Cloud benchmarks
This page contains the software and data presented in:
- Preliminary work: "Benchmarking Personal Cloud Storage" by Idilio Drago, Enrico Bocchi, Marco Mellia, Herman Slatman and Aiko Pras. In Proceedings of the 13th ACM Internet Measurement Conference. IMC 2013.
- Extended version: "Personal Cloud Storage Benchmarks and Comparison" by Enrico Bocchi, Idilio Drago, Marco Mellia. In IEEE Transactions on Cloud Computing.
More results of our work on personal cloud storage can be found on this page and on this page.
The slides of the presentation can be downloaded from here.
Contents
Benchmarks Scripts
The scripts are written in python. See the README for instructions on how to execute the benchmarks
Traces
Some traffic traces that generated the results in the IMC paper can be downloaded from these links:
| Provider | File Size |
|---|---|
| Amazon Cloud Drive | 197M |
| Dropbox | 88M |
| Google Drive | 70M |
| Microsoft SkyDrive | 69M |
| LaCie Wuala | 63M |
These traces produce the results in Figure 7 of the paper. More details about this dataset can also be obtained in Chapter 5 of:
- Drago, I. (2013) "Understanding and Monitoring Cloud Services". PhD thesis, University of Twente. CTIT Ph.D. thesis Series No. 13-279. ISBN 978-90-365-3577-9.
Traffic Identification Example
The identification of the cloud storage traffic in the testbed can be done using the FQDNs that cloud storage clients use to contact to servers. This can be achieved, for example, by means of the methodology implemented in Tstat DN-Hunter. Here we post a list of FQDNs used by three popular providers as an example.
Acceptable Use Policy
- When writing a paper using software or data from this page, please cite:
@inproceedings{drago2013_imc,
author = {Idilio Drago and Enrico Bocchi and Marco Mellia and Herman Slatman and Aiko Pras},
title = {Benchmarking Personal Cloud Storage},
booktitle = {Proceedings of the 13th ACM Internet Measurement Conference},
series = {IMC'13},
pages = {205--212},
year = {2013}
}
Acknowledgments
This work was partly funded by the Network of Excellence project Flamingo (ICT-318488) and the EU-IP project mPlane (n-318627). Both projects are supported by the European Commission under its Seventh Framework Programme.
