Lessons Learned From Using the RIPE Atlas Platform for Measurement Research

Bajpai, Vaibhav; Eravuchira, Steffie Jacob; Schönwälder, Jürgen

doi:10.1145/2805789.2805796

Cited by 63 publications

(36 citation statements)

References 5 publications

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“…Countries with fewer probes tend to show worse latency than those we show, but we wish to exclude outliers. We do not know the local network of each VP, and it would be unfeasible to treat each probe individually, so we do not account for poor "last-mile" connections [4]. Figure 12 shows the latency for all the countries with at least 5 probes.…”

Section: Who Sees Poor Latency?mentioning

confidence: 99%

Anycast Latency: How Many Sites Are Enough?

Schmidt

Heidemann²,

Kuipers

2017

Lecture Notes in Computer Science

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Anycast is widely used today to provide important services including naming and content, with DNS and Content Delivery Networks (CDNs). An anycast service uses multiple sites to provide high availability, capacity and redundancy, with BGP routing associating users to nearby anycast sites. Routing defines the catchment of the users that each site serves. Although prior work has studied how users associate with anycast services informally, in this paper we examine the key question how many anycast sites are needed to provide good latency, and the worst case latencies that specific deployments see. To answer this question, we must first define the optimal performance that is possible, then explore how routing, specific anycast policies, and site location affect performance. We develop a new method capable of determining optimal performance and use it to study four real-world anycast services operated by different organizations: C-, F-, K-, and L-Root, each part of the Root DNS service. We measure their performance from more than 7,900 worldwide vantage points (VPs) in RIPE Atlas. (Given the VPs uneven geographic distribution, we evaluate and control for potential bias.) Key results of our study are to show that a few sites can provide performance nearly as good as many, and that geographic location and good connectivity have a far stronger effect on latency than having many nodes. We show how often users see the closest anycast site, and how strongly routing policy affects site selection.

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Section: Who Sees Poor Latency?mentioning

confidence: 99%

Anycast Latency: How Many Sites Are Enough?

Schmidt

Heidemann²,

Kuipers

2017

Lecture Notes in Computer Science

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“…In [BES15], Bajpai et al showed that RTTs from v1 and v2 probes to the first hop router are consistently higher than for v3 probes. They do not however study the relation between the measured delays and the load of the probes.…”

Section: Lanmentioning

confidence: 99%

Quantifying Interference between Measurements on the RIPE Atlas Platform

Holterbach

Pelsser²,

Bush³

et al. 2015

Proceedings of the 2015 Internet Measurement Conference

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Public measurement platforms composed of low-end hardware devices such as RIPE Atlas have gained significant traction in the research community. Such platforms are indeed particularly interesting as they provide Internet-wide measurement capabilities together with an ever growing set of measurement tools. To be scalable though, they allow for concurrent measurements between users. This paper answers a fundamental question for any platform user : Do measurements launched by others impact my results ? If so, what can I do about it ?We measured the impact of multiple users running experiments in parallel on the RIPE Atlas platform. We found that overlapping measurements do interfere with each other. We found that increasing hardware CPU greatly helped in limiting interference on the measured delays.

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“…is makes it impossible for a reviewer to check for reproducibility of a submi ed work because the authors cannot reveal or may even have to obfuscate artifacts (see [1] for a formal de nition) at review time to allow double-blinding reviewing. Furthermore, datasets cannot be properly understood and appreciated without the metadata [3] that describes them which o en tends to break anonymity. e time invested in obfuscating the paper for a double-blinded submission can instead be used to prepare artifacts for reproducibility and to improve science.…”

Section: Double-blind Review Requires Obfuscationmentioning

confidence: 99%