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59 \frametitle{Presentation Outline}
60 \tableofcontents[currentsection]
65 \title{\textbf{Distributed Coverage Optimization Techniques for Improving Lifetime of Wireless Sensor Networks} \\\vspace{0.1cm}\hspace{2cm}\textbf{\textcolor{cyan}{\small PhD Dissertation Defense}}}
66 \author{\textbf{\textcolor{green}{Ali Kadhum IDREES}} \\\vspace{0.5cm} \small Under Supervision: \\\textcolor{cyan}{\small Raphaël COUTURIER, Karine DESCHINKEL \& Michel SALOMON} \\\vspace{0.2cm} \textcolor{blue}{ University of Franche-Comté - FEMTO-ST - DISC Dept. - AND Team} \\\vspace{0.2cm}~~~~~~~~~~~~~~~~\textbf{\textcolor{green}{1 October 2015 }}}
68 %\institute[FEMTO-ST, DISC]{\textit{FEMTO-ST - DISC Departement - AND Team}}
75 % ____ _____ ____ _ _ _____
76 % | _ \| ____| __ )| | | |_ _|
77 % | | | | _| | _ \| | | | | |
78 % | |_| | |___| |_) | |_| | | |
79 % |____/|_____|____/ \___/ |_|
87 \setbeamertemplate{background}{\titrefemto}
95 \setbeamertemplate{background}{\pagefemto}
101 \begin{frame} {Problem definition and solution}
104 \includegraphics[width=0.495\textwidth]{Figures/6}
106 % \includegraphics[width=0.475\textwidth]{Figures/8}
108 \includegraphics[width=0.495\textwidth]{Figures/10}
110 % \includegraphics[width=0.475\textwidth]{Figures/13}
113 \begin{block}{\textcolor{white}{MAIN QUESTION}}
114 \textcolor{black}{How to minimize the energy consumption and extend the network lifetime when covering a certain area?}
122 \begin{frame}{Problem definition and solution}
124 \begin{block}{\textcolor{white}{OUR SOLUTION $\blacktriangleright$ Distributed optimization process}}
125 \begin{enumerate} [i)]
126 \item \bf \textcolor{black}{Division into subregions}
127 \item \bf \textcolor{black}{For each subregion}
132 \item \bf \textcolor{magenta}{Leader election}
133 \item \bf \textcolor{magenta}{Activity Scheduling based optimization}
139 \includegraphics[width=0.475\textwidth]{Figures/div2}
141 \includegraphics[width=0.475\textwidth]{Figures/act2}
149 %\begin{frame}{Problem Definition, Solution, and Objectives}
151 %\begin{block}{\textcolor{white}{OUR SOLUTION}}
153 % %\item Leader Election for each subregion.
154 % \item \bf \textcolor{magenta}{Activity Scheduling based optimization is planned for each subregion.}
159 % \includegraphics[width=0.775\textwidth]{Figures/act}
168 %\begin{frame}{Problem Definition, Solution, and Objectives}
170 %\begin{block}{\bf \textcolor{white}{Dissertation Objectives}}
171 %\bf \textcolor{black}{Develop energy-efficient distributed optimization protocols that should be able to:}
173 % \item \bf \textcolor{blue}{Schedule node activities by optimize both coverage and lifetime.}
174 % \item \bf \textcolor{blue}{Combine two efficient techniques: leader election and sensor activity scheduling.}
175 % \item \bf \textcolor{blue}{Perform a distributed optimization process.}
188 \frametitle{Presentation Outline}
190 \tableofcontents[section,subsection]
198 \section{\small {State of the Art}}
204 \begin{frame}{Wireless Sensor Networks (WSNs)}
208 \column{.58\textwidth}
211 \includegraphics[height = 3cm]{Figures/WSNT.jpg}
219 \item Electronic low-cost tiny device
220 \item Sense, process and transmit data
221 \item Limited energy, memory and processing capabilities
225 \column{.52\textwidth}
228 \includegraphics[height = 4.5cm]{Figures/WSN.jpg}
232 \includegraphics[height = 2cm]{Figures/sn.jpg}
246 \begin{frame}{Types of Wireless Sensor Networks}
251 %\column{.52\textwidth}
253 % \item Terrestrial WSNs.
