Node failure in self-organized sensor networks

Abstract Wireless sensor networks (WSNs) encountered substantial obstacles in contexts characterized by frequent sensor node failures. Overcoming these obstacles requires a remedy that not only identifies node failures but also improves network self-organization. This work introduces a method that merges the Cuckoo Search Optimization algorithm (CSO) with the suggested Guided and Effective Search (GES) algorithm to improve the network’s ability to self-organize and maintain efficiency during node failures. The method combines CSO’s search capability for finding node configurations with GES’ effectiveness in local searches within the network structure. Together, they establish a system for fault detection network optimization, and improve self-organization, ensuring that the network could adapt and withstand disruptions. Comprehensive simulation results demonstrated the method’s superiority compared to the existing methods. The system demonstrates enhancements in fault detection accuracy, network self-organization, packet delivery rate, and overall energy efficiency. In addition, the simulation results highlight the improved performance of the combined approach compared to the Particle Swarm Optimization algorithm. Integrating CSO and GES marked advancement in creating self-organizing WSNs offers reliability and longevity for networks used in critical applications.