att_abstract={{Understanding Internet traffic dynamics in large cellular networks
is important for network design, troubleshooting, performance
evaluation, and optimization. In this paper, we
present the results from our study, which is based upon a
week-long aggregated flow level mobile device traffic data
collected from a major cellular operator�s core network. In
this study, we measured the spatial and temporal dynamics
of Internet traffic to characterize the behavior of mobile devices
used to access cellular networks. We distinguish our
study from other related work by conducting the measurement
at a larger scale and exploring device traffic patterns
along two new dimensions � device types and applications
carried by network traffic. Based on the findings of our measurement
analysis, we propose a Zipf-like model to capture
the distribution and a Markov model to capture the volume
dynamics of aggregate Internet traffic. We further customize
our models for different device types using an unsupervised
clustering algorithm to improve prediction accuracy.}},
	att_authors={lj1412, jw2129},
	att_copyright_notice={{(c) ACM, 2011. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM SIGMetrics 2011{{, 2011-06-07}}}},
	author={Lusheng Ji and Jia Wang and M. Zubair Shafiq and Alex X. Liu},
	institution={{ACM SIGMETRICS 2011}},
	title={{Characterizing and Modeling Internet Traffic Dynamics of Cellular Devices}},