Optimizing sampling for Ontario's K-12 wireless network data
Nihad Al-Juboori, Salam A. Ismaeel, Mirza Kamaludeen · IET conference proceedings. · 2025
In today’s educational landscape, the effective operation and stability of a school’s network infrastructure play a pivotal role in enabling uninterrupted connectivity crucial for educational and administrative functions. This research is centred on the development of an optimal sampling methodology designed to efficiently collect wireless network health data from a vast array of access points (APs). With an extensive network spanning numerous locations, the paper focuses on crafting a method that minimizes the number of Aps sampled while providing comprehensive insights into network health. Emphasizing the importance of systematic sampling strategies, the study details the calculation of sampling intervals, selection criteria, and the determination of an optimal sample size using specialized equations. The objective is to create a methodology that offers a holistic perspective on network health derived from a strategically selected subset of APs, ensuring robust and accurate assessments.