Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

On the Suitability of Wi-Fi for Interconnecting Moving Equipment in Industrial Environments

Pietro Chiavassa, Stefano Scanzio, Gianluca Cena

TL;DR

This work assesses Wi-Fi suitability for interconnecting moving industrial devices by simulating an infrastructure WLAN in ns-3 with a moving station and potential interferers. It jointly analyzes end-to-end latency, reliability, energy, and spectrum usage under three configurations (NO_INT, VISIBLE, HIDDEN) to quantify how attenuation and interference shape soft real-time performance. Key findings show zero packet loss without interference, increased latency with visible interference, and severe QoS degradation with hidden-node conditions, including occasional packet drops and higher energy consumption. The study provides empirical foundations for fast, approximate QoS models and digital twin tools to optimize runtime behavior of industrial Wi-Fi networks.

Abstract

To ensure an unprecedented degree of flexibility, next-generation Industry 4.0/5.0 production plants increasingly rely on mobile devices, e.g., autonomous mobile robots and wearables. In these cases, a major requirement is getting rid of cables through the adoption of wireless networks. To this purpose, Wi-Fi is currently deemed one of the most promising solutions. Achieving reliable communications over the air for distributed real-time control applications is, however, not devoid of troubles. In fact, bounded transmission latency must be ensured for most of the exchanged packets. Moreover, for devices powered on batteries, energy consumption also needs to be taken into account. In this paper, a joint simulated analysis of these aspects is carried out to quantitatively evaluate what we can practically expect from Wi-Fi technology.

On the Suitability of Wi-Fi for Interconnecting Moving Equipment in Industrial Environments

TL;DR

This work assesses Wi-Fi suitability for interconnecting moving industrial devices by simulating an infrastructure WLAN in ns-3 with a moving station and potential interferers. It jointly analyzes end-to-end latency, reliability, energy, and spectrum usage under three configurations (NO_INT, VISIBLE, HIDDEN) to quantify how attenuation and interference shape soft real-time performance. Key findings show zero packet loss without interference, increased latency with visible interference, and severe QoS degradation with hidden-node conditions, including occasional packet drops and higher energy consumption. The study provides empirical foundations for fast, approximate QoS models and digital twin tools to optimize runtime behavior of industrial Wi-Fi networks.

Abstract

To ensure an unprecedented degree of flexibility, next-generation Industry 4.0/5.0 production plants increasingly rely on mobile devices, e.g., autonomous mobile robots and wearables. In these cases, a major requirement is getting rid of cables through the adoption of wireless networks. To this purpose, Wi-Fi is currently deemed one of the most promising solutions. Achieving reliable communications over the air for distributed real-time control applications is, however, not devoid of troubles. In fact, bounded transmission latency must be ensured for most of the exchanged packets. Moreover, for devices powered on batteries, energy consumption also needs to be taken into account. In this paper, a joint simulated analysis of these aspects is carried out to quantitatively evaluate what we can practically expect from Wi-Fi technology.

Paper Structure

This paper contains 14 sections, 1 equation, 9 figures.

Table of Contents

  1. Introduction
  2. Wi-Fi Basics
  3. Contribution
  4. Methodology
  5. Network configurations
  6. NO_INT configuration
  7. VISIBLE configuration
  8. HIDDEN configuration
  9. Simulation setup
  10. Evaluation metrics
  11. Results
  12. No Interfering Devices
  13. Single Interfering Device
  14. Discussion and Conclusion

Figures (9)

  • Figure 1: Physical placement of devices (one-dimensional map).
  • Figure 2: Latency ($\mu_\mathrm{d}$, $d_{\min}$) and tx attempts ($\mu_\mathrm{a}$) vs. $D_\mathrm{S}$ (NO_INT).
  • Figure 3: Relative success frequency $s_{r_i}$ of each data rate $r_i$ vs. $D_\mathrm{S}$ (NO_INT).
  • Figure 4: Selection frequency $f_{r_i}$ of data rate $r_i$ vs. $D_\mathrm{S}$ (NO_INT).
  • Figure 5: Latency percentiles $d_\mathrm{p99}$ and $d_\mathrm{p99.9}$ vs. $D_\mathrm{S}$ (NO_INT).
  • ...and 4 more figures