att_abstract={{3G cellular data networks have recently witnessed explosive
growth. In this work, we focus on UMTS, one of the
most popular 3G mobile communication technologies. Our
work is the first to accurately infer, for any UMTS network,
the state machine (both transitions and timer values)
that guides the radio resource allocation policy through a
light-weight probing scheme. We systematically characterize
the impact of operational state machine settings by analyzing
traces collected from a commercial UMTS network, and
pinpoint the inefficiencies caused by the interplay between
smartphone applications and the state machine behavior.
Besides the basic characterization, we explore the optimal
state machine settings in terms of several critical timer values
evaluated using real network traces.
Our findings suggest that the fundamental limitation of
the current state machine design is the static nature of treating
all traffic according to the same inactivity timer, making
it difficult to balance the tradeoffs among radio resource usage
efficiency, network management overhead, device radio
energy consumption, and performance. To the best of our
knowledge, our work is the first empirical study that employs
real cellular traces to investigate the optimality of the state
machine configurations. Our analysis also demonstrates that
traffic patterns impose significant impact on the radio resource
and energy consumption. In particular, We propose
a simple improvement that reduces YouTube streaming energy
by 80% by leveraging an existing feature called fast
dormancy supported by the 3GPP specifications.}},
	att_authors={os1872, ss2864, ag1971},
	att_categories={C_NSS.10, C_NSS.18},
	att_copyright_notice={{(c) ACM, 2010. 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 Internet Measurement Conference {{, 2010-11-01}}.
	att_tags={wireless , umts, radio resource optimization, measurement},
	author={Oliver Spatscheck and Subhabrata Sen and Alexandre Gerber and Feng Qian and Zhaoguang Wang and Z. Morley Mao},
	institution={{in Proc. of ACM Internet Measurement Conference (IMC)}},
	title={{Characterizing Radio Resource Allocation for 3G Networks}},