Secure and energy-efficient inter- and intra-cluster optimization scheme for smart cities using UAV-assisted wireless sensor networks

In recent years, lightweight sensors have become essential for advancing technologies, particularly in wireless sensor networks (WSNs). A persistent challenge in WSNs is maintaining continuous operation while achieving balanced energy consumption across sensor nodes. Wireless mobile energy transmitters (WMETs) provide a promising solution by wirelessly recharging sensor nodes. However, most existing approaches fail to optimize WMET charging locations, resulting in energy imbalance and reduced network coverage. Furthermore, conventional clustering systems often overlook both inter- and intra-cluster energy balancing, degrading overall network performance. Security issues, such as insufficient data encryption, further exacerbate these challenges, leaving WSNs vulnerable to attacks. To address these gaps, we propose the secure and energy-efficient inter- and intra-cluster optimization scheme (SEI2), a novel WMET-based framework that ensures balanced energy utilization among cluster heads (CHs) and member nodes (MNs) while securing data transmission. The SEI2 system incorporates UAVs to dynamically recharge sensor nodes, determining optimal charging locations within clusters to maximize energy efficiency. Additionally, robust data encryption mechanisms are applied at both the CH and base station (BS) levels to safeguard transmitted data. Key parameters considered include node energy levels, data transmission rates, optimal charging locations, and encryption overhead. Experimental evaluations demonstrate that SEI2 improves network lifetime by 35%, reduces compromised data packets by 19%, enhances coverage time by 15%, and significantly minimizes energy variance by 62% for CHs and 88% for MNs. These results highlight SEI2's potential as a comprehensive solution for extending WSN lifetimes, enhancing energy efficiency, and strengthening data security, making it particularly suitable for smart city applications.

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Publication Details

Journal
Scientific Reports
Published
2025-02-04
DOI
https://doi.org/10.1038/s41598-025-88532-0
Citations
12
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
59.92
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article

Secure and energy-efficient inter- and intra-cluster optimization scheme for smart cities using UAV-assisted wireless sensor networks

Aliaa M. Alabdali, Niayesh Gharaei
12 citations
Scientific Reports
UAV Applications and Optimization
59.92
article

Secure and energy-efficient inter- and intra-cluster optimization scheme for smart cities using UAV-assisted wireless sensor networks

Aliaa M. Alabdali, Niayesh Gharaei
article en
12 citations

Abstract

In recent years, lightweight sensors have become essential for advancing technologies, particularly in wireless sensor networks (WSNs). A persistent challenge in WSNs is maintaining continuous operation while achieving balanced energy consumption across sensor nodes. Wireless mobile energy transmitters (WMETs) provide a promising solution by wirelessly recharging sensor nodes. However, most existing approaches fail to optimize WMET charging locations, resulting in energy imbalance and reduced network coverage. Furthermore, conventional clustering systems often overlook both inter- and intra-cluster energy balancing, degrading overall network performance. Security issues, such as insufficient data encryption, further exacerbate these challenges, leaving WSNs vulnerable to attacks. To address these gaps, we propose the secure and energy-efficient inter- and intra-cluster optimization scheme (SEI2), a novel WMET-based framework that ensures balanced energy utilization among cluster heads (CHs) and member nodes (MNs) while securing data transmission. The SEI2 system incorporates UAVs to dynamically recharge sensor nodes, determining optimal charging locations within clusters to maximize energy efficiency. Additionally, robust data encryption mechanisms are applied at both the CH and base station (BS) levels to safeguard transmitted data. Key parameters considered include node energy levels, data transmission rates, optimal charging locations, and encryption overhead. Experimental evaluations demonstrate that SEI2 improves network lifetime by 35%, reduces compromised data packets by 19%, enhances coverage time by 15%, and significantly minimizes energy variance by 62% for CHs and 88% for MNs. These results highlight SEI2's potential as a comprehensive solution for extending WSN lifetimes, enhancing energy efficiency, and strengthening data security, making it particularly suitable for smart city applications.

Scientific ReportsVol. 15(1)
King Abdulaziz University (SA), Ostim Technical University (TR)
Openalex Percentile: Top 0%
UAV Applications and Optimization
59.92
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