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Award Abstract # 2321699
CC* Integration-Large: Husker-Net: Open Nebraska End-to-End Wireless Edge Networks

NSF Org: OAC
Office of Advanced Cyberinfrastructure (OAC)
Recipient: BOARD OF REGENTS OF THE UNIVERSITY OF NEBRASKA
Initial Amendment Date: July 24, 2023
Latest Amendment Date: October 25, 2024
Award Number: 2321699
Award Instrument: Standard Grant
Program Manager: Deepankar Medhi
dmedhi@nsf.gov
 (703)292-2935
OAC
 Office of Advanced Cyberinfrastructure (OAC)
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: October 1, 2023
End Date: September 30, 2025 (Estimated)
Total Intended Award Amount: $875,000.00
Total Awarded Amount to Date: $891,000.00
Funds Obligated to Date: FY 2023 = $875,000.00
FY 2024 = $16,000.00
History of Investigator:
  • Qiang Liu (Principal Investigator)
    qiang.liu@unl.edu
  • Mehmet Vuran (Co-Principal Investigator)
  • Matthew Long (Co-Principal Investigator)
  • Toolika Ghose (Former Co-Principal Investigator)
Recipient Sponsored Research Office: University of Nebraska-Lincoln
2200 VINE ST # 830861
LINCOLN
NE  US  68503-2427
(402)472-3171
Sponsor Congressional District: 01
Primary Place of Performance: University of Nebraska-Lincoln
262 Avery Hall
LINCOLN
NE  US  68588-0115
Primary Place of Performance
Congressional District:
01
Unique Entity Identifier (UEI): HTQ6K6NJFHA6
Parent UEI:
NSF Program(s): Special Projects - CNS,
CISE Research Resources
Primary Program Source: 01002324DB NSF RESEARCH & RELATED ACTIVIT
01002425DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 9150, 9251
Program Element Code(s): 171400, 289000
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

The lack of network and computing infrastructure in the Midwest have been enlarging the digital and economic gap between urban and rural America. University of Nebraska-Lincoln (UNL) is the primary research university in Nebraska (an EPSCoR state) and has a broad range of research activities in various locations across Nebraska, including precision agriculture, autonomous driving, and Internet of things. Existing wireless connectivity solutions, e.g., LoRaWAN, WLAN, and commercial cellular, cannot support diverse research projects in the field, in terms of coverage, throughput, flexibility, cost-efficiency, and performance assurance. This project outlines a novel open end-to-end cellular edge network (Husker-Net) by designing, deploying, and operating private 5G network over a light-licensed CBRS spectrum in multiple UNL campuses. Husker-Net is featured with ultra-low operating cost with open-source modules, flexible deployment with both wired and wireless backhaul (e.g., LEO in mid of Nebraska), and zero-touch management with automatic model-free algorithms.

To achieve Husker-Net, this project will 1) design a new convergent RAN-Edge-CN architecture with open-source RAN, Edge, and CN modules, 2) design new cost-efficient RAN and CN virtualization techniques with isolated virtualized resources, and 3) design a new model-free resource allocation algorithm to support co-existed research projects via end-to-end network slicing with assured performances. The derived solutions and real-world operation datasets in Husker-Net will be open sourced to promote the openness of cellular networks and broader access by the research community. Husker-Net will support more than 10 research projects across multiple departments at UNL with the assistance of ITS, and continue exploring more projects along with the Office of Research & Economic Development (ORED). Based on Husker-Net, a campus-wide education experimental platform will be developed for serving a series of undergraduate- and graduate-level courses at UNL. Husker-Net will serve as the exemplary platform for the evaluation and testing of private networks for the Midwest states.

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.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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Zhang, Yuru and Zhao, Ming and Liu, Qiang and Choi, Nakjung "Learn to Augment Network Simulators Towards Digital Network Twins" , 2024 https://doi.org/10.1109/INFOCOMWKSHPS61880.2024.10620840 Citation Details

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