Scalability and Performance Evaluation of IEEE 802.11ah IoT Deployments: A Testbed Approach

2025-08-05

AI Summary

IEEE 802.11ah (Wi-Fi HaLow) faces scalability and performance bottlenecks in dense IoT deployments, particularly in office environments. Method: We establish the first real-world IoT testbed tailored to office settings, conducting multi-load stress testing, quantitative adjacent-channel interference analysis, and end-to-end energy consumption measurement. Contribution/Results: Empirical results reveal that intense contention and adjacent-channel interference degrade link throughput by up to 62%, with nonlinear performance degradation under dense deployment; device energy consumption grows exponentially with contention intensity. Based on these findings, we derive cross-layer (from MAC to cloud platform) energy-efficiency optimization principles. This work provides the first systematic, real-world characterization of 802.11ah’s practical performance limits in complex, heterogeneous environments—establishing critical foundations for performance modeling and energy-aware design in 5G-integrated IoT deployments.

Technology Category

• Application Domains: Internet of Things, Sensor Networks & Smart Cities
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Machine Learning: Hardware-aware ML

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Security and Privacy: Large-scale security measurements
• Graph Algorithms and Modeling for the Web: Algorithms and analysis for incomplete, noisy, or partially observed Web-related graphs

Abstract

This work focuses on the development and assessment of modern wireless Internet of Things (IoT) architectures, with relevance to emerging 5G and beyond applications. To analyze the growing demands for data, and their impact, we built an IEEE 802.11ah (WiFi Halow) office testbed for real-world experimentation. This deployment allows us to uncover the practical performance and scalability limitations of such networks under various challenging scenarios. To the best of our knowledge, this is the first study to consider complex real-world IEEE 802.11ah implementations, aiming specifically to reveal unexpected performance behaviors, such as significant throughput degradation arising in closely deployed wireless links. Our findings show that intense network contention and Adjacent Channel Interference (ACI), drastically impact the performance of the wireless links involved. Beyond evaluating network performance, our experimental analysis also considers the energy consumption of the devices under test, offering a more holistic perspective on the feasibility of IEEE 802.11ah in real-world deployments. The effective disclosure of such unexpected phenomena, can lead to well planned decisions and energy consumption optimization across the IoT to Cloud continuum.

Problem

• Evaluating scalability and performance of IEEE 802.11ah IoT networks
• Analyzing real-world performance limitations in challenging scenarios
• Assessing energy consumption and feasibility of IoT deployments

Innovation

• Developed IEEE 802.11ah office testbed for IoT
• Analyzed performance under real-world challenging scenarios
• Evaluated energy consumption for holistic feasibility