X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/ThesisAli.git/blobdiff_plain/127dd5ebfa42d2c6220639b057082517a4502c38..b191d9759ebf18d2e624b3b4704485e1187621b2:/SlidesAli/These.tex?ds=sidebyside

diff --git a/SlidesAli/These.tex b/SlidesAli/These.tex
index 4658b27..272a409 100644
--- a/SlidesAli/These.tex
+++ b/SlidesAli/These.tex
@@ -52,7 +52,7 @@
 
 \setbeamertemplate{section in toc}[sections numbered] 
 \setbeamertemplate{subsection in toc}[subsections numbered]
-
+\pagenumbering{roman}
 \AtBeginSection[]
 {
 \begin{frame}
@@ -98,20 +98,20 @@
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 02    %%
 %%%%%%%%%%%%%%%%%%%% 
-\begin{frame} {Problem Definition, Solution, and Objectives}
+\begin{frame} {Problem definition and solution}
  \vspace{-3.5em}
  \begin{figure}
-   \includegraphics[width=0.475\textwidth]{Figures/6}
+   \includegraphics[width=0.495\textwidth]{Figures/6}
    \hfill
 %   \includegraphics[width=0.475\textwidth]{Figures/8}
 %   \hfill
-   \includegraphics[width=0.475\textwidth]{Figures/10}
+   \includegraphics[width=0.495\textwidth]{Figures/10}
 %   \hfill
 %   \includegraphics[width=0.475\textwidth]{Figures/13}
 \end{figure}
 
- \begin{block}{\textcolor{white}{ MAIN QUESTION?}}
-  		How to reduce the redundancy while coverage preservation for prolong the network lifetime continuously and effectively when monitoring a certain area of interest?
+ \begin{block}{\textcolor{white}{MAIN QUESTION}}
+  		\textcolor{black}{How to minimize the energy consumption and extend the network lifetime when covering a certain area?}
 \end{block}
  \end{frame}
 
@@ -119,21 +119,26 @@
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 03    %%
 %%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{Problem Definition, Solution, and Objectives}
+\begin{frame}{Problem definition and solution}
 
-\begin{block}{\textcolor{white}{OUR SOLUTION}}
-The area of interest is divided into subregions using a divide-and conquer method and then combine two efficient techniques :
+\begin{block}{\textcolor{white}{OUR SOLUTION $\blacktriangleright$ Distributed optimization process}}
+\begin{enumerate} [i)]
+\item \bf \textcolor{black}{Division into subregions}
+\item \bf \textcolor{black}{For each subregion}
   	
+\end{enumerate}
+
  \begin{itemize}
-         \item Leader Election for each subregion.
-        % \item Activity Scheduling based optimization is planned for each subregion.
+         \item \bf \textcolor{magenta}{Leader election}
+         \item \bf \textcolor{magenta}{Activity Scheduling based optimization}
          \end{itemize}
    		
-  		\end{block} 	
+  		\end{block}
+\vspace{-1.5em} 		 	
 \begin{figure}
-   \includegraphics[width=0.475\textwidth]{Figures/div}
-   \hfill
    \includegraphics[width=0.475\textwidth]{Figures/div2}
+   \hfill
+   \includegraphics[width=0.475\textwidth]{Figures/act2}
 \end{figure}
   	
 \end{frame}
@@ -141,39 +146,39 @@ The area of interest is divided into subregions using a divide-and conquer metho
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 03.1    %%
 %%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{Problem Definition, Solution, and Objectives}
-
-\begin{block}{\textcolor{white}{OUR SOLUTION}}
- \begin{itemize}
-         %\item Leader Election for each subregion.
-         \item Activity Scheduling based optimization is planned for each subregion.
-  \end{itemize}
-   		
- \end{block} 	
-\begin{figure}
-   \includegraphics[width=0.775\textwidth]{Figures/act}
-   
-\end{figure}
-  	
-\end{frame}
+%\begin{frame}{Problem Definition, Solution, and Objectives}
+%
+%\begin{block}{\textcolor{white}{OUR SOLUTION}}
+% \begin{itemize}
+%         %\item Leader Election for each subregion.
+%         \item \bf \textcolor{magenta}{Activity Scheduling based optimization is planned for each subregion.}
+%  \end{itemize}
+%   		
+% \end{block} 	
+%\begin{figure}
+%   \includegraphics[width=0.775\textwidth]{Figures/act}
+%   
+%\end{figure}
+%  	
+%\end{frame}
 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 03.2    %%
 %%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{Problem Definition, Solution, and Objectives}
-
-\begin{block}{\textcolor{white}{Dissertation Objectives}}
-Develop energy-efficient distributed optimization protocols that should be able to:
- \begin{itemize}
-    \item Schedule node activities by optimize both coverage and lifetime.
-    \item Combine two efficient techniques: leader election and sensor activity scheduling.
-    \item Perform a distributed optimization process.
-  \end{itemize}
-   		
- \end{block} 	
-
-  	
-\end{frame}
+%\begin{frame}{Problem Definition, Solution, and Objectives}
+%
+%\begin{block}{\bf \textcolor{white}{Dissertation Objectives}}
+%\bf \textcolor{black}{Develop energy-efficient distributed optimization protocols that should be able to:}
+% \begin{itemize}
+%    \item \bf \textcolor{blue}{Schedule node activities by optimize both coverage and lifetime.}
+%    \item \bf \textcolor{blue}{Combine two efficient techniques: leader election and sensor activity scheduling.}
+%    \item \bf \textcolor{blue}{Perform a distributed optimization process.}
+%  \end{itemize}
+%   		
+% \end{block} 	
+%
+%  	
+%\end{frame}
 
 
 %%%%%%%%%%%%%%%%%%%%
@@ -211,9 +216,9 @@ Develop energy-efficient distributed optimization protocols that should be able
     \begin{femtoBlock}	
 	{Sensor \\}
 		 \begin{itemize}
-  			\item  Electronic Low-cost tiny device.
-  			\item Sense, process and transmit data.
-  			\item Limited energy, memory and processing capabilities.
+  			\item Electronic low-cost tiny device
+  			\item Sense, process and transmit data
+  			\item Limited energy, memory and processing capabilities
   		\end{itemize}
 	\end{femtoBlock}
 	 
