X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/ThesisAli.git/blobdiff_plain/c89964e41e4051ab0de84db6ed19780f7e287887..e2db4b545180bb46a9490b6c675068eee6005374:/CHAPITRE_01.tex

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@@ -285,7 +285,7 @@ nodes in order to achieve their tasks efficiently.
 \indent The topology control schemes deal with the redundancy in the WSNs. The WSN is always deploying with high density and in a random way, where a large number of wireless sensor nodes are usually throwing by the airplane over the area of interest. The purpose of deploying a dense WSN is to cope with the sensor failure during or after the WSN deployment and to maximize the network lifetime by means of exploiting the overlapping among the sensor nodes in the network by putting the redundant sensor nodes into sleep mode in order to benefit from it later. The major goal of topology control protocols is to dynamically adapt network topology based on requirements of application so as to minimize the number of active sensor nodes, achieve the tasks of the network, and prolong the network lifetime~\cite{ref56,ref22}. Many factors can be used to decide which sensor nodes should be turned on or off and when. The topology control schemes have been classified into two categories~\cite{ref56}: 
  
 \begin{enumerate} [(I)]
-\item \textbf{Location Driven Protocols} in which determining which wireless sensor node to turn on or off based on its location that should be known; for example, Geographical Adaptive Fidelity (GAF) protocol~\cite{ref84}. These schemes are called network coverage that describing how the sensing field is monitored using minimum number of wireless sensor nodes in order to achieve application requirements and prolong the network lifetime~\cite{ref102}.
+\item \textbf{Location Driven Protocols} in which determining which wireless sensor node to turn on or off based on its location that should be known; for example, Geographical Adaptive Fidelity (GAF) protocol~\cite{GAF}. These schemes are called network coverage that describing how the sensing field is monitored using minimum number of wireless sensor nodes in order to achieve application requirements and prolong the network lifetime~\cite{ref102}.
 
 \item \textbf{Connectivity Driven Protocols} in which the wireless sensor nodes are activated or deactivated so that the sensing coverage and connectivity of WSN are assured such as Span protocol~\cite{ref85}.
 \end{enumerate}
@@ -342,17 +342,17 @@ In the WSNs include a static sink, the wireless sensor nodes, which are near the
 
 \item The time spent by WSN until the death of the first wireless sensor node ( or cluster head ) in the network due to its energy depletion~\cite{ref162,ref163}.
 \item The time spent by WSN and has at least a specific set $\beta$ of alive sensor nodes in WSN~\cite{ref164,ref165}.
-\item The time spent by WSN until the death of all wireless sensor nodes in WSN because they have depleted their energy~\cite{ref166}.
+\item The time spent by WSN until the death of all wireless sensor nodes in WSN because they have depleted their energy~\cite{ref124}.
 \item For k-coverage, is the time spent by WSN in covering the area of interest by at least $k$ sensor nodes~\cite{DESK}.
 \item For 100 $\%$ coverage is the time spent by WSN in covering each target or the whole area by at least one sensor node~\cite{ref167}.
 \item For $\alpha$-coverage: the total time by which at least $\alpha$ part of the sensing field is covered with at least one node~\cite{ref168}; or is the time spent by WSN until the coverage ratio becomes less than a predetermined threshold $\alpha$~\cite{ref169}.
 \item The working time spent by the system before either the coverage ratio or delivery ratio become less than a predetermined threshold~\cite{ref170}.
-\item The number of the successful data gathering trips~\cite{ref173}.
+\item The number of the successful data gathering trips~\cite{ref53}.
 \item The number of sent packets~\cite{ref174}.
 \item The percentage of wireless sensor nodes that have a route to the sink~\cite{ref170}.
 \item The prediction of the total period of time during which the probability of ensuring the connectivity and k-coverage concurrently is at least $\alpha$~\cite{ref175}.
 \item The time spent by WSN until losing the connectivity or the coverage~\cite{ref171}.
-\item The time spent by WSN until acceptable event detection ratio is not acceptable in the network~\cite{ref166}.
+\item The time spent by WSN until acceptable event detection ratio is not acceptable in the network~\cite{ref124}.
 \item The time during which the application requirement is satisfied~\cite{ref172}.
 \end{enumerate}
 
@@ -365,10 +365,10 @@ The network lifetime has been defined in this dissertation as the time spent by
 \label{ch1:sec:8}
 %\indent Energy efficiency is  a crucial issue in wireless sensor networks since sensory consumption, in  order to  maximize the network lifetime, represents  the major difficulty when designing WSNs. As a consequence, 
 
-One of the scientific research challenges in  WSNs, which has  been addressed by a large amount of literature during the  last few  years, is  the design of  energy efficient  approaches for coverage and connectivity~\cite{ref94,ref101}. Coverage reflects how well a sensor field is  monitored. On the one hand, we want to monitor the  area of interest in the most efficient way~\cite{ref95}.  On the other hand, we want to use as less energy as possible. Sensor nodes are battery-powered with no mean  of recharging  or replacing,  usually  due to  environmental (hostile  or unpractical environments)  or cost reasons.   Therefore, it is desired  that the WSNs are deployed  with high densities so as to  exploit the overlapping sensing regions of some sensor  nodes to save energy by turning off  some of them during the sensing phase to prolong the network lifetime. The most discussed coverage problems in literature can be classified into three types~\cite{ref96}:
+One of the scientific research challenges in  WSNs, which has  been addressed by a large amount of literature during the  last few  years, is  the design of  energy efficient  approaches for coverage and connectivity~\cite{ref94,ref101}. Coverage reflects how well a sensor field is  monitored. On the one hand, we want to monitor the  area of interest in the most efficient way~\cite{ref95}.  On the other hand, we want to use as less energy as possible. Sensor nodes are battery-powered with no mean  of recharging  or replacing,  usually  due to  environmental (hostile  or unpractical environments)  or cost reasons.   Therefore, it is desired  that the WSNs are deployed  with high densities so as to  exploit the overlapping sensing regions of some sensor  nodes to save energy by turning off  some of them during the sensing phase to prolong the network lifetime. The most discussed coverage problems in literature can be classified into three types~\cite{ref102}:
 \begin{enumerate}[(i)] 
-\item \textbf{Area coverage}~\cite{ref97,ref153} where every point inside an area is to be monitored. The work in this dissertation deals with this type of coverage.
-\item \textbf{Target coverage}~\cite{ref98,ref153} where the main objective is to cover only a finite number of discrete points called targets.
+\item \textbf{Area coverage}~\cite{ref97,ref101} where every point inside an area is to be monitored. The work in this dissertation deals with this type of coverage.
+\item \textbf{Target coverage}~\cite{ref98,ref101} where the main objective is to cover only a finite number of discrete points called targets.
 \item \textbf{Barrier coverage}~\cite{ref99,ref100} to prevent intruders from entering into the region of interest. 
 \end{enumerate}