Update by Ali

[ThesisAli.git] / CHAPITRE_04.tex

diff --git a/CHAPITRE_04.tex b/CHAPITRE_04.tex
index c359b8b2a7509eccb45413e941f92f4748c66d42..a692dc32d0b86eca3012833c7ff1af8bc26f599b 100644 (file)
--- a/CHAPITRE_04.tex
+++ b/CHAPITRE_04.tex
@@ -350,7 +350,7 @@ The modeling language for Mathematical Programming (AMPL)~\cite{AMPL} is  employ
 \label{tab:EC}
 \begin{tabular}{|l||cccc|}
   \hline
 \label{tab:EC}
 \begin{tabular}{|l||cccc|}
   \hline

-  {\bf Sensor status} & MCU & Radio & Sensor & {\it Power (mW)} \\
+  {\bf Sensor status} & MCU & Radio & Sensing & {\it Power (mW)} \\

   \hline
   LISTENING & On & On & On & 20.05 \\
   ACTIVE & On & Off & On & 9.72 \\
   \hline
   LISTENING & On & On & On & 20.05 \\
   ACTIVE & On & Off & On & 9.72 \\


@@ -504,7 +504,7 @@ As shown in Figures~\ref{Figures/ch4/R1/EC}(a) and~\ref{Figures/ch4/R1/EC}(b), D
 \item {{\bf Execution Time}}
 %\subsubsection{Execution Time}
 
 \item {{\bf Execution Time}}
 %\subsubsection{Execution Time}
 

-In this experiment, the execution time of the distributed optimization approach has been studied. Figure~\ref{Figures/ch4/R1/T} gives the average execution times in seconds for the decision phase (solving of the optimization problem) during one period. They are given for the different approaches and various numbers of sensors. The original execution time is computed as described in section \ref{ch4:sec:04:04}. \\ \\ \\ \\
+In this experiment, the execution time of the distributed optimization approach has been studied. Figure~\ref{Figures/ch4/R1/T} gives the average execution times in seconds for the decision phase (solving of the optimization problem) during one period. They are given for the different approaches and various numbers of sensors.  \\ \\% \\ \\ \\

 
 
 
 
 
 


@@ -515,7 +515,7 @@ In this experiment, the execution time of the distributed optimization approach
 \label{Figures/ch4/R1/T}
 \end{figure} 
 
 \label{Figures/ch4/R1/T}
 \end{figure} 
 

-We can see from Figure~\ref{Figures/ch4/R1/T} that DiLCO-32 has very low execution times in comparison with other DiLCO versions because it is distributed on larger number of small subregions.  Conversely, DiLCO-2 requires to solve an optimization problem considering half the nodes in each subregion and thus presents high execution times. Overall, to be able to deal with very large networks,  a distributed method is clearly required.
+The original execution time is computed as described in section \ref{ch4:sec:04:04}. We can see from Figure~\ref{Figures/ch4/R1/T} that DiLCO-32 has very low execution times in comparison with other DiLCO versions because it is distributed on larger number of small subregions.  Conversely, DiLCO-2 requires to solve an optimization problem considering half the nodes in each subregion and thus presents high execution times. Overall, to be able to deal with very large networks,  a distributed method is clearly required.

 
 \item {{\bf Network Lifetime}}
 %\subsubsection{The Network Lifetime}
 
 \item {{\bf Network Lifetime}}
 %\subsubsection{The Network Lifetime}