254 % \item Underground WSNs.
255 % \item Underwater WSNs.
256 % \item Multimedia WSNs.
261 % \column{.58\textwidth}
263 \includegraphics[height = 7cm]{Figures/typesWSN.pdf}
273 \begin{frame}{Applications}
277 \includegraphics[height = 7cm]{Figures/WSNAP.pdf}
285 \begin{frame}{Energy-Efficient Mechanisms of a working WSN}
290 \includegraphics[height = 5cm]{Figures/WSN-M.pdf}
293 \bf \textcolor{blue} {Our approach includes cluster architecture and scheduling schemes}
296 %\begin{frame}{Energy-Efficient Mechanisms of a working WSN}
300 % \includegraphics[height = 7cm]{Figures/WSN-S.pdf}
307 \begin{frame}{Network lifetime}
309 \begin{block}{\textcolor{white} {Some definitions}}
311 \begin{enumerate}[i)]
312 \item \textcolor{black} {Time spent until death of the first sensor (or cluster head)}
313 \item \textcolor{black} {Time spent until death of all wireless sensor nodes in WSN}
314 \item \textcolor{black} {Time spent by WSN in covering each target by at least one sensor}
315 \item \textcolor{black} {Time during which the area of interest is covered by at least k nodes}
316 \item \textcolor{black} {Elapsed time until losing the connectivity or the coverage}
317 \item \bf \textcolor{red} {Time elapsed until the coverage ratio becomes less than a predetermined threshold $\alpha$}
321 %\begin{block}{\textcolor{white} {Network lifetime In this dissertation:}}
322 %\textcolor{blue} {Time elapsed until the coverage ratio becomes less than a predetermined threshold $\alpha$.}
331 \begin{frame}{Coverage in Wireless Sensor Networks}
333 \begin{block} <1-> {\textcolor{white} {Coverage definition}}
334 \textcolor{blue} {Coverage} reflects how well a sensor field is monitored efficiently using as less energy as possible
339 \begin{block} <2-> {\textcolor{white} {Coverage types}}
340 \begin{enumerate}[i)]
341 \item \small \textcolor{red} {Area coverage $\blacktriangleright$ every point inside an area has to be monitored}
342 \item \textcolor{blue} {Target coverage} $\blacktriangleright$ only a finite number of discrete points called targets have to be monitored
344 \item \textcolor{blue} {Barrier coverage} $\blacktriangleright$ detection of targets as they cross a barrier such as in intrusion detection and border surveillance applications
350 %\begin{block} <3-> {\textcolor{white} {Coverage type in this dissertation:}}
351 %The work presented in this dissertation deals with \textcolor{red} {area coverage}.
359 \begin{frame}{Existing works}
361 \begin{block} {\textcolor{white} {Coverage approaches}}
362 %Most existing coverage approaches in literature classified into
363 \begin{enumerate}[i)]
364 \item \textcolor{blue} { Full centralized coverage algorithms}
366 \item Optimal or near optimal solution
367 \item Low computation power for the sensors (except for base station)
368 \item Higher energy consumption for communication in large WSN
369 \item Not scalable for large WSNs
371 \item \textcolor{blue} {Full distributed coverage algorithms}
373 \item Lower quality solution
374 \item Less energy consumption for communication in large WSN
375 \item Reliable and scalable for large WSNs
377 \item \textcolor{red} {Hybrid approaches}
379 \item \textcolor{red} {Globally distributed and locally centralized}
387 %\begin{block} {\textcolor{white} {Coverage protocols in this dissertation:}}
388 %The protocols presented in this dissertation combine between the two above approaches.
