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.