Mosharaf Chowdhury and Rachit Agarwal and Vyas Sekar and Ion Stoica

EECS Department, University of California, Berkeley

Technical Report No. UCB/EECS-2014-172

October 11, 2014

http://www2.eecs.berkeley.edu/Pubs/TechRpts/2014/EECS-2014-172.pdf

We present a retrospective and longitudinal study of Internet latency and path stability using three large-scale traceroute datasets collected over several years: Ark and iPlane from 2008 to 2013 and a proprietary CDN’s traceroute dataset spanning 2012 and 2013. Using these different “lenses”, we revisit classical properties of Internet paths such as end-to- end latency, stability, and of routing graph structure. Iterative data analysis at this scale is challenging given the idiosyncrasies of different collection tools, measurement noise, and the diverse analysis we desire. To this end, we leverage re- cent big-data techniques to develop a scalable data analysis toolkit, Hummus, that enables rapid and iterative analysis on large traceroute measurement datasets. Our key findings are: (1) overall latency seems to be decreasing; (2) some geographical regions still have poor latency; (3) route stability (prevalence and persistence) is increasing; and (4) we ob- serve a mixture of effects in the routing graph structure with high-degree ASes rapidly increasing in degree and lower- degree ASes forming denser “communities”.

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BibTeX citation:

@techreport{Chowdhury:EECS-2014-172,
    Author= {Chowdhury, Mosharaf and Agarwal, Rachit and Sekar, Vyas and Stoica, Ion},
    Title= {A Longitudinal and Cross-Dataset Study of Internet Latency and Path Stability},
    Year= {2014},
    Month= {Oct},
    Url= {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2014/EECS-2014-172.html},
    Number= {UCB/EECS-2014-172},
    Abstract= {We present a retrospective and longitudinal study of Internet latency and path stability using three large-scale traceroute datasets collected over several years: Ark and iPlane from 2008 to 2013 and a proprietary CDN’s traceroute dataset spanning 2012 and 2013. Using these different “lenses”, we revisit classical properties of Internet paths such as end-to- end latency, stability, and of routing graph structure. Iterative data analysis at this scale is challenging given the idiosyncrasies of different collection tools, measurement noise, and the diverse analysis we desire. To this end, we leverage re- cent big-data techniques to develop a scalable data analysis toolkit, Hummus, that enables rapid and iterative analysis on large traceroute measurement datasets. Our key findings are: (1) overall latency seems to be decreasing; (2) some geographical regions still have poor latency; (3) route stability (prevalence and persistence) is increasing; and (4) we ob- serve a mixture of effects in the routing graph structure with high-degree ASes rapidly increasing in degree and lower- degree ASes forming denser “communities”.},
}

EndNote citation:

%0 Report
%A Chowdhury, Mosharaf 
%A Agarwal, Rachit 
%A Sekar, Vyas 
%A Stoica, Ion 
%T A Longitudinal and Cross-Dataset Study of Internet Latency and Path Stability
%I EECS Department, University of California, Berkeley
%D 2014
%8 October 11
%@ UCB/EECS-2014-172
%U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2014/EECS-2014-172.html
%F Chowdhury:EECS-2014-172