394 \begin{frame}{Existing works $\blacktriangleright$ DESK algorithm (Vu et al.)}
397 \includegraphics[height = 4.0cm]{Figures/DESK.eps}
402 \item Requires only one-hop neighbor information (fully distributed)
403 \item Each sensor decides its status (Active or Sleep) based on the perimeter coverage model, without optimization
408 %\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.}
413 \begin{frame}{Existing works $\blacktriangleright$ GAF algorithm (Xu et al.)}
418 \column{.58\textwidth}
421 \includegraphics[height = 2.7cm]{Figures/GAF1.eps}
425 \includegraphics[height = 3.3cm]{Figures/GAF2.eps}
428 \column{.52\textwidth}
432 \item Distributed energy-based scheduling approach
433 \item Uses geographic location information to divide the area into a fixed square grids
434 \item Nodes are in one of three sates $\blacktriangleright$ discovery, active, or sleep
435 \item Only one node staying active in grid
436 \item The fixed grid is square with r units on a side
437 \item Nodes cooperate within each grid to choose the active node
443 % \item \tiny enat: estimated node active time
444 % \item enlt: estimated node lifetime
445 % \item Td,Ta, Ts: discovery, active, and sleep timers
447 % \item Ts = [enat/2, enat]
456 %\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.}
459 \section{\small {The main scheme for our protocols}}
462 \begin{frame}{Assumptions for our protocols}
465 \begin{enumerate} [$\divideontimes$]
466 \item Static wireless sensor, homogeneous in terms of
468 \item Sensing, communication, and processing capabilities
470 \item Heterogeneous initial energy
471 \item High density uniform deployment
472 \item $R_c\geq 2R_s$ complete coverage $\Rightarrow$ connectivity (proved by Zhang and Zhou)
474 \item Multi-hop communication
475 \item Known location by
477 \item Embedded GPS or location discovery algorithm
480 \item Using two kinds of packets
483 \item ActiveSleep packet
485 \item Five status for each node
487 \item \small LISTENING, ACTIVE, SLEEP, COMPUTATION, and COMMUNICATION
495 \begin{frame}{Assumptions for our protocols}
498 \includegraphics[height = 7.0cm]{Figures/Pmodels.pdf}
506 \begin{frame}{General scheme}
509 \includegraphics[width=110mm]{Figures/GeneralModel.jpg}
513 \item DiLCO and PeCO $\blacktriangleright$ one round sensing ($T=1$)
514 \item MuDiLCO $\blacktriangleright$ multiple rounds sensing ($T=1\cdots T$)
520 \begin{frame}{General scheme}
522 \begin{enumerate} [i)]
523 \item \textcolor{blue}{\textbf{INFORMATION EXCHANGE}} $\blacktriangleright$ Sensors exchange through multi-hop communication, their
525 \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}
530 \item \textcolor{blue}{\textbf{LEADER ELECTION}} $\blacktriangleright$ The selection criteria are, in order
532 \item Larger number of neighbors
533 \item Larger remaining energy, and then in case of equality
539 \item \textcolor{blue}{\textbf{DECISION}} $\blacktriangleright$ Leader solves an integer program to
541 \item Select which sensors will be activated in the sensing phase
542 \item Send Active-Sleep packet to each sensor in the subregion
546 \item \textcolor{blue}{\textbf{SENSING}} $\blacktriangleright$ Based on Active-Sleep Packet Information
