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Completed STANDARD GRANT National Science Foundation (US)

Collaborative Research: CNS Core: Medium: Real-Time Liquid Wireless Networking for Data-Intensive Rural Applications

$1.5M USD

Funder National Science Foundation (US)
Recipient Organization International Computer Science Institute
Country United States
Start Date Oct 01, 2022
End Date Sep 30, 2025
Duration 1,095 days
Number of Grantees 1
Roles Principal Investigator
Data Source National Science Foundation (US)
Grant ID 2212574
Grant Description

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 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.

All Grantees

International Computer Science Institute

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