MopEye: Monitoring Per-app Network Performance with Zero Measurement Traffic

• Main Authors: WU, Daoyuan, LI, Weichao, CHANG, Rocky K. C., GAO, Debin
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2015
• Subjects: Measurement Tool; Mobile Network Performance; Computer Sciences; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/2920; https://ink.library.smu.edu.sg/context/sis_research/article/3920/viewcontent/CoNext_15_Student_Mopeye.pdf
• Institution: Singapore Management University

Mobile network performance measurement is important for understanding mobile user experience, problem diagnosis, and service comparison. A number of crowdsourcing measurement apps (e.g., MobiPerf and Netalyzr) have been embarked for the last few years. Unlike existing apps that use active measurement methods, we employ a novel passive-active approach to continuously monitor per-app network performance on unrooted smartphones without injecting additional network traffic. By leveraging the VpnService API on Android, MopEye, our measurement app, intercepts all network traffic and then relays them to their destinations using socket APIs. Therefore, not only MopEye can measure the round-trip time accurately, it can do so without injecting additional traffic. As a result, the bandwidth cost (and monetary cost of data usage) for conducting such a measurement is eliminated, and the measurement can be conducted free of user intervention. Our evaluation shows that MopEye’s RTT measurement is very close to result of tcpdump and is more accurate than MobiPerf. We have used MopEye to conduct a one-week measurement revealing multiple interesting findings on different apps’ performance.