
NSF Org: |
CNS Division Of Computer and Network Systems |
Recipient: |
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Initial Amendment Date: | February 15, 2022 |
Latest Amendment Date: | May 7, 2025 |
Award Number: | 2145813 |
Award Instrument: | Continuing Grant |
Program Manager: |
Deepankar Medhi
dmedhi@nsf.gov (703)292-2935 CNS Division Of Computer and Network Systems CSE Directorate for Computer and Information Science and Engineering |
Start Date: | June 1, 2022 |
End Date: | May 31, 2027 (Estimated) |
Total Intended Award Amount: | $529,090.00 |
Total Awarded Amount to Date: | $409,099.00 |
Funds Obligated to Date: |
FY 2023 = $99,319.00 FY 2024 = $105,958.00 FY 2025 = $108,924.00 |
History of Investigator: |
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Recipient Sponsored Research Office: |
1776 E 13TH AVE EUGENE OR US 97403-1905 (541)346-5131 |
Sponsor Congressional District: |
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Primary Place of Performance: |
OR US 97403-5219 |
Primary Place of
Performance Congressional District: |
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Unique Entity Identifier (UEI): |
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Parent UEI: |
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NSF Program(s): | Networking Technology and Syst |
Primary Program Source: |
01002324DB NSF RESEARCH & RELATED ACTIVIT 01002425DB NSF RESEARCH & RELATED ACTIVIT 01002526DB NSF RESEARCH & RELATED ACTIVIT 01002627DB NSF RESEARCH & RELATED ACTIVIT |
Program Reference Code(s): |
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Program Element Code(s): |
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Award Agency Code: | 4900 |
Fund Agency Code: | 4900 |
Assistance Listing Number(s): | 47.070 |
ABSTRACT
Multi-cloud networks are federations of private network infrastructures from the distinct cloud and third-party providers, and serve as increasingly vital underlays for a range of application domains such as genomics, healthcare, and high performance computing. This emerging connectivity paradigm poses significant management barriers to enterprises that seek to deploy overlays and applications due to providers' distinct operational practices, privacy concerns, egress costs, among others. This CAREER project will investigate a novel measurement-informed learning-based framework called Argus to significantly lower the management barriers faced by modern enterprises.
This project will focus on scientific inquiries in three synergistic thrusts to realize the Argus framework. First, it will design calibrated measurement tools and techniques, using which enterprises can gain visibility into the federated underlays. Second, adhering to the privacy concerns of providers, it will investigate learning-based modeling capabilities, using which enterprises can accurately infer, localize, and attribute performance bottlenecks to appropriate providers. Third, it will take a principled approach to design a management capability, using which enterprises can effectively and efficiently navigate egress costs and operational goals while avoiding inferred performance bottlenecks.
This project's goal is to lower multi-cloud management barriers, to enhance the operational productivity of enterprises, and to foster breakthroughs in the aforementioned domains and beyond. The research will be tightly integrated with education, emphasizing experiential learning. Activities include inviting underrepresented students from local community colleges to participate in a mini-research experience, organizing virtual summer schools on project-related topics, involving undergraduates in research, and developing a curriculum on multi-cloud networks.
Software artifacts, publications, and course materials resulting from this project will be made available at https://ix.cs.uoregon.edu/~ram/CAREER.html. The website will be actively maintained during the entire period of the project, and for at least one year past the ending of the project.
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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