MopEye: Opportunistic Monitoring of Per-app Mobile Network Performance
- Homepage: https://mopeye.github.io/
- App link: https://play.google.com/store/apps/details?id=com.mopeye (will re-upload soon)
- Paper link: https://www.usenix.org/conference/atc17/technical-sessions/presentation/wu
MopEye was published in USENIX ATC'17, and the following is the bib information:
@INPROCEEDINGS{MopEye17,
AUTHOR = {Daoyuan Wu and Rocky K. C. Chang and Weichao Li and Eric K. T. Cheng and Debin Gao},
TITLE = {{MopEye}: Opportunistic Monitoring of Per-app Mobile Network Performance},
BOOKTITLE = {Proc. USENIX Annual Technical Conference (ATC)},
PAGES = {445--457},
YEAR = {2017},
}
We are periodically releasing the datasets of MopEye for benefiting networking research.
We request that applicants:
- Do not redistribute the dataset without our consent;
- Do not make a commercial usage of the dataset;
- Get a faculty, or someone in a permanent position, to agree and commit to the policy.
To access the following database files, please send an application email (with the corresponding email subject) to dywu(at)ie.cuhk.edu.hk stating the name of your research institution and the name of the person requesting access. Make sure to send your application from your university (or research institution) email account.
- Peroid: From 16 May 2016 to 3 January 2017 approximately;
- Five million measurements from 6,266 Android apps on 2,351 smartphones;
- Used in our initial ATC'17 paper: https://daoyuan14.github.io/papers/ATC17_MopEye.pdf;
- DB file: https://www.dropbox.com/s/4d5mw9yqle6ka29/170103MopEyeDataset.db?dl=0;
- Email subject: "Requesting the 170103 MopEye dataset from XXX", where XXX is the abbreviation of your institution.
- Applicants' institution and potential research outputs:
- Shanghai Jiao Tong University, China [INFOCOM'19]
- Southern University of Science and Technology, China [IWQoS'19]
- Nanjing University, China
- Harbin Engineering University, China
- K. N. Toosi University of Technology, Iran
- Xidian University, China
- You can access the dataset db file using the SQLite Browser.
- Then make SQL query according to your need.
For the meaning of database structure, please refer to Table 1 in https://daoyuan14.github.io/papers/IWQoS19_MopEyeDatasetAnalysis.pdf