Energy-efficient smart architecture for fog-based WSN using NSGA-III and improved layer-wise clustering for enhanced building evacuation safety

This paper proposes an energy-efficient smart architecture for a Fog-based Wireless Sensor Network to facilitate safe evacuation in smart buildings during emergencies. The architecture comprises two layers: the sensing layer and the fog layer. Throughout the building, strategically distributed sensors continuously monitor potential emergencies and communicate with a central fog computing server, facilitating efficient emergency response management. To optimize evacuation routes, sensor nodes independently determine quick and safe paths using local intelligence, effectively addressing potential fog computing delays. The implementation of dynamic routing algorithms helps prevent congestion and evenly distribute evacuees across multiple routes. To achieve these objectives, the paper proposes an Improved Layer-wise Clustering Protocol (ILC) to establish an equal number of cluster heads at each floor of the smart building. Furthermore, Non-dominated Sorting Genetic Algorithm III (NSGA-III) is utilized to further enhance the system’s performance. The combination of fog computing and smart sensing in this architecture presents a promising solution for ensuring the safety and effectiveness of building evacuations during critical situations. The extensive experimental analysis demonstrates that the ILC with NSGA-III (ILC-NSGA-III) surpasses the performance of competitive protocols in various key metrics such as stable period, network lifetime, energy conservation, and end-to-end delay.