+
+\afterpage{\blankpage}
+
\chapter*{Abstract \markboth{Abstract}{Abstract}}
\label{cha}
\addcontentsline{toc}{chapter}{Abstract}
The remainder of this chapter is organized as follows. The next section is devoted to the DiLCO protocol description. Section \ref{ch4:sec:03} gives the primary points based coverage problem formulation which is used to schedule the activation of sensors. Section \ref{ch4:sec:04} shows the simulation results obtained using the discrete event simulator OMNeT++ \cite{ref158}. They fully demonstrate the usefulness of the proposed approach. Finally, we give concluding remarks in section \ref{ch4:sec:05}.
-
+\vfill
\section{Description of the DiLCO Protocol}
\label{ch4:sec:02}
As highlighted by Figures~\ref{Figures/ch4/R3/LT}(a) and \ref{Figures/ch4/R3/LT}(b), the network lifetime obviously increases when the size of the network increases, with DiLCO-16 protocol and DiLCO-32 protocol which lead to maximize the lifetime of the network compared with other approaches.
%In figures~\ref{Figures/ch4/R3/LT95} and \ref{Figures/ch4/R3/LT50}, network lifetime, $Lifetime95$ and $Lifetime50$ respectively, are illustrated for different network sizes.
-\begin{figure}[h!]
-\centering
+%%\begin{figure}[p!]
+%%\centering
% \begin{multicols}{0}
-\centering
-\includegraphics[scale=0.8]{Figures/ch4/R3/LT95.eps}\\~ ~ ~ ~ ~(a) \\
+%%\centering
+%%\includegraphics[scale=0.8]{Figures/ch4/R3/LT95.eps}\\~ ~ ~ ~ ~(a) \\
%\hfill
-\includegraphics[scale=0.8]{Figures/ch4/R3/LT50.eps}\\~ ~ ~ ~ ~(b)
+%%\includegraphics[scale=0.8]{Figures/ch4/R3/LT50.eps}\\~ ~ ~ ~ ~(b)
%\end{multicols}
-\caption{Network lifetime for (a) $Lifetime_{95}$ and (b) $Lifetime_{50}$}
- \label{Figures/ch4/R3/LT}
-\end{figure}
+%%\caption{Network lifetime for (a) $Lifetime_{95}$ and (b) $Lifetime_{50}$}
+%% \label{Figures/ch4/R3/LT}
+%%\end{figure}
By choosing the best suited nodes, for each period, by optimizing the coverage and lifetime of the network to cover the area of interest and by letting the other ones sleep in order to be used later in next periods, DiLCO-16 protocol and DiLCO-32 protocol efficiently prolong the network lifetime.
Comparison shows that DiLCO-16 protocol and DiLCO-32 protocol, which use distributed optimization over the subregions, are the best ones because they are robust to network disconnection during the network lifetime as well as they consume less energy in comparison with other approaches.
%It also means that distributing the algorithm 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.
-
\end{enumerate}
\section{Conclusion}
A crucial problem in WSN is to schedule the sensing activities of the different nodes in order to ensure both coverage of the area of interest and longer network lifetime. The inherent limitations of sensor nodes, in energy provision, communication, and computing capacities, require protocols that optimize the use of the available resources to fulfill the sensing task. To address this problem, this chapter proposes a two-step approach. Firstly, the field of sensing
is divided into smaller subregions using the concept of divide-and-conquer method. Secondly, a distributed protocol called Distributed Lifetime Coverage Optimization is applied in each subregion to optimize the coverage and lifetime performances. In a subregion, our protocol consists in electing a leader node, which will then perform a sensor activity scheduling. The challenges include how to select the most efficient leader in each subregion and the best representative set of active nodes to ensure a high level of coverage. To assess the performance of our approach, we compared it with two other approaches using many performance metrics like coverage ratio or network lifetime. We have also studied the impact of the number of subregions chosen to subdivide the area of interest, considering different network sizes. The experiments show that increasing the number of subregions improves the lifetime. The more subregions there are, the more robust the network is against random disconnection resulting from dead nodes. However, for a given sensing field and network size there is an optimal number of subregions. Therefore, in case of our simulation context a subdivision in $16$~subregions seems to be the most relevant.
