TRUST-ENHANCED SECURE CLUSTER ROUTING IN WIRELESS SENSOR NETWORKS USING A MODIFIED MOTH FLAME OPTIMIZATION ALGORITHM

Wireless Sensor Networks (WSNs) are self-organizing systems composed of numerous small sensor nodes used to monitor and track various applications across extensive areas. In the context of healthcare, wireless sensor networks can play a crucial role by continuously monitoring patients' vital signs and ensuring timely data transmission to medical professionals. Despite their usefulness, WSNs face significant challenges related to energy consumption and security due to their open and limited resources. Implementing a Trust-based Modified Moth Flame Optimization (T-MMFO) algorithm in healthcare WSNs can help select secure and efficient routes for data transmission, thereby improving the overall reliability and longevity of the network. This enhanced security and energy efficiency ensure that critical health data is transmitted accurately and promptly, supporting better patient outcomes and more efficient healthcare delivery. The algorithm's performance was evaluated based on Packet Delivery Ratio (PDR), energy consumption, delay, and throughput. The results showed that T-MMFOA achieved a high PDR of 98.5% and 95.7% for networks with 200 and 400 nodes, respectively, outperforming existing methods like Fuzzy Grey Wolf Optimization (F-GWO), Quality of Service-aware Multipath Routing (QMR), Improved Duck and Traveller Optimization Multi-Hop Routing (IDTOMHR), and Quantum Behaviour and Gaussian Mutation Archimedes Optimization Algorithm (QGAOA)