Enhanced aperiodic threshold sensitive stable election protocol (EATSEP) for WSNs

Wireless sensor networks (WSNs) have emerged as vital technologies for safety-critical applications due to their flexibility, scalability, and reliability. However, existing models such as LEACH, SEP, and TSEP exhibit limitations in energy efficiency, stability, and adaptability to heterogeneous node conditions. To address these gaps, this research proposes a multilevel heterogeneity-based WSN model that optimizes cluster-head (CH) selection and energy utilization for enhanced network performance. Simulations were conducted in MATLAB under unequal energy level variations and compared with established protocols. Results demonstrate that the proposed model consistently outperforms existing approaches in terms of network lifetime, throughput, and energy efficiency. Statistical analysis reveals a best-case improvement of approximately 9000 rounds and a worst-case gain of about 3000 rounds when four heterogeneity levels are employed, compared to three levels. These findings highlight that both the degree of energy diversity and the distribution of energy nodes across levels are crucial for achieving optimal performance. Overall, the proposed architecture significantly enhances reliability, stability, and energy efficiency, making it well-suited for disaster management and other safety-critical applications.