+\begin{figure}[p!]
+\centering
+% \begin{multicols}{0}
+\centering
+\includegraphics[scale=0.8]{Figures/ch4/R3/LT95.eps}\\~ ~ ~ ~ ~(a) \\
+%\hfill
+\includegraphics[scale=0.8]{Figures/ch4/R3/LT50.eps}\\~ ~ ~ ~ ~(b)
+%\end{multicols}
+\caption{Network lifetime for (a) $Lifetime_{95}$ and (b) $Lifetime_{50}$}
+ \label{Figures/ch4/R3/LT}
+\end{figure}
%The energy consumption and some other constraints can easily be taken into account since the sensors can update and then exchange their information (including their residual energy) at the beginning of each period. However, the pre-sensing phases (Information Exchange, Leader Election, and Decision) are energy consuming for some nodes, even when they do not join the network to monitor the area.
-
-
-
-
-
\section{Primary Points based Multiround Coverage Problem Formulation}
\label{ch5:sec:03}
We extend the mathematical formulation given in section \ref{ch4:sec:03} to take into account multiple rounds.
+\newpage
+
For a primary point $p$, let $\alpha_{j,p}$ denote the indicator function of
whether the point $p$ is covered, that is
\begin{equation}
Simulations results show the relevance of the proposed protocol in terms of lifetime, coverage ratio, active sensors ratio, energy consumption, execution time. Indeed, when dealing with large wireless sensor networks, a distributed approach, like the one we propose, allows to reduce the difficulty of a single global optimization problem by partitioning it into many smaller problems, one per subregion, that can be solved more easily. Nevertheless, results also show that it is not possible to plan the activity of sensors over too many rounds because the resulting optimization problem leads to too high-resolution times and thus to an excessive energy consumption. Compared with DiLCO, it is clear that MuDiLCO improves the network lifetime especially for the dense network, but it is less robust than DiLCO under sensor nodes failures. Therefore, choosing the number of rounds $T$ depends on the type of application the WSN is deployed for.
-
\ No newline at end of file
+
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
\include{Abstruct}
\include{Resume}
-%% Sommaire
+%% Sommaire
+
\tableofcontents
\addcontentsline{toc}{chapter}{Table of Contents}
\contentsline {subsection}{\numberline {4.4.5}Performance Analysis for Different Number of Subregions}{87}{subsection.4.4.5}
\contentsline {subsection}{\numberline {4.4.6}Performance Analysis for Different Number of Primary Points}{92}{subsection.4.4.6}
\contentsline {subsection}{\numberline {4.4.7}Performance Comparison with other Approaches}{96}{subsection.4.4.7}
-\contentsline {section}{\numberline {4.5}Conclusion}{105}{section.4.5}
-\contentsline {chapter}{\numberline {5}Multiround Distributed Lifetime Coverage Optimization Protocol}{107}{chapter.5}
-\contentsline {section}{\numberline {5.1}Introduction}{107}{section.5.1}
-\contentsline {section}{\numberline {5.2}Description of the MuDiLCO Protocol }{107}{section.5.2}
-\contentsline {section}{\numberline {5.3}Primary Points based Multiround Coverage Problem Formulation}{109}{section.5.3}
-\contentsline {section}{\numberline {5.4}Experimental Study and Analysis}{111}{section.5.4}
-\contentsline {subsection}{\numberline {5.4.1}Simulation Setup}{111}{subsection.5.4.1}
-\contentsline {subsection}{\numberline {5.4.2}Metrics}{111}{subsection.5.4.2}