548 \item Active sensors will execute their sensing task
549 \item Sleep sensors will wait a time equal to the period of sensing to wakeup
561 \section{\small {Distributed Lifetime Coverage Optimization Protocol (DiLCO)}}
567 \begin{frame}{\small DiLCO protocol $\blacktriangleright$ Coverage problem formulation}
570 \includegraphics[height = 7.2cm]{Figures/modell1.pdf}
578 \begin{frame}{\small DiLCO protocol $\blacktriangleright$ DiLCO protocol algorithm}
579 %\begin{femtoBlock} {}
581 %\includegraphics[height = 7.2cm]{Figures/algo.jpeg}
582 \includegraphics[height = 7.2cm]{Figures/Algo1.png}
593 \begin{frame}{\small DiLCO protocol $\blacktriangleright$ Simulation framework}
597 \caption{Relevant parameters for simulation}
601 Parameter & Value \\ [0.5ex]
603 Sensing Field & $(50 \times 25)~m^2 $ \\
604 Nodes Number & 50, 100, 150, 200 and 250~nodes \\
605 Initial Energy & 500-700~joules \\
606 Sensing Period & 60 Minutes \\
607 $E_{th}$ & 36 Joules\\
612 Modeling Language & A Mathematical Programming Language (AMPL) \\
613 Optimization Solver & GNU linear Programming Kit (GLPK) \\
614 Network Simulator & Discrete Event Simulator OMNeT++
625 \begin{frame}{\small DiLCO protocol $\blacktriangleright$ Energy model \& performance metrics }
627 \begin{femtoBlock} {Energy consumption model}
632 %\caption{Power consumption values}
634 \begin{tabular}{|l||cccc|}
636 {\bf Sensor status} & MCU & Radio & Sensing & {\it Power (mW)} \\
638 LISTENING & On & On & On & 20.05 \\
639 ACTIVE & On & Off & On & 9.72 \\
640 SLEEP & Off & Off & Off & 0.02 \\
641 COMPUTATION & On & On & On & 26.83 \\
643 \multicolumn{4}{|l}{Energy needed to send or receive a 2-bit content message} & 0.515 \\
650 \begin{femtoBlock} {Performance metrics}
652 \begin{enumerate}[$\blacktriangleright$]
654 \item {{\bf Coverage Ratio (CR)}}
655 \item {{\bf Number of Active Sensors Ratio (ASR)}}
656 \item {{\bf Energy consumption}}
657 \item {{\bf Network lifetime}}
658 %\item {{\bf Execution Time}}
659 %\item {{\bf Stopped Simulation Runs}}
670 \begin{frame}{ \small DiLCO protocol $\blacktriangleright$ Performance comparison}
675 \includegraphics[scale=0.5] {Figures/R3/CR.eps}
676 \caption{Coverage ratio for 150 deployed nodes}
677 \label{Figures/ch4/R3/CR}
689 \begin{frame}{ \small DiLCO protocol $\blacktriangleright$ Performance comparison}
694 \includegraphics[scale=0.5]{Figures/R3/ASR.eps}
695 \caption{Active sensors ratio for 150 deployed nodes }
696 \label{Figures/ch4/R3/ASR}
704 %\begin{frame}{ \small DiLCO Protocol $\blacktriangleright$ Performance Comparison}
708 %\includegraphics[scale=0.5]{Figures/R3/SR.eps}
709 %\caption{Percentage of stopped simulation runs for 150 deployed nodes }
710 %\label{Figures/ch4/R3/SR}
718 \begin{frame}{ \small DiLCO protocol $\blacktriangleright$ Performance comparison}
722 \column{.50\textwidth}
723 \includegraphics[scale=0.35]{Figures/R3/EC95.eps}
724 \footnotesize \\~~~~~~~~~~~~~~~~~~~~~~~~~~~~~(a)\\
725 \column{.50\textwidth}
726 \includegraphics[scale=0.35]{Figures/R3/EC50.eps}
727 \footnotesize \\~~~~~~~~~~~~~~~~~~~~~~~~~~~~~(b) \\
729 \caption{Energy consumption for (a) $Lifetime_{95}$ and (b) $Lifetime_{50}$}
