From 8cd280629e3ea236d72f6e60ee5f72a171a1fb03 Mon Sep 17 00:00:00 2001 From: Jinghao Shi Date: Tue, 6 Jan 2015 15:04:12 -0500 Subject: [PATCH] incorprating Dr. Qiao's comments --- design.tex | 36 +++++++++++++++++++----------------- introduction.tex | 44 +++++++++++++++++++++++--------------------- progress.tex | 12 +++++++----- 3 files changed, 49 insertions(+), 43 deletions(-) diff --git a/design.tex b/design.tex index 50b49f6..b2d46b2 100644 --- a/design.tex +++ b/design.tex @@ -3,10 +3,11 @@ \begin{figure}[t!] \centering - \includegraphics[width=0.46\textwidth]{./figures/system-crop.pdf} - \vspace*{3mm} + \includegraphics[width=0.45\textwidth]{./figures/system-crop.pdf} + \vspace{2mm} \caption{\textbf{System Components}} \label{fig:system} + \vspace{-6mm} \end{figure} \PS{} collects two types of measurements from clients---spectrum utilization, @@ -15,19 +16,20 @@ ways---synchronously and asynchronously. Figure~\ref{fig:system} shows the main components of \PS{}. Idle smartphones can be used to improve nearby device's network performance. For -example, in Figure~\ref{fig:system}, when \PS{} Access Point (AP) sends -synchronous query about spectrum condition of the active device (laptop), -nearby \PS{} client -(smartphone) will perform detailed measurements \textit{on behalf of} the -laptop. This information can then be feed into AP adaption algorithms for -channel assignment, rate adaption or power control---all without disturbing the -current network session of the active client. +example, in Figure~\ref{fig:system}, when \PS{} Access Point (AP) sends a +synchronous query about spectrum condition of the active device (e.g., a +laptop), nearby \PS{} client (smartphone) will perform detailed measurements +\textit{on behalf of} the laptop. This information can then be fed into AP +adaption (e.g., channel assignment, rate and power control, etc.) algorithms for +better network performance---all without disrupting the current network session +of the active client. -On other hand, to cope with rapidly-changing network environment caused by mobility, -smartphones already perform aggressive network exploration and thus naturally -generate a high-resolution flow of measurements. Harnessing this behavior for -network monitoring purpose only requires to deliver the measurements to those -who can make use of it. Besides, lightweight network performance tests can be -conducted using smartphones' idle cycles without consuming noticeable amount of -energy. All these measurements can be uploaded in a energy neutral way -asynchronously for long-term network monitoring purpose. +On the other hand, to cope with rapidly-changing network environment caused by +mobility, smartphones already perform aggressive network exploration and thus +naturally generate a flow of measurements of high temporal resolution. +Harnessing this behavior for network monitoring purpose only requires to deliver +the measurements to those who can make use of it. Besides, lightweight network +performance tests can be conducted using smartphones' idle cycles without +consuming noticeable amount of energy. All these measurements can be uploaded +asynchronously in a energy-neutral way (e.g., by only uploading when phone is +charging) for long-term network monitoring purpose. diff --git a/introduction.tex b/introduction.tex index 2449052..0caca3f 100644 --- a/introduction.tex +++ b/introduction.tex @@ -1,26 +1,28 @@ \section{Introduction} -\sloppypar{% - The rapid proliferation of smartphones creates both challenges and new - opportunities for wireless networks. On one hand, smartphones compete for the - same limited spectrum already crowded with other devices. On the other hand, - because smartphones are \textit{always on} but \textit{mostly idle}, they are - ideal for observing the network conditions on behalf of nearby active wireless - devices. When used for continuous network adaptation, - offloading measurements to inactive clients avoids - disturbing active sessions, a capability that has not been adequately - exploited by other systems using client-side feedback. When used for network - monitoring and debugging, smartphones provide more valuable measurements than - planned site surveys, since the data that - smartphones provide is continuous and representative of wireless conditions - experienced by users while surveys are neither. We refer to these approaches - collectively as \textbf{c}rowdsourcing \textbf{a}ccess \textbf{n}etwork - \textbf{s}pectrum \textbf{a}llocation using \textbf{s}martphones, or - \textbf{CANSAS}. -} +\begin{sloppypar} +The rapid proliferation of smartphones creates both challenges and new +opportunities for wireless networks. On one hand, smartphones compete for the +same limited spectrum already crowded with other devices. On the other hand, +because smartphones are \textit{always on} but \textit{mostly idle}, they are +ideal for observing the network conditions on behalf of nearby active wireless +devices. When used for continuous network adaptation, +offloading measurements to inactive clients avoids +disrupting active sessions, a capability that has not been adequately +exploited by other systems using client-side feedback. When used for network +monitoring and debugging, smartphones provide more valuable measurements than +planned site surveys, since the data that +smartphones provide is continuous and representative of wireless conditions +experienced by users while surveys are neither. We refer to these approaches +collectively as \textbf{c}rowdsourcing \textbf{a}ccess \textbf{n}etwork +\textbf{s}pectrum \textbf{a}llocation using \textbf{s}martphones, or +\textbf{CANSAS}. +\end{sloppypar} -We're currently developing an prototype system implementing CANSAS for \wifi{} -networks called \PS{}. It collects measurements from passive smartphones to -improve network performance. \PS{} also captures the large number of +\begin{sloppypar} +We are currently developing a prototype system called \PS{} that implements CANSAS for \wifi{} +networks. It collects measurements from passive smartphones to +improve network performance. \PS{} also captures a variety of measurements generated naturally by smartphones as they discover and connect to networks---valuable data that is currently discarded. +\end{sloppypar} diff --git a/progress.tex b/progress.tex index a60ad95..b5e9542 100644 --- a/progress.tex +++ b/progress.tex @@ -1,11 +1,13 @@ +\vspace{-3mm} \section{Current Progress} \label{sec:progress} -We modified the \wifi{} chipset driver of Android to enable \wifi{} monitor -mode, which enables the smartphone to perform detailed spectrum measurements. +We modified Android \wifi{} driver to support monitor +mode, which enables the smartphone to collect detailed spectrum measurements. We have set up a group of OpenWRT APs to experiment spectrum allocation -algorithms. We are conducting small scale experiments to show: the usefulness of +algorithms. We expect to report preliminary results to show: the value of detailed client-side measurements, the performance penalty of collecting them from active clients, and the feasibility of using smartphones to help nearby -devices. We are also preparing to deploy our system on \PhoneLab{}---a large -smartphone testbed operated at UB. +devices. We also plan to deploy our system on +\PhoneLab{}\footnote{\url{http://www.phone-lab.org}}---a large +smartphone testbed at UB. -- libgit2 0.22.2