@@ -226,18 +231,7 @@ Develop energy-efficient distributed optimization protocols that should be able
      \begin{figure}[!t]
            \includegraphics[height = 2cm]{Figures/sn.jpg}
      \end{figure}  
-    
-    
- % \begin{femtoBlock} {}%	{SOME APPLICATIONS OF WSNs \\}
-  
-%		\includegraphics[height =1 cm]{1.png}
-%		\includegraphics[height =1cm]{2.png}\\
-%	     \includegraphics[height =1cm]{5.jpg}
-%	     \includegraphics[height = 1cm]{traffic.jpg}
-%   	     \includegraphics[height = 1cm]{3.png}
-%
-
- %	\end{femtoBlock}
+   
 	
 \end{columns}
 
@@ -295,6 +289,8 @@ Develop energy-efficient distributed optimization protocols that should be able
 
      \includegraphics[height = 5cm]{Figures/WSN-M.pdf}
  \end{figure} 
+ \vspace{-1.0em}
+ \bf \textcolor{blue} {Our approach includes cluster architecture and scheduling schemes}
 \end{frame}
 
 %\begin{frame}{Energy-Efficient Mechanisms of a working WSN}
@@ -308,21 +304,23 @@ Develop energy-efficient distributed optimization protocols that should be able
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 10    %%
 %%%%%%%%%%%%%%%%%%%%
-\begin{frame}{Network Lifetime}
+\begin{frame}{Network lifetime}
 \vspace{-1.5em}
-\begin{block}{\textcolor{white} {Some network lifetime defintions:}}
+\begin{block}{\textcolor{white} {Some definitions}}
+\small
 \begin{enumerate}[i)]
-\item \small Time spent until death of the first sensor ( or cluster head ).
-\item Time spent until death of all wireless sensor nodes in WSN.
-\item  Time spent by WSN in covering each target by at least one sensor.
-\item  Time during which the area of interest is covered by at least k nodes.
-\item Elapsed time until losing the connectivity or the coverage.
+\item \textcolor{black} {Time spent until death of the first sensor (or cluster head)}
+\item \textcolor{black} {Time spent until death of all wireless sensor nodes in WSN}
+\item  \textcolor{black} {Time spent by WSN in covering each target by at least one sensor}
+\item  \textcolor{black} {Time during which the area of interest is covered by at least k nodes}
+\item \textcolor{black} {Elapsed time until losing the connectivity or the coverage}
+\item \bf \textcolor{red} {Time elapsed until the coverage ratio becomes less than a predetermined threshold $\alpha$}
 \end{enumerate}
 \end{block}
 
-\begin{block}{\textcolor{white} {Network lifetime In this dissertation:}}
-Time elapsed until the coverage ratio becomes less than a predetermined threshold $\alpha$.
-\end{block}
+%\begin{block}{\textcolor{white} {Network lifetime In this dissertation:}}
+%\textcolor{blue} {Time elapsed until the coverage ratio becomes less than a predetermined threshold $\alpha$.}
+%\end{block}
 
 
 \end{frame}
@@ -332,231 +330,244 @@ Time elapsed until the coverage ratio becomes less than a predetermined threshol
 %%%%%%%%%%%%%%%%%%%%
 \begin{frame}{Coverage in Wireless Sensor Networks}
  
-\begin{block} <1-> {\textcolor{white} {Coverage Definition:}} 
-\textcolor{blue} {Coverage} reflects how well a sensor field is monitored efficiently using as less energy as possible.
+\begin{block} <1-> {\textcolor{white} {Coverage definition}} 
+\textcolor{blue} {Coverage} reflects how well a sensor field is monitored efficiently using as less energy as possible
 \end{block}
  
 
  
-\begin{block} <2-> {\textcolor{white} {Coverage Types:}} 
-\begin{enumerate}
-\item \small \textcolor{blue} {Area coverage:} every point inside an area has to be monitored.
-\item \textcolor{blue} {Target coverage:} is to cover only a finite number of discrete points called targets.
+\begin{block} <2-> {\textcolor{white} {Coverage types}} 
+\begin{enumerate}[i)]
+\item \small  \textcolor{red} {Area coverage $\blacktriangleright$ every point inside an area has to be monitored}
+\item  \textcolor{blue} {Target coverage} $\blacktriangleright$ only a finite number of discrete points called targets have to be monitored
 
-\item \textcolor{blue} {Barrier coverage:} is to detect targets as they cross a barrier such as in intrusion detection and border surveillance applications.
+\item  \textcolor{blue} {Barrier coverage} $\blacktriangleright$ detection of targets as they cross a barrier such as in intrusion detection and border surveillance applications
 \end{enumerate}
 \end{block}
  
 
  
-\begin{block} <3-> {\textcolor{white} {Coverage type in this dissertation:}} 
-The work presented in this dissertation deals with area coverage.
-\end{block}
+%\begin{block} <3-> {\textcolor{white} {Coverage type in this dissertation:}} 
+%The work presented in this dissertation deals with \textcolor{red} {area coverage}.
+%\end{block}
  
 \end{frame}
 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 11    %%
 %%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{Existing Works}
+\begin{frame}{Existing works}
 \vspace{-0.3em}
-\begin{block}  {\textcolor{white} {Coverage Approaches:}} 
-Most existing coverage approaches in literature classified into
-\begin{enumerate}[A)]
-\item  Full centralized coverage algorithms.
+\begin{block}  {\textcolor{white} {Coverage approaches}} 
+%Most existing coverage approaches in literature classified into
+\begin{enumerate}[i)]
+\item \textcolor{blue} { Full centralized coverage algorithms}
     \begin{itemize}
-    \item  Optimal or near optimal solution.
-    \item  low computation power for the sensors (except for base station).
-    \item  High  communication overhead.
-    \item  Not scalable for large WSNs.
+    \item  Optimal or near optimal solution
+    \item  Low computation power for the sensors (except for base station)
+    \item  Higher energy consumption for communication in large WSN
+    \item  Not scalable for large WSNs
     \end{itemize}
-\item Full distributed coverage algorithms.
+\item \textcolor{blue} {Full distributed coverage algorithms}
+   \begin{itemize}
+    \item  Lower quality solution
+    \item Less energy consumption for communication in large WSN
+    \item  Reliable and scalable for large WSNs
+   \end{itemize}
+   \item  \textcolor{red} {Hybrid approaches}
    \begin{itemize}
-    \item  Lower quality solution.
-    \item  High communication overhead especially for dense WSNs.
-    \item  Reliable and scalable for large WSNs.
+   \item \textcolor{red} {Globally distributed and locally centralized}
    \end{itemize}
+   
 \end{enumerate}
 
