| NSF Org: |
CNS Division Of Computer and Network Systems |
| Recipient: |
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| Initial Amendment Date: | April 27, 2020 |
| Latest Amendment Date: | April 27, 2020 |
| Award Number: | 2028506 |
| Award Instrument: | Standard 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: | May 1, 2020 |
| End Date: | October 31, 2020 (Estimated) |
| Total Intended Award Amount: | $137,578.00 |
| Total Awarded Amount to Date: | $137,578.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
9500 GILMAN DR LA JOLLA CA US 92093-0021 (858)534-4896 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
9500 Gilman Drive La Jolla CA US 92093-0934 |
| 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): | COVID-19 Research |
| Primary Program Source: |
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| 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
In the crisis of the CoVID-19 pandemic, the Internet is facing unprecedented surges of traffic induced by the use of cloud-based telecommuting and remote education tools for real-time video meetings and online classes. However, existing network throughput measurement (speed test) platforms are often not representative of the performance of cloud-based applications due to the location of test servers. Measuring the performance of interconnections between cloud platforms and Internet Service Providers (cloud-ISP links) is a critical missing piece to understanding user-experienced performance of cloud-based videoconferencing applications.
This project will design and deploy novel experiments to measure network congestion of cloud-ISP links, tracking evolution of performance degradations during mandatory sheltering-in-place orders, and as large segments of the U.S. work force transition back to their workplaces. This scientific measurement project will tackle three challenges: 1) strategic selection of test servers within residential access and transit ISPs, based on topology measurements and analytics, 2) scientific characterization of the algorithms and behavior of speed tests, and 3) correct interpretation measurement results. The experiments will leverage speed test servers deployed by various commercial platforms (e.g., Ookla) as vantage points to conduct throughput measurements from cloud platforms hosting high-bandwidth applications. Operationalizing this experiment will provide longitudinal data to analyze performance degradation of cloud-ISP interconnections.
This research will enable studying the performance and reliability of critical Internet infrastructures in the U.S. during this pandemic, by collecting and sharing data that sheds light on the quality of experience of cloud-based telework applications. Visualized data will be generated to provide longitudinal views of network performance, and identify performance degradations at fine granularity, geographically and topologically. The resulting tools and methods will help guide future infrastructure improvements, and advance the ability to monitor an increasing critical communications ecosystem.
Detail information and the data of this project is available at https://webspeedtest.caida.org.
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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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
During the crisis of the COVID-19 pandemic, the Internet is facing unprecedented surges of traffic induced by the use of cloud-based telecommuting and remote education tools for real-time videoconferencing and online classes. Measuring the performance of paths that connect cloud platforms to access ISPs is important to understanding the performance users experience when using these tools.
We designed and implemented the Cloud-based Applications Speed measurement Platform (CLASP), which leverages globally distributed speed test servers to perform network throughput tests from virtual machines in three major cloud platforms to various networks hosting these servers. We developed a topology-aware approach to select a representative set of servers in different types of networks. We also implemented a measurement toolkit that can instrument the launch and data collection for the web-based speed tests. Our experiments illustrated that our toolkit induces negligible system overhead to throughput measurement. The collected cross-layer metadata can support analysis of the accuracy of speed tests in cloud environments.
In our 5-month measurement campaign, we performed hourly throughput measurements using over 1,500 speed test servers from three major cloud platforms. We found evidence of congestion on the network paths to/from access ISPs in all three cloud platforms, particularly during peak hours, i.e., those that coincide with primetime video streaming hours. In our macroscopic analysis, we observed downward trends in throughput to large access networks and educational networks, i.e., evidence of congestion, as the country reopened and increased adoption of remote learning.
Last Modified: 11/23/2020
Modified by: Ka Pui Mok
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