Presentations 2015 IPv4 versus IPv6 – Who connects faster? (V. Bajpai, IFIP Networking 2015, Toulouse, May 2015) Measuring YouTube from Dual-Stacked Hosts (V. Bajpai, PAM 2015, New York, March 2015) Large MeAsurement Platform Protocol (V. Bajpai, IETF 91, Honolulu, November 2014) Measurement Research within the Python3 Ecosystem (S.J. Eravuchira, RIPE69, London, November 2014) 2014 Service Discovery in Resource Constrained Networks using Multicast DNS (A. Sehgal, EuCNC 2014, Bologna, June 2014) Identifying TCP Congestion Control Algorithms Used on the Internet
Vaibhav Bajpai presented a paper summarizing his PhD thesis at the IFIP/IEEE International Symposium on Integrated Network Management (IM 2017) and he received the best dissertation paper award.
We helped to organize a Dagstuhl seminar on Using Networks to Teach About Networks, which took place March 12–15, 2017. During the seminar, we discussed the different approaches to teach computer networking and how to best use of online resources to better educate students. For details, see the seminar report.
We presented our work on measuring webpage similarity delivered over IPv4 and IPv6 at the RIPE 72 plenary in Copenhagen. A recording of the talk can be found on Vimeo.
We discussed the usage of system tags for performing vantage point selection of dual-stacked probes. Our exploration reveals how with around 2K dual-stacked probes, RIPE Atlas provides the richest source of vantage points for IPv6 measurement studies. User tags on the other hand are based on a manual process which is largely dependent on proactive participation of probe hosts. We show that user tags tend to become stale over time. This work was presented at the MAT working group at RIPE 72 meeting in Copenhagen.
We helped organize a Dagstuhl seminar on Global Measurements: Practice and Experience from January 04–07, 2016. This was a followup of the seminar on Global Measurement Framework. The second seminar aimed at discussing the practical experience gained with building global measurement platforms. It brought together people who are actively involved in the design and maintenance of global measurement systems, who do research on the data delivered by global measurement systems, and who use data derived from global measurement systems in order to manage networks or services or as input for regulatory decisions.
Our research group is taking an active leadership role in the organization of some key scientific events this year: We are involved in the organization of the demo track of the IFIP/IEEE International Symposium on Integrated Management (IM 2015), which takes place in Ottawa (Canada) in May 2015. We co-chair the technical program committee of the 11th International Conference on Network and Service Management (CNSM 2015), which takes place in Barcelona (Spain) in October 2015.
In this talk, we present a set of tools that we find useful for measurement research and would like to share them with the larger RIPE community. Given the nature of the talk, we will make a live demo of running code snippets using the IPython notebook. A recording of our presentation can be found on Vimeo.
We have demonstrated an implementation of the LOWPAN-MIB at the Low-power Lossy Networks (LLN) plugfest, which took place on Sunday before the 90th IETF meeting. We showed how to access the counters via our Contiki SNMP implementation and Contiki's CoAP implementation. The plugfest was overall very interesting and very well organized. People involved in several interesting projects attended the plugfest and it was nice to get into personal contact. Further details can be found on the plugfest slides.
We gave a talk in which we share our experiences and lessons learned from using the RIPE Atlas platform for conducting measurement research. We describe how subtle rate limits can affect experiment design. We show how calibration of probes from hardware revision down to the firmware version is useful when analyzing measurement results. We describe the usefulness by showing how different hardware revisions affect measurement results. We show how per-hop aggregation mistakes during data analysis can have impacts on measurement results.