Award Abstract # 2145813
CAREER: Argus: A Measurement-informed Learning Approach to Managing Multi-cloud Networks

NSF Org: CNS
Division Of Computer and Network Systems
Recipient: UNIVERSITY OF OREGON
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 2022 = $94,898.00
FY 2023 = $99,319.00

FY 2024 = $105,958.00

FY 2025 = $108,924.00
History of Investigator:
  • Ramakrishnan Durairajan (Principal Investigator)
    ram@cs.uoregon.edu
Recipient Sponsored Research Office: University of Oregon Eugene
1776 E 13TH AVE
EUGENE
OR  US  97403-1905
(541)346-5131
Sponsor Congressional District: 04
Primary Place of Performance: University of Oregon Eugene
OR  US  97403-5219
Primary Place of Performance
Congressional District:
04
Unique Entity Identifier (UEI): Z3FGN9MF92U2
Parent UEI: Z3FGN9MF92U2
NSF Program(s): Networking Technology and Syst
Primary Program Source: 01002223DB NSF RESEARCH & RELATED ACTIVIT
01002324DB NSF RESEARCH & RELATED ACTIVIT

01002425DB NSF RESEARCH & RELATED ACTIVIT

01002526DB NSF RESEARCH & RELATED ACTIVIT

01002627DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 1045, 7363
Program Element Code(s): 736300
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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Colton, Joseph and Durairajan, Ramakrishnan and Rejaie, Reza and Willinger, Walter "On the Impact of Submarine Cable Deployments on Multi-Cloud Network Latencies" , 2024 https://doi.org/10.1109/CloudNet62863.2024.10815788 Citation Details
Knofczynski, Jared and Durairajan, Ramakrishnan and Willinger, Walter "ARISE: A Multitask Weak Supervision Framework for Network Measurements" IEEE Journal on Selected Areas in Communications , v.40 , 2022 https://doi.org/10.1109/JSAC.2022.3180783 Citation Details

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