Fault tolerant and load balanced deployment of access points in WLANs: a heuristic algorithm with multi-AP and single-AP search

Purpose Fault tolerance plays a pivotal role in enhancing network resilience and ensuring uninterrupted Web service in indoor Wireless Local Area Networks (WLANs). This paper aims to integrate a fault tolerance mechanism into optimal Access Point (AP) deployment to eliminate coverage gaps in the event of AP failures. To further improve the Quality of Experience (QoE) and achieve load balancing within the WLAN, the authors formulate the Optimal Deployment Problem of Access Points with Fault Tolerance (ODPAPFT) as a constrained optimization problem. The objective is to improve load balancing among APs while maintaining fault tolerance, thereby enhancing the overall performance and reliability of the WLAN. Design/methodology/approach To solve the proposed problem, a novel optimization approach based on Particle Swarm Optimization (PSO) with Multi-AP and Single-AP Search (PSOMSAS) is proposed. The method iteratively refines AP deployment schemes by leveraging multi-AP and single-AP search strategies. Practical scenarios, including real-world building layouts and obstacle distributions, were used to evaluate the proposed approach. Findings Experimental results demonstrate that the PSOMSAS method guarantees full coverage under any AP failure scenario, ensuring uninterrupted service. Additionally, it significantly enhances the load balancing among APs, achieving superior load-balancing performance compared to existing AP deployment optimization methods. The optimized deployment schemes also highlight the inefficiency of uniform AP distribution and emphasize the need for context-specific optimization. Originality/value The proposed ODPAPFT formulation and the PSOMSAS approach provide a reliable framework for designing robust AP deployment schemes in real-world scenarios, supporting fault tolerance and enhanced load balancing. This work offers a valuable reference for network designers aiming to optimize WLAN deployments for modern web applications and services.