X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/JournalMultiRounds.git/blobdiff_plain/7ae9cfc438e6cbd516743f82902f4ca7ceb4e19c..1e248125c11122508fff14c90cf49b57b1e4622f:/elsarticle-template-num.tex

diff --git a/elsarticle-template-num.tex b/elsarticle-template-num.tex
index 691beda..63e8018 100644
--- a/elsarticle-template-num.tex
+++ b/elsarticle-template-num.tex
@@ -382,7 +382,7 @@ $X_{13}=( p_x + R_s * (0), p_y + R_s * (\frac{-\sqrt{2}}{2})) $.
 \centering
 \includegraphics[scale=0.20]{fig21.pdf}\\~ ~ ~ ~ ~(a)
 \includegraphics[scale=0.20]{fig22.pdf}\\~ ~ ~ ~ ~(b)
-\includegraphics[scale=0.20]{principles13.eps}\\~ ~ ~ ~ ~(c)
+\includegraphics[scale=0.20]{principles13.pdf}\\~ ~ ~ ~ ~(c)
 %\includegraphics[scale=0.10]{fig25.pdf}\\~ ~ ~(d)
 %\includegraphics[scale=0.10]{fig26.pdf}\\~ ~ ~(e)
 %\includegraphics[scale=0.10]{fig27.pdf}\\~ ~ ~(f)
@@ -398,7 +398,7 @@ then  our coverage  protocol  will be  implemented  in each  subregion
 simultaneously. Our DiLCO protocol works in rounds fashion as shown in figure~\ref{fig2}.
 \begin{figure}[ht!]
 \centering
-\includegraphics[width=95mm]{FirstModel.eps} % 70mm
+\includegraphics[width=95mm]{FirstModel.pdf} % 70mm
 \caption{DiLCO protocol}
 \label{fig2}
 \end{figure} 
@@ -840,7 +840,7 @@ In this experiment, Figure~\ref{fig3} shows the average coverage ratio for 150 d
 \parskip 0pt    
 \begin{figure}[h!]
 \centering
- \includegraphics[scale=0.5] {R1/CR.eps} 
+ \includegraphics[scale=0.5] {R1/CR.pdf} 
 \caption{The impact of the number of rounds on the coverage ratio for 150 deployed nodes}
 \label{fig3}
 \end{figure} 
@@ -856,7 +856,7 @@ the area of interest into 8, 16 and 32~subregions if one of the subregions becom
  Figure~\ref{fig4} shows the average active nodes ratio for 150 deployed nodes.
 \begin{figure}[h!]
 \centering
-\includegraphics[scale=0.5]{R1/ASR.eps}  
+\includegraphics[scale=0.5]{R1/ASR.pdf}  
 \caption{The impact of the number of rounds on the active sensors ratio for 150 deployed nodes }
 \label{fig4}
 \end{figure} 
@@ -866,7 +866,7 @@ The results presented in figure~\ref{fig4} show  the increase in the number of s
 Figure~\ref{fig6} illustrates the percentage of stopped simulation runs per round for 150 deployed nodes. 
 \begin{figure}[h!]
 \centering
-\includegraphics[scale=0.43]{R1/SR.eps} 
+\includegraphics[scale=0.43]{R1/SR.pdf} 
 \caption{The percentage of stopped simulation runs compared to the number of rounds for 150 deployed nodes }
 \label{fig6}
 \end{figure} 
@@ -879,7 +879,7 @@ We measure the energy consumed by the sensors during the communication, listenin
 
 \begin{figure}[h!]
 \centering
-\includegraphics[scale=0.5]{R1/EC95.eps} 
+\includegraphics[scale=0.5]{R1/EC95.pdf} 
 \caption{The Energy Consumption for Lifetime95}
 \label{fig95}
 \end{figure} 
@@ -890,7 +890,7 @@ The results show that  DiLCO-16 and DiLCO-32 are the most competitive from the e
 As shown in Figures~\ref{fig95} and ~\ref{fig50} , DiLCO-2 consumes more energy than the other versions of DiLCO, especially for large sizes of network. This is easy to understand since the bigger the number of sensors involved in the integer program, the larger the time computation to solve the optimization problem as well as the higher energy consumed during the communication.  
 \begin{figure}[h!]
 \centering
-\includegraphics[scale=0.5]{R1/EC50.eps} 
+\includegraphics[scale=0.5]{R1/EC50.pdf} 
 \caption{The Energy Consumption for Lifetime50}
 \label{fig50}
 \end{figure} 
@@ -902,7 +902,7 @@ The original execution time is computed on a laptop DELL with intel Core i3 2370
 
