Delay Analysis of Wi-Fi-Based Multi-Source Networked Data Acquisition

Establishing an analytical model framework can provide a meaningful theoretical foundation for further enhancing network performance, as well as for the design and improvement of communication protocols. This paper analyzes the performance of Wi-Fi-based multi-source data acquisition scenarios within Industrial Internet of Things (IIoT). Each Station (STA) uses a polling strategy to schedule packet transmission and communicates via the IEEE 802.11 protocol. Using Markov chain and polling system theory, an accurate model for the Distributed Coordination Function (DCF) and queueing processes is developed. A numerical iterative algorithm is proposed to calculate the delay distribution, including average delay and percentiles under high-load conditions. The flexible model can adapt to various network configurations and access scenarios. Simulation results confirm the model’s accuracy and effectiveness.