X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/ThesisAli.git/blobdiff_plain/cd18d10c8b21709c65c71c19c28340bb9d82a5bc..HEAD:/SlidesAli/These.tex diff --git a/SlidesAli/These.tex b/SlidesAli/These.tex index 1841431..769d815 100644 --- a/SlidesAli/These.tex +++ b/SlidesAli/These.tex @@ -1,5 +1,10 @@ \documentclass{beamer} +%\usepackage[timeinterval=10]{tdclock} + + + \usepackage{beamerthemefemto} + \usepackage[T1]{fontenc} \usepackage{amsfonts,amsmath,amssymb,stmaryrd} \usepackage[frenchb]{babel} @@ -28,7 +33,10 @@ \usepackage{array} \usepackage{picture} \usepackage{float} - + + +% \usepackage[font=Times,timeinterval=10, timeduration=2.0, timedeath=0, fillcolorwarningsecond=white!60!yellow, timewarningfirst=50,timewarningsecond=80,resetatpages=2]{tdclock} + \def\setgrouptext#1{\gdef\grouptext{#1}} \newenvironment{groupeditems}{\begin{displaymath}\left.\vbox\bgroup\setgrouptext}{% \egroup\right\rbrace\hbox{\grouptext}\end{displaymath}} @@ -56,7 +64,7 @@ \AtBeginSection[] { \begin{frame} -\frametitle{Presentation Outline} +\frametitle{Presentation outline} \tableofcontents[currentsection] \end{frame} } @@ -80,12 +88,14 @@ % \begin{document} - +%\initclock +%\tdclock %%%%%%%%%%%%%%%%%%%% %% SLIDE 01 %% %%%%%%%%%%%%%%%%%%%% \setbeamertemplate{background}{\titrefemto} \begin{frame}[plain] +%\transduration{0.75} \begin{center} \titlepage \end{center} @@ -100,6 +110,7 @@ %%%%%%%%%%%%%%%%%%%% \begin{frame} {Problem definition and solution} \vspace{-3.5em} + \begin{figure} \includegraphics[width=0.495\textwidth]{Figures/6} \hfill @@ -111,7 +122,7 @@ \end{figure} \begin{block}{\textcolor{white}{MAIN QUESTION}} - \textcolor{black}{How to minimize the energy consumption and extend the network lifetime when covering a certain area?} + \textcolor{black}{How to minimize the energy consumption and extend the network lifetime when covering the area of interest?} \end{block} \end{frame} @@ -185,7 +196,7 @@ %% SLIDE 04 %% %%%%%%%%%%%%%%%%%%%% \begin{frame} - \frametitle{Presentation Outline} + \frametitle{Presentation outline} \begin{small} \tableofcontents[section,subsection] \end{small} @@ -282,15 +293,16 @@ %%%%%%%%%%%%%%%%%%%% %% SLIDE 09 %% %%%%%%%%%%%%%%%%%%%% -\begin{frame}{Energy-Efficient Mechanisms of a working WSN} +\begin{frame}{Energy-efficient mechanisms of a working WSN} \vspace{-2.5em} - \centering + \begin{figure}[!t] - - \includegraphics[height = 5cm]{Figures/WSN-M.pdf} +\centering + % \includegraphics[height = 5cm]{Figures/WSN-M.pdf} + \includegraphics[height = 4.8cm]{Figures/EEM.eps} \end{figure} \vspace{-1.0em} - \bf \textcolor{blue} {Our approach includes cluster architecture and scheduling schemes} + %\bf \textcolor{blue} {Our approach includes cluster architecture and scheduling schemes} \end{frame} %\begin{frame}{Energy-Efficient Mechanisms of a working WSN} @@ -306,21 +318,21 @@ %%%%%%%%%%%%%%%%%%%% \begin{frame}{Network lifetime} \vspace{-1.5em} -\begin{block}{\textcolor{white} {Some definitions}} -\small -\begin{enumerate}[i)] +\begin{femtoBlock} + { Some definitions\\} + \begin{enumerate}[i)] \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} {Time spent by WSN in covering each target by at least one sensor} +\item \textcolor{black} {Time spent in covering area of interest 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 $\alpha$} +\item \bf \textcolor{red} {Elapsed time