 \end{block}
  
 
-\begin{block} {\textcolor{white} {Coverage protocols in this dissertation:}} 
-The protocols presented in this dissertation combine between the two above approaches.
-\end{block}
+%\begin{block} {\textcolor{white} {Coverage protocols in this dissertation:}} 
+%The protocols presented in this dissertation combine between the two above approaches.
+%\end{block}
  
 
 \end{frame}
 
+\begin{frame}{Existing works $\blacktriangleright$ DESK algorithm (Vu et al.)}
+\vspace{-1.5em}
+\begin{figure}[!t]
+	   \includegraphics[height = 4.0cm]{Figures/DESK.eps}
+    \end{figure}  
+     \vspace{-2.5em}
+     
+     \begin{itemize}
+       \item Requires only one-hop neighbor information (fully distributed)
+       \item Each sensor decides its status (Active or Sleep) based on the perimeter coverage model, without optimization
+              
+\end{itemize}
 
-%%%%%%%%%%%%%%%%%%%%
-%%    SLIDE 12    %%
-%%%%%%%%%%%%%%%%%%%% 
-\section{\small {Distributed Lifetime Coverage Optimization Protocol (DiLCO)}}
 
+%\tiny \bf \textcolor{blue}{DESK is chosen for comparison because it works into rounds fashion similar to our approaches, as well as DESK is a full distributed coverage approach.}
 
-%%%%%%%%%%%%%%%%%%%%
-%%    SLIDE 13    %%
-%%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{\small DiLCO Protocol $\blacktriangleright$ Assumptions and Network Model:}
-\vspace{-0.5cm}
 
+\end{frame}
 
-\begin{femtoBlock} {} %{Assumptions and Network Model:}
- 
-	\begin{columns}[c]
-	
-    \column{.50\textwidth}
-    
-  	\vspace{-1.0cm}
+\begin{frame}{Existing works $\blacktriangleright$ GAF algorithm (Xu et al.)}
+
+\vspace{-3.3em}
+ \begin{columns}[c]
+  
+\column{.58\textwidth}
+
+     \begin{figure}[!t]
+           \includegraphics[height = 2.7cm]{Figures/GAF1.eps}
+    \end{figure}  
+    \vspace{-2.5em}
+    \begin{figure}[!t]
+	   \includegraphics[height = 3.3cm]{Figures/GAF2.eps}
+    \end{figure}
+	 
+	\column{.52\textwidth}
+	 \vspace{1.2em}
+\small
+	\begin{itemize}
+	\item Distributed energy-based scheduling approach
+  	\item Uses geographic location information to divide the area into a fixed square grids
+  	\item Nodes are in one of three sates $\blacktriangleright$ discovery, active, or sleep
+  	\item  Only one node staying active in grid
+  	\item  The fixed grid is square with r units on a side
+  	 \item  Nodes cooperate within each grid to choose the active node
+  	\end{itemize}
   	
-  		\begin{enumerate} [$\divideontimes$]
-  		    \item Static Wireless Sensors.
-  			\item  Uniform deployment.  
-  			\item  High density deployment.
-  			\item  Homogeneous in terms of: 
+	   
+      
+%     \begin{itemize}
+%       \item \tiny enat: estimated node active time
+%       \item enlt: estimated node lifetime
+%       \item Td,Ta, Ts: discovery, active, and sleep timers
+%       \item Ta = enlt/2 
+%       \item Ts = [enat/2, enat]
+%     \end{itemize}
+     
+
+	
+\end{columns}
+
+\vspace{1.0em}
+
+%\tiny \bf \textcolor{blue}{GAF is chosen for comparison because it is famous and easy to implement, as well as many authors referred to it in many publications.}
+\end{frame}
+
+\section{\small {The main scheme for our protocols}}
+
+
+\begin{frame}{Assumptions for our protocols}
+\vspace{-0.1cm}
+
+\begin{enumerate} [$\divideontimes$]
+  		    \item  Static wireless sensor, homogeneous in terms of  
              \begin{itemize}
-             \item Sensing, Communication, and Processing capabilities
+             \item Sensing, communication, and processing capabilities
              \end{itemize}
-  			\item  Heterogeneous Energy.
-  			 \item Its $R_c\geq 2R_s$.
-  			 \item  Multi-hop communication.
-  			 \item  Know Its location by:
+  			\item  Heterogeneous initial energy
+  			\item  High density uniform deployment 
+  			 \item $R_c\geq 2R_s$   complete coverage $\Rightarrow$ connectivity (proved by Zhang and Zhou)
+
+  			 \item  Multi-hop communication
+  			 \item  Known location by 
     \begin{itemize}
-     \item Embedded GPS  or
-     \item Location Discovery Algorithm.           
+     \item Embedded GPS  or location discovery algorithm          
     \end{itemize}
-  		\end{enumerate}		
-  		
-	
-  		
-  	\column{.50\textwidth}
-  	\begin{enumerate} [$\divideontimes$]
-    	\item Using two kinds of packet: 
+    
+    \item Using two kinds of packets  
         \begin{itemize}    	
-    	   \item INFO packet.
-    	   \item ActiveSleep packet.
+    	   \item INFO packet
+    	   \item ActiveSleep packet
         \end{itemize}
-        \item Five status for each node:
+        \item Five status for each node 
         \begin{itemize}    	
-    	   \item  LISTENING, ACTIVE, SLEEP, COMPUTATION, and COMMUNICATION.
+    	   \item  \small LISTENING, ACTIVE, SLEEP, COMPUTATION, and COMMUNICATION
         \end{itemize}
-  	\end{enumerate}		
-  	
-  	\begin{femtoBlock} { \small Primary point coverage model}
-  	\vspace{-1.2cm}
-  	\begin{center}
-  	  	 \includegraphics[height = 4.0cm]{Figures/fig21.pdf}
-  	  	 
-   	\end{center}
-  	\end{femtoBlock}
+  		\end{enumerate}		
   		
