X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/ThesisAli.git/blobdiff_plain/32808ea756588e2c67d047ff4e644c9aeeeee844..823922b46fe128564f6ed32de2930828d6b74368:/CHAPITRE_04.tex

diff --git a/CHAPITRE_04.tex b/CHAPITRE_04.tex
index cb2c91f..3e691b7 100644
--- a/CHAPITRE_04.tex
+++ b/CHAPITRE_04.tex
@@ -32,7 +32,7 @@ The remainder of this chapter is organized as follows. The next section is devot
 \noindent  We consider a sensor  network composed  of static  nodes distributed independently and uniformly at random.  A high-density deployment ensures a high coverage ratio of the interested area at the start. The nodes are supposed to have homogeneous characteristics from a communication and a processing point of view, whereas they  have heterogeneous energy provisions.  Each  node has access to its location thanks,  either to a hardware component (like a  GPS unit) or a location discovery algorithm. Furthermore, we assume that sensor nodes are time synchronized in order to properly coordinate their operations to achieve complex sensing tasks~\cite{ref157}. Two sensor nodes are supposed to be neighbors if the euclidean distance between them is at most equal to 2$R_s$, where $R_s$ is the sensing range.
  
 
-\indent We consider a boolean disk coverage model which is the most widely used sensor coverage  model in the  literature. Thus, since  a sensor has a constant sensing range $R_s$, every space points within a disk centered at a sensor with the radius of the sensing range is said to be covered with this sensor. We also assume  that  the communication  range $R_c$ is at least twice the sensing range $R_s$ (i.e., $R_c \geq  2R_s$). In  fact, Zhang and Hou~\cite{ref126} proved  that if the transmission range  fulfills the previous hypothesis, a complete coverage of  a convex area implies connectivity among the working nodes in the active mode. we consider multi-hop communication.
+\indent We consider a boolean disk coverage model which is the most widely used sensor coverage  model in the  literature. Thus, since  a sensor has a constant sensing range $R_s$, each space point within a disk centered at a sensor with the radius of the sensing range is said to be covered with this sensor. We also assume  that  the communication  range $R_c$ is at least twice the sensing range $R_s$ (i.e., $R_c \geq  2R_s$). In  fact, Zhang and Hou~\cite{ref126} proved  that if the transmission range  fulfills the previous hypothesis, a complete coverage of  a convex area implies connectivity among the working nodes in the active mode. we consider multi-hop communication.
 %We assume that each sensor node can directly transmit its measurements toward a mobile sink node. 
 %For example, a sink can be an unmanned aerial vehicle (UAV) flying regularly over the sensor field to collect measurements from sensor nodes. The mobile sink node collects the measurements and transmits them to the base station.
 
@@ -139,7 +139,7 @@ This  step includes choosing  a wireless  sensor node called leader, which  will
 
 \subsubsection{Decision phase}
 \label{ch4:sec:02:03:03}
-The  leader will  solve an  integer  program (see  section~\ref{ch4:sec:03}) to select which sensors will be  activated in the following sensing phase to cover  the subregion.  It will send  ActiveSleep packet  to each sensor in the subregion based on the algorithm's results.
+The  leader will  solve an  integer  program (see  section~\ref{ch4:sec:03}) to select which sensors will be  activated in the following sensing phase to cover  the subregion.  It will send an ActiveSleep packet  to each sensor in the subregion based on the algorithm's results.
 
 %($RE_j$)  corresponds to its remaining energy) to be alive during  the selected periods knowing  that $E_{th}$ is the  amount of energy required to be alive during one period.
 
@@ -519,7 +519,7 @@ In this experiment, the execution time of the distributed optimization approach
 
 
 
-\begin{figure}[h!t]
+\begin{figure}[t]
 \centering
 \includegraphics[scale=0.8]{Figures/ch4/R1/T.pdf}  
 \caption{Execution Time (in seconds)}