X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/ThesisAli.git/blobdiff_plain/a5b27a679ef2809581fb27959ecfcf348dcbbe39..9eaa0b57db7b53eb9338a3fe8205215cdb0f9683:/SlidesAli/These.tex?ds=sidebyside diff --git a/SlidesAli/These.tex b/SlidesAli/These.tex index 94c4bef..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} @@ -98,8 +108,9 @@ %%%%%%%%%%%%%%%%%%%% %% SLIDE 02 %% %%%%%%%%%%%%%%%%%%%% -\begin{frame} {Problem Definition, Solution, and Objectives} +\begin{frame} {Problem definition and solution} \vspace{-3.5em} + \begin{figure} \includegraphics[width=0.495\textwidth]{Figures/6} \hfill @@ -110,8 +121,8 @@ % \includegraphics[width=0.475\textwidth]{Figures/13} \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?} + \begin{block}{\textcolor{white}{MAIN QUESTION}} + \textcolor{black}{How to minimize the energy consumption and extend the network lifetime when covering the area of interest?} \end{block} \end{frame} @@ -119,12 +130,15 @@ %%%%%%%%%%%%%%%%%%%% %% SLIDE 03 %% %%%%%%%%%%%%%%%%%%%% -\begin{frame}{Problem Definition, Solution, and Objectives} +\begin{frame}{Problem definition and solution} -\begin{block}{\textcolor{white}{OUR SOLUTION: distributed optimization process}} -\bf \textcolor{black}{Division into subregions}\\ -\bf \textcolor{black}{For each subregion:} +\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 \bf \textcolor{magenta}{Leader election} \item \bf \textcolor{magenta}{Activity Scheduling based optimization} @@ -182,7 +196,7 @@ %% SLIDE 04 %% %%%%%%%%%%%%%%%%%%%% \begin{frame} - \frametitle{Presentation Outline} + \frametitle{Presentation outline} \begin{small} \tableofcontents[section,subsection] \end{small} @@ -213,7 +227,7 @@ \begin{femtoBlock} {Sensor \\} \begin{itemize} - \item Electronic low-cost tiny device + \item Electronic low-cost tiny device \item Sense, process and transmit data \item Limited energy, memory and processing capabilities \end{itemize} @@ -279,15 +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} - - \bf \textcolor{blue} {Our approach: includes cluster architecture and scheduling schemes} + \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} @@ -303,21 +318,21 @@ %%%%%%%%%%%%%%%%%%%% \begin{frame}{Network lifetime} \vspace{-1.5em} -\begin{block}{\textcolor{white} {Some definitions:}} -\small -\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} {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 $\alpha$.} +\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 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} {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} @@ -327,18 +342,19 @@ %%%%%%%%%%%%%%%%%%%% \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{block} <2-> {\textcolor{white} {Coverage types}} +\begin{block} {\bf \textcolor{white} {Coverage types}} \begin{enumerate}[i)] -\item \small \textcolor{red} {Area coverage: every point inside an area has to be monitored.} -\item \textcolor{blue} {Target coverage:} 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:} detection of 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} @@ -355,7 +371,7 @@ %%%%%%%%%%%%%%%%%%%% \begin{frame}{Existing works} \vspace{-0.3em} -\begin{block} {\textcolor{white} {Coverage approaches:}} +\begin{block} {\textcolor{white} {Coverage approaches}} %Most existing coverage approaches in literature classified into \begin{enumerate}[i)] \item \textcolor{blue} { Full centralized coverage algorithms} @@ -368,6 +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} @@ -388,18 +405,18 @@ \end{frame} -\begin{frame}{Existing works: DESK algorithm (Vu et al.)} -\vspace{-1.5em} +\begin{frame}{Existing works $\blacktriangleright$ DESK algorithm (Vu et al.)} +\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} \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 + \item Each sensor decides its status (Active or Sleep) based on the perimeter coverage model, without optimization - \end{itemize} +\end{itemize} %\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.