%It also means that distributing the algorithm in each node and subdividing the sensing field into many subregions, which are managed independently and simultaneously, is the most relevant way to maximize the lifetime of a network.
\end{enumerate}
-
-\section{Conclusion}
-\label{ch4:sec:05}
-A crucial problem in WSN is to schedule the sensing activities of the different nodes in order to ensure both coverage of the area of interest and longer network lifetime. The inherent limitations of sensor nodes, in energy provision, communication, and computing capacities, require protocols that optimize the use of the available resources to fulfill the sensing task. To address this problem, this chapter proposes a two-step approach. Firstly, the field of sensing
-is divided into smaller subregions using the concept of divide-and-conquer method. Secondly, a distributed protocol called Distributed Lifetime Coverage Optimization is applied in each subregion to optimize the coverage and lifetime performances. In a subregion, our protocol consists in electing a leader node, which will then perform a sensor activity scheduling. The challenges include how to select the most efficient leader in each subregion and the best representative set of active nodes to ensure a high level of coverage. To assess the performance of our approach, we compared it with two other approaches using many performance metrics like coverage ratio or network lifetime. We have also studied the impact of the number of subregions chosen to subdivide the area of interest, considering different network sizes. The experiments show that increasing the number of subregions improves the lifetime. The more subregions there are, the more robust the network is against random disconnection resulting from dead nodes. However, for a given sensing field and network size there is an optimal number of subregions. Therefore, in case of our simulation context a subdivision in $16$~subregions seems to be the most relevant.
-
\begin{figure}[p!]
\centering
% \begin{multicols}{0}
\caption{Network lifetime for (a) $Lifetime_{95}$ and (b) $Lifetime_{50}$}
\label{Figures/ch4/R3/LT}
\end{figure}
+\section{Conclusion}
+\label{ch4:sec:05}
+A crucial problem in WSN is to schedule the sensing activities of the different nodes in order to ensure both coverage of the area of interest and longer network lifetime. The inherent limitations of sensor nodes, in energy provision, communication, and computing capacities, require protocols that optimize the use of the available resources to fulfill the sensing task. To address this problem, this chapter proposes a two-step approach. Firstly, the field of sensing
+is divided into smaller subregions using the concept of divide-and-conquer method. Secondly, a distributed protocol called Distributed Lifetime Coverage Optimization is applied in each subregion to optimize the coverage and lifetime performances. In a subregion, our protocol consists in electing a leader node, which will then perform a sensor activity scheduling. The challenges include how to select the most efficient leader in each subregion and the best representative set of active nodes to ensure a high level of coverage. To assess the performance of our approach, we compared it with two other approaches using many performance metrics like coverage ratio or network lifetime. We have also studied the impact of the number of subregions chosen to subdivide the area of interest, considering different network sizes. The experiments show that increasing the number of subregions improves the lifetime. The more subregions there are, the more robust the network is against random disconnection resulting from dead nodes. However, for a given sensing field and network size there is an optimal number of subregions. Therefore, in case of our simulation context a subdivision in $16$~subregions seems to be the most relevant.
+
+
\contentsline {subsection}{\numberline {4.4.5}Performance Analysis for Different Number of Subregions}{87}{subsection.4.4.5}
\contentsline {subsection}{\numberline {4.4.6}Performance Analysis for Different Number of Primary Points}{92}{subsection.4.4.6}
\contentsline {subsection}{\numberline {4.4.7}Performance Comparison with other Approaches}{96}{subsection.4.4.7}
-\contentsline {section}{\numberline {4.5}Conclusion}{103}{section.4.5}
-\contentsline {chapter}{\numberline {5}Multiround Distributed Lifetime Coverage Optimization Protocol}{105}{chapter.5}
-\contentsline {section}{\numberline {5.1}Introduction}{105}{section.5.1}
-\contentsline {section}{\numberline {5.2}Description of the MuDiLCO Protocol }{105}{section.5.2}
-\contentsline {section}{\numberline {5.3}Primary Points based Multiround Coverage Problem Formulation}{107}{section.5.3}
-\contentsline {section}{\numberline {5.4}Experimental Study and Analysis}{109}{section.5.4}
-\contentsline {subsection}{\numberline {5.4.1}Simulation Setup}{109}{subsection.5.4.1}
