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figures/tables/tableALL.tex
| ... | ... | @@ -84,6 +84,7 @@ |
| 84 | 84 | \num{7} & \texttt{Android Calculator} & 9.189 \\ |
| 85 | 85 | \num{8} & \texttt{Twitter} & 8.645 \\ |
| 86 | 86 | \num{9} & \texttt{Chrome Browser} & 8.524 \\ |
| 87 | +\num{10} & & \\ | |
| 87 | 88 | \bottomrule |
| 88 | 89 | \num{10} & \texttt{Yahoo Mail} & 3.287 \\ |
| 89 | 90 | \num{9} & \texttt{ESPN SportsCenter} & 3.184 \\ |
| ... | ... | @@ -100,6 +101,8 @@ |
| 100 | 101 | |
| 101 | 102 | \caption{\small \textbf{Apps sorted by foreground energy efficiency.}} |
| 102 | 103 | |
| 104 | +\label{table-foreground} | |
| 105 | + | |
| 103 | 106 | \end{subtable}% |
| 104 | 107 | \begin{subtable}[t]{0.5\textwidth} |
| 105 | 108 | {\small |
| ... | ... | @@ -117,6 +120,7 @@ |
| 117 | 120 | \num{7} & \texttt{Twitter} & 5610.394 \\ |
| 118 | 121 | \num{8} & \texttt{Android Clock} & 5085.873 \\ |
| 119 | 122 | \num{9} & \texttt{Yahoo Mail} & 5083.615 \\ |
| 123 | +\num{10} & & \\ | |
| 120 | 124 | \bottomrule |
| 121 | 125 | \num{10} & \texttt{NFL Mobile} & 1275.985 \\ |
| 122 | 126 | \num{9} & \texttt{UB Parking} & 1071.529 \\ |
| ... | ... | @@ -132,6 +136,8 @@ |
| 132 | 136 | } |
| 133 | 137 | |
| 134 | 138 | \caption{\small \textbf{Apps sorted by content energy efficiency.}} |
| 139 | + | |
| 140 | +\label{table-content} | |
| 135 | 141 | \end{subtable} |
| 136 | 142 | |
| 137 | 143 | \caption{\small \textbf{Evaluating Components of a Value Measure.} | ... | ... |
results.tex
| ... | ... | @@ -39,7 +39,7 @@ it through a survey completed by 47~experiment participants. Unfortunately, |
| 39 | 39 | our results are inconclusive and open to several possible interpretations |
| 40 | 40 | which we conclude by discussing. |
| 41 | 41 | |
| 42 | -\subsection{Total Consumption} | |
| 42 | +\subsection{Total Energy} | |
| 43 | 43 | |
| 44 | 44 | \input{./figures/tables/tableALL.tex} |
| 45 | 45 | |
| ... | ... | @@ -52,32 +52,61 @@ list of low consumers is dominated by apps with few installs. This table does |
| 52 | 52 | serve, however, to identify the popular apps in use by \PhoneLab{} |
| 53 | 53 | participants, and as a point of comparison for the remainder of our results. |
| 54 | 54 | |
| 55 | -\subsection{Consumption Rate} | |
| 55 | +\subsection{Power} | |
| 56 | 56 | |
| 57 | -Computing the rate at which apps consume energy by scaling their total energy | |
| 58 | -usage against the total time they were running, either in the background or | |
| 57 | +Computing each app's power consumption by scaling their total energy usage | |
| 58 | +against the total time they were running, either in the background or | |
| 59 | 59 | foreground, reveals more information, as shown in Table~\ref{table-rate}. Our |
| 60 | 60 | results identify Facebook Messenger, Google+, and the Super-Bright LED |
| 61 | 61 | Flashlight as apps that rapidly-consume energy, while the Bank of America and |
| 62 | 62 | Weather Channel apps consume energy slowly. Differences between apps in |
| 63 | 63 | similar categories may begin to identify apps with problematic energy |
| 64 | 64 | consumption, such as contrasting the high energy usage of Facebook Messenger |
| 65 | -with other messaging clients such as WhatsApp, Twitter, and Android Messaging. | |
| 65 | +with other messaging clients such as WhatsApp, Twitter, and Android | |
| 66 | +Messaging. | |
| 66 | 67 | |
| 67 | 68 | \subsection{Foreground Energy Efficiency} |
| 68 | 69 | |
| 69 | -Consumption rate alone, however, is insufficient to answer important | |
| 70 | -questions about how efficient smartphone apps are. Youtube, for example, may | |