} @@ -407,7 +424,7 @@ \end{frame} -\begin{frame}{Existing works: GAF algorithm (Xu et al.)} +\begin{frame}{Existing works $\blacktriangleright$ GAF algorithm (Xu et al.)} \vspace{-3.3em} \begin{columns}[c] @@ -428,7 +445,7 @@ \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: discovery, active, or sleep + \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 @@ -460,28 +477,47 @@ \vspace{-0.1cm} \begin{enumerate} [$\divideontimes$] - \item Static wireless sensor, homogeneous in terms of: + \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 Its $R_c\geq 2R_s$ for imply connectivity among active nodes during complete coverage (hypothesis 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: + \item Using two kinds of packets \begin{itemize} \item INFO packet \item ActiveSleep packet \end{itemize} - \item Five status for each node: + \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} @@ -489,10 +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} @@ -500,26 +540,26 @@ -\begin{frame}{Our general scheme} +\begin{frame}{General scheme} \vspace{-0.2cm} \begin{figure}[ht!] \includegraphics[width=110mm]{Figures/GeneralModel.jpg} \end{figure} \begin{itemize} -\item DiLCO and PeCO $\blacktriangleright$ use one round sensing ($T=1$) -\item MuDiLCO $\blacktriangleright$ uses multiple rounds sensing ($T=1\cdots T$) +\item DiLCO and PeCO $\blacktriangleright$ one round sensing ($T=1$) +\item MuDiLCO $\blacktriangleright$ multiple rounds sensing ($t=1, \cdots, T$) \end{itemize} \end{frame} -\begin{frame}{Our general scheme} +\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} +\item Position coordinates, current remaining energy, sensor node ID, and number of its one-hop live neighbors \end{itemize} @@ -527,7 +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} @@ -561,7 +601,7 @@ %%%%%%%%%%%%%%%%%%%% %% SLIDE 15 %% %%%%%%%%%%%%%%%%%%%% -\begin{frame}{\small DiLCO Protocol $\blacktriangleright$ Coverage Problem Formulation} +\begin{frame}{\small DiLCO protocol $\blacktriangleright$ Coverage problem formulation} \vspace{0.2cm} \centering \includegraphics[height = 7.2cm]{Figures/modell1.pdf} @@ -572,7 +612,7 @@ %%%%%%%%%%%%%%%%%%%% %% 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} @@ -587,11 +627,11 @@ %%%%%%%%%%%%%%%%%%%% %% 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 simulation.} +\caption{Relevant parameters for simulation} \centering \begin{tabular}{c|c} \hline @@ -619,9 +659,9 @@ 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 @@ -644,14 +684,14 @@ Network Simulator & Discrete Event Simulator OMNeT++ \end{femtoBlock} \vspace{-0.5cm} -\begin{femtoBlock} {Performance Metrics} +\begin{femtoBlock} {Performance metrics} \small -\begin{enumerate}[$\mapsto$] +\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}} @@ -664,7 +704,7 @@ 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!] @@ -683,7 +723,7 @@ 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!] @@ -712,7 +752,7 @@ 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] @@ -734,7 +774,7 @@ 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] @@ -778,7 +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 @@ -801,7 +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 @@ -815,7 +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 @@ -856,7 +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] @@ -876,7 +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] @@ -902,7 +942,7 @@ Network Simulator & Discrete Event Simulator OMNeT++ %%%%%%%%%%%%%%%%%%%% %% 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!] @@ -913,7 +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 @@ -926,22 +966,27 @@ $$\alpha = \arccos \left(\dfrac{Dist(u,v)}{2R_s} %%%%%%%%%%%%%%%%%%%% %% SLIDE 46 %% %%%%%%%%%%%%%%%%%%%% -\begin{frame}{\small PeCO Protocol $\blacktriangleright$ Assumptions and Models} +\begin{frame}{\small PeCO protocol $\blacktriangleright$ Assumptions and models} -\vspace{-0.5cm} +\vspace{-1.2cm} \begin{figure}%[h!] -\begin{columns}[c] - \column{.50\textwidth} -\includegraphics[scale=0.33]{Figures/ch6/expcm2.jpg} -\footnotesize \\~~~~~~~~~~~~~~~~~~~~~~~~~~(a)\\ -\column{.50\textwidth} -\includegraphics[scale=0.38]{Figures/tbl.jpeg} -\footnotesize \\~~~~~~~~~~~~~~~~~~~~~~~~~~(b) \\ -\end{columns} -\caption{(a) Maximum coverage levels for perimeter of sensor node $0$. and (b) Coverage intervals and contributing sensors for sensor node 0.