Internship proposal 2015/2016
Topic: End-user Quality of Experience (QoE) Monitoring with Mobile Devices Duration: 4 to 6 months
Hosting team: Muse, Inria Paris-Rocquencourt (https://team.inria.fr/muse/) Contact: [email protected]
Mentor:
Renata Teixeira, Senior Researcher, Inria (head of Muse team) Anna-Kaisa Pietilainen, Researcher, Inria
Keywords: Internet measurements, network traffic, QoE, data analysis Description:
As our lives become more dependent on Internet connectivity, it is easy to understand people’s frustration when their Internet experience is poor. Network disruptions can adversely impact web browsing, cause video/audio interruptions, or render web sites unreachable or unusable. The goal of our research is to build techniques and tools to prevent performance degradations that affect users’ online experience. For this purpose, we need performance data from end-users’ computers and mobile devices. In contrast to many previous works, we are not only interested in raw performance metrics such as bandwidth or network delays (often called Quality of Service, QoS), but in addition, we try to measure the user experience (aka Quality of Experience, QoE) using techniques from Human Computer Interaction domain. In particular, we use experience sampling method (ESM) that basically consists of asking for user feedback at regular times with a short questionnaire.
The goal of this internship is to develop such a data collection tool for Android devices (mobile phones and tablets). The tool will collect network traffic (in pcap format), system performance data (cpu, memory and disk use; running applications;
foreground application; I/O, e.g. microphone, speaker etc. use; network configuration and performance) together with feedback from the user on his experience with the network/system performance. In our prior work, we have built similar tool for Linux and OS X (called Hostview [1]), and more recently, a completely updated version for Windows PCs [2]. The Android tool will leverage the design ideas, source code (if possible) and other lessons learned from building these tools.
Similarly, the tool will integrate with our existing data collection backend, so most development effort will be on the client side. As the tool is collecting potentially large amounts of data on a possibly resource limited mobile platform, the performance of the tool itself is an important challenge to tackle during the internship.
We hope to deploy the tool during the internship in small test group (colleagues from the group and the lab), and time permitting, in a larger-scale study together with the new Windows version of Hostview. Finally, if we have time and depending on the interests of the student, the project can conclude with an initial data analysis of typical QoE problems on mobile devices and how they correlate with raw performance metrics observed by the tool.
The student should develop engineering and scientific skills on mobile devices application development, computer system performance and end-user QoE measurements; data analysis; as well as scientific writing and presentation. If the student is interested, there is a possibility of staying for the doctoral studies after the internship.
Desirable skills:
- Comfortable communicating in English
- Good knowledge of Java programming, Android experience is a plus - Good knowledge of computer networks and protocols (TCP/IP) - Knowledge of web technologies (HTML, CSS, Javascript) - Knowledge of computer systems performance measurement - Knowledge of data analysis techniques
References:
[1] D. Joumblatt, R. Teixeira, J. Chandrashekar, N. Taft, "HostView: Annotating end-host performance measurements with user feedback", ACM SIGMETRICS Performance Evaluation Review, 38(3), 2010.
[2] http://muse.inria.fr/hostview
