Secure and Energy-Efficient Data Collection in Wireless Sensor Networks using Trust-Aware Clustering and Intelligent Mobile Sinks
DOI:
https://doi.org/10.15662/IJEETR.2026.0802395Keywords:
Trust-aware clustering, wireless sensor networks, mobile sinks, energy efficiency, secure data collection, routing optimization, anomaly detectionAbstract
Energy consumption is one of the major factors affecting network lifetime in Wireless Sensor Networks (WSNs) and remains a critical research challenge. In existing systems, data collection is typically performed using a single mobile sink, which leads to increased energy depletion, routing inefficiencies, and reduced network lifetime. To address these issues, this work proposes a multi-mobile sink–based data collection framework combined with energy-aware and secure clustering mechanisms. In the proposed system, the sensor network is divided into clusters using the K-Means clustering algorithm, where each cluster contains a single Cluster Head (CH). The CH selection process is dynamic in nature and is enhanced using a secure Energy-LEACH++ protocol. Initially, CHs are selected randomly, while in subsequent rounds, CH selection is performed based on a composite fitness function that considers both residual energy and trust value of sensor nodes. The trust value is computed using lightweight parameters such as packet forwarding success, data consistency, and energy honesty, ensuring secure and reliable CH selection with minimal overhead. Communication between Cluster Members (CMs) and CHs follows a single-hop transmission model to reduce energy consumption. To efficiently address the problem of optimal data collection paths and avoid redundant routing, a Weighted Rendezvous Planning (WRP) strategy is employed.
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