} - \label{pcm2sensors} +%\begin{columns}[c] +% \column{.50\textwidth} +\includegraphics[scale=0.6]{Figures/ch6/expcm2.jpg} +%\footnotesize \\~~~~~~~~~~~~~~~~~~~~~~~~~~(a)\\ +%\column{.50\textwidth} +%\includegraphics[scale=0.38]{Figures/tbl.jpeg} +%\footnotesize \\~~~~~~~~~~~~~~~~~~~~~~~~~~(b) \\ +%\end{columns} +%\caption{(a) Maximum coverage levels for perimeter of sensor node $0$. and (b) Coverage intervals and contributing sensors for sensor node 0.} +% \label{pcm2sensors} \end{figure} +\vspace{-0.9cm} +\textcolor {red} {Set of sensors involved in coverage interval of sensor 0 between 5L to 6L $\Rightarrow$ [0,2,5]\\ +Maximum coverage level: 3 +}%$a^0_{i0}= 1$ +%For example, the interval between 3R to 4R is covered by 4 sensors (0,1,2,4), it means the coverage level is 4 \end{frame} @@ -950,13 +995,13 @@ $$\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} \begin{figure}[h!] \centering - \includegraphics[height = 7.2cm]{Figures/Algo3.png} + \includegraphics[height = 7.2cm]{Figures/ch6/Algo3n.pdf} \end{figure} \end{frame} @@ -964,12 +1009,12 @@ $$\alpha = \arccos \left(\dfrac{Dist(u,v)}{2R_s} %%%%%%%%%%%%%%%%%%%% %% SLIDE 48 %% %%%%%%%%%%%%%%%%%%%% -\begin{frame}{\small PeCO Protocol $\blacktriangleright$ Perimeter-based Coverage Problem Formulation} -\vspace{-0.7cm} +\begin{frame}{\small PeCO protocol $\blacktriangleright$ Perimeter-based coverage problem formulation} +\vspace{-0.72cm} \begin{figure}[h!] \centering -\includegraphics[scale=0.49]{Figures/modell3.pdf} +\includegraphics[scale=0.5]{Figures/modell3.pdf} \end{figure} \end{frame} @@ -979,7 +1024,7 @@ $$\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 @@ -994,7 +1039,7 @@ $$\alpha = \arccos \left(\dfrac{Dist(u,v)}{2R_s} %%%%%%%%%%%%%%%%%%%% %% SLIDE %% %%%%%%%%%%%%%%%%%%%% -\begin{frame}{\small PeCO Protocol $\blacktriangleright$ Performance Evaluation and Analysis} +\begin{frame}{\small PeCO protocol $\blacktriangleright$ Performance comparison} \vspace{-0.5cm} \begin{figure}[h!] \centering @@ -1008,7 +1053,7 @@ $$\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] @@ -1029,7 +1074,7 @@ $$\alpha = \arccos \left(\dfrac{Dist(u,v)}{2R_s} %%%%%%%%%%%%%%%%%%%% %% SLIDE %% %%%%%%%%%%%%%%%%%%%% -\begin{frame}{\small PeCO Protocol $\blacktriangleright$ Performance Evaluation and Analysis} +\begin{frame}{\small PeCO protocol $\blacktriangleright$ Performance comparison} \vspace{-0.5cm} \begin{figure}%[h!] \begin{columns}[c] @@ -1040,7 +1085,7 @@ $$\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} @@ -1063,7 +1108,7 @@ $$\alpha = \arccos \left(\dfrac{Dist(u,v)}{2R_s} %%%%%%%%%%%%%%%%%%%% %% SLIDE %% %%%%%%%%%%%%%%%%%%%% -\section{\small {Conclusion and Perspectives}} +\section{\small {Conclusion and perspectives}} %%%%%%%%%%%%%%%%%%%% @@ -1074,22 +1119,21 @@ $$\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 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. +\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} \end{enumerate} @@ -1104,30 +1148,30 @@ 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 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 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 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} +\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} @@ -1153,12 +1197,11 @@ Coverage and lifetime optimization in heterogeneous energy wireless sensor netwo %%%%%%%%%%%%%%%%%%%% \begin{frame}{Perspectives} \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 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 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 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. \end{enumerate}