PROTEUS: Network Performance Forecast for Real-Time, Interactive Mobile Applications

Qiang Xu, Sanjeev Mehrotra, Z. Morley Mao, and Jin Li


Real-time communication (RTC) applications such as VoIP,

video conferencing, and online gaming are

ourishing. To

adapt and deliver good performance, these applications require

accurate estimations of short-term network performance

metrics, e.g., loss rate, one-way delay, and throughput. However,

the wide variation in mobile cellular network performance

makes running RTC applications on these networks

problematic. To address this issue, various performance

adaptation techniques have been proposed, but one common

problem of such techniques is that they only adjust application

behavior reactively after performance degradation is

visible. Thus, proactive adaptation based on accurate shortterm,

fine-grained network performance prediction can be a

preferred alternative that benefits RTC applications.

In this study, we show that forecasting the short-term performance

in cellular networks is possible in part due to the

channel estimation scheme on the device and the radio resource

scheduling algorithm at the base station. We develop

a system interface called PROTEUS, which passively collects

current network performance, such as throughput, loss, and

one-way delay, and then uses regression trees to forecast future

network performance. PROTEUS successfully predicts

the occurrence of packet loss within a 0.5s time window for

98% of the time windows and the occurrence of long one-way

delay for 97% of the time windows. We also demonstrate

how PROTEUS can be integrated with RTC applications to

significantly improve the perceptual quality. In particular,

we increase the peak signal-to-noise ratio of a video conferencing

application by up to 15dB and reduce the perceptual

delay in a gaming application by up to 4s.


Publication typeProceedings
Published inMobiSys 2013
PublisherACM International Conference in Mobile Systems, Applications, and Services (MobiSys)
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