Update by Ali

[ThesisAli.git] / CHAPITRE_04.tex

diff --git a/CHAPITRE_04.tex b/CHAPITRE_04.tex
old mode 100755 (executable)
new mode 100644 (file)
index c06ac21..9770cc7
--- a/CHAPITRE_04.tex
+++ b/CHAPITRE_04.tex
@@ -8,25 +8,6 @@
 \label{ch4}
 
 
 \label{ch4}
 
 

-\iffalse
-\section{Summary}
-\label{ch4:sec:01}
-In this chapter, a Distributed Lifetime Coverage Optimization protocol (DiLCO) to maintain
-the coverage and to improve  the  lifetime  in  wireless sensor  networks  is
-proposed.   The  area of  interest  is first  divided  into  subregions using  a
-divide-and-conquer  method and  then the  DiLCO protocol  is distributed  on the
-sensor nodes  in each  subregion. The DiLCO  combines two  efficient techniques:
-leader election  for each subregion, followed by  an optimization-based planning
-of activity  scheduling decisions for  each subregion. The proposed  DiLCO works
-into rounds during which a small  number of nodes, remaining active for sensing,
-is selected to ensure coverage so as to maximize the lifetime of wireless sensor
-network.   Each  round  consists   of  four  phases:  (i)~Information  Exchange,
-(ii)~Leader Election, (iii)~Decision, and (iv)~Sensing.  The decision process is
-carried out  by a leader node,  which solves an integer  program.  Compared with
-some existing protocols, simulation results  show that the proposed protocol can
-prolong the network lifetime and improve the coverage performance effectively.
-
-\fi

 
 \section{Introduction}
 \label{ch4:sec:01}
 
 \section{Introduction}
 \label{ch4:sec:01}


@@ -77,8 +58,7 @@ There are five possible status for each sensor node in the network:
 \subsection{Primary Point Coverage Model}
 \label{ch4:sec:02:02}
 \indent Instead of working with the coverage area, we consider for each sensor a set of points called primary points. We also assume that the sensing disk defined by a sensor is covered if all the primary points of this sensor are covered. By  knowing the  position (point  center: ($p_x,p_y$))  of  a wireless sensor node  and it's $R_s$,  we calculate the primary  points directly based on the proposed model. We  use these primary points (that can be increased or decreased if necessary)  as references to ensure that the monitored  region  of interest  is  covered by the selected  set  of sensors, instead of using all the points in the area. 
 \subsection{Primary Point Coverage Model}
 \label{ch4:sec:02:02}
 \indent Instead of working with the coverage area, we consider for each sensor a set of points called primary points. We also assume that the sensing disk defined by a sensor is covered if all the primary points of this sensor are covered. By  knowing the  position (point  center: ($p_x,p_y$))  of  a wireless sensor node  and it's $R_s$,  we calculate the primary  points directly based on the proposed model. We  use these primary points (that can be increased or decreased if necessary)  as references to ensure that the monitored  region  of interest  is  covered by the selected  set  of sensors, instead of using all the points in the area. 

-
-\indent  We can  calculate  the positions of the selected primary
+We can  calculate  the positions of the selected primary

 points in the circle disk of the sensing range of a wireless sensor
 node (see figure~\ref{fig1}) as follows:\\
 
 points in the circle disk of the sensing range of a wireless sensor
 node (see figure~\ref{fig1}) as follows:\\
 


@@ -109,22 +89,26 @@ $X_{23}=( p_x + R_s * (\frac{- 1}{2}), p_y + R_s * (\frac{\sqrt{3}}{2})) $\\
 $X_{24}=( p_x + R_s * (\frac{- 1}{2}), p_y + R_s * (\frac{-\sqrt{3}}{2})) $\\
 $X_{25}=( p_x + R_s * (\frac{1}{2}), p_y + R_s * (\frac{-\sqrt{3}}{2})) $.
 
 $X_{24}=( p_x + R_s * (\frac{- 1}{2}), p_y + R_s * (\frac{-\sqrt{3}}{2})) $\\
 $X_{25}=( p_x + R_s * (\frac{1}{2}), p_y + R_s * (\frac{-\sqrt{3}}{2})) $.
 

-\begin{figure}[h!]
+
+ 
+\begin{figure} %[h!]

 \centering
 \centering

- \begin{multicols}{3}
+ \begin{multicols}{2}

 \centering
 \centering

-\includegraphics[scale=0.20]{Figures/ch4/fig21.pdf}\\~ ~ ~ ~ ~(a)
-\includegraphics[scale=0.20]{Figures/ch4/fig22.pdf}\\~ ~ ~ ~ ~(b)
-\includegraphics[scale=0.20]{Figures/ch4/principles13.pdf}\\~ ~ ~ ~ ~(c) 
-\hfill
-\includegraphics[scale=0.20]{Figures/ch4/fig24.pdf}\\~ ~ ~(d)
-\includegraphics[scale=0.20]{Figures/ch4/fig25.pdf}\\~ ~ ~(e)
-\includegraphics[scale=0.20]{Figures/ch4/fig26.pdf}\\~ ~ ~(f)
+\includegraphics[scale=0.33]{Figures/ch4/fig21.pdf}\\~ ~ ~ ~ ~ ~ ~ ~(a)
+\includegraphics[scale=0.33]{Figures/ch4/principles13.pdf}\\~ ~ ~ ~ ~ ~(c) 
+\hfill \hfill
+\includegraphics[scale=0.33]{Figures/ch4/fig25.pdf}\\~ ~ ~ ~ ~ ~(e)
+\includegraphics[scale=0.33]{Figures/ch4/fig22.pdf}\\~ ~ ~ ~ ~ ~ ~ ~ ~(b)
+\hfill \hfill
+\includegraphics[scale=0.33]{Figures/ch4/fig24.pdf}\\~ ~ ~ ~ ~ ~ ~(d)
+\includegraphics[scale=0.33]{Figures/ch4/fig26.pdf}\\~ ~ ~ ~ ~ ~ ~(f)

 \end{multicols} 
 \caption{Wireless Sensor Node represented by (a)5, (b)9, (c)13, (d)17, (e)21 and (f)25 primary points respectively}
 \label{fig1}
 \end{figure}
 \end{multicols} 
 \caption{Wireless Sensor Node represented by (a)5, (b)9, (c)13, (d)17, (e)21 and (f)25 primary points respectively}
 \label{fig1}
 \end{figure}

-
+ 
+    

 
 
 \subsection{Main Idea}
 
 
 \subsection{Main Idea}


@@ -350,7 +334,7 @@ $w_{U}$ & $|P|^2$
 % is used to refer this table in the text
 \end{table}
 
 % is used to refer this table in the text
 \end{table}
 

-Simulations with five  different node densities going from  50 to 250~nodes were
+Simulations with five different node densities going from  50 to 250~nodes were

 performed  considering  each  time  25~randomly generated  networks,  to  obtain
 experimental results  which are relevant. The  nodes are deployed on  a field of
 interest of $(50 \times 25)~m^2 $ in such a way that they cover the field with a
 performed  considering  each  time  25~randomly generated  networks,  to  obtain
 experimental results  which are relevant. The  nodes are deployed on  a field of
 interest of $(50 \times 25)~m^2 $ in such a way that they cover the field with a