Update by Ali

diff --git a/CHAPITRE_01.tex b/CHAPITRE_01.tex
index 338d61c59736ee183ee7ede08d3dd43fec15818e..201174b85ff0cb723b0834b7bcd9062cc0294739 100755 (executable)
--- a/CHAPITRE_01.tex
+++ b/CHAPITRE_01.tex
@@ -387,7 +387,7 @@ where $d(s_i,P) = \sqrt{(x_i - x)^2 + (y_i - y)^2}$, denotes the Euclidean dista
 
 
 \item \textbf{The Probabilistic Sensing Model}
 
 
 \item \textbf{The Probabilistic Sensing Model}

-In reality, the event detection by sensor node is imprecise; therefore, the coverage $C_{xy}$ requires to be represented in probabilistic manner. The probabilistic sensing model is more practical, which can be used as an extension for the binary disc sensing model. The equation \ref{eq2-ch1} shows the probabilistic sensing model that expresses the coverage $C_{xy}$ of the point P by sensor node $s_i$.
+In reality, the event detection by sensor node is imprecise; therefore, the coverage $C_{xy}$ requires to be represented in probabilistic manner. The probabilistic sensing model is more practical, which can be used as an extension for the binary disc sensing model. The equation \ref{eq2-ch1} shows the probabilistic sensing model that expresses the coverage $C_{xy}$ of the point P by sensor node $s_i$ as follow

 
 \begin{equation}
 C_{xy}\left(s_i \right)  = \left \{ 
 
 \begin{equation}
 C_{xy}\left(s_i \right)  = \left \{ 


@@ -410,7 +410,7 @@ The coverage protocols proposed in this dissertation use the binary disc sensing
 
 \section{Design Issues for Coverage Problems:}
 \label{ch1:sec:11}
 
 \section{Design Issues for Coverage Problems:}
 \label{ch1:sec:11}

-\indent Several design issues that should be considered in order to produce a solutions for the coverage problems in WSNs. These design issues can be classified into~\cite{ref103}:
+\indent Several design issues should be considered in order to produce solutions for the coverage problems in WSNs. These design issues can be classified into~\cite{ref103}:

 
 \begin{enumerate}[(i)]
 \item $\textbf{Coverage Type}$ refers to determining what is it exactly that you are trying to cover. Typically, it may be required to monitor a whole area, observe a set of targets, or look for a breach among a barrier. 
 
 \begin{enumerate}[(i)]
 \item $\textbf{Coverage Type}$ refers to determining what is it exactly that you are trying to cover. Typically, it may be required to monitor a whole area, observe a set of targets, or look for a breach among a barrier. 


@@ -493,4 +493,4 @@ The typical parameters are set as: $E_{elec}$ = 50 nJ/bit, $\varepsilon_{fs}$ =
 \section{Conclusion}
 \label{ch1:sec:10}
 
 \section{Conclusion}
 \label{ch1:sec:10}
 

-\indent In this chapter, an overview about the wireless sensor networks have been presented that represent our focus in this dissertation.  The structure of the the typical wireless sensor network and the main components of the sensor nodes have been demonstrated. Several types of wireless sensor networks are described. Various fields of applications covering a wide spectrum for a WSNs have been presented, including health, home, environmental, military, and industrial applications.  As demonstrated, since sensor nodes have limited battery life; since it is impossible to replace batteries, especially in remote and hostile environments; the limited power of a battery represents the critical challenge in WSNs. The main challenges in WSNs have been explained; on the other hand, the energy efficient solutions have been proposed in order to handle these challenges through energy conservation to prolong the network lifetime. Many energy efficient mechanisms have been illustrated, which are aimed to reduce the energy consumption by the different units of the wireless sensor nodes in WSNs. The definition of the network lifetime has been presented and in different contexts.  The problem of the coverage is explained, where constructing energy efficient coverage protocols one of the main scientific research challenges in WSNs. This chapter highlights the main design issues for the coverage problems that need to be considered during designing a coverage protocol for WSNs. In addition, the energy consumption Modeling have been demonstrated. 
+\indent In this chapter, an overview about the wireless sensor networks have presented that represent our focus in this dissertation.  The structure of the typical wireless sensor network and the main components of the sensor nodes have been demonstrated. Several types of wireless sensor networks are described. Various fields of applications covering a wide spectrum for a WSNs have been presented, including health, home, environmental, military, and industrial applications.  As demonstrated, since sensor nodes have limited battery life; since it is impossible to replace batteries, especially in remote and hostile environments; the limited power of a battery represents the critical challenge in WSNs. The main challenges in WSNs have explained; on the other hand, the energy efficient solutions have proposed in order to handle these challenges through energy conservation to prolong the network lifetime. Many energy efficient mechanisms have been illustrated, which are aimed to reduce the energy consumption by the different units of the wireless sensor nodes in WSNs. The definition of the network lifetime has been presented and in different contexts.  The problem of the coverage is explained, where constructing energy efficient coverage protocols one of the main scientific research challenges in WSNs. This chapter highlights the main design issues for the coverage problems that need to be considered during designing a coverage protocol for WSNs. In addition, the energy consumption Modeling have been demonstrated. 

