IMR: MT: xGTracker -- Mobile xG Performance Monitoring and Data Collection Platform to Enable Large-Scale Crowd-Sourced Measurement

Regents Of The University Of Michigan - Ann Arbor, Ann Arbor MI

Investigators

Abstract

Commercial 5G networks are becoming more widely available. Their key advantage is much higher speeds, enabling emerging applications such as multimedia streaming, VR/AR (virtual reality/augmented reality), and autonomous vehicles, to name a few. Measuring the performance of these networks and emerging applications becomes important to understand how they function and to identify areas of improvement especially for designing the next generation of such technologies. This collaborative project brings together investigators from the University of Michigan and University of Minnesota to create a platform for measuring the performance of 5G, 6G, (i.e., xG) networks and show the changes over time along with the performance of the emerging applications. xGTracker is modular, extensible, configurable, cross-technology, and application-centric measurement platform. First, xGTracker has several configurable components and enables researchers to add/replace components. It is capable of selecting available radio bands/technologies to conduct measurements. Second, xGTracker will integrate existing real open-source applications as well as generating different workloads to emulate others for collecting application Quality of Experience metrics. Third, xGTracker allows for dynamic server selection based on several parameters such as (location, carrier, and workload). This helps understand the impact of server location on the collected metrics. Fourth, XGTracker will report energy consumption for different system/device components which enables monitoring the energy consumption for emerging applications. Finally, xGTracker fully considers user privacy allowing users to choose what and how to share their data. The broader impact of the project has multiple dimensions. First, xGTracker provides tools that measure and characterize the performance of commercial xG networks. This will benefit xG customers, application developers, and xG carriers. XGTracker has the potential to be integrated with industrial collaborators improving the quality of experience for hundreds of millions of xG users in the future. Second, xGTracker presents an opportunity to integrate research and education. It will contribute new content to networking and mobile courses taught and help design various course projects. xGTracker will also be used to show 5G technology to students especially from underrepresented groups and simulate their interest in STEM. The repository for the xGTracker Platform is at https://github.com/xGTracker-Platform. The project is expected to be open-source under a BSD-style permissive free software license for other researchers to contribute to it and add new features. The data collected through the xGTracker platform will then be made available through different performance maps to show the performance of the different technologies over time as well as the quality of experience for different applications. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.