-  	\end{columns}
-	\end{femtoBlock}
-	
 \end{frame}
 
 
-%%%%%%%%%%%%%%%%%%%%
-%%    SLIDE 14    %%
-%%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{\small DiLCO Protocol $\blacktriangleright$ Main Idea}
-%\vspace{-3.2cm}
-\begin{femtoBlock} {}%{Main Idea:\\}
-\centering
-\includegraphics[height = 2.5cm]{Figures/OneSensingRound.jpg}
 
-\vspace{1.2cm}
-\begin{enumerate}
-\item \textcolor{blue}{ \textbf{INFORMATION EXCHANGE:}}\\ 
-Sensors exchanges through multi-hop communication, their:
-\begin{itemize}
-\item Position coordinates, 
-\item current remaining energy, 
-\item sensor node ID, and 
-\item number of its one-hop live neighbors.
-\end{itemize}
+\begin{frame}{Assumptions for our protocols}
+  \vspace{-0.5cm}
+\begin{center}
+  	\includegraphics[height = 7.0cm]{Figures/Pmodels.pdf}  
+\end{center}
 
+\end{frame}
 
-\end{enumerate}
 
-\end{femtoBlock}
+
+
+\begin{frame}{General scheme}
+\vspace{-0.2cm}
+\begin{figure}[ht!]
+ \includegraphics[width=110mm]{Figures/GeneralModel.jpg}
+ \end{figure} 
+ 
+\begin{itemize}
+\item DiLCO and PeCO  $\blacktriangleright$ one round sensing ($T=1$)
+\item MuDiLCO $\blacktriangleright$ multiple rounds sensing ($T=1\cdots T$)
+\end{itemize}
+
 \end{frame}
 
 
-%%%%%%%%%%%%%%%%%%%%
-%%    SLIDE 14.1    %%
-%%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{\small DiLCO Protocol $\blacktriangleright$ Main Idea}
-%\vspace{-3.2cm}
-\begin{femtoBlock} {}%{Main Idea:\\}
+\begin{frame}{General scheme}
+  \vspace{-0.2cm}
+\begin{enumerate} [i)]
+\item \textcolor{blue}{\textbf{INFORMATION EXCHANGE}} $\blacktriangleright$ Sensors exchange through multi-hop communication, their
+\begin{itemize}
+\item \textcolor{magenta}{Position coordinates}, \textcolor{violet}{current remaining energy}, \textcolor{cyan}{sensor node ID}, and \textcolor{red}{number of its one-hop live neighbors}
+ 
+\end{itemize}
 
-\begin{enumerate} [2.]
 
-\item \textcolor{blue}{ \textbf{   LEADER ELECTION:}}\\
-The selection criteria are, in order of importance:
+\item \textcolor{blue}{\textbf{LEADER ELECTION}} $\blacktriangleright$ The selection criteria are, in order 
 \begin{itemize}
-\item   larger number of neighbors, 
-\item larger remaining energy, and then in case of equality, 
-\item larger ID. 
+\item Larger number of neighbors
+\item Larger remaining energy, and then in case of equality 
+\item Larger ID
 \end{itemize}
-\end{enumerate}
 
-\begin{enumerate} [3.]
-\item \textcolor{blue}{ \textbf{   DECISION:}} \\
-Leader solves an integer program(see next slide) to:
+
+ 
+\item \textcolor{blue}{\textbf{DECISION}} $\blacktriangleright$ Leader solves an integer program to
 \begin{itemize}
-\item  Select which sensors will be activated in the sensing phase.
-\item Send Active-Sleep packet to each sensor in the subregion.
+\item  Select which sensors will be activated in the sensing phase
+\item Send Active-Sleep packet to each sensor in the subregion
 \end{itemize}
-\end{enumerate}
-\begin{enumerate} [4.]
-\item \textcolor{blue}{ \textbf{   SENSING:}} \\
-Based on Active-Sleep Packet Information:
+
+ 
+\item \textcolor{blue}{\textbf{SENSING}} $\blacktriangleright$ Based on Active-Sleep Packet Information
 \begin{itemize}
-\item Active sensors will execute their sensing task.
-\item Sleep sensors will wait a time equal to the period of sensing to wakeup.
+\item Active sensors will execute their sensing task
+\item Sleep sensors will wait a time equal to the period of sensing to wakeup
 
 \end{itemize}
-
 \end{enumerate}
-
-\end{femtoBlock}
+ 
 \end{frame}
 
 
+
 %%%%%%%%%%%%%%%%%%%%
-%%    SLIDE 15    %%
+%%    SLIDE 12    %%
 %%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{\small DiLCO Protocol $\blacktriangleright$ Coverage Problem Formulation}
-\begin{femtoBlock} { }
-\noindent Our coverage optimization problem can then be formulated as follows:
-\begin{equation*} \label{eq:ip2r}
-\left \{
-\begin{array}{ll}
-\min \sum_{p \in P} (w_{\theta} \Theta_{p} + w_{U} U_{p})&\\
-\textrm{subject to :}&\\
-\sum_{j \in J}  \alpha_{jp} X_{j} - \Theta_{p}+ U_{p} =1, &\forall p \in P\\
-%\label{c1} 
-%\sum_{t \in T} X_{j,t} \leq \frac{RE_j}{e_t} &\forall j \in J \\
-%\label{c2}
-\Theta_{p}\in \mathbb{N}, &\forall p \in P\\
-U_{p} \in \{0,1\}, &\forall p \in P \\
-X_{j} \in \{0,1\}, &\forall j \in J
-\end{array}
-\right.
-\end{equation*}
+\section{\small {Distributed Lifetime Coverage Optimization Protocol (DiLCO)}}
 
