Quantifying Interference between Measurements on the RIPE Atlas Platform

Holterbach, Thomas; Pelsser, Cristel; Bush, Randy; Vanbever, Laurent

doi:10.1145/2815675.2815710

Cited by 32 publications

(15 citation statements)

References 13 publications

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“…Although past research has shown that v1 and v2 probes can be less reliable [13], in our experiments we observe only slight differences in our aggregated results when using these probes. As a trade-off between precision and coverage, we avoid using these probes when it is not needed ( §4) but we include them when surveying last-mile latency at large scale ( §3).…”

Section: From Traceroute To Last-mile Congestioncontrasting

confidence: 82%

Persistent Last-mile Congestion

Fontugne

Shah

Cho

2020

Proceedings of the ACM Internet Measurement Conference

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Last-mile is the centerpiece of broadband connectivity, as poor last-mile performance generally translates to poor quality of experience. In this work we investigate last-mile latency using traceroute data from RIPE Atlas probes located in 646 ASes and focus on recurrent performance degradation. We find that in normal times probes in only 10% ASes experience persistent last-mile congestion but we recorded 55% more congested ASes during the COVID-19 outbreak. Persistent last-mile congestion is not uncommon, it is usually seen in large eyeball networks and may span years. With the help of CDN access log data, we dissect results for major ISPs in Japan, the most severely affected country in our study, and ascertain bottlenecks in the shared legacy infrastructure.

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Section: From Traceroute To Last-mile Congestioncontrasting

confidence: 82%

Persistent Last-mile Congestion

Fontugne

Shah

Cho

2020

Proceedings of the ACM Internet Measurement Conference

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“…This is the basic insight behind the measurement of in-network buffering performed by Netalyzr [34] and other measurement platforms, and has been used more recently in the inference of congestion at network interconnects [35]. Load on the endpoint can also be visible in RTT measurements, as shown by Holterbach et al [36], who showed in a study of the load dependent accuracy of the Atlas platform that several milliseconds of RTT error could be induced and measured by varying the load on RIPE Atlas probes.…”

Section: Load Telemetrymentioning

confidence: 97%

Revisiting the Privacy Implications of Two-Way Internet Latency Data

Trammell

Kühlewind

2018

Passive and Active Measurement

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The Internet measurement community is increasingly sensitive to the privacy implications of both active and passive measurement. Research into the drawbacks of network data anonymization has led the community to investigate data sharing techniques, as well as to focus on active measurements and active measurement datasets. A key metric in these datasets is round-trip-time (RTT) as measured e.g. by ping or traceroute. This paper examines the assumption that the analysis of Internet RTT data is safe for open research by posing the question: what potentually-private inferences can be made about a remote target given periodic latency measurements from known vantage points under one's control? We explore the risks to end-user privacy both through a review of diverse literature touching on the subject as well as on the analysis of RTT data from fixed and mobile Internet measurement infrastruture. While we find that the common assumption of safety generally holds, we explore caveats and give recommendations for mitigation in those cases where it may not.

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“…• RIPE Atlas [19], [27] is a global network of probes that measure Internet connectivity and reachability, and is primarily deployed by home users to provide an understanding of the state of the commercial Internet (not R&E networks) in real time.…”

Section: Related Workmentioning

confidence: 99%

Testing the Feasibility of a Low-Cost Network Performance Measurement Infrastructure

Chevalier¹,

Schopf²,

Miller³

et al. 2016

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Abstract-Todays science collaborations depend on reliable, high performance networks, but monitoring the end-to-end performance of a network can be costly and difficult. The most accurate approaches involve using measurement equipment in many locations, which can be both expensive and difficult to manage due to immobile or complicated assets.The perfSONAR [11] framework facilitates network measurement making management of the tests more reasonable. Traditional deployments have used over-provisioned servers, which can be expensive to deploy and maintain. As scientific network uses proliferate, there is a desire to instrument more facets of a network to better understand trends.This work explores low cost alternatives to assist with network measurement. Benefits include the ability to deploy more resources quickly, and reduced capital and operating expenditures. We present candidate platforms and a testing scenario that evaluated the relative merits of four types of small form factor equipment to deliver accurate performance measurements.

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Quantifying Interference between Measurements on the RIPE Atlas Platform

Cited by 32 publications

References 13 publications

Persistent Last-mile Congestion

Persistent Last-mile Congestion

Revisiting the Privacy Implications of Two-Way Internet Latency Data

Testing the Feasibility of a Low-Cost Network Performance Measurement Infrastructure

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