9 citations · 34 across the 12 of their papers we have counts for
12 papers
Machine Learning to Predict Slot Usage in TSCH Wireless Sensor Networks
Stefano Scanzio, Gabriele Formis, Tullio Facchinetti +1
Wireless sensor networks (WSNs) are employed across a wide range of industrial applications where ultra-low power consumption is a critical prerequisite. At the same time, these sy…
Widening the Coverage of Reference Broadcast Infrastructure Synchronization in Wi-Fi Networks
Gianluca Cena, Pietro Chiavassa, Gabriele Formis +1
Precise clock synchronization protocols are increasingly used to ensure that all the nodes in a network share the very same time base. They enable several mechanisms aimed at impro…
On the Prediction of Wi-Fi Performance through Deep Learning
Gabriele Formis, Amanda Ericson, Stefan Forsstrom +3
Ensuring reliable and predictable communications is one of the main goals in modern industrial systems that rely on Wi-Fi networks, especially in scenarios where continuity of oper…
Accurate and Efficient Prediction of Wi-Fi Link Quality Based on Machine Learning
Gabriele Formis, Gianluca Cena, Lukasz Wisniewski +1
Wireless communications are characterized by their unpredictability, posing challenges for maintaining consistent communication quality. This paper presents a comprehensive analysi…
Improving Wi-Fi Network Performance Prediction with Deep Learning Models
Gabriele Formis, Amanda Ericson, Stefan Forsstrom +3
The increasing need for robustness, reliability, and determinism in wireless networks for industrial and mission-critical applications is the driver for the growth of new innovativ…
Compression of executable QR codes or sQRy for Industry: an example for Wi-Fi access points
Stefano Scanzio, Gabriele Formis, Pietro Chiavassa +2
Executable QR codes, or sQRy, is a technology dated 2022 that permits to include a runnable program inside a QR code, enabling interaction with the user even in the absence of an I…
Wireless Sensor Networks based on TSCH/TDMA with Power Consumption and Latency Constraints
Stefano Scanzio, Gabriele Formis, Tullio Facchinetti +2
One of the main goals of wireless sensor networks is to permit the involved nodes to communicate with low energy budgets, as they are typically battery-powered. When such networks…
On the Accuracy and Precision of Moving Averages to Estimate Wi-Fi Link Quality
Gianluca Cena, Gabriele Formis, Matteo Rosani +1
The radio spectrum is characterized by a noticeable variability, which impairs performance and determinism of every wireless communication technology. To counteract this aspect, me…
Mixing Neural Networks and Exponential Moving Averages for Predicting Wireless Links Behavior
Gabriele Formis, Stefano Scanzio, Lukasz Wisniewski +1
Predicting the behavior of a wireless link in terms of, e.g., the frame delivery ratio, is a critical task for optimizing the performance of wireless industrial communication syste…
Multi-Link Operation and Wireless Digital Twin to Support Enhanced Roaming in Next-Gen Wi-Fi
Stefano Scanzio, Matteo Rosani, Gabriele Formis +4
The next generation of Wi-Fi is meant to achieve ultra-high reliability for wireless communication. Several approaches are available to this extent, some of which are being conside…
Linear Combination of Exponential Moving Averages for Wireless Channel Prediction
Gabriele Formis, Stefano Scanzio, Gianluca Cena +1
The ability to predict the behavior of a wireless channel in terms of the frame delivery ratio is quite valuable, and permits, e.g., to optimize the operating parameters of a wirel…
Predicting Wireless Channel Quality by means of Moving Averages and Regression Models
Gabriele Formis, Stefano Scanzio, Gianluca Cena +1
The ability to reliably predict the future quality of a wireless channel, as seen by the media access control layer, is a key enabler to improve performance of future industrial ne…