incorprating Dr. Qiao's comments

Jinghao Shi
1 parent b521591f
Showing 3 changed files with 49 additions and 43 deletions
design.tex
introduction.tex
progress.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.
 \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}
+\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.