A Novel Lucas-based Clustering Optimization for Enhancing Survivability in Smart Home Design
Kanaka Raju Rajana, Shanmuk Srinivas Amiripalli · Engineering Technology & Applied Science Research · 2025
This study presents a novel Lucas-based topology optimization framework to enhance network survivability in smart homes, particularly against random node failures. As the proliferation of interconnected devices in the Internet of Things (IoT) environments increases, so does the vulnerability of these networks to node failures, which can significantly disrupt connectivity and functionality. By integrating the mathematical properties of Lucas numbers with advanced graph theory concepts, specifically the Trimet Graph Optimization (TGO) model, this framework systematically addresses the challenges posed by random node failures. The proposed model optimizes network topologies to ensure robust connectivity and resilience, allowing smart home networks to maintain operational integrity even under adverse conditions. Simulations and theoretical analyses demonstrate the effectiveness of this approach, highlighting its potential to improve the reliability of smart home networks.