spelling corrections

Anudipa Maiti
1 parent f092c4d9
Showing 3 changed files with 11 additions and 11 deletions
abstract.tex
results.tex
usage.tex
@@ -7,7 +7,7 @@ mobile devices. What is urgently needed is a way to put energy consumption in
 context by measuring the value delivered by mobile apps. An accurate value
 measure would enable cross-app comparison, app improvement, energy virus
 detection, and effective runtime energy allocation and prioritization. Given
-that gains in modeling will be lost without a measure of value, we believe
+that gains in modelling will be lost without a measure of value, we believe
 that this is the most important open problem in energy management. Our paper
 motivates the problem, describes requirements for a candidate value measure,
 discusses possible inputs to such a metric, and presents result from a
@@ -6,7 +6,7 @@ large dataset of energy consumption measurements collected by an IRB-approved
 experiment run on the \PhoneLab{} testbed. \PhoneLab{} is a public smartphone
 platform testbed located at the University at
 Buffalo~\cite{phonelab-sensemine13}. 220~students, faculty, and staff carry
-instrumented Android Nexus~5 smartphones and receiv subsidized service in
+instrumented Android Nexus~5 smartphones and receive subsidized service in
 return for willingness to participate in experiments. \PhoneLab{} provides
 access to a representative group of participants balanced between genders and
 across a wide variety of age brackets, making our results more
@@ -85,7 +85,7 @@ looked better when their foreground usage was considered.
 Finally, we the data we collected by instrumenting the
 \texttt{SurfaceFlinger} and \texttt{AudioFlinger} components to compute a
 simple measure of content delivery. We measure the audio and video frame
-rates and combine them into a single measure by using bitrates corresponding
+rates and combine them into a single measure by using bit-rates corresponding
 to a 30~fps YouTube-encoded video and 128~kbps two-channel audio, with the
 weights representing the fact that a single frame of video contains much more
 content than a single sample of audio. We use this combined metric as the
@@ -36,12 +36,12 @@ respectively:
 %
 \begin{enumerate}
-\item An adversary will require you to remove some number of apps from your
+\item An advisory will require you to remove some number of apps from your
 smartphone. Order the apps you are currently using from least important to
 most important. The N least important apps will be removed.
 \item Your smartphone will require you to create an energy budget for the
-apps you use. During any discharging cycle, once an app runs out of energy
+apps you use. During any discharging cycle, once an app runs out of energy quota
 you will not be able to use it until you plug in your smartphone. Allocate
 battery percentages to each app you use.
@@ -54,7 +54,7 @@ the second experiment to make it more similar to the first, the adversary
 could remove the apps consuming the least energy up to a given target.
 For our value measure we are hopeful that users will prove capable of
-assiging cardinal utilities to apps---as in the second experiment---since
+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,
@@ -85,10 +85,10 @@ The most powerful use of a value measure would be to compare apps by
 comparing their energy efficiency, therefore overcoming the most critical
 flaw in current attempts to compare or categorize apps by their energy
 consumption alone~\cite{carat-sensys13}. Consider attempting to compare a
-chat client and videoconferencing app by only measuring their energy
+chat client and video-conferencing app by only measuring their energy
 consumption. Unless it is terribly written, the chat client will consume less
 energy. But this does not mean that it is efficient, or that the
-videconferencing app is not. Ultimately, all the energy consumption
+video-conferencing app is not. Ultimately, all the energy consumption
 comparison truly reveals is that the two apps do different things---which we
 knew.
@@ -104,7 +104,7 @@ By computing value and, thus, energy efficiency, we can overcome these
 weaknesses. A value measure should allow us to compare the efficiency of two
 apps in different categories based on how efficiently they use energy to
 deliver user value, making it possible to compare games to email clients to
-video players. Comparisons within the same app category shoud allow users to
+video players. Comparisons within the same app category should allow users to
 select the most efficient email client or web browser. Aggregating results
 over all users, differences in app energy efficiency should reflect how well
 the app is written and how well it predicts and adapts to users, not just
@@ -132,7 +132,7 @@ 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
-impossible to produce a single efficiency cutoff that cleanly separates
+impossible to produce a single efficiency cut-off that cleanly separates
 malicious apps from ones that are merely poorly-written. Note also that this
 definition of energy virus can be made on a per-user basis. This is important
 since a non-malicious but poorly-written app that continues to consume energy
@@ -154,7 +154,7 @@ However, all of these previous efforts have ignored the critical question of
 mechanisms are, systems that rely on rates will fail if they provide the same
 rate to Skype and Snapchat, or to a very efficient app and an energy virus.
-A measure of value can be used alone or in conjuction with energy consumption
+A measure of value can be used alone or in conjunction with energy consumption
 to help prioritize limited energy resources. The simplest approach is to
 attempt to enforce an energy allocation based on the relative value assigned
 to each app. To encourage apps to be more energy efficient, it may also be