until the coverage ratio becomes less than a predetermined threshold $\alpha$} \end{enumerate} -\end{block} + + \end{femtoBlock} + + -%\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} @@ -336,10 +348,11 @@ -\begin{block} <2-> {\textcolor{white} {Coverage types}} +%\begin{block} <2-> {\textcolor{white} {Coverage types}} +\begin{block} {\bf \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 \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 has to be monitored \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} @@ -371,6 +384,7 @@ \item \textcolor{blue} {Full distributed coverage algorithms} \begin{itemize} \item Lower quality solution + \item Decision process is localized inside sensor and may requires a high computation power for dense WSNs \item Less energy consumption for communication in large WSN \item Reliable and scalable for large WSNs \end{itemize} @@ -392,9 +406,9 @@ \end{frame} \begin{frame}{Existing works $\blacktriangleright$ DESK algorithm (Vu et al.)} -\vspace{-1.5em} +\vspace{-2.0em} \begin{figure}[!t] - \includegraphics[height = 4.0cm]{Figures/DESK.eps} + \includegraphics[height = 5.0cm]{Figures/DESKp.eps} \end{figure} \vspace{-2.5em} @@ -465,16 +479,31 @@ \begin{enumerate} [$\divideontimes$] \item Static wireless sensor, homogeneous in terms of \begin{itemize} - \item Sensing, communication, and processing capabilities + \item Sensing + \item Communication + \item Processing capabilities \end{itemize} \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 $R_c\geq 2R_s$ + \begin{itemize} + \item Complete coverage $\Rightarrow$ connectivity (proved by Zhang and Zhou) + \end{itemize} \item Multi-hop communication - \item Known location by + + \end{enumerate} + +\end{frame} + + +\begin{frame}{Assumptions for our protocols} +\vspace{-0.1cm} + +\begin{enumerate} [$\divideontimes$] + \item Known location by \begin{itemize} - \item Embedded GPS or location discovery algorithm + \item Embedded GPS + \item location discovery algorithm \end{itemize} \item Using two kinds of packets @@ -484,7 +513,11 @@ \end{itemize} \item Five status for each node \begin{itemize} - \item \small LISTENING, ACTIVE, SLEEP, COMPUTATION, and COMMUNICATION + \item LISTENING + \item ACTIVE + \item SLEEP + \item COMPUTATION + \item COMMUNICATION \end{itemize} \end{enumerate} @@ -492,10 +525,14 @@ + + + + \begin{frame}{Assumptions for our protocols} \vspace{-0.5cm} \begin{center} - \includegraphics[height = 7.0cm]{Figures/Pmodels.pdf} + \includegraphics[height = 7.0cm]{Figures/Pmodelsn.pdf} \end{center} \end{frame} @@ -511,7 +548,7 @@ \begin{itemize} \item DiLCO and PeCO $\blacktriangleright$ one round sensing ($T=1$) -\item MuDiLCO $\blacktriangleright$ multiple rounds sensing ($T=1\cdots T$) +\item MuDiLCO $\blacktriangleright$ multiple rounds sensing ($t=1, \cdots, T$) \end{itemize} \end{frame} @@ -522,7 +559,7 @@ \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} +\item Position coordinates, current remaining energy, sensor node ID, and number of its one-hop live neighbors \end{itemize} @@ -530,7 +567,7 @@ \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 remaining energy \item Larger ID \end{itemize} @@ -652,9 +689,9 @@ Network Simulator & Discrete Event Simulator OMNeT++ \begin{enumerate}[$\blacktriangleright$] \item {{\bf Coverage Ratio (CR)}} -\item {{\bf Number of Active