-\begin{itemize}
-\item $X_{j}$ :  indicates whether or not the sensor $j$  is actively sensing (1
-  if yes and 0 if not);
-\item $\Theta_{p}$  : {\it overcoverage}, the  number of sensors  minus one that
-  are covering the primary point $p$;
-\item $U_{p}$ : {\it undercoverage},  indicates whether or not the primary point
-  $p$ is being covered (1 if not covered and 0 if covered).
-\end{itemize}
 
-\end{femtoBlock}
+%%%%%%%%%%%%%%%%%%%%
+%%    SLIDE 15    %%
+%%%%%%%%%%%%%%%%%%%% 
+\begin{frame}{\small DiLCO protocol $\blacktriangleright$ Coverage problem formulation}
+\vspace{0.2cm}
+\centering
+\includegraphics[height = 7.2cm]{Figures/modell1.pdf}
 
 \end{frame}
 
@@ -564,7 +575,7 @@ X_{j} \in \{0,1\}, &\forall j \in J
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 16    %%
 %%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{\small DiLCO Protocol $\blacktriangleright$ DiLCO Protocol Algorithm}
+\begin{frame}{\small DiLCO protocol $\blacktriangleright$ DiLCO protocol algorithm}
 %\begin{femtoBlock} {}
 \centering
 %\includegraphics[height = 7.2cm]{Figures/algo.jpeg}
@@ -579,11 +590,11 @@ X_{j} \in \{0,1\}, &\forall j \in J
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 18    %%
 %%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{\small DiLCO Protocol $\blacktriangleright$ Simulation Framework}
+\begin{frame}{\small DiLCO protocol $\blacktriangleright$ Simulation framework}
 \vspace{-0.8cm}
 \small
 \begin{table}[ht]
-\caption{Relevant parameters for network initializing.}
+\caption{Relevant parameters for simulation}
 \centering
 \begin{tabular}{c|c}
 \hline
@@ -611,9 +622,9 @@ Network Simulator & Discrete Event Simulator OMNeT++
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 19    %%
 %%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{\small DiLCO Protocol $\blacktriangleright$ Energy Model \& Performance Metrics }
+\begin{frame}{\small DiLCO protocol $\blacktriangleright$ Energy model \& performance metrics }
 %\vspace{-1.8cm}
-\begin{femtoBlock} {Energy Consumption Model}
+\begin{femtoBlock} {Energy consumption model}
 \vspace{-1.0cm}
 \begin{table}[h]
 %\centering
@@ -636,14 +647,15 @@ Network Simulator & Discrete Event Simulator OMNeT++
 
 \end{femtoBlock}
 \vspace{-0.5cm}
-\begin{femtoBlock} {Performance Metrics}
+\begin{femtoBlock} {Performance metrics}
 \small
-\begin{enumerate}[$\mapsto$]
-\item {{\bf Network Lifetime}}
+\begin{enumerate}[$\blacktriangleright$]
+
 \item {{\bf Coverage Ratio (CR)}}
-\item {{\bf  Energy Consumption}}
-\item{{\bf Number of Active Sensors Ratio (ASR)}} 
-\item {{\bf Execution Time}}
+\item {{\bf Number of Active Sensors Ratio (ASR)}}
+\item {{\bf Energy consumption}}
+\item {{\bf Network lifetime}}
+%\item {{\bf Execution Time}}
 %\item {{\bf Stopped Simulation Runs}}
 
 \end{enumerate}
@@ -655,7 +667,7 @@ Network Simulator & Discrete Event Simulator OMNeT++
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 20    %%
 %%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{ \small DiLCO Protocol $\blacktriangleright$ Performance Comparison}
+\begin{frame}{ \small DiLCO protocol $\blacktriangleright$ Performance comparison}
 
 \vspace{-0.5cm}
 \begin{figure}[h!]
@@ -674,7 +686,7 @@ Network Simulator & Discrete Event Simulator OMNeT++
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 20    %%
 %%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{ \small DiLCO Protocol $\blacktriangleright$ Performance Comparison}
+\begin{frame}{ \small DiLCO protocol $\blacktriangleright$ Performance comparison}
 \vspace{-0.5cm}
 
 \begin{figure}[h!]
@@ -703,7 +715,7 @@ Network Simulator & Discrete Event Simulator OMNeT++
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 22    %%
 %%%%%%%%%%%%%%%%%%%%
-\begin{frame}{ \small DiLCO Protocol $\blacktriangleright$ Performance Comparison}
+\begin{frame}{ \small DiLCO protocol $\blacktriangleright$ Performance comparison}
 \vspace{-0.5cm}
 \begin{figure}%[h!]
 \begin{columns}[c]
@@ -725,7 +737,7 @@ Network Simulator & Discrete Event Simulator OMNeT++
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 23    %%
 %%%%%%%%%%%%%%%%%%%%
-\begin{frame}{ \small DiLCO Protocol $\blacktriangleright$ Performance Comparison}
+\begin{frame}{ \small DiLCO protocol $\blacktriangleright$ Performance comparison}
 \vspace{-0.5cm}
 \begin{figure}%[h!]
 \begin{columns}[c]
@@ -756,75 +768,43 @@ Network Simulator & Discrete Event Simulator OMNeT++
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 28    %%
 %%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{\small MuDiLCO Protocol $\blacktriangleright$ Main Idia}
-\vspace{-0.2cm}
-\begin{figure}[ht!]
- \includegraphics[width=110mm]{Figures/GeneralModel.jpg}
-\caption{MuDiLCO protocol.}
-\label{fig2}
-\end{figure} 
-\end{frame}
+%\begin{frame}{\small MuDiLCO Protocol $\blacktriangleright$ Main Idea}
+%\vspace{-0.2cm}
+%\begin{figure}[ht!]
+% \includegraphics[width=110mm]{Figures/GeneralModel.jpg}
+%\caption{MuDiLCO protocol.}
+%\label{fig2}
+%\end{figure} 
+%\end{frame}
 