diff --git a/CONCLUSION.tex b/CONCLUSION.tex
index 8855ada12d088262025d9f362abc0074059e6f56..f48618e45b3b2af23f422d4e3027991912550c58 100644 (file)
--- a/CONCLUSION.tex
+++ b/CONCLUSION.tex
@@ -6,20 +6,27 @@
 
 In this dissertation, we have concentrated on proposing a distributed optimization protocols so as to prolong the lifetime of wireless sensor networks. We have addressed the problem of the area coverage and the lifetime optimization in wireless sensor networks, where the ultimate goal is the coverage preservation and the extension of the network lifetime continuously and effectively when monitoring a certain area (or region) of interest. 
 
 
 In this dissertation, we have concentrated on proposing a distributed optimization protocols so as to prolong the lifetime of wireless sensor networks. We have addressed the problem of the area coverage and the lifetime optimization in wireless sensor networks, where the ultimate goal is the coverage preservation and the extension of the network lifetime continuously and effectively when monitoring a certain area (or region) of interest. 
 

-\section*{Perspectives}
+The first part of the dissertation has presented the scientific background including WSNs, brief survey of related works, and evaluation tools as well as optimization solvers.  
+
+In chapter 1, We have began with a general overview on wireless sensor networks. We have described various concepts, mechanisms, types, applications, and challenges in WSNs. We have presented several energy-efficient techniques so as to improve the network lifetime of WSNs. The coverage problem, the network lifetime, and the energy consumption modeling in WSNs have explained. A brief survey about coverage algorithms in literature is achieved in chapter 2.
+We have classified those works into centralized and distributed algorithms. We have given a brief comparison of the main characteristics of each approach. This part finally included in chapter 3, a comparative study of different evaluation tools dedicated to WSNs. In addition, we have illustrated a various commercial and free optimization solvers considering the main features of each one.

 
 

+In the second part of the dissertation, We have designed a new three different optimization protocols, which schedules nodes’ activities (wake up and sleep stages) with the objective of maintaining a good coverage ratio while maximizing the network lifetime in WSNs. This part proposes a two-step approaches. Firstly, the field of sensing is divided into smaller subregions using the concept of divide-and-conquer method. Secondly, one of the proposed optimization protocols is applied in each subregion in a distributed parallel way to optimize the coverage and lifetime performances.

 
 

+In chapter 4, 
+ 

 
 

+ 

 
 
 
 
 
 
 
 
 
 

+\section*{Perspectives}

 
 
 
 

- 

 
 
 
 
 
 
 
 

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diff --git a/Thesis.tex b/Thesis.tex
index a4416ce5e64e0b092d2826f94664794cc6b68ddb..ea9beb0fe9114d08edae9b208e0d64c8bf4f8ef3 100755 (executable)
--- a/Thesis.tex
+++ b/Thesis.tex
@@ -55,7 +55,6 @@
 
 \include{CHAPITRE_05}
 
 
 \include{CHAPITRE_05}
 

-%% 

 \include{CHAPITRE_06}
 
 
 \include{CHAPITRE_06}
 
 


@@ -74,5 +73,5 @@
 \addcontentsline{toc}{part}{Bibliographie}
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 \addcontentsline{toc}{part}{Bibliographie}
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- 
+

 \end{document}
 \end{document}