730 \label{Figures/ch4/R3/EC}
740 \begin{frame}{ \small DiLCO protocol $\blacktriangleright$ Performance comparison}
744 \column{.50\textwidth}
745 \includegraphics[scale=0.35]{Figures/R3/LT95.eps}
746 \footnotesize \\~~~~~~~~~~~~~~~~~~~~~~~~~~~~~(a)\\
747 \column{.50\textwidth}
748 \includegraphics[scale=0.35]{Figures/R3/LT50.eps}
749 \footnotesize \\~~~~~~~~~~~~~~~~~~~~~~~~~~~~~(b) \\
751 \caption{Network lifetime for (a) $Lifetime_{95}$ and (b) $Lifetime_{50}$}
752 \label{Figures/ch4/R3/LT}
765 \section{\small{Multiround Distributed Lifetime Coverage Optimization Protocol (MuDiLCO)}}
771 %\begin{frame}{\small MuDiLCO Protocol $\blacktriangleright$ Main Idea}
774 % \includegraphics[width=110mm]{Figures/GeneralModel.jpg}
775 %\caption{MuDiLCO protocol.}
784 \begin{frame}{\small MuDiLCO protocol $\blacktriangleright$ Multiround coverage problem Formulation}
788 \includegraphics[height = 7.2cm]{Figures/modell2.pdf}
795 %\begin{frame}{\small MuDiLCO Protocol $\blacktriangleright$ MuDiLCO Protocol Algorithm}
797 %\begin{femtoBlock} {}
799 %\includegraphics[height = 7.2cm]{Figures/Algo2.png}
807 \begin{frame}{\small MuDiLCO protocol $\blacktriangleright$ Results analysis and comparison}
811 \includegraphics[scale=0.5] {Figures/R1/CR.pdf}
812 \caption{Average coverage ratio for 150 deployed nodes}
821 \begin{frame}{\small MuDiLCO protocol $\blacktriangleright$ Results analysis and comparison}
825 \includegraphics[scale=0.5]{Figures/R1/ASR.pdf}
826 \caption{Active sensors ratio for 150 deployed nodes}
835 %\begin{frame}{\small MuDiLCO Protocol $\blacktriangleright$ Results Analysis and Comparison}
839 %\includegraphics[scale=0.5]{Figures/R1/SR.pdf}
840 %\caption{Cumulative percentage of stopped simulation runs for 150 deployed nodes }
848 %\begin{frame}{\small MuDiLCO Protocol $\blacktriangleright$ Results Analysis and Comparison}
852 %\includegraphics[scale=0.5]{Figures/R1/T.pdf}
853 %\caption{Execution Time (in seconds)}
862 \begin{frame}{\small MuDiLCO protocol $\blacktriangleright$ Results analysis and comparison}
866 \column{.50\textwidth}
867 \includegraphics[scale=0.35]{Figures/R1/EC95.eps}
868 \footnotesize \\~~~~~~~~~~~~~~~~~~~~~~~~~~~~~(a)\\
869 \column{.50\textwidth}
870 \includegraphics[scale=0.35]{Figures/R1/EC50.eps}
871 \footnotesize \\~~~~~~~~~~~~~~~~~~~~~~~~~~~~~(b) \\
873 \caption{Energy consumption for (a) $Lifetime_{95}$ and (b) $Lifetime_{50}$}
874 \label{Figures/ch4t/R3/EC}
882 \begin{frame}{\small MuDiLCO protocol $\blacktriangleright$ Results analysis and comparison}
886 \column{.50\textwidth}
887 \includegraphics[scale=0.35]{Figures/R1/LT95.eps}
888 \footnotesize \\~~~~~~~~~~~~~~~~~~~~~~~~~~~~~(a)\\
889 \column{.50\textwidth}
890 \includegraphics[scale=0.35]{Figures/R1/LT50.eps}
891 \footnotesize \\~~~~~~~~~~~~~~~~~~~~~~~~~~~~~(b) \\
893 \caption{Network lifetime for (a) $Lifetime_{95}$ and (b) $Lifetime_{50}$}
894 \label{Figures/ch4/Rh3/EC}
902 \section{\small {Perimeter-based Coverage Optimization (PeCO)}}
908 \begin{frame}{\small PeCO protocol $\blacktriangleright$ Assumptions and models}
913 \column{.50\textwidth}
914 \includegraphics[scale=0.40]{Figures/ch6/pcm.jpg}
915 \footnotesize \\~~~~~~~~~~~~~~~~~~~~~~~~~~(a)\\
