From a78b622f9c7d2c5c81db3589e170ca68cd38e0fb Mon Sep 17 00:00:00 2001 From: Scott Haseley Date: Fri, 15 Apr 2016 10:36:39 -0400 Subject: [PATCH] clean up --- badwords | 2 +- design.tex | 8 ++++---- introduction.tex | 22 +++++++++++----------- paper.tex | 2 +- 4 files changed, 17 insertions(+), 17 deletions(-) diff --git a/badwords b/badwords index 41f14d3..9edf0ec 100644 --- a/badwords +++ b/badwords @@ -6,7 +6,7 @@ Challen challen edu Haseley -HotMobile +MobiSys ondemand pdfinfo prioritization diff --git a/design.tex b/design.tex index c01d677..1297e2e 100644 --- a/design.tex +++ b/design.tex @@ -18,14 +18,14 @@ without developer participation. As principle, if a user is waiting for something, priority should be given to any task that contributes to that end. This priority must extend across -multiple shared components, namely CPUs, disks, networks, batteries. +multiple shared components, such as CPUs, disks, networks, and batteries. % To achieve this goal, the OS must be designed in such a way that gives it -the visiblity it currently lacks into how its actions will affect QoE. +the visibility it currently lacks into how its actions will affect QoE. % To further improve QoE for apps that use the network, this visibility should -extend past the device and into the network so priority decisions can be made -by the network to improve QoE. +extend past the device and into the network so priority can be given to +QoE-sensitive network traffic. % The design of QoE-centric operating systems may require deep and fundamental changes in order to measure QoE, understand its effect on various components, diff --git a/introduction.tex b/introduction.tex index 1f6f28e..d3b4079 100644 --- a/introduction.tex +++ b/introduction.tex @@ -6,7 +6,7 @@ users care more about resources such as time, battery life, and money, that are unmanaged or poorly managed by today's smartphone platforms. When apps slow down our typing, they waste our time. When apps download unnecessary resources, they waste battery life and potentially money, if using -a metered data plan. It is the degree two which mobile devices effectively +a metered data plan. It is the degree to which mobile devices effectively manage these human-facing resources that determines a user's \textit{quality of experience} (QoE), and it is QoE which should drive not just policy, but decisions on mobile devices. @@ -16,12 +16,12 @@ While modern operating systems such as Android make decisions based on policies meant to improve QoE, it is unclear that these static policies always result in the right decisions. For example, Android uses two mechanisms to control the underlying task scheduling in Linux: thread priority and control groups (cgroup). -Background threads -- any thread running in another app, or low priority threads +Background threads -- threads running in another app, or low priority threads running in the foreground app -- are placed in a cgroup that receives a very limited share of the processor, \( \approx \) 5\% on Nexus 5 running stock -Android 5.1.1. Furthermore, the scheduler considers priority for tasks withing +Android 5.1.1. Furthermore, the scheduler considers thread priority for tasks within the same cgroup. However, thread priorities can be set by app developers both -directly through the API, and indirectly by creating an \texttt{AsyncTask}. +directly through the API, and indirectly by using an \texttt{AsyncTask}. While this policy was created based on the assumed effect on QoE, it is still possible to negatively affect QoE by assigning the wrong priority to a thread or by inappropriately using \texttt{AsyncTasks}. @@ -29,15 +29,15 @@ or by inappropriately using \texttt{AsyncTasks}. The \texttt{ondemand} CPU frequency governor that is enabled in Android Linux is another example of where static policy meant to improve QoE may not -result in correct decisions being made. This governor changes the CPU frequency +result in correct decisions. This governor changes the CPU frequency depending on the current CPU load with the goal of improving performance. However since running at higher frequencies is less efficient, this increased performance comes at the cost. If QoE would not be improved by increasing the frequency, such as for time-insensitive background tasks or when the performance -increase would not be perceivable, negative QoE may manifest itself through a -quicker draining battery. +increase would not be perceivable, negative QoE may manifest itself through +poor battery life. -Static policies can lead to resource allocation decisions that are less than -optimal in terms of QoE. To remedy this, we propose designing QoE-centric -mobile operating systems that can accurately quantify QoE and use it as feedback -to drive resource allocation decisions. +In terms of QoE, static policies can lead to resource allocation decisions that +are less than optimal. To remedy this, we propose designing QoE-centric +mobile operating systems that use QoE as input to drive resource allocation +decisions. diff --git a/paper.tex b/paper.tex index 60e56c9..561180c 100644 --- a/paper.tex +++ b/paper.tex @@ -1,6 +1,6 @@ \input{./include/start.tex} -\def\theconference{HotMobile'16} +\def\theconference{MobiSys'16} \def\thetitle{Poster: QoE-centric Mobile Operating System Design} \def\theauthors{Scott Haseley, Geoffrey Challen} \def\theemails{\{shaseley,challen\}@buffalo.edu} -- libgit2 0.22.2