@techreport{TD:101402,
	att_abstract={{Recent studies have shown that web browsing is one of the most prominent cellular applications. It is therefore important for cellular network operators to understand how radio network characteristics (such as signal strength, handovers, load, etc.) influence users' web browsing Quality-of-Experience (web QoE). Understanding the relationship between web QoE and network characteristics is a pre-requisite for  cellular network operators to detect when and where degraded network conditions actually impact web QoE. Unfortunately, cellular network operators do not have access to detailed server-side or client-side logs to directly measure web QoE metrics, such as abandonment rate and session length. In this paper, we first devise a machine-learning-based mechanism to infer web QoE metrics from network traces accurately. We then present a large-scale study characterizing the impact of network characteristics on web QoE using a month-long anonymized dataset collected from a major cellular network provider. Our results show that improving signal-to-noise ratio, decreasing load and reducing handovers can improve user experience. We find that web QoE is very sensitive to inter-radio-access-technology (IRAT) handovers. We further find that radio data link rate is not correlated with web QoE.    Since many network characteristics are interrelated, we also use machine learning to accurately model the influence of radio network characteristics on user experience metrics. This model can be used by cellular network operators to prioritize the improvement of network factors that most influence web QoE.}},
	att_authors={jp935w, eh679n, va037f, sv1623, hy312y},
	att_categories={C_BB.6},
	att_copyright={{ACM}},
	att_copyright_notice={{(c) ACM, 2014. 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 2014 {{, 2014-09-07}}.
}},
	att_donotupload={},
	att_private={false},
	att_projects={},
	att_tags={},
	att_techdoc={true},
	att_techdoc_key={TD:101402},
	att_url={http://web1.research.att.com:81/techdocs_downloads/TD:101402_DS1_2014-06-23T02:23:34.135Z.pdf},
	author={Jeffrey Pang and Emir Halepovic and Vaneet Aggarwal and Shobha Venkataraman and He Yan and Athula Balachandran and Srinivasan Seshan},
	institution={{ACM Mobicom 2014}},
	month={September},
	title={{Modeling Web Quality-of-Experience on Cellular Networks}},
	year=2014,
}