references
TL;DR
Simulation results demonstrate that the proposed DRGNN–StBOA framework significantly outperforms existing approaches, achieving a network lifetime of 2200 rounds, an average residual energy of 0.8 J, a packet delivery ratio (PDR) of 70%, a throughput of 700 kbps, and an end-to-end delay of 99 ms.
Wireless Sensor Networks (WSNs) are highly susceptible to cluster head (CH) failures due to limited node energy and unstable communication links, resulting in data loss and reduced network reliability. This work presents a fault-tolerant cluster-based routing model that integrates an Improved Graph Neural Network (IGNN...
S. P. Kumar, S. Asklany, E. Alabdulkreem et al.· Scientific Reports· 0 citations
Clustering and routing protocols are widely regarded as effective methods for improving energy efficiency and extending network lifetime in wireless sensor networks. However, existing protocols often insufficiently consider dynamic energy distribution and topology characteristics, which may lead to imbalanced cluster...
Wireless sensor networks (WSNs) plays a dynamic role in enabling industrial applications such as production, logistics, and predictive maintenance. The present study investigates optimal strategies for sensor node placement and energy consumption optimisation to enhance the functionality of industrial WSNs. Currently...
B. Ravindrakumar, M. V. Babu· Scientific Reports· 0 citations
The use of wireless sensor networks (WSNs) for location‐based services is gaining importance in situations where conventional positioning systems are ineffective, such as GPS. Mobile and large‐scale deployments, in particular, pose a significant challenge in terms of maintaining high localization accuracy while maint...
Siva Sudheer Mahadasu, B. Rallabandi, Neelakantam Gudla et al.· Internet Technology Letters· 0 citations
A multi-cluster WSN model with optimal CH selection (the MO model) in which the CHs are selected by a particle swarm optimization (PSO) algorithm, by solving a multipurpose optimization problem based on three criteria: residual energy, distance between candidate CHs and the base station, and intra-cluster distance.
I. Kamil, Goodness Adeleke Adetokun· International Journal of Lat...· 0 citations
Wireless sensor networks (WSNs) require energy-efficient clustering and adaptive routing to maintain reliable communication and prolong network lifetime under varying node density, initial energy, communication range, packet size, residual energy, routing distance, latency, and mobile-sink conditions. However, conventi...
Kishore Kumar Kamarajugadda, Movva Pavani, G. Anandbabu et al.· Discover Computing· 0 citations
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