-\contentsline {subsection}{\numberline {5.4.3}Results Analysis and Comparison }{112}{subsection.5.4.3}
-\contentsline {section}{\numberline {5.5}Conclusion}{118}{section.5.5}
-\contentsline {chapter}{\numberline {6} Perimeter-based Coverage Optimization to Improve Lifetime in WSNs}{119}{chapter.6}
-\contentsline {section}{\numberline {6.1}Introduction}{119}{section.6.1}
-\contentsline {section}{\numberline {6.2}Description of the PeCO Protocol}{119}{section.6.2}
-\contentsline {subsection}{\numberline {6.2.1}Assumptions and Models}{119}{subsection.6.2.1}
-\contentsline {subsection}{\numberline {6.2.2}PeCO Protocol Algorithm}{122}{subsection.6.2.2}
-\contentsline {section}{\numberline {6.3}Perimeter-based Coverage Problem Formulation}{125}{section.6.3}
-\contentsline {section}{\numberline {6.4}Performance Evaluation and Analysis}{126}{section.6.4}
-\contentsline {subsection}{\numberline {6.4.1}Simulation Settings}{126}{subsection.6.4.1}
-\contentsline {subsection}{\numberline {6.4.2}Simulation Results}{127}{subsection.6.4.2}
-\contentsline {subsubsection}{\numberline {6.4.2.1}Coverage Ratio}{127}{subsubsection.6.4.2.1}
-\contentsline {subsubsection}{\numberline {6.4.2.2}Active Sensors Ratio}{127}{subsubsection.6.4.2.2}
-\contentsline {subsubsection}{\numberline {6.4.2.3}Energy Consumption}{128}{subsubsection.6.4.2.3}
-\contentsline {subsubsection}{\numberline {6.4.2.4}Network Lifetime}{128}{subsubsection.6.4.2.4}
-\contentsline {subsubsection}{\numberline {6.4.2.5}Impact of $\alpha $ and $\beta $ on PeCO's performance}{129}{subsubsection.6.4.2.5}
-\contentsline {section}{\numberline {6.5}Conclusion}{133}{section.6.5}
-\contentsline {part}{III\hspace {1em}Conclusion and Perspectives}{135}{part.3}
-\contentsline {chapter}{\numberline {7}Conclusion and Perspectives}{137}{chapter.7}
-\contentsline {section}{\numberline {7.1}Conclusion}{137}{section.7.1}
-\contentsline {section}{\numberline {7.2}Perspectives}{138}{section.7.2}
-\contentsline {part}{Publications}{141}{chapter*.15}
-\contentsline {part}{Bibliographie}{156}{chapter*.19}
+\contentsline {section}{\numberline {4.5}Conclusion}{103}{section.4.5}
+\contentsline {chapter}{\numberline {5}Multiround Distributed Lifetime Coverage Optimization Protocol}{105}{chapter.5}
+\contentsline {section}{\numberline {5.1}Introduction}{105}{section.5.1}
+\contentsline {section}{\numberline {5.2}Description of the MuDiLCO Protocol }{105}{section.5.2}
+\contentsline {section}{\numberline {5.3}Primary Points based Multiround Coverage Problem Formulation}{107}{section.5.3}
+\contentsline {section}{\numberline {5.4}Experimental Study and Analysis}{109}{section.5.4}
+\contentsline {subsection}{\numberline {5.4.1}Simulation Setup}{109}{subsection.5.4.1}
+\contentsline {subsection}{\numberline {5.4.2}Metrics}{109}{subsection.5.4.2}
+\contentsline {subsection}{\numberline {5.4.3}Results Analysis and Comparison }{110}{subsection.5.4.3}
+\contentsline {section}{\numberline {5.5}Conclusion}{116}{section.5.5}
+\contentsline {chapter}{\numberline {6} Perimeter-based Coverage Optimization to Improve Lifetime in WSNs}{117}{chapter.6}
+\contentsline {section}{\numberline {6.1}Introduction}{117}{section.6.1}
+\contentsline {section}{\numberline {6.2}Description of the PeCO Protocol}{117}{section.6.2}
+\contentsline {subsection}{\numberline {6.2.1}Assumptions and Models}{117}{subsection.6.2.1}