916 \column{.50\textwidth}
917 $$\alpha = \arccos \left(\dfrac{Dist(u,v)}{2R_s}
919 \includegraphics[scale=0.40]{Figures/ch6/twosensors.jpg}
920 \footnotesize \\~~~~~~~~~~~~~~~~~~~~~~~~~~(b) \\
922 \caption{(a) Perimeter coverage of sensor node 0 and (b) finding the arc of
923 $u$'s perimeter covered by $v$.}
932 \begin{frame}{\small PeCO protocol $\blacktriangleright$ Assumptions and models}
937 % \column{.50\textwidth}
938 \includegraphics[scale=0.6]{Figures/ch6/expcm2.jpg}
939 %\footnotesize \\~~~~~~~~~~~~~~~~~~~~~~~~~~(a)\\
940 %\column{.50\textwidth}
941 %\includegraphics[scale=0.38]{Figures/tbl.jpeg}
942 %\footnotesize \\~~~~~~~~~~~~~~~~~~~~~~~~~~(b) \\
944 %\caption{(a) Maximum coverage levels for perimeter of sensor node $0$. and (b) Coverage intervals and contributing sensors for sensor node 0.}
945 % \label{pcm2sensors}
949 \textcolor {red} {Set of sensors involved in coverage interval of sensor 0 between 3R to 4R $\Rightarrow$ [0,1,2,4]\\
950 Maximum coverage level: 4
952 %For example, the interval between 3R to 4R is covered by 4 sensors (0,1,2,4), it means the coverage level is 4
961 \begin{frame}{\small PeCO protocol $\blacktriangleright$ PeCO protocol algorithm}
963 %\includegraphics[height = 7.2cm]{Figures/algo6.jpeg}
967 \includegraphics[height = 7.2cm]{Figures/Algo3.png}
975 \begin{frame}{\small PeCO protocol $\blacktriangleright$ Perimeter-based coverage problem formulation}
980 \includegraphics[scale=0.5]{Figures/modell3.pdf}
990 \begin{frame}{\small PeCO protocol $\blacktriangleright$ Performance evaluation and analysis}
994 \includegraphics[scale=0.5] {Figures/ch6/R/CR.eps}
995 \caption{Coverage ratio for 200 deployed nodes.}
1002 %%%%%%%%%%%%%%%%%%%%
1004 %%%%%%%%%%%%%%%%%%%%
1005 \begin{frame}{\small PeCO protocol $\blacktriangleright$ Performance evaluation and analysis}
1009 \includegraphics[scale=0.5]{Figures/ch6/R/ASR.eps}
1010 \caption{Active sensors ratio for 200 deployed nodes.}
1016 %%%%%%%%%%%%%%%%%%%%
1018 %%%%%%%%%%%%%%%%%%%%
1019 \begin{frame}{\small PeCO protocol $\blacktriangleright$ Performance evaluation and analysis}
1023 \column{.50\textwidth}
1024 \includegraphics[scale=0.35]{Figures/ch6/R/EC95.eps}
1025 \footnotesize \\~~~~~~~~~~~~~~~~~~~~~~~~~~~~~(a)\\
1026 \column{.50\textwidth}
1027 \includegraphics[scale=0.35]{Figures/ch6/R/EC50.eps}
1028 \footnotesize \\~~~~~~~~~~~~~~~~~~~~~~~~~~~~~(b) \\
1030 \caption{Energy consumption per period for (a)~$Lifetime_{95}$ and (b)~$Lifetime_{50}$.}
1037 %%%%%%%%%%%%%%%%%%%%
1039 %%%%%%%%%%%%%%%%%%%%
1040 \begin{frame}{\small PeCO protocol $\blacktriangleright$ Performance evaluation and analysis}
1044 \column{.50\textwidth}
1045 \includegraphics[scale=0.35]{Figures/ch6/R/LT95.eps}
1046 \footnotesize \\~~~~~~~~~~~~~~~~~~~~~~~~~~~~~(a)\\
1047 \column{.50\textwidth}
1048 \includegraphics[scale=0.35]{Figures/ch6/R/LT50.eps}
1049 \footnotesize \\~~~~~~~~~~~~~~~~~~~~~~~~~~~~~(b) \\
1051 \caption{Network lifetime for (a)~$Lifetime_{95}$ and (b)~$Lifetime_{50}$.}
1057 %%%%%%%%%%%%%%%%%%%%
1059 %%%%%%%%%%%%%%%%%%%%
1060 %\begin{frame}{\small PeCO Protocol $\blacktriangleright$ Performance Evaluation and Analysis}
1062 %\begin{figure} [h!]
