[hops] lessons learned from using ripe atlas

"Bajpai, Vaibhav" <v.bajpai@jacobs-university.de> Thu, 06 August 2015 10:14 UTC

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From: "Bajpai, Vaibhav" <v.bajpai@jacobs-university.de>
To: "hops@ietf.org" <hops@ietf.org>
Thread-Topic: lessons learned from using ripe atlas
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Date: Thu, 6 Aug 2015 10:14:02 +0000
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Cc: "Bajpai, Vaibhav" <v.bajpai@jacobs-university.de>
Subject: [hops] lessons learned from using ripe atlas
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Dear hops,


>     We, as chairs, will start a Wiki (soon) to collect information about
>     measurement platforms as well as measurement tools (and take this as a
>     starting point). Let us as well as the group know if you have further
>     knowledge about this kind of overview papers or similar things by posting a
>     pointer on the list!

Perhaps one more that might interest folks:

As you know RIPE Atlas was initially designed to measure reachability and
connectivity of the Internet. With the deployment of 14K probes, there is
seen trend to use the platform for performance-based measurements
(such as comparing v4/v6 latency on the Internet).

Given, we have been in a position to have close collaboration (through
the LEONE project) with SamKnows (a dedicated performance-measurement
platform), we decided to share our experiences in using the RIPE Atlas
platform from this lens. This work recently got accepted to ACM CCR
July 2015 issue and came online (PDF link below) today. Thought folks
might find it interesting so sharing it along:

Lessons Learned from using the RIPE Atlas Platform for Measurement Research
Vaibhav Bajpai, Steffie Jacob Eravuchira, Jürgen Schönwälder
ACM Computer Communication Review (CCR),
July, 2015

We reflect upon our experience in using the RIPE Atlas platform for
measurement-based research. We show how in addition to credits, control checks
using rate limits are in place to ensure that the platform does not get
overloaded with measurements. We show how the Autonomous System (AS)-based
distribution of RIPE Atlas probes is heavily skewed which limits possibilities
of measurements sourced from a specific origin-AS. We discuss the significance
of probe calibration and how we leverage it to identify load issues in older
hardware versions (38.6% overall as of Sep 2014) of probes. We show how
performance measurement platforms (such as RIPE Atlas, SamKnows, BISmark and
Dasu) can benefit from each other by demonstrating two example use-cases. We
also open discussion on how RIPE Atlas deployment can be made more useful by
relaying more probe metadata information back to the scientific community and
by strategically deploying probes to reduce the inherent sampling bias
embedded in probe-based measurement platforms.

Paper: http://dx.doi.org/10.1145/2805789.2805796
Mirror: http://vaibhavbajpai.com/documents/papers/proceedings/ripeatlas-ccr-2015.pdf

Best, Vaibhav

Vaibhav Bajpai

Room 91, Research I
School of Engineering and Sciences
Jacobs University Bremen, Germany