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usage.tex
| ... | ... | @@ -38,10 +38,9 @@ each user enjoys whichever approach is most effective for them. |
| 38 | 38 | \subsection{\texttt{\large PhoneLab} Conductor} |
| 39 | 39 | |
| 40 | 40 | \PhoneLab{} is a large scale smartphone platform testbed at the University at |
| 41 | -Buffalo~\cite{phonelab-sensemine13}. We leverage the Android | |
| 42 | -\texttt{logcat} subsystem as a data collection mechanism---experiment apps | |
| 43 | -write their data into a system-wide log buffer and we collect and upload this | |
| 44 | -data on their behalf. | |
| 41 | +Buffalo~\cite{phonelab-sensemine13}. We leverage the Android \texttt{logcat} | |
| 42 | +subsystem as a data collection mechanism---experiments log their data into a | |
| 43 | +system-wide log buffer and we collect and upload this data on their behalf. | |
| 45 | 44 | |
| 46 | 45 | We developed an app called the \PhoneLab{} Conductor for this purpose which |
| 47 | 46 | provides a good example of custom \texttt{maybe} evaluation logic. The goal |
| ... | ... | @@ -50,7 +49,7 @@ storage usage, and metered data usage. With the \texttt{maybe} statement |
| 50 | 49 | branching between multiple policies for uploading data---such as always |
| 51 | 50 | waiting until the user reaches a plug, or always initiating an upload once |
| 52 | 51 | the storage allocated is 50\% full---the evaluation logic would provide the |
| 53 | -lowest possible score if data had been lost, or otherwise a score combining | |
| 52 | +worst possible score if data had been lost, or otherwise a score combining | |
| 54 | 53 | the multiple attributes the app is trying to minimize. |
| 55 | 54 | |
| 56 | 55 | Due to the uncertainties we faced during development, we implemented a |
| ... | ... | @@ -63,7 +62,7 @@ proven essential after deployment---for example, when an upload policy that |
| 63 | 62 | worked previously abruptly stopped working on a newer Android version. |
| 64 | 63 | Development of this app would have been considerably easier using |
| 65 | 64 | \texttt{maybe}, which could automate the process of pushing policies to |
| 66 | -clients in an energy-efficient way, and enable per-user goal-driven | |
| 65 | +clients in an energy-efficient way, and enabling per-user goal-driven | |
| 67 | 66 | adaptation. |
| 68 | 67 | |
| 69 | 68 | ... | ... |