WiFi, LTE, or Both? Measuring Multi-Homed Wireless Internet Performance

Over the past two or three years, wireless cellular networks have become faster than before, most notably due to the deployment of LTE, HSPA+, and other similar networks. LTE throughputs can reach many megabits per second and can even rival WiFi throughputs in some locations. This paper addresses a...

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Bibliographic Details
Main Authors: Deng, Shuo (Contributor), Balakrishnan, Hari (Contributor), Netravali, Ravi Arun (Contributor), Sivaraman Kaushalram, Anirudh (Contributor)
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor)
Format: Article
Language:English
Published: Association for Computing Machinery (ACM), 2015-11-04T17:35:09Z.
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Summary:Over the past two or three years, wireless cellular networks have become faster than before, most notably due to the deployment of LTE, HSPA+, and other similar networks. LTE throughputs can reach many megabits per second and can even rival WiFi throughputs in some locations. This paper addresses a fundamental question confronting transport and application-layer protocol designers: which network should an application use? WiFi, LTE, or Multi-Path TCP (MPTCP) running over both? We compare LTE and WiFi for transfers of different sizes along both directions (i.e. the uplink and the downlink) using a crowd-sourced mobile application run by 750 users over 180 days in 16 different countries. We find that LTE outperforms WiFi 40\% of the time, which is a higher fraction than one might expect at first sight. We measure flow-level MPTCP performance and compare it with the performance of TCP running over exclusively WiFi or LTE in 20 different locations across 7 cities in the United States. For short flows, we find that MPTCP performs worse than regular TCP running over the faster link; further, selecting the correct network for the primary subflow in MPTCP is critical in achieving good performance. For long flows, however, selecting the proper MPTCP congestion control algorithm is equally important. To complement our flow-level analysis, we analyze the traffic patterns of several mobile apps, finding that apps can be categorized as "short-flow dominated" or "long-flow dominated". We then record and replay these patterns over emulated WiFi and LTE links. We find that application performance has a similar dependence on the choice of networks as flow-level performance: an application dominated by short flows sees little gain from MPTCP, while an application with longer flows can benefit much more from MPTCP --- if the application can pick the right network for the primary subflow and the right choice of MPTCP congestion control.
National Science Foundation (U.S.) (Grant 1407470)
National Science Foundation (U.S.) (Grant 1161964)