| 71 | -consume a great deal of energy either because it is poorly written, or | |
| 72 | -because it is delivering a great deal of content. Given the observations | |
| 73 | -about background usage presented earlier, we were interested in using an apps | |
| 74 | -foreground time as a utility metric to compute energy efficiency. In this | |
| 75 | -conceptual framework, smartphone apps deliver utility through screen time | |
| 76 | -with users, and should consume energy in proportion to the amount of time | |
| 77 | -users spend actively interacting with them. | |
| 70 | +Isolating the foreground component of execution time provides a better | |
| 71 | +measure of value, since it ignores the time that users spend ignoring apps. | |
| 72 | +Table~\ref{table-foreground} shows a measure of energy efficiency computed by | |
| 73 | +utilizing foreground time alone as our value measure. Some surprising changes | |
| 74 | +from the power results can be seen. Some apps have remaining in their former | |
| 75 | +categories: Bank of America, which was identified as a low-power app, is also | |
| 76 | +a highly-efficient app when using foreground time as the value measure; and | |
| 77 | +Facebook Messenger, which was identified as a high-power app, is also marked | |
| 78 | +as inefficient. Other apps, however, have switched categories. ESPN | |
| 79 | +Sportscenter and Yahoo Mail do not consume much power, but also don't spend | |
| 80 | +much time in the foreground; interestingly, none of the high-power apps | |
| 81 | +looked better when their foreground usage was considered. | |
| 78 | 82 | |
| 79 | 83 | \subsection{Content Energy Efficiency} |
| 80 | 84 | |
| 85 | +Finally, we the data we collected by instrumenting the | |
| 86 | +\texttt{SurfaceFlinger} and \texttt{AudioFlinger} components to compute a | |
| 87 | +simple measure of content delivery. We measure the audio and video frame | |
| 88 | +rates and combine them into a single measure by using bitrates corresponding | |
| 89 | +to a 30~fps YouTube-encoded video and 128~kbps two-channel audio, with the | |
| 90 | +weights representing the fact that a single frame of video contains much more | |
| 91 | +content than a single sample of audio. We use this combined metric as the | |
| 92 | +value measure and again use it to weight the energy consumption of each app, | |
| 93 | +with the results shown in Table~\ref{table-content}. | |
| 94 | + | |
| 95 | +Comparing with the foreground energy efficiency again shows several | |
| 96 | +interesting changes. Yahoo Mail, which foreground energy efficiency marked as | |
| 97 | +inefficiency, looks more efficient when content delivery is considered. While | |
| 98 | +it is possible that one \PhoneLab{} participant uses it to read email very | |
| 99 | +quickly, it may be more likely that it uses a ``spinner'' or other fancy UI | |
| 100 | +elements that generate artificially high frame rates without delivering much | |
| 101 | +information. The inability to distinguish between meaningless and meaningful | |
| 102 | +video frame content is a significant weakness of this simple approach. | |
| 103 | +YouTube and Candy Crush Saga both earn high marks, which is encouraging given | |
| 104 | +that they are very different apps but also might be a result of overweighting | |
| 105 | +screen refreshes. The Android Clock is also an unsurprising result, as it | |
| 106 | +requires almost no energy to generate a relatively-large number of screen | |
| 107 | +redraws. | |
| 108 | + | |
| 109 | +\subsection{Survey Results and Discussion} | |
| 81 | 110 | |
| 82 | 111 | \begin{figure*}[t] |
| 83 | 112 | \centering | ... | ... |