From: ali Date: Fri, 11 Sep 2015 10:16:23 +0000 (+0200) Subject: Update by Ali X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/ThesisAli.git/commitdiff_plain/cd18d10c8b21709c65c71c19c28340bb9d82a5bc Update by Ali --- diff --git a/SlidesAli/These.pdf b/SlidesAli/These.pdf index 2a4cb97..64e8dcf 100644 Binary files a/SlidesAli/These.pdf and b/SlidesAli/These.pdf differ diff --git a/SlidesAli/These.tex b/SlidesAli/These.tex index 94c4bef..1841431 100644 --- a/SlidesAli/These.tex +++ b/SlidesAli/These.tex @@ -98,7 +98,7 @@ %%%%%%%%%%%%%%%%%%%% %% 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} @@ -110,7 +110,7 @@ % \includegraphics[width=0.475\textwidth]{Figures/13} \end{figure} - \begin{block}{\textcolor{white}{ MAIN QUESTION?}} + \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} @@ -119,12 +119,15 @@ %%%%%%%%%%%%%%%%%%%% %% 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} @@ -213,7 +216,7 @@ \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} @@ -286,8 +289,8 @@ \includegraphics[height = 5cm]{Figures/WSN-M.pdf} \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} @@ -303,15 +306,15 @@ %%%%%%%%%%%%%%%%%%%% \begin{frame}{Network lifetime} \vspace{-1.5em} -\begin{block}{\textcolor{white} {Some definitions:}} +\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 $\alpha$.} +\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} @@ -327,18 +330,18 @@ %%%%%%%%%%%%%%%%%%%% \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{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 have 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 +358,7 @@ %%%%%%%%%%%%%%%%%%%% \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} @@ -388,7 +391,7 @@ \end{frame} -\begin{frame}{Existing works: DESK algorithm (Vu et al.)} +\begin{frame}{Existing works $\blacktriangleright$ DESK algorithm (Vu et al.)} \vspace{-1.5em} \begin{figure}[!t] \includegraphics[height = 4.0cm]{Figures/DESK.eps} @@ -397,9 +400,9 @@ \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 +410,7 @@ \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 +431,7 @@ \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 @@ -460,26 +463,26 @@ \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 \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 $R_c\geq 2R_s$ complete coverage $\Rightarrow$ connectivity (proved by Zhang and Zhou) \item Multi-hop communication - \item Known location by: + \item Known location by \begin{itemize} \item Embedded GPS or 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 \end{itemize} @@ -500,21 +503,21 @@ -\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 @@ -561,7 +564,7 @@ %%%%%%%%%%%%%%%%%%%% %% 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 +575,7 @@ %%%%%%%%%%%%%%%%%%%% %% 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 +590,11 @@ %%%%%%%%%%%%%%%%%%%% %% 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 +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 @@ -644,14 +647,14 @@ 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 Number of Active Sensors Ratio (ASR)}} +\item {{\bf Energy consumption}} +\item {{\bf Network lifetime}} %\item {{\bf Execution Time}} %\item {{\bf Stopped Simulation Runs}} @@ -664,7 +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!] @@ -683,7 +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!] @@ -712,7 +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] @@ -734,7 +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] @@ -778,7 +781,7 @@ 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 +804,7 @@ Network Simulator & Discrete Event Simulator OMNeT++ %%%%%%%%%%%%%%%%%%%% %% SLIDE 31 %% %%%%%%%%%%%%%%%%%%%% -\begin{frame}{\small MuDiLCO Protocol $\blacktriangleright$ Results Analysis and Comparison} +\begin{frame}{\small MuDiLCO protocol $\blacktriangleright$ Results analysis and comparison} \vspace{-0.5cm} \begin{figure}[h!] \centering @@ -815,7 +818,7 @@ Network Simulator & Discrete Event Simulator OMNeT++ %%%%%%%%%%%%%%%%%%%% %% SLIDE 32 %% %%%%%%%%%%%%%%%%%%%% -\begin{frame}{\small MuDiLCO Protocol $\blacktriangleright$ Results Analysis and Comparison} +\begin{frame}{\small MuDiLCO protocol $\blacktriangleright$ Results analysis and comparison} \vspace{-0.5cm} \begin{figure}[h!] \centering @@ -856,7 +859,7 @@ Network Simulator & Discrete Event Simulator OMNeT++ %%%%%%%%%%%%%%%%%%%% %% SLIDE 35 %% %%%%%%%%%%%%%%%%%%%% -\begin{frame}{\small MuDiLCO Protocol $\blacktriangleright$ Results Analysis and Comparison} +\begin{frame}{\small MuDiLCO protocol $\blacktriangleright$ Results analysis and comparison} \vspace{-0.5cm} \begin{figure}%[h!] \begin{columns}[c] @@ -876,7 +879,7 @@ Network Simulator & Discrete Event Simulator OMNeT++ %%%%%%%%%%%%%%%%%%%% %% SLIDE 36 %% %%%%%%%%%%%%%%%%%%%% -\begin{frame}{\small MuDiLCO Protocol $\blacktriangleright$ Results Analysis and Comparison} +\begin{frame}{\small MuDiLCO protocol $\blacktriangleright$ Results analysis and comparison} \vspace{-0.5cm} \begin{figure}%[h!] \begin{columns}[c] @@ -902,7 +905,7 @@ 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!] @@ -926,22 +929,24 @@ $$\alpha = \arccos \left(\dfrac{Dist(u,v)}{2R_s} %%%%%%%%%%%%%%%%%%%% %% SLIDE 46 %% %%%%%%%%%%%%%%%%%%%% -\begin{frame}{\small PeCO Protocol $\blacktriangleright$ Assumptions and Models} +\begin{frame}{\small PeCO protocol $\blacktriangleright$ Assumptions and models} -\vspace{-0.5cm} +\vspace{-1.2cm} \begin{figure}%[h!] -\begin{columns}[c] - \column{.50\textwidth} -\includegraphics[scale=0.33]{Figures/ch6/expcm2.jpg} -\footnotesize \\~~~~~~~~~~~~~~~~~~~~~~~~~~(a)\\ -\column{.50\textwidth} -\includegraphics[scale=0.38]{Figures/tbl.jpeg} -\footnotesize \\~~~~~~~~~~~~~~~~~~~~~~~~~~(b) \\ -\end{columns} -\caption{(a) Maximum coverage levels for perimeter of sensor node $0$. and (b) Coverage intervals and contributing sensors for sensor node 0.} - \label{pcm2sensors} +%\begin{columns}[c] +% \column{.50\textwidth} +\includegraphics[scale=0.6]{Figures/ch6/expcm2.jpg} +%\footnotesize \\~~~~~~~~~~~~~~~~~~~~~~~~~~(a)\\ +%\column{.50\textwidth} +%\includegraphics[scale=0.38]{Figures/tbl.jpeg} +%\footnotesize \\~~~~~~~~~~~~~~~~~~~~~~~~~~(b) \\ +%\end{columns} +%\caption{(a) Maximum coverage levels for perimeter of sensor node $0$. and (b) Coverage intervals and contributing sensors for sensor node 0.} +% \label{pcm2sensors} \end{figure} +\vspace{-0.5cm} +\textcolor {red} {For example, the interval between 3R to 4R is covered by 4 sensors (0,1,2,4), it means the coverage level is 4} \end{frame} @@ -950,7 +955,7 @@ $$\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} @@ -964,12 +969,12 @@ $$\alpha = \arccos \left(\dfrac{Dist(u,v)}{2R_s} %%%%%%%%%%%%%%%%%%%% %% SLIDE 48 %% %%%%%%%%%%%%%%%%%%%% -\begin{frame}{\small PeCO Protocol $\blacktriangleright$ Perimeter-based Coverage Problem Formulation} -\vspace{-0.7cm} +\begin{frame}{\small PeCO protocol $\blacktriangleright$ Perimeter-based coverage problem formulation} +\vspace{-0.72cm} \begin{figure}[h!] \centering -\includegraphics[scale=0.49]{Figures/modell3.pdf} +\includegraphics[scale=0.5]{Figures/modell3.pdf} \end{figure} \end{frame} @@ -979,7 +984,7 @@ $$\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 @@ -994,7 +999,7 @@ $$\alpha = \arccos \left(\dfrac{Dist(u,v)}{2R_s} %%%%%%%%%%%%%%%%%%%% %% SLIDE %% %%%%%%%%%%%%%%%%%%%% -\begin{frame}{\small PeCO Protocol $\blacktriangleright$ Performance Evaluation and Analysis} +\begin{frame}{\small PeCO protocol $\blacktriangleright$ Performance evaluation and analysis} \vspace{-0.5cm} \begin{figure}[h!] \centering @@ -1008,7 +1013,7 @@ $$\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] @@ -1029,7 +1034,7 @@ $$\alpha = \arccos \left(\dfrac{Dist(u,v)}{2R_s} %%%%%%%%%%%%%%%%%%%% %% SLIDE %% %%%%%%%%%%%%%%%%%%%% -\begin{frame}{\small PeCO Protocol $\blacktriangleright$ Performance Evaluation and Analysis} +\begin{frame}{\small PeCO protocol $\blacktriangleright$ Performance evaluation and analysis} \vspace{-0.5cm} \begin{figure}%[h!] \begin{columns}[c] @@ -1040,7 +1045,7 @@ $$\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 +1068,7 @@ $$\alpha = \arccos \left(\dfrac{Dist(u,v)}{2R_s} %%%%%%%%%%%%%%%%%%%% %% SLIDE %% %%%%%%%%%%%%%%%%%%%% -\section{\small {Conclusion and Perspectives}} +\section{\small {Conclusion and perspectives}} %%%%%%%%%%%%%%%%%%%% @@ -1074,20 +1079,19 @@ $$\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, +\item Information exchange +\item Network leader election +\item Decision based optimization \item Sensing. \end{itemize} \end{enumerate} @@ -1104,16 +1108,16 @@ 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} @@ -1153,12 +1157,11 @@ 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 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}