 \begin{figure}[h!]
 \centering
-\includegraphics[scale=0.5]{R1/T.eps}  
+\includegraphics[scale=0.5]{R1/T.pdf}  
 \caption{Execution Time (in seconds)}
 \label{fig8}
 \end{figure} 
@@ -918,7 +918,7 @@ In figure~\ref{figLT95} and \ref{figLT50}, network lifetime, $Lifetime95$ and $L
 
 \begin{figure}[h!]
 \centering
-\includegraphics[scale=0.5]{R1/LT95.eps}  
+\includegraphics[scale=0.5]{R1/LT95.pdf}  
 \caption{The Network Lifetime for $Lifetime95$}
 \label{figLT95}
 \end{figure} 
@@ -934,7 +934,7 @@ our DiLCO-16 protocol efficiently extends  the network lifetime because the bene
 Comparison shows that the DiLCO-16 protocol, which uses 16 leaders, is the best one because it is used less number of active nodes during the network lifetime compared with DiLCO-32. It also  means that distributing the protocol in each node and subdividing the sensing field into many subregions, which are managed independently and simultaneously, is the most relevant way to maximize the lifetime of a network.
 \begin{figure}[h!]
 \centering
-\includegraphics[scale=0.5]{R1/LT50.eps}  
+\includegraphics[scale=0.5]{R1/LT50.pdf}  
 \caption{The Network Lifetime for $Lifetime50$}
 \label{figLT50}
 \end{figure} 
@@ -949,7 +949,7 @@ In this experiment, we Figure~\ref{fig33} shows the average coverage ratio for 1
 \parskip 0pt    
 \begin{figure}[h!]
 \centering
- \includegraphics[scale=0.5] {R2/CR.eps} 
+ \includegraphics[scale=0.5] {R2/CR.pdf} 
 \caption{The impact of the number of rounds on the coverage ratio for 150 deployed nodes}
 \label{fig33}
 \end{figure} 
@@ -962,7 +962,7 @@ thanks to  Model~2, which is slightly more efficient than other Models, because
  Figure~\ref{fig44} shows the average active nodes ratio for 150 deployed nodes.
 \begin{figure}[h!]
 \centering
-\includegraphics[scale=0.5]{R2/ASR.eps}  
+\includegraphics[scale=0.5]{R2/ASR.pdf}  
 \caption{The impact of the number of rounds on the active sensors ratio for 150 deployed nodes }
 \label{fig44}
 \end{figure} 
@@ -978,7 +978,7 @@ runs per round for 150 deployed nodes.
 
 \begin{figure}[h!]
 \centering
-\includegraphics[scale=0.5]{R2/SR.eps} 
+\includegraphics[scale=0.5]{R2/SR.pdf} 
 \caption{The percentage of stopped simulation runs compared to the number of rounds for 150 deployed nodes }
 \label{fig66}
 \end{figure} 
@@ -990,14 +990,14 @@ As shown in Figure~\ref{fig66}, when the number of primary points are increased,
 In this experiment, we study the effect of increasing the primary points to represent the area of the sensor on the energy consumed by the wireless sensor network for different network densities.  Figures~\ref{fig2EC95} and ~\ref{fig2EC50} illustrate the energy consumption for different network sizes for $Lifetime95$ and $Lifetime50$.
 \begin{figure}[h!]
 \centering
-\includegraphics[scale=0.5]{R2/EC95.eps} 
+\includegraphics[scale=0.5]{R2/EC95.pdf} 
 \caption{The Energy Consumption with $95\%-Lifetime$}
 \label{fig2EC95}
 \end{figure} 
  
 \begin{figure}[h!]
 \centering
-\includegraphics[scale=0.5]{R2/EC50.eps} 
+\includegraphics[scale=0.5]{R2/EC50.pdf} 
 \caption{The Energy Consumption with $Lifetime50$}
 \label{fig2EC50}
 \end{figure} 
@@ -1010,7 +1010,7 @@ In this experiment, we study the impact of the increase in primary points on the
 