Sensors Ratio (ASR)}} -\item {{\bf Energy consumption}} -\item {{\bf Network lifetime}} +\item {{\bf Active Sensors Ratio (ASR)}} +\item {{\bf Energy consumption $(Lifetime_{95}$, $Lifetime_{50})$}} +\item {{\bf Network lifetime $(Lifetime_{95}$, $Lifetime_{50})$}} %\item {{\bf Execution Time}} %\item {{\bf Stopped Simulation Runs}} @@ -781,7 +818,7 @@ Network Simulator & Discrete Event Simulator OMNeT++ %%%%%%%%%%%%%%%%%%%% %% 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} \centering @@ -804,7 +841,7 @@ Network Simulator & Discrete Event Simulator OMNeT++ %%%%%%%%%%%%%%%%%%%% %% SLIDE 31 %% %%%%%%%%%%%%%%%%%%%% -\begin{frame}{\small MuDiLCO protocol $\blacktriangleright$ Results analysis and comparison} +\begin{frame}{\small MuDiLCO protocol $\blacktriangleright$ Performance comparison} \vspace{-0.5cm} \begin{figure}[h!] \centering @@ -818,7 +855,7 @@ Network Simulator & Discrete Event Simulator OMNeT++ %%%%%%%%%%%%%%%%%%%% %% SLIDE 32 %% %%%%%%%%%%%%%%%%%%%% -\begin{frame}{\small MuDiLCO protocol $\blacktriangleright$ Results analysis and comparison} +\begin{frame}{\small MuDiLCO protocol $\blacktriangleright$ Performance comparison} \vspace{-0.5cm} \begin{figure}[h!] \centering @@ -859,7 +896,7 @@ Network Simulator & Discrete Event Simulator OMNeT++ %%%%%%%%%%%%%%%%%%%% %% SLIDE 35 %% %%%%%%%%%%%%%%%%%%%% -\begin{frame}{\small MuDiLCO protocol $\blacktriangleright$ Results analysis and comparison} +\begin{frame}{\small MuDiLCO protocol $\blacktriangleright$ Performance comparison} \vspace{-0.5cm} \begin{figure}%[h!] \begin{columns}[c] @@ -879,7 +916,7 @@ Network Simulator & Discrete Event Simulator OMNeT++ %%%%%%%%%%%%%%%%%%%% %% SLIDE 36 %% %%%%%%%%%%%%%%%%%%%% -\begin{frame}{\small MuDiLCO protocol $\blacktriangleright$ Results analysis and comparison} +\begin{frame}{\small MuDiLCO protocol $\blacktriangleright$ Performance comparison} \vspace{-0.5cm} \begin{figure}%[h!] \begin{columns}[c] @@ -916,7 +953,7 @@ Network Simulator & Discrete Event Simulator OMNeT++ \column{.50\textwidth} $$\alpha = \arccos \left(\dfrac{Dist(u,v)}{2R_s} \right).$$ -\includegraphics[scale=0.40]{Figures/ch6/twosensors.jpg} +\includegraphics[scale=0.30]{Figures/ch6/twosensors.eps} \footnotesize \\~~~~~~~~~~~~~~~~~~~~~~~~~~(b) \\ \end{columns} \caption{(a) Perimeter coverage of sensor node 0 and (b) finding the arc of @@ -945,8 +982,11 @@ $$\alpha = \arccos \left(\dfrac{Dist(u,v)}{2R_s} % \label{pcm2sensors} \end{figure} -\vspace{-0.5cm} -\textcolor {red} {For example, the interval between 3R to 4R is covered by 4 sensors (0,1,2,4), it means the coverage level is 4} +\vspace{-0.9cm} +\textcolor {red} {Set of sensors involved in coverage interval of sensor 0 between 5L to 6L $\Rightarrow$ [0,2,5]\\ +Maximum coverage level: 3 +}%$a^0_{i0}= 1$ +%For example, the interval between 3R to 4R is covered by 4 sensors (0,1,2,4), it means the coverage level is 4 \end{frame} @@ -961,7 +1001,7 @@ $$\alpha = \arccos \left(\dfrac{Dist(u,v)}{2R_s} \begin{figure}[h!] \centering - \includegraphics[height = 7.2cm]{Figures/Algo3.png} + \includegraphics[height = 7.2cm]{Figures/ch6/Algo3n.pdf} \end{figure} \end{frame} @@ -984,7 +1024,7 @@ $$\alpha = \arccos \left(\dfrac{Dist(u,v)}{2R_s} %%%%%%%%%%%%%%%%%%%% %% SLIDE %% %%%%%%%%%%%%%%%%%%%% -\begin{frame}{\small PeCO protocol $\blacktriangleright$ Performance evaluation and