An empirical study of mobile network behavior and application performance in the wild

Zhang, Shiwei1; Li, Weichao1; Wu, Daoyuan2; Jin, Bo1; Gao, Debin2; Wang, Yi1; Chang, Rocky K. C.3; Mok, Ricky K. P.4

10.1145/3326285.3329039

2019

1548-615X

978-1-7281-6661-2

2019 International Symposium on Quality of Service, IWQoS 2019

1-10

24-25 June 2019

Phoenix, AZ, United states

Association for Computing Machinery, Inc

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 ofWiFi 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.
© 2019 Association for Computing Machinery.

Servers Wireless fidelity Smart phones Cellular networks Crowdsourcing IP networks Quality of experience

第一 ; 通讯

EI

National Natural Science Foundation of China[]

20192907215675

HTTP ; Internet telephony ; Mobile telecommunication systems ; Network performance ; Voice/data communication systems ; Web services ; Wireless networks

Radio Systems and Equipment:716.3 ; Computer Software, Data Handling and Applications:723

EV Compendex

1.Southern University of Science and Technology, Peng Cheng Laboratory, China
2.Singapore Management University, Singapore
3.Hong Kong Polytechnic University, Hong Kong
4.University of California, San Diego and CAIDA, United States

Zhang, Shiwei,Li, Weichao,Wu, Daoyuan,et al. An empirical study of mobile network behavior and application performance in the wild[C]:Association for Computing Machinery, Inc,2019:1-10.