 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 29    %%
 %%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{\small MuDiLCO Protocol $\blacktriangleright$  Multiround Coverage Problem Formulation}
+\begin{frame}{\small MuDiLCO protocol $\blacktriangleright$  Multiround coverage problem Formulation}
 \vspace{0.2cm}
-\small
-Our coverage optimization problem can then be formulated as follows
-\vspace{-0.2cm}
-\begin{equation*}
- \min \sum_{t=1}^{T} \sum_{p=1}^{P} \left(W_{\theta}* \Theta_{t,p} + W_{U} * U_{t,p}  \right)  \label{eq15} 
-\end{equation*}
-
-Subject to
-\vspace{-0.2cm}
-\begin{equation*}
-  \sum_{j=1}^{|J|} \alpha_{j,p} * X_{t,j}   = \Theta_{t,p} - U_{t,p} + 1 \label{eq16} \hspace{6 mm} \forall p \in P, t = 1,\dots,T
-\end{equation*}
-
-\begin{equation*}
-  \sum_{t=1}^{T}  X_{t,j}   \leq  \lfloor {RE_{j}/E_{th}} \rfloor \hspace{6 mm} \forall j \in J, t = 1,\dots,T
-  \label{eq144} 
-\end{equation*}
-
-\begin{equation*}
-X_{t,j} \in \lbrace0,1\rbrace,   \hspace{10 mm} \forall j \in J, t = 1,\dots,T \label{eq17} 
-\end{equation*}
-
-\begin{equation*}
-U_{t,p} \in \lbrace0,1\rbrace, \hspace{10 mm}\forall p \in P, t = 1,\dots,T  \label{eq18} 
-\end{equation*}
-
-\begin{equation*}
- \Theta_{t,p} \geq 0 \hspace{10 mm}\forall p \in P, t = 1,\dots,T \label{eq178}
-\end{equation*}
-
-
-
-
 
+\centering
+\includegraphics[height = 7.2cm]{Figures/modell2.pdf}
 
 \end{frame}
 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 30    %%
 %%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{\small MuDiLCO Protocol $\blacktriangleright$ MuDiLCO Protocol Algorithm}
-%\vspace{0.2cm}
-\begin{femtoBlock} {}
-\centering
-%\includegraphics[height = 7.2cm]{Figures/algo2.jpeg}
-\includegraphics[height = 7.2cm]{Figures/Algo2.png}
-\end{femtoBlock}
-\end{frame}
+%\begin{frame}{\small MuDiLCO Protocol $\blacktriangleright$ MuDiLCO Protocol Algorithm}
+%%\vspace{0.2cm}
+%\begin{femtoBlock} {}
+%\centering
+%\includegraphics[height = 7.2cm]{Figures/Algo2.png}
+%\end{femtoBlock}
+%\end{frame}
 
 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 31    %%
 %%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{\small MuDiLCO Protocol $\blacktriangleright$ Results Analysis and Comparison}
+\begin{frame}{\small MuDiLCO protocol $\blacktriangleright$ Results analysis and comparison}
 \vspace{-0.5cm}
 \begin{figure}[h!]
 \centering
@@ -838,7 +818,7 @@ U_{t,p} \in \lbrace0,1\rbrace, \hspace{10 mm}\forall p \in P, t = 1,\dots,T  \la
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 32    %%
 %%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{\small MuDiLCO Protocol $\blacktriangleright$ Results Analysis and Comparison}
+\begin{frame}{\small MuDiLCO protocol $\blacktriangleright$ Results analysis and comparison}
 \vspace{-0.5cm}
 \begin{figure}[h!]
 \centering
@@ -865,21 +845,21 @@ U_{t,p} \in \lbrace0,1\rbrace, \hspace{10 mm}\forall p \in P, t = 1,\dots,T  \la
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 34    %%
 %%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{\small MuDiLCO Protocol $\blacktriangleright$ Results Analysis and Comparison}
-\vspace{-0.5cm}
-\begin{figure}[h!]
-\centering
-\includegraphics[scale=0.5]{Figures/R1/T.pdf}  
-\caption{Execution Time (in seconds)}
-\label{fig77}
-\end{figure} 
-\end{frame}
+%\begin{frame}{\small MuDiLCO Protocol $\blacktriangleright$ Results Analysis and Comparison}
+%\vspace{-0.5cm}
+%\begin{figure}[h!]
+%\centering
+%\includegraphics[scale=0.5]{Figures/R1/T.pdf}  
+%\caption{Execution Time (in seconds)}
+%\label{fig77}
+%\end{figure} 
+%\end{frame}
 
 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 35    %%
 %%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{\small MuDiLCO Protocol $\blacktriangleright$ Results Analysis and Comparison}
+\begin{frame}{\small MuDiLCO protocol $\blacktriangleright$ Results analysis and comparison}
 \vspace{-0.5cm}
 \begin{figure}%[h!]
 \begin{columns}[c]
@@ -899,7 +879,7 @@ U_{t,p} \in \lbrace0,1\rbrace, \hspace{10 mm}\forall p \in P, t = 1,\dots,T  \la
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 36    %%
 %%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{\small MuDiLCO Protocol $\blacktriangleright$ Results Analysis and Comparison}
+\begin{frame}{\small MuDiLCO protocol $\blacktriangleright$ Results analysis and comparison}
 \vspace{-0.5cm}
 \begin{figure}%[h!]
 \begin{columns}[c]
@@ -919,14 +899,13 @@ U_{t,p} \in \lbrace0,1\rbrace, \hspace{10 mm}\forall p \in P, t = 1,\dots,T  \la
 
 
 
-\section{\small {Perimeter-based Coverage Optimization (PeCO) to Improve Lifetime in WSNs
-}}
+\section{\small {Perimeter-based Coverage Optimization (PeCO)}}
 
 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 45    %%
 %%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{\small PeCO Protocol $\blacktriangleright$ Assumptions and Models}
+\begin{frame}{\small PeCO protocol $\blacktriangleright$ Assumptions and models}
 