 \begin{figure}[h!]
 \centering
-\includegraphics[scale=0.5]{R2/T.eps}  
+\includegraphics[scale=0.5]{R2/T.pdf}  
 \caption{The Execution Time(s) vs The Number of Sensors }
 \label{figt}
 \end{figure} 
@@ -1024,7 +1024,7 @@ Finally, we will study the effect of increasing the primary points on the lifeti
 
 \begin{figure}[h!]
 \centering
-\includegraphics[scale=0.5]{R2/LT95.eps}  
+\includegraphics[scale=0.5]{R2/LT95.pdf}  
 \caption{The Network Lifetime for $Lifetime95$}
 \label{fig2LT95}
 \end{figure} 
@@ -1032,7 +1032,7 @@ Finally, we will study the effect of increasing the primary points on the lifeti
 
 \begin{figure}[h!]
 \centering
-\includegraphics[scale=0.5]{R2/LT50.eps}  
+\includegraphics[scale=0.5]{R2/LT50.pdf}  
 \caption{The Network Lifetime for $Lifetime50$}
 \label{fig2LT50}
 \end{figure} 
@@ -1051,7 +1051,7 @@ In this experiment, Figure~\ref{fig333} shows  the average coverage ratio for 15
 \parskip 0pt    
 \begin{figure}[h!]
 \centering
- \includegraphics[scale=0.5] {R3/CR.eps} 
+ \includegraphics[scale=0.5] {R3/CR.pdf} 
 \caption{The coverage ratio for 150 deployed nodes}
 \label{fig333}
 \end{figure} 
@@ -1067,7 +1067,7 @@ in  order to  minimize the energy consumption and maximize the network lifetime.
 
 \begin{figure}[h!]
 \centering
-\includegraphics[scale=0.5]{R3/ASR.eps}  
+\includegraphics[scale=0.5]{R3/ASR.pdf}  
 \caption{The active sensors ratio for 150 deployed nodes }
 \label{fig444}
 \end{figure} 
@@ -1080,7 +1080,7 @@ Figure~\ref{fig666} illustrates the percentage of stopped simulation
 runs per round for 150 deployed nodes. 
 \begin{figure}[h!]
 \centering
-\includegraphics[scale=0.5]{R3/SR.eps} 
+\includegraphics[scale=0.5]{R3/SR.pdf} 
 \caption{The percentage of stopped simulation runs compared to the number of rounds for 150 deployed nodes }
 \label{fig666}
 \end{figure} 
@@ -1091,14 +1091,14 @@ In this experiment, we study the effect of the energy consumed by the wireless s
 
 \begin{figure}[h!]
 \centering
-\includegraphics[scale=0.5]{R3/EC95.eps} 
+\includegraphics[scale=0.5]{R3/EC95.pdf} 
 \caption{The Energy Consumption with $95\%-Lifetime$}
 \label{fig3EC95}
 \end{figure} 
 
 \begin{figure}[h!]
 \centering
-\includegraphics[scale=0.5]{R3/EC50.eps} 
+\includegraphics[scale=0.5]{R3/EC50.pdf} 
 \caption{The Energy Consumption with $Lifetime50$}
 \label{fig3EC50}
 \end{figure} 
@@ -1110,7 +1110,7 @@ In this experiment, we are observed the superiority of our DiLCO-16 and DiLCO-32
 
 \begin{figure}[h!]
 \centering
-\includegraphics[scale=0.5]{R3/LT95.eps}  
+\includegraphics[scale=0.5]{R3/LT95.pdf}  
 \caption{The Network Lifetime for $Lifetime95$}
 \label{fig3LT95}
 \end{figure}
@@ -1118,7 +1118,7 @@ In this experiment, we are observed the superiority of our DiLCO-16 and DiLCO-32
 
 \begin{figure}[h!]
 \centering
-\includegraphics[scale=0.5]{R3/LT50.eps}  
+\includegraphics[scale=0.5]{R3/LT50.pdf}  
 \caption{The Network Lifetime for $Lifetime50$}
 \label{fig3LT50}
 \end{figure} 
