43 lines
2.4 KiB
TeX
43 lines
2.4 KiB
TeX
\subsection{PhoneLab}
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\PhoneLab{}~\cite{phonelab} is a public smartphone platform testbed operated
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at the University at Buffalo (UB). Approximately 200~UB students, faculty,
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and staff use instrumented LG Nexus~5 smartphones as their
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primary device and receive discounted service in return for providing data to
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smartphone experiments. \PhoneLab{} participants are balanced between genders
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and distributed across ages, and thus representative of the broader
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smartphone user population. \PhoneLab{} smartphones run a modified version of
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the Android Open Source Platform (AOSP) 4.4.4 "KitKat" including
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instrumentation and logging developed in collaboration with the mobile
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systems community. Participating smartphones log experimental results which
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are uploaded to a centralized server when the device is charging.
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\subsection{Data Collection and Analysis}
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We instrumented the \PhoneLab{} AOSP platform image to log SQLite activity by
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modifying the SQLite source code and distributing the updated binary library
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as an over-the-air (OTA) platform update to \PhoneLab{} participants.
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%
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Our logging recorded each SQL statement that was executed, along with its
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resulting runtime and the number of rows returned as appropriate.
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%
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All current \PhoneLab{} instrumentation including our SQLite logging
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statements are documented at \url{https://phone-lab.org/experiment/data/}.
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%
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To protect participant privacy, our instrumentation removes as much
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personally-identifying information as possible and well as recording prepared
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statement arguments only as hash values.
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Our trace data-set is drawn from publicly-available data provided by
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11~\PhoneLab{} developers who willingly
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released\footnote{\url{https://phone-lab.org/static/experiment/sample_dataset.tgz}}
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complete trace data for their phones for March, 2015. Of the eleven
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participants, seven had phones that were participating in the SQLite
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experiment every day for the full month, with the remaining phones were
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active for 1, 3, 14, and 19 days. A total of 254 phone/days of data were
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collected including 45,399,550 SQL statements. Of these, we were unable to
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interpret 308,752 statements (representing slightly over half a percent of
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the trace) due to a combination of data corruption and the use of unusual SQL
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syntax. Results presented in this paper that include SQL interpretation are
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based on the 45,090,798 queries that we were able to successfully parse.
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