 \vspace{-0.5cm}
 \begin{figure}%[h!]
@@ -950,22 +929,27 @@ $$\alpha =  \arccos \left(\dfrac{Dist(u,v)}{2R_s}
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 46    %%
 %%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{\small PeCO Protocol $\blacktriangleright$ Assumptions and Models}
+\begin{frame}{\small PeCO protocol $\blacktriangleright$ Assumptions and models}
 
-\vspace{-0.5cm}
+\vspace{-1.2cm}
 \begin{figure}%[h!]
-\begin{columns}[c]
-	\column{.50\textwidth}
-\includegraphics[scale=0.33]{Figures/ch6/expcm2.jpg}  
-\footnotesize \\~~~~~~~~~~~~~~~~~~~~~~~~~~(a)\\	
-\column{.50\textwidth}
-\includegraphics[scale=0.38]{Figures/tbl.jpeg} 
-\footnotesize \\~~~~~~~~~~~~~~~~~~~~~~~~~~(b)	\\
-\end{columns}
-\caption{(a) Maximum coverage levels for perimeter of sensor node $0$. and (b) Coverage intervals and contributing sensors for sensor node 0.}
-  \label{pcm2sensors}
+%\begin{columns}[c]
+%	\column{.50\textwidth}
+\includegraphics[scale=0.6]{Figures/ch6/expcm2.jpg}  
+%\footnotesize \\~~~~~~~~~~~~~~~~~~~~~~~~~~(a)\\	
+%\column{.50\textwidth}
+%\includegraphics[scale=0.38]{Figures/tbl.jpeg} 
+%\footnotesize \\~~~~~~~~~~~~~~~~~~~~~~~~~~(b)	\\
+%\end{columns}
+%\caption{(a) Maximum coverage levels for perimeter of sensor node $0$. and (b) Coverage intervals and contributing sensors for sensor node 0.}
+%  \label{pcm2sensors}
 \end{figure}
 
+\vspace{-0.9cm}
+\textcolor {red} {Set of sensors involved in coverage interval of sensor 0 between 3R to 4R $\Rightarrow$ [0,1,2,4]\\
+Maximum coverage level: 4 
+}%$a^0_{i0}= 1$
+%For example, the interval between 3R to 4R is covered by 4 sensors (0,1,2,4), it means the coverage level is 4
 
 \end{frame}
 
@@ -974,7 +958,7 @@ $$\alpha =  \arccos \left(\dfrac{Dist(u,v)}{2R_s}
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 47    %%
 %%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{\small PeCO Protocol $\blacktriangleright$ PeCO Protocol Algorithm}
+\begin{frame}{\small PeCO protocol $\blacktriangleright$ PeCO protocol algorithm}
 \vspace{-0.7cm}
 %\includegraphics[height = 7.2cm]{Figures/algo6.jpeg}
 
@@ -988,12 +972,12 @@ $$\alpha =  \arccos \left(\dfrac{Dist(u,v)}{2R_s}
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 48    %%
 %%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{\small PeCO Protocol $\blacktriangleright$ Perimeter-based Coverage Problem Formulation}
-\vspace{-1.1cm}
+\begin{frame}{\small PeCO protocol $\blacktriangleright$ Perimeter-based coverage problem formulation}
+\vspace{-0.72cm}
 
 \begin{figure}[h!]
 \centering
-\includegraphics[scale=0.5]{Figures/ch6/formula6.png}  
+\includegraphics[scale=0.5]{Figures/modell3.pdf}  
 \end{figure} 
 
 \end{frame}
@@ -1003,7 +987,7 @@ $$\alpha =  \arccos \left(\dfrac{Dist(u,v)}{2R_s}
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE     %%
 %%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{\small PeCO Protocol $\blacktriangleright$ Performance Evaluation and Analysis}
+\begin{frame}{\small PeCO protocol $\blacktriangleright$ Performance evaluation and analysis}
 \vspace{-0.5cm}
 \begin{figure}[h!]
 \centering
@@ -1012,12 +996,13 @@ $$\alpha =  \arccos \left(\dfrac{Dist(u,v)}{2R_s}
 \label{fig333}
 \end{figure} 
 
+
 \end{frame}
 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE     %%
 %%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{\small PeCO Protocol $\blacktriangleright$ Performance Evaluation and Analysis}
+\begin{frame}{\small PeCO protocol $\blacktriangleright$ Performance evaluation and analysis}
 \vspace{-0.5cm}
 \begin{figure}[h!]
 \centering
@@ -1031,7 +1016,7 @@ $$\alpha =  \arccos \left(\dfrac{Dist(u,v)}{2R_s}
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE     %%
 %%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{\small PeCO Protocol $\blacktriangleright$ Performance Evaluation and Analysis}
+\begin{frame}{\small PeCO protocol $\blacktriangleright$ Performance evaluation and analysis}
 \vspace{-0.5cm}
 \begin{figure}%[h!]
 \begin{columns}[c]
@@ -1052,7 +1037,7 @@ $$\alpha =  \arccos \left(\dfrac{Dist(u,v)}{2R_s}
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE     %%
 %%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{\small PeCO Protocol $\blacktriangleright$ Performance Evaluation and Analysis}
+\begin{frame}{\small PeCO protocol $\blacktriangleright$ Performance evaluation and analysis}
 \vspace{-0.5cm}
 \begin{figure}%[h!]
 \begin{columns}[c]
@@ -1063,7 +1048,7 @@ $$\alpha =  \arccos \left(\dfrac{Dist(u,v)}{2R_s}
 \includegraphics[scale=0.35]{Figures/ch6/R/LT50.eps} 
 \footnotesize \\~~~~~~~~~~~~~~~~~~~~~~~~~~~~~(b)	\\
 \end{columns}
-\caption{Network Lifetime for (a)~$Lifetime_{95}$ and (b)~$Lifetime_{50}$.}
+\caption{Network lifetime for (a)~$Lifetime_{95}$ and (b)~$Lifetime_{50}$.}
   \label{fig3LT}
 \end{figure}
 
