Enhancing Network Lifetime and Stability in IoT-Based HWSNs for Elderly Care Through Optimized Cluster Head Selection
R. Preethi, A.K. Karthikeyan · 2025
Wireless sensor networks (WSNs), a key component of the Internet of Things (IoT), offer a promising avenue, particularly in the form of heterogeneous WSNs (HWSNs) comprising diverse sensor modalities relevant to elder care. Addressing the inherent energy constraints of HWSN nodes is critical for prolonged operation. The proposed methodology strategically selects CHs based on the integration of the Multi-Objective African Vulture Optimization algorithm and the Whale Optimization Algorithm. This optimized CH selection aims to achieve enhanced energy efficiency, balanced energy expenditure across network nodes, improved data aggregation efficacy, and increased network scalability. MOAVWOA aims to improve network lifetime and stability and is uniquely independent of the network's heterogeneity level. Performance evaluations indicate that MOAVWOA outperforms BEENISH, IBEENISH, MBEENISH, and IMBEENISH in terms of network lifespan and demonstrate enhanced stability. This adaptable approach is particularly beneficial for elderly digital healthcare applications, enabling proactive and localized services that enhance the safety and well-being of older adults.