analysis} +\begin{frame}{\small PeCO protocol $\blacktriangleright$ Performance comparison} \vspace{-0.5cm} \begin{figure}[h!] \centering @@ -999,7 +1039,7 @@ $$\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 comparison} \vspace{-0.5cm} \begin{figure}[h!] \centering @@ -1013,7 +1053,7 @@ $$\alpha = \arccos \left(\dfrac{Dist(u,v)}{2R_s} %%%%%%%%%%%%%%%%%%%% %% SLIDE %% %%%%%%%%%%%%%%%%%%%% -\begin{frame}{\small PeCO protocol $\blacktriangleright$ Performance evaluation and analysis} +\begin{frame}{\small PeCO protocol $\blacktriangleright$ Performance comparison} \vspace{-0.5cm} \begin{figure}%[h!] \begin{columns}[c] @@ -1034,7 +1074,7 @@ $$\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 comparison} \vspace{-0.5cm} \begin{figure}%[h!] \begin{columns}[c] @@ -1082,18 +1122,18 @@ $$\alpha = \arccos \left(\dfrac{Dist(u,v)}{2R_s} \item Sensing field is divided into smaller subregions using divide-and-conquer method \item One of the proposed optimization protocols is applied in each subregion in a distributed parallel way \end{itemize} -\item The proposed protocols (DiLCO, MuDiLCO, PeCO) combine two efficient mechanisms +\item Our proposed protocols combine two efficient mechanisms \begin{itemize} \item Network leader election, and \item Sensor activity scheduling based optimization \end{itemize} \item Our protocols are periodic where each period consists of 4 phases -\begin{itemize} -\item Information exchange -\item Network leader election -\item Decision based optimization -\item Sensing. -\end{itemize} +%\begin{itemize} +%\item Information exchange +%\item Network leader election +%\item Decision based optimization +%\item Sensing. +%\end{itemize} \end{enumerate} @@ -1110,12 +1150,12 @@ $$\alpha = \arccos \left(\dfrac{Dist(u,v)}{2R_s} \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 Comparison results show that our 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 More powerful against network disconnections +% \item Perform the optimization with suitable execution times \item Consume less energy \item Prolong the network lifetime @@ -1123,15 +1163,15 @@ $$\alpha = \arccos \left(\dfrac{Dist(u,v)}{2R_s} \end{enumerate} \end{frame} -\begin{frame}{Conclusion} +\begin{frame}{Publications} \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. Perimeter-based Coverage Optimization to Improve Lifetime in Wireless Sensor Networks. \textit{\textcolor{red}{Engineering Optimization}, 2015, ($2^{nd}$ Revision 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. Multiround Distributed Lifetime Coverage Optimization Protocol in Wireless Sensor Networks. \textit{\textcolor{red}{Ad Hoc Networks}, 2015, ($1^{st}$ Revision 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)}. +\item Ali Kadhum Idrees, Karine Deschinkel, Michel Salomon, and Rapha\"el Couturier. Distributed Lifetime Coverage Optimization Protocol in Wireless Sensor Networks. \textit{\textcolor{red}{Journal of Supercomputing}, 2015, ($1^{st}$ Revision Submitted)}. \end{enumerate} \end{block} @@ -1159,7 +1199,7 @@ Coverage and lifetime optimization in heterogeneous energy wireless sensor netwo \begin{enumerate} [$\blacktriangleright$] \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 Extend PeCO protocol so that the schedules are planned for multiple rounds per period \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.