WiFresh: Age-of-Information from Theory to Implementation

Abstract

Emerging applications, such as smart factories and fleets of drones, increasingly rely on sharing time-sensitive information for monitoring and control. In such application domains, it is essential to keep information fresh, as outdated information loses its value and can lead to system failures and safety risks. The Age-of-Information is a performance metric that captures how fresh the information is from the perspective of the destination. In this paper, we show that as the congestion in the wireless network increases, the Age-of-Information degrades sharply, leading to outdated information at the destination. Leveraging years of theoretical research, we propose WiFresh: an unconventional architecture that achieves near optimal information freshness in wireless networks of any size, even when the network is overloaded. Our experimental results show that WiFresh can improve information freshness by two orders of magnitude when compared to an equivalent standard WiFi network. We propose and realize two strategies for implementing WiFresh: one at the MAC layer using hardware-level programming and another at the Application layer using Python.

An Experimental Framework for Age of Information and Networked Control via Software-Defined Radios

“…They are implemented using GNU Radio which is a software framework that provides a wide range of signal processing blocks. The resulting code is run on Ettus Research's USRP B200mini-i which are lower-priced SDRs than the ones used in [9] and [12]. Our implementation is publicly available at: https://github.com/oayan/gr-ieee802-15-4/tree/maint-3.7.…”

“…To the best of our knowledge, the only implementationbased works mentioning AoI and proposing a customized solution are [9], [12]. They measure AoI in a network of multiple software-defined radios (SDRs) where the considered application is timestamped packet exchange but not a realworld example requiring time-critical information.…”

“…They measure AoI in a network of multiple software-defined radios (SDRs) where the considered application is timestamped packet exchange but not a realworld example requiring time-critical information. In [9], authors propose a MAC layer protocol using last come first serve (LCFS) queues and polling mechanism managed by a central node. They show that AoI is decreased significantly through the use of LCFS strategy.…”

“…Moreover, most of the practical AoI research consists of measurements conducted on real-world equipment without any modifications inside the communication stack. Even though [9] and [12] propose a customized MAC layer implementation with SDRs, they are neither able to provide any open-source code to be used by the AoI community, nor any comprehensive study including different queuing and medium access strategies jointly.…”