+\contentsline {subsection}{\numberline {6.2.2}PeCO Protocol Algorithm}{120}{subsection.6.2.2}
+\contentsline {section}{\numberline {6.3}Perimeter-based Coverage Problem Formulation}{123}{section.6.3}
+\contentsline {section}{\numberline {6.4}Performance Evaluation and Analysis}{124}{section.6.4}
+\contentsline {subsection}{\numberline {6.4.1}Simulation Settings}{124}{subsection.6.4.1}
+\contentsline {subsection}{\numberline {6.4.2}Simulation Results}{125}{subsection.6.4.2}
+\contentsline {subsubsection}{\numberline {6.4.2.1}Coverage Ratio}{125}{subsubsection.6.4.2.1}
+\contentsline {subsubsection}{\numberline {6.4.2.2}Active Sensors Ratio}{125}{subsubsection.6.4.2.2}
+\contentsline {subsubsection}{\numberline {6.4.2.3}Energy Consumption}{126}{subsubsection.6.4.2.3}
+\contentsline {subsubsection}{\numberline {6.4.2.4}Network Lifetime}{126}{subsubsection.6.4.2.4}
+\contentsline {subsubsection}{\numberline {6.4.2.5}Impact of $\alpha $ and $\beta $ on PeCO's performance}{127}{subsubsection.6.4.2.5}
+\contentsline {section}{\numberline {6.5}Conclusion}{131}{section.6.5}
+\contentsline {part}{III\hspace {1em}Conclusion and Perspectives}{133}{part.3}
+\contentsline {chapter}{\numberline {7}Conclusion and Perspectives}{135}{chapter.7}
+\contentsline {section}{\numberline {7.1}Conclusion}{135}{section.7.1}
+\contentsline {section}{\numberline {7.2}Perspectives}{136}{section.7.2}
+\contentsline {part}{Publications}{139}{chapter*.15}
+\contentsline {part}{Bibliographie}{154}{chapter*.19}
The long journey of my Ph.D. study has finished. It is with great pleasure that I acknowledge my debts to those who have greatly contributed to the success of this dissertation. It was only through support and encouragement of many that I have been able to complete this amazing journey.
-Foremost, I would like to express my sincere gratitude to all my supervisors Prof. Dr. Rapha\"el Couturier, Asst. Prof. Dr. Karine Deschinkel, and Asst. Prof. Dr. Michel Salomon for their continuous support, encouragement, and advice they have provided throughout my Ph.D. study. Their patience, motivation, enthusiasm, and immense knowledge taught me alot. Their tireless guidance has helped me immensely in researching and writing this dissertation. I have been extremely lucky to have supervisors who cared so much about my work, and who responded to my questions and queries so promptly.
+Foremost, I would like to express my sincere gratitude to all my supervisors: Prof.~Dr.~Rapha\"el~Couturier, Asst.~Prof.~Dr.~Karine~Deschinkel, and Asst.~Prof. Dr.~Michel~Salomon for their continuous support, encouragement, and advice they have provided throughout my Ph.D.~study. Their patience, motivation, enthusiasm, and immense knowledge taught me a lot. Their tireless guidance has helped me immensely in researching and writing this dissertation. I have been extremely lucky to have supervisors who cared so much about my work, and who responded to my questions and queries so promptly.
-
-Besides my supervisors, I would like to express my gratitude to Prof. Dr. YE-Q IONG SONG and Assoc Prof. Dr. HAMIDA SEBA (HDR) for accepting to review my dissertation and for their insightful and appreciated comments. I would like to thank also Prof. Dr. SYLVAIN CONTASSOT-VIVIER for accepting to participate in my dissertation committee.
