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Inside Dropbox: Understanding Personal Cloud Storage Services

TitleInside Dropbox: Understanding Personal Cloud Storage Services
Publication TypeConference Paper
Year of Publication2012
AuthorsDrago, I., M. Mellia, M. M. Munafo', A. Sperotto, R. Sadre, and A. Pras
Conference NameInternet Measurement Conference - IMC
Date Published11/2012
PublisherACM
Conference LocationBoston, MA
KeywordsDropbox, passive measurement
Abstract

Personal cloud storage services are gaining popularity. With a rush of providers to enter the market and an increasing of- fer of cheap storage space, it is to be expected that cloud storage will soon generate a high amount of Internet traffic. Very little is known about the architecture and the perfor- mance of such systems, and the workload they have to face. This understanding is essential for designing efficient cloud storage systems and predicting their impact on the network.

This paper presents a characterization of Dropbox, the leading solution in personal cloud storage in our datasets. By means of passive measurements, we analyze data from four vantage points in Europe, collected during 42 consecu- tive days. Our contributions are threefold: Firstly, we are the first to study Dropbox, which we show to be the most widely-used cloud storage system, already accounting for a volume equivalent to around one third of the YouTube traffic at campus networks on some days. Secondly, we character- ize the workload users in different environments generate to the system, highlighting how this reflects on network traf- fic. Lastly, our results show possible performance bottle- necks caused by both the current system architecture and the storage protocol. This is exacerbated for users connected far from storage data-centers.

All measurements used in our analyses are publicly avail- able in anonymized form at the SimpleWeb trace repository: http://traces.simpleweb.org/dropbox/ 

URLhttp://dl.acm.org/citation.cfm?id=2398776.2398827&coll=DL&dl=GUIDE&CFID=225051145&CFTOKEN=42401286
DOI10.1145/2398776.2398827
Citation KeyDra2012
Project year: 
First year
WP(s) associated with the paper: 
WP4 - mPlane Supervisor: Iterative and Adaptive Analysis
WP6 - Demonstration
Partner(s) associated with the paper's author(s): 
Politecnico di Torino
Is this an OFFICIALLY supported mPlane paper?: 
Yes
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