Overview
Rural broadband is a foundation for a strong rural economy and quality of life, and many rural applications require real-time data-intensive communications. Wireless networks are essential building blocks of rural broadband; however, rural wireless is subject to environmental factors such as weather, terrain, foliage, and crop types and densities, and rural wireless networks need to provide coverage to much larger areas with less density than urban networks. To support real-time data-intensive rural applications, this project will investigate Real-Time Liquid Wireless Networking (RT-LWN). The RT-LWN framework is expected to become a foundational component of rural broadband solutions, and the enabled real-time data-intensive rural applications such as agriculture automation and immersive online education are expected to have a transformative impact on rural industries and communities. This project will generate first-of-its-kind real-world measurement data and models of rural access and backhaul links, and they will be of broad use by the research and education communities. This project will create exciting opportunities for broadening participation in computing, and it will help enrich undergraduate and graduate research and education as well as K-12 outreach. Project results will be broadly disseminated.
In the RT-LWN framework, application data are encoded using fountain codes and then delivered across wireless access and backhaul networks with probabilistic real-time packet delivery guarantees. The liquidity of fountain-encoded data, together with a field-deployable approach to probabilistic real-time communication guarantees across wireless access and backhaul, enables efficient, real-time delivery of each source block while fully leveraging the aggregate capacity of heterogeneous wireless networks in the presence of fast-varying dynamics and uncertainties. The RT-LWN framework effectively integrates fountain-encoded liquid data with the design of predictable wireless networking. In particular, with predictable control of communication reliability, timeliness, and throughput at the link, network, and liquid transport layers, RT-LWN enables “predictability by design”, and it tackles the resiliency and performance challenges of rural wireless at the same time, to enable transformative real-time data-intensive applications. RT-LWN embeds liquid data networking into a rural wireless network architecture featuring 1) novel, effective integration of the liquid transport layer into end-points, 2) functional decomposition across the liquid transport layer and lower layers based on the end-to-end principle, and 3) field-deployable, holistic designs for addressing complex, fast-varying wireless dynamics and uncertainties.
This project is a part of the National Science Foundation CNS Core and NeTS program.
Publications
- Zhibo Meng, Hongwei Zhang, Joint Scheduling and Power Control for Predictable Per-Packet Reliability in URLLC, IEEE International Conference on Network Protocols (ICNP), 2024
- Zhibo Meng, Hongwei Zhang, James Gross, Scheduling with Probabilistic Per-Packet Real-Time Guarantee for Industrial URLLC, IEEE International Conference on Industrial Cyber-Physical Systems (ICPS), 2024 (Best Student Paper Award)
- E. K. A. Permatasari, E. Gosling, M. Nadim, S. Babu, D. Qiao, H. Zhang, M. Luby, J. W. Byers, L. Minder, and P. Aggrawal, Real-Time Liquid Wireless Transport for Video Streaming in Rural and Agricultural Applications, ACM Mile High Video (MHV), 2024
- Taimoor Ul Islam, Tianyi Zhang, Joshua Ofori Boateng, Evan Gossling, Guoying Zu, Sarath Babu, Hongwei Zhang, Daji Qiao, AraMIMO: Programmable TVWS mMIMO Living Lab for Rural Wireless, ACM Workshop on Wireless Network Testbeds, Experimental evaluation and CHaracterization (WiNTECH), 2023 (Best Paper Award)
- Tianyi Zhang, Guoying Zu, Taimoor Ul Islam, Evan Gossling, Sarath Babu, Daji Qiao, Hongwei Zhang, Exploring Wireless Channels in Rural Areas: A Comprehensive Measurement Study, IEEE Future Networks World Forum (FNWF), 2023 (Best Paper Honorable Mention)
- Guoying Zu, Md Nadim, Salil Reddy, Taimoor Ul Islam, Sarath Babu, Tianyi Zhang, Daji Qiao, Hongwei Zhang, Anish Arora, AraHaul: Multi-Modal Wireless X-Haul Living Lab for Long-Distance, High-Capacity Communications, IEEE Future Networks World Forum (FNWF), 2023
- Zhibo Meng, Hongwei Zhang, James Gross, Scheduling with Probabilistic Per-Packet Real-Time Guarantee for URLLC, ArXiv 2101.01768v7, 2023
Demos
- Real-Time Liquid Wireless Networking for Data-Intensive Applications at Farm Progress Show, August 2024
- Real-Time Liquid Wireless Networking for Data-Intensive Applications at ARA Public Launch, September 2023 [video]
Outreach / Engagement
The RT-LWN demo at the 2024 Farm Progress Show (pictured below) allowed us to engage with broad stakeholder communities ranging from farmers to local, state, and federal government as well as industries. Through the Nation’s Largest Outdoor Ag Show and a premiere international event in AgTech, the project team was able to engage with industry members and leaders from across the country and world, showcasing RT-LWN while gaining invaluable insights and feedback at the same time.
Project Team
- Iowa State University: Daji Qiao, Hongwei Zhang (Lead PI)
- International Computer Science Institute: Mike Luby
- Boston University: John W. Byers