diff --git a/metric.tex b/metric.tex index dd62bef..5f1c445 100644 --- a/metric.tex +++ b/metric.tex @@ -48,16 +48,16 @@ app value. Notification view and click-through rates also help put into context the energy used by apps when they are running in the background. Legitimate -background energy consumption should be for one of two purposes: to prepare -the app to deliver more value the next time it is foregrounded, as is the -case when music players download songs and store them locally to reduce their -runtime networking usage; or to deliver realtime notifications to the user. -The effectiveness of background energy consumption to fill caches will be -reflected in the apps overall energy usage, since retrieving local content is -more energy efficient than using the network. Effectiveness of background -consumption to deliver notifications may be reflected in the rate at which -notifications are viewed or clicked, since a notification that is not -consumed did not need to be retrieved. +background energy consumption should be for one of two purposes: (1) to +prepare the app to deliver more value the next time it is foregrounded, as is +the case when music players download songs and store them locally to reduce +their runtime networking usage; or (2) to deliver realtime notifications to +the user. The effectiveness of background energy consumption to fill caches +will be reflected in the apps overall energy usage, since retrieving local +content is more energy efficient than using the network. Effectiveness of +background consumption to deliver notifications may be reflected in the rate +at which notifications are viewed or clicked, since a notification that is +not consumed did not need to be retrieved. However, in some cases apps may do an effective job at summarizing the event within the notification itself, providing no need for the user to bring the @@ -79,10 +79,10 @@ messages as replies. Value is measured by the content of the messages. Efficient chat clients exchange many messages per joule. \item \textbf{Video player:} the content is the video delivered to the user -and efficiency is determined by the amount of network bandwidth and processing -needed to render the video. Value is measured by the information delivered by -the videos and efficient video players present a large amount of video -content to their users per joule. +and efficiency is determined by the amount of network bandwidth and +processing needed to retrieve and render the video. Value is measured by the +information delivered by the videos and efficient video players present a +large amount of video content to their users per joule. \item \textbf{Pedometer:} the content is the count of the number of steps presented to the user and efficiency is determined by the accelerometer rate diff --git a/results.tex b/results.tex index cbccf8c..f47ac12 100644 --- a/results.tex +++ b/results.tex @@ -109,7 +109,7 @@ YouTube and Candy Crush Saga both earn high marks, which is encouraging given that they are very different apps but also might be a result of overweighting screen refreshes. The Android Clock is also an unsurprising result, as it requires almost no energy to generate a relatively-large number of screen -redraws. +redraws in timer and stopwatch mode. \subsection{Survey Results and Discussion} @@ -148,8 +148,8 @@ Overall the results are inconclusive, with the content-delivery measure not clearly outperforming the straw-man usage measure at predicting which apps each user would be willing to remove to save battery life. Given the crude nature of our metric, this is not particularly surprising, and can be -interpreted as a clear sign that we need a more sophisticated value measure -incorporating several of the potential inputs we have previously discussed. +interpreted as a sign that we need a more sophisticated value measure +incorporating more of the potential inputs we have previously discussed. However, on one level the results are very encouraging: most users were willing to consider removing one or more apps if that app would improve their battery lifetime. Clearly users are making this decision based on some idea diff --git a/usage.tex b/usage.tex index 84d061d..85d9893 100644 --- a/usage.tex +++ b/usage.tex @@ -31,17 +31,18 @@ battery percentages to each app you use. % We plan to engage smartphone users in studies to explore in more detail which of these approaches is more effective, comparing them by comparing users' -levels of satisfaction under each scenario. In the first experiment we ask users -to uninstall apps because often apps have a background component that keeps consuming -energy even when not used by users any more. For our value measure we are -hopeful that users will prove capable of assigning cardinal utilities to -apps---as in the second experiment---since this matches most directly with -our proposed value measure and could provide ground truth for a value measure -computed automatically. The second experiment also engages users directly in -the task of allocating energy, which is one way that a value measure could be -used. However, if ordinal utilities prove more intuitive we can still compare -the ordering generated by our measure with the ordering generated by users, -although the values of the measure will still require justification. +levels of satisfaction under each scenario. In the first experiment we ask +users to uninstall apps because often apps have a background component that +keeps consuming energy even when the app is no longer being used. For our +value measure we are hopeful that users will prove capable of assigning +cardinal utilities to apps---as in the second experiment---since this matches +most directly with our proposed value measure and could provide ground truth +for a value measure computed automatically. The second experiment also +engages users directly in the task of allocating energy, which is one way +that a value measure could be used. However, if ordinal utilities prove more +intuitive we can still compare the ordering generated by our measure with the +ordering generated by users, although the values of the measure will still +require justification. In either case, we believe that these experiments do suggest the existence of quantifiable value for smartphone apps. We are not claiming, however, that @@ -106,12 +107,12 @@ defer work on everything else. A measure of app value makes it possible to produce a rigorous definition of the term \textit{energy virus}: an app that produces little to no value per -joule. The choice of threshold will require some study, as it is unlikely and +joule. The choice of threshold will require some study, as it is probably impossible to produce a single efficiency cutoff that cleanly separates -malicious apps from ones that are merely poorly-written. This -definition of energy virus can also be made on a per-user basis. This is important -since a non-malicious but poorly-written app that continues to consume energy -even long after the user has stopped using it---and it has stopped providing +malicious apps from ones that are merely poorly-written. This definition of +energy virus can also be made on a per-user basis. This is important since a +non-malicious but poorly-written app that continues to consume energy even +long after the user has stopped using it---and it has stopped providing value---functions as an energy virus for that user, but may not for a user that interacts with it more frequently.