@techreport{TD:101739,
	att_abstract={{Smartphone manufacturers often release software upgrades to their users for improving service performance, patching security vulnerabilities, enhancing device stability, fixing bugs, increasing battery life, or even enriching the graphical user interface. It is crucial to monitor the smartphones after software upgrades to either confirm their expected impacts, or quickly identify any undesirable behaviors. In this paper, we focus on automatically detecting the software upgrades on smartphones and analyzing their service performance impacts. The complex interactions between the smartphones and the cellular networks make it hard to differentiate if the impacts are smartphone-centric, or network-centric. We propose a new approach, SSM for conducting pre/post impact analysis of multiple service performance metrics across smartphones aggregated by their type, make, model (e.g., Apple iPhone 6S, Samsung Galaxy S6 Edge, and Microsoft Lumia 950) and network locations. Using one-year worth of operational network data, we demonstrate the effectiveness of SSM in accurately detecting and diagnosing the performance impact of smartphone software upgrades.}},
	att_authors={am649n},
	att_categories={},
	att_copyright={{IFIP}},
	att_copyright_notice={{This version of the work is reprinted here with permission of IEEE for your personal use. Not for redistribution. The definitive version was published in IFIP/IEEE CNSM . {{, 2016-10-31}}
}},
	att_donotupload={},
	att_private={false},
	att_projects={},
	att_tags={},
	att_techdoc={true},
	att_techdoc_key={TD:101739},
	att_url={http://web1.research.att.com:81/techdocs_downloads/TD:101739_DS1_2016-05-08T14:09:17.276Z.pdf},
	author={Ajay Mahimkar},
	institution={{IFIP/IEEE CNSM }},
	month={October},
	title={{Detecting and Diagnosing Performance Impact of Smartphone Software Upgrades}},
	year=2016,
}