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www.caida.org > publications : papers : 2019 : empirical_study_mobile_network_behavior
An Empirical Study of Mobile Network Behavior and Application Performance in the Wild
S. Zhang, W. Li, D. Wu, B. Jin, R. Chang, D. Gao, Y. Wang, and R. Mok, "An Empirical Study of Mobile Network Behavior and Application Performance in the Wild", in IEEE/ACM International Symposium on Quality of Service (IWQoS), Jun 2019.
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An Empirical Study of Mobile Network Behavior and Application Performance in the Wild

Shiwei Zhang3, 5
Weichao Li3, 5
Daoyuan Wu4
Bo Jin3, 5
Rocky K. C. Chang2
Debin Gao4
Yi Wang3, 5
Ricky K. P. Mok1
1

CAIDA, San Diego Supercomputer Center, University of California San Diego

2

Hong Kong Polytechnic University

3

Peng Cheng Laboratory, P.R. China

4

Singapore Management University

5

Southern University of Science and Technology, P.R. China

Monitoring mobile network performance is critical for optimizing the QoE of mobile apps. Until now, few studies have considered the actual network performance that mobile apps experience in a per-app or per-server granularity. In this paper, we analyze a two-year-long dataset collected by a crowdsourcing per-app measurement tool to gain new insights into mobile network behavior and application performance. We observe that only a small portion of WiFi networks can work in high-speed mode, and more than one-third of the observed ISPs still have not deployed 4G networks. For cellular networks, the DNS settings on smartphones can have a significant impact on mobile app network performance. Moreover, we notice that instant messaging (IM) and voice over IP (VoIP) services nowadays are not as performant as Web services, because the traffic using XMPP experiences longer latencies than HTTPS. We propose an automatic performance degradation detection and localization method for finding possible network problems in our huge, imbalanced and sparse dataset. Our evaluation and case studies show that our method is effective and the running time is acceptable.

Keywords: data, mobile, passive data analysis, QoE
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