+Besides my supervisors, I would like to express my gratitude to Prof.~Dr.~Ye-Qiong~Song and Assoc~Prof.~Dr.~Hamida~Seba (HDR) for accepting to review my dissertation and for their insightful and appreciated comments. I would like to thank also Prof.~Dr.~Sylvain~Contassot-Vivier for accepting to participate in my dissertation committee.
I would like to gratefully acknowledge the University of Babylon, Iraq for financial support; Campus France and University of Franche-Comté for the received support.
-My appreciation and thanks go to the members of the team AND (Algorithms and Distributed Digital) for the warm and friendly atmosphere in which he allowed me to work. So thank you to Jacques Bahi, Pierre-Cyrille HEAM, Huu Quan Do, Bassam Alkindy, Abdallah Makhoul, Huda AL-NAYYEF, Jean-Claude Charr, Jean-François Couchot, Ahmed Mostefaoui, Ahmed Fanfakh, Yousra Ahmed Fadil, Stéphane Domas, Pierre SAENGER, Zeinab FAWAZ, Arnaud Giersch, Christophe Guyeux, Mourad Hakem, David LAIYMANI, Gilles PERROT, Christian Salim, Bashar AL-NUAIMI, Santiago Costarelli, Carol Habib, Hassan MOUSTAFA HARB, and Ke Du. I would like to express my thanks and my best wishes to Ingrid Couturier for all the received assistance during my study. I would also like to express my thanks to Dr. Lilia Ziane Khodja, PostDoc at $LTAS-A\&M$, Liege, Belgium. I would like to thank Béatrice Domenge and Maxim Moureaux in the Reprographie service for all received assistance during my study. I would also like to thank Patricia Py in the Computer Department secretary. I dare not risk missing to mention anyone’s name, so I will simply say 'thank you ALL for being there for me'.
+My appreciation and thanks go to the members of the team AND ({\it Algorithmique Numérique Distribuée}) for the warm and friendly atmosphere in which they allowed me to work. So thank you to Jacques Bahi, Pierre-Cyrille Héam, Huu Quan Do, Bassam Alkindy, Abdallah Makhoul, Huda Al-Nayyef, Jean-Claude Charr, Jean-François Couchot, Ahmed Mostefaoui, Ahmed Fanfakh, Yousra Ahmed Fadil, Stéphane Domas, Pierre Saenger, Zeinab Fawaz, Arnaud Giersch, Christophe Guyeux, Mourad Hakem, David Laiymani, Gilles Perrot, Christian Salim, Bashar Al-Nuaimi, Santiago Costarelli, Carol Habib, Hassan Moustafa Harb, and Ke Du. I would like to express my thanks and my best wishes to Ingrid Couturier for all the received assistance during my study. I would also like to express my thanks to Dr.~Lilia~Ziane Khodja, PostDoc at $LTAS-A\&M$, Liege, Belgium. I would like to thank Béatrice Domenge and Maxim Moureaux from the {\it Reprographie service} for all received assistance during my study. I would also like to thank Patricia Py, Computer Science Department secretary. I dare not risk missing to mention anyone’s name, so I will simply say 'thank you ALL for being there for me'.
-Last but not the least, I would like to extend a warm appreciation to those families and friends who have been encouraging along the way.
\ No newline at end of file
+Last but not the least, I would like to extend a warm appreciation to those families and friends who have been encouraging along the way.
+
\usepackage{picture}
\usepackage[section]{placeins}
\usepackage{float}
+\usepackage{afterpage}
+
+\newcommand\blankpage{%
+ \null
+ \thispagestyle{empty}%
+ \addtocounter{page}{-1}%
+ \newpage}
\def\setgrouptext#1{\gdef\grouptext{#1}}
\newenvironment{groupeditems}{\begin{displaymath}\left.\vbox\bgroup\setgrouptext}{%