@@ -1086,7 +1071,7 @@ $$\alpha =  \arccos \left(\dfrac{Dist(u,v)}{2R_s}
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE     %%
 %%%%%%%%%%%%%%%%%%%% 
-\section{\small {Conclusion and Perspectives}}
+\section{\small {Conclusion and perspectives}}
 
 
 %%%%%%%%%%%%%%%%%%%%
@@ -1097,20 +1082,19 @@ $$\alpha =  \arccos \left(\dfrac{Dist(u,v)}{2R_s}
 
 \item  Two-step approaches are proposed to optimize both coverage and lifetime performances, where:
 \begin{itemize}
-\item Sensing field is divided into smaller subregions using divide-and-conquer method.
-\item One of the proposed optimization protocols is applied in each subregion in a distributed parallel way.
+\item Sensing field is divided into smaller subregions using divide-and-conquer method
+\item One of the proposed optimization protocols is applied in each subregion in a distributed parallel way
 \end{itemize}
-\item The proposed protocols (DiLCO, MuDiLCO, PeCO) combine two efficient mechanisms: 
+\item The proposed protocols (DiLCO, MuDiLCO, PeCO) combine two efficient mechanisms 
 \begin{itemize}
 \item Network leader election, and
-\item Sensor activity scheduling based optimization.
+\item Sensor activity scheduling based optimization
 \end{itemize}
-\item Our protocols are periodic where each period consists of 4
-phases:
+\item Our protocols are periodic where each period consists of 4 phases
 \begin{itemize}
-\item Information exchange,
-\item Network leader election, 
-\item Decision based optimization, and
+\item Information exchange
+\item Network leader election
+\item Decision based optimization 
 \item Sensing.
 \end{itemize}
 \end{enumerate}
@@ -1127,34 +1111,61 @@ phases:
 \begin{frame}{Conclusion}
 \begin{enumerate} [$\blacktriangleright$]
 
-\item DiLCO and PeCO provide a schedule for one round per period.
-\item MuDiLCO provides a schedule for multiple rounds per period.
-\item Comparison results show that DiLCO, MuDiLCO, and PeCO protocols:
+\item DiLCO and PeCO provide a schedule for one round per period
+\item MuDiLCO provides a schedule for multiple rounds per period
+\item Comparison results show that DiLCO, MuDiLCO, and PeCO protocols
 \begin{itemize}
- \item maintain the coverage for a larger number of rounds.
- \item use less active nodes to save energy efficiently during sensing.
- \item are more powerful against network disconnections.
- \item perform the optimization with suitable execution times.
- \item consume less energy.
- \item prolong the network lifetime.
+ \item Maintain the coverage for a larger number of rounds
+ \item Use less active nodes to save energy efficiently during sensing
+ \item Are more powerful against network disconnections
+ \item Perform the optimization with suitable execution times
+ \item Consume less energy
+ \item Prolong the network lifetime
 
 \end{itemize}
 \end{enumerate}
 \end{frame}
 
+\begin{frame}{Conclusion}
+\tiny
+\begin{block}{\textcolor{white}{Journal Articles}}
+\begin{enumerate}[$\lbrack$1$\rbrack$]
+\item Ali Kadhum Idrees, Karine Deschinkel, Michel Salomon, and Rapha\"el Couturier. Perimeter-based Coverage Optimization to Improve Lifetime in Wireless Sensor Networks. \textit{Engineering Optimization, 2015, (Submitted)}.
+
+\item Ali Kadhum Idrees, Karine Deschinkel, Michel Salomon, and Rapha\"el Couturier. Multiround Distributed Lifetime Coverage Optimization Protocol in Wireless Sensor Networks. \textit{Ad Hoc Networks, 2015, (Submitted)}. 
+
+\item Ali Kadhum Idrees, Karine Deschinkel, Michel Salomon, and Rapha\"el Couturier. Distributed Lifetime Coverage Optimization Protocol in Wireless Sensor Networks. \textit{Journal of Supercomputing , 2015, (Submitted)}.
+\end{enumerate}
+\end{block}
+
+\begin{block}{\textcolor{white}{Technical Reports}}
+ 
+\begin{enumerate}[$\lbrack$1$\rbrack$]
+\item Ali Kadhum Idrees, Karine Deschinkel, Michel Salomon, and Rapha\"el
+Distributed lifetime coverage optimization protocol in wireless sensor networks. Technical Report DISC2014-X, University of Franche-Comte - FEMTO-ST Institute, DISC Research Department, Octobre 2014.
+\end{enumerate}
+\end{block}
+
+\begin{block}{\textcolor{white}{Conference Articles}}
+\begin{enumerate}[$\lbrack$1$\rbrack$]
+\item Ali Kadhum Idrees, Karine Deschinkel, Michel Salomon, and Rapha\"el
+Coverage and lifetime optimization in heterogeneous energy wireless sensor networks. In ICN 2014, The Thirteenth International Conference on Networks, pages 49â54, 2014.
+\end{enumerate}
+\end{block}
+
+\end{frame}
 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 52    %%
 %%%%%%%%%%%%%%%%%%%% 
 \begin{frame}{Perspectives}
 \begin{enumerate} [$\blacktriangleright$]
-\item The optimal number of subregions will be investigated.
-\item Design a heterogeneous integrated optimization protocol to integrate coverage, routing, and data aggregation protocols.
-\item Extend PeCO protocol so that the schedules are planned for multiple
-sensing periods.
-\item We plan to consider particle swarm optimization or evolutionary algorithms to obtain quickly near optimal solutions.
-\item Improve our mathematical models to take into account heterogeneous sensors from both energy and node characteristics point of views. 
-\item The cluster head will be selected in a distributed way and based on local information.
+\item Investigate the optimal number of subregions
+\item Design a heterogeneous integrated optimization protocol to integrate coverage, routing, and data aggregation protocols
+\item Extend PeCO protocol so that the schedules are planned for multiple sensing periods
+\item Consider particle swarm optimization or evolutionary algorithms to obtain quickly near optimal solutions
+\item Improve our mathematical models to take into account heterogeneous sensors from both energy and node characteristics point of views
+%\item The cluster head will be selected in a distributed way and based on local information.
 \end{enumerate}
 
 