1063 %\centering \includegraphics[scale=0.5]{Figures/ch6/R/LTa.eps}
1064 %\caption{Network lifetime for different coverage ratios.}
1071 %%%%%%%%%%%%%%%%%%%%
1073 %%%%%%%%%%%%%%%%%%%%
1074 \section{\small {Conclusion and perspectives}}
1077 %%%%%%%%%%%%%%%%%%%%
1079 %%%%%%%%%%%%%%%%%%%%
1080 \begin{frame}{Conclusion}
1081 \begin{enumerate} [$\blacktriangleright$]
1083 \item Two-step approaches are proposed to optimize both coverage and lifetime performances, where:
1085 \item Sensing field is divided into smaller subregions using divide-and-conquer method
1086 \item One of the proposed optimization protocols is applied in each subregion in a distributed parallel way
1088 \item The proposed protocols (DiLCO, MuDiLCO, PeCO) combine two efficient mechanisms
1090 \item Network leader election, and
1091 \item Sensor activity scheduling based optimization
1093 \item Our protocols are periodic where each period consists of 4 phases
1095 \item Information exchange
1096 \item Network leader election
1097 \item Decision based optimization
1108 %%%%%%%%%%%%%%%%%%%%
1110 %%%%%%%%%%%%%%%%%%%%
1111 \begin{frame}{Conclusion}
1112 \begin{enumerate} [$\blacktriangleright$]
1114 \item DiLCO and PeCO provide a schedule for one round per period
1115 \item MuDiLCO provides a schedule for multiple rounds per period
1116 \item Comparison results show that DiLCO, MuDiLCO, and PeCO protocols
1118 \item Maintain the coverage for a larger number of rounds
1119 \item Use less active nodes to save energy efficiently during sensing
1120 \item Are more powerful against network disconnections
1121 \item Perform the optimization with suitable execution times
1122 \item Consume less energy
1123 \item Prolong the network lifetime
1129 \begin{frame}{Conclusion}
1131 \begin{block}{\textcolor{white}{Journal Articles}}
1132 \begin{enumerate}[$\lbrack$1$\rbrack$]
1133 \item Ali Kadhum Idrees, Karine Deschinkel, Michel Salomon, and Rapha\"el Couturier. Perimeter-based Coverage Optimization to Improve Lifetime in Wireless Sensor Networks. \textit{Engineering Optimization, 2015, (Submitted)}.
1135 \item Ali Kadhum Idrees, Karine Deschinkel, Michel Salomon, and Rapha\"el Couturier. Multiround Distributed Lifetime Coverage Optimization Protocol in Wireless Sensor Networks. \textit{Ad Hoc Networks, 2015, (Submitted)}.
1137 \item Ali Kadhum Idrees, Karine Deschinkel, Michel Salomon, and Rapha\"el Couturier. Distributed Lifetime Coverage Optimization Protocol in Wireless Sensor Networks. \textit{Journal of Supercomputing , 2015, (Submitted)}.
1141 \begin{block}{\textcolor{white}{Technical Reports}}
1143 \begin{enumerate}[$\lbrack$1$\rbrack$]
1144 \item Ali Kadhum Idrees, Karine Deschinkel, Michel Salomon, and Rapha\"el
1145 Distributed lifetime coverage optimization protocol in wireless sensor networks. Technical Report DISC2014-X, University of Franche-Comte - FEMTO-ST Institute, DISC Research Department, Octobre 2014.
1149 \begin{block}{\textcolor{white}{Conference Articles}}
1150 \begin{enumerate}[$\lbrack$1$\rbrack$]
1151 \item Ali Kadhum Idrees, Karine Deschinkel, Michel Salomon, and Rapha\"el
1152 Coverage and lifetime optimization in heterogeneous energy wireless sensor networks. In ICN 2014, The Thirteenth International Conference on Networks, pages 49–54, 2014.
1158 %%%%%%%%%%%%%%%%%%%%
1160 %%%%%%%%%%%%%%%%%%%%
1161 \begin{frame}{Perspectives}
1162 \begin{enumerate} [$\blacktriangleright$]
1163 \item Investigate the optimal number of subregions
1164 \item Design a heterogeneous integrated optimization protocol to integrate coverage, routing, and data aggregation protocols
1165 \item Extend PeCO protocol so that the schedules are planned for multiple sensing periods
1166 \item Consider particle swarm optimization or evolutionary algorithms to obtain quickly near optimal solutions
1167 \item Improve our mathematical models to take into account heterogeneous sensors from both energy and node characteristics point of views
1168 %\item The cluster head will be selected in a distributed way and based on local information.
1175 %%%%%%%%%%%%%%%%%%%%
1177 %%%%%%%%%%%%%%%%%%%%
1178 %\begin{frame}{Mes perspectives}
1182 %%%%%%%%%%%%%%%%%%%%
1184 %%%%%%%%%%%%%%%%%%%%
1188 \textcolor{BleuFemto}{Thank You for Your Attention!}\\\vspace{2cm}
1189 \textcolor{BleuFemto}{Questions?}\\