-\contentsline {subsection}{\numberline {5.4.2}Metrics}{109}{subsection.5.4.2}
-\contentsline {subsection}{\numberline {5.4.3}Results Analysis and Comparison }{110}{subsection.5.4.3}
-\contentsline {section}{\numberline {5.5}Conclusion}{116}{section.5.5}
-\contentsline {chapter}{\numberline {6} Perimeter-based Coverage Optimization to Improve Lifetime in WSNs}{117}{chapter.6}
-\contentsline {section}{\numberline {6.1}Introduction}{117}{section.6.1}
-\contentsline {section}{\numberline {6.2}Description of the PeCO Protocol}{117}{section.6.2}
-\contentsline {subsection}{\numberline {6.2.1}Assumptions and Models}{117}{subsection.6.2.1}
-\contentsline {subsection}{\numberline {6.2.2}PeCO Protocol Algorithm}{120}{subsection.6.2.2}
-\contentsline {section}{\numberline {6.3}Perimeter-based Coverage Problem Formulation}{123}{section.6.3}
-\contentsline {section}{\numberline {6.4}Performance Evaluation and Analysis}{124}{section.6.4}
-\contentsline {subsection}{\numberline {6.4.1}Simulation Settings}{124}{subsection.6.4.1}
-\contentsline {subsection}{\numberline {6.4.2}Simulation Results}{125}{subsection.6.4.2}
-\contentsline {subsubsection}{\numberline {6.4.2.1}Coverage Ratio}{125}{subsubsection.6.4.2.1}
-\contentsline {subsubsection}{\numberline {6.4.2.2}Active Sensors Ratio}{125}{subsubsection.6.4.2.2}
-\contentsline {subsubsection}{\numberline {6.4.2.3}Energy Consumption}{126}{subsubsection.6.4.2.3}
-\contentsline {subsubsection}{\numberline {6.4.2.4}Network Lifetime}{126}{subsubsection.6.4.2.4}
-\contentsline {subsubsection}{\numberline {6.4.2.5}Impact of $\alpha $ and $\beta $ on PeCO's performance}{127}{subsubsection.6.4.2.5}
-\contentsline {section}{\numberline {6.5}Conclusion}{131}{section.6.5}
-\contentsline {part}{III\hspace {1em}Conclusion and Perspectives}{133}{part.3}
-\contentsline {chapter}{\numberline {7}Conclusion and Perspectives}{135}{chapter.7}
-\contentsline {section}{\numberline {7.1}Conclusion}{135}{section.7.1}
-\contentsline {section}{\numberline {7.2}Perspectives}{136}{section.7.2}
-\contentsline {part}{Publications}{139}{chapter*.15}
-\contentsline {part}{Bibliographie}{141}{section*.18}
+\contentsline {section}{\numberline {4.5}Conclusion}{105}{section.4.5}
+\contentsline {chapter}{\numberline {5}Multiround Distributed Lifetime Coverage Optimization Protocol}{107}{chapter.5}
+\contentsline {section}{\numberline {5.1}Introduction}{107}{section.5.1}
+\contentsline {section}{\numberline {5.2}Description of the MuDiLCO Protocol }{107}{section.5.2}
+\contentsline {section}{\numberline {5.3}Primary Points based Multiround Coverage Problem Formulation}{109}{section.5.3}
+\contentsline {section}{\numberline {5.4}Experimental Study and Analysis}{111}{section.5.4}
+\contentsline {subsection}{\numberline {5.4.1}Simulation Setup}{111}{subsection.5.4.1}
+\contentsline {subsection}{\numberline {5.4.2}Metrics}{111}{subsection.5.4.2}
+\contentsline {subsection}{\numberline {5.4.3}Results Analysis and Comparison }{112}{subsection.5.4.3}
+\contentsline {section}{\numberline {5.5}Conclusion}{118}{section.5.5}
+\contentsline {chapter}{\numberline {6} Perimeter-based Coverage Optimization to Improve Lifetime in WSNs}{119}{chapter.6}
+\contentsline {section}{\numberline {6.1}Introduction}{119}{section.6.1}
+\contentsline {section}{\numberline {6.2}Description of the PeCO Protocol}{119}{section.6.2}
+\contentsline {subsection}{\numberline {6.2.1}Assumptions and Models}{119}{subsection.6.2.1}
+\contentsline {subsection}{\numberline {6.2.2}PeCO Protocol Algorithm}{122}{subsection.6.2.2}
+\contentsline {section}{\numberline {6.3}Perimeter-based Coverage Problem Formulation}{125}{section.6.3}
+\contentsline {section}{\numberline {6.4}Performance Evaluation and Analysis}{126}{section.6.4}
+\contentsline {subsection}{\numberline {6.4.1}Simulation Settings}{126}{subsection.6.4.1}
+\contentsline {subsection}{\numberline {6.4.2}Simulation Results}{127}{subsection.6.4.2}
+\contentsline {subsubsection}{\numberline {6.4.2.1}Coverage Ratio}{127}{subsubsection.6.4.2.1}
+\contentsline {subsubsection}{\numberline {6.4.2.2}Active Sensors Ratio}{127}{subsubsection.6.4.2.2}
+\contentsline {subsubsection}{\numberline {6.4.2.3}Energy Consumption}{128}{subsubsection.6.4.2.3}
+\contentsline {subsubsection}{\numberline {6.4.2.4}Network Lifetime}{128}{subsubsection.6.4.2.4}
+\contentsline {subsubsection}{\numberline {6.4.2.5}Impact of $\alpha $ and $\beta $ on PeCO's performance}{129}{subsubsection.6.4.2.5}
+\contentsline {section}{\numberline {6.5}Conclusion}{133}{section.6.5}
+\contentsline {part}{III\hspace {1em}Conclusion and Perspectives}{135}{part.3}
+\contentsline {chapter}{\numberline {7}Conclusion and Perspectives}{137}{chapter.7}
+\contentsline {section}{\numberline {7.1}Conclusion}{137}{section.7.1}
+\contentsline {section}{\numberline {7.2}Perspectives}{138}{section.7.2}
+\contentsline {part}{Publications}{141}{chapter*.15}
+\contentsline {part}{Bibliographie}{156}{chapter*.19}
