Award Abstract # 2201536
CC* Integration-Small: A Software-Defined Edge Infrastructure Testbed for Full-stack Data-Driven Wireless Network Applications

NSF Org: OAC
Office of Advanced Cyberinfrastructure (OAC)
Recipient: SAINT LOUIS UNIVERSITY
Initial Amendment Date: May 3, 2022
Latest Amendment Date: July 27, 2023
Award Number: 2201536
Award Instrument: Standard Grant
Program Manager: Deepankar Medhi
dmedhi@nsf.gov
�(703)292-2935
OAC
�Office of Advanced Cyberinfrastructure (OAC)
CSE
�Direct For Computer & Info Scie & Enginr
Start Date: July 1, 2022
End Date: June 30, 2025�(Estimated)
Total Intended Award Amount: $500,000.00
Total Awarded Amount to Date: $516,000.00
Funds Obligated to Date: FY 2022 = $500,000.00
FY 2023 = $16,000.00
History of Investigator:
  • Flavio Esposito (Principal Investigator)
    flavio.esposito@slu.edu
  • Francesco Restuccia (Co-Principal Investigator)
Recipient Sponsored Research Office: Saint Louis University
221 N GRAND BLVD
SAINT LOUIS
MO �US �63103-2006
(314)977-3925
Sponsor Congressional District: 01
Primary Place of Performance: Saint Louis University
MO �US �63103-2006
Primary Place of Performance
Congressional District:
01
Unique Entity Identifier (UEI): JNBLLTBTLLD8
Parent UEI: JNBLLTBTLLD8
NSF Program(s): Special Projects - CNS,
CISE Research Resources
Primary Program Source: 01002223DB�NSF RESEARCH & RELATED ACTIVIT
01002324DB�NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 9251
Program Element Code(s): 171400, 289000
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

Interdisciplinary research advances often require devices to collect, process, and transfer large scientific datasets over high bandwidth links. The overarching goal of this project is to build a wireless virtual network testbed at Saint Louis University, in collaboration with Northeastern University, to evaluate network management solutions that integrate the use of machine learning and artificial intelligence with programmable radios and programmable network switches. To evaluate the proposed innovation in computer networking, the cyberinfrastructure will be used to prototype network protocols and systems in support of a few interdisciplinary initiatives on campus.

In particular, this project's contributions will be developed around the integration of learning techniques with network mechanisms such as medium access control, routing, and transport services. First, the team will explore the design and implementation of effective transport and routing protocols that integrate the network stack at different scopes using recent advances in reinforcement learning. Second, novel network architectures will be proposed integrating edge network mechanisms with federated and split learning techniques. Third, cross-layer distributed learning protocols will be designed to create self-adaptive wireless networks. Such solutions will be tested on campus and on other network testbeds.

By combining synergies from the fields of data science and network virtualization protocols and architectures, this work will lay the foundation for further research in adaptive resource management for (wireless) edge computing applications that can improve the quality of life in our society. This project's results will be valuable for other fields interested in real-time prediction, such as robotics, medicine, anthropology, and finance. The research in this project will be impactful also thanks to the planned industry and international collaborations. Students from underrepresented groups will be involved with research activities and hackathon events on campuses in Missouri and Maine.

The project will have a web presence at: https://cs.slu.edu/testbed/. Such website will be maintained by the Computer Science Department at Saint Louis University, and will be active at least 5 years beyond the end date of this project. The website will contain links to datasets collected with the testbed, technical reports, scientific publications, and code repositories developed by students and collaborators.

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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Galantino, S and Pinto, A and Esposito, F and Manzalini, A and Risso, F "Balancing Energy Efficiency and Infrastructure Knowledge in Cloud-to-Edge Task Distribution Systems" Proceedings of ACM EuroSys 1st International Workshop on MetaOS for the Cloud-Edge-IoT Continuum (MECC 2024). , 2024 Citation Details
Angi, Antonino and Sacco, Alessio and Esposito, Flavio and Marchetto, Guido and Clemm, Alexander "Howdah: Load Profiling via In-Band Flow Classification and P4" , 2022 https://doi.org/10.23919/CNSM55787.2022.9964510 Citation Details
Ahmed, Nurzaman and Esposito, Flavio and Okafor, Okwudilichukwu and Shakoor, Nadia "SoftFarmNet: Reconfigurable Wi-Fi HaLow Networks for Precision Agriculture" , 2023 https://doi.org/10.1109/CLOUDNET59005.2023.10490078 Citation Details
Rifat, Shahriar and Ashdown, Jonathan and Turck, Kurt and Restuccia, Francesco "Zero-Shot Dynamic Neural Network Adaptation in Tactical Wireless Systems" , 2023 https://doi.org/10.1109/MILCOM58377.2023.10356318 Citation Details
Sacco, Alessio and Angi, Antonino and Marchetto, Guido and Esposito, Flavio "P4FL: An Architecture for Federating Learning With In-Network Processing" IEEE Access , v.11 , 2023 https://doi.org/10.1109/ACCESS.2023.3318109 Citation Details
Bhavanasi, Sai Shreyas and Pappone, Lorenzo and Esposito, Flavio "Dealing with Changes: Resilient Routing via Graph Neural Networks and Multi-Agent Deep Reinforcement Learning" IEEE Transactions on Network and Service Management , 2023 https://doi.org/10.1109/TNSM.2023.3287936 Citation Details
Pinto, Andrea and Santaromita, Giuseppe and Fiandrino, Claudio and Giustiniano, Domenico and Esposito, Flavio "Characterizing Location Management Function Performance in 5G Core Networks" 2022 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN) , 2022 https://doi.org/10.1109/NFV-SDN56302.2022.9974927 Citation Details
Bhavanasi, Sai Shreyas and Pappone, Lorenzo and Esposito, Flavio "Routing with Graph Convolutional Networks and Multi-Agent Deep Reinforcement Learning" 2022 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN) , 2022 https://doi.org/10.1109/NFV-SDN56302.2022.9974607 Citation Details
Angi, Antonino and Sacco, Alessio and Esposito, Flavio and Marchetto, Guido and Clemm, Alexander "Load Profiling via In-Band Flow Classification and P4 With Howdah" IEEE Transactions on Network and Service Management , 2023 https://doi.org/10.1109/TNSM.2023.3299729 Citation Details

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