X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/ThesisAli.git/blobdiff_plain/946555d85197e77a0b8f06b8ee4e4d2b6c788f3d..dd42ca97656c19804fa0624b8e9095293f58976f:/CHAPITRE_04.tex?ds=sidebyside

diff --git a/CHAPITRE_04.tex b/CHAPITRE_04.tex
index 0cdeebe..9e478cc 100644
--- a/CHAPITRE_04.tex
+++ b/CHAPITRE_04.tex
@@ -1,6 +1,6 @@
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 %%                          %%
-%%       CHAPITRE 04        %%
+%%       CHAPTER 04        %%
 %%                          %%
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
@@ -29,11 +29,11 @@ The area of  interest can be divided using  the divide-and-conquer strategy into
 smaller  areas,  called  subregions,  and  then our MuDiLCO  protocol will be
 implemented in each subregion in a distributed way.
 
-As  can be seen  in Figure~\ref{fig2},  our protocol  works in  periods fashion,
+As can be seen  in Figure~\ref{fig2},  our protocol  works in  periods fashion,
 where  each is  divided  into 4  phases: Information~Exchange,  Leader~Election,
 Decision, and Sensing.  Each sensing phase may be itself divided into $T$ rounds
 and for each round a set of sensors (a cover set) is responsible for the sensing
-task. In  this way  a multiround optimization  process is performed  during each
+task. In this way a multiround optimization  process is performed  during each
 period  after  Information~Exchange  and  Leader~Election phases,  in  order  to
 produce $T$ cover sets that will take the mission of sensing for $T$ rounds.
 \begin{figure}[ht!]
@@ -46,18 +46,9 @@ produce $T$ cover sets that will take the mission of sensing for $T$ rounds.
 This protocol minimizes the impact of unexpected node failure (not due to batteries
 running out of energy), because it works in periods. 
 
- On the one hand, if a node failure is detected before  making the
-decision, the node will not participate to this phase, and, on the other hand,
-if the node failure occurs after the decision, the sensing  task of the network
-will be temporarily affected:  only during  the period of sensing until a new
-period starts.
+ On the one hand, if a node failure is detected before making the decision, the node will not participate to this phase, and, on the other hand, if the node failure occurs after the decision, the sensing  task of the network will be temporarily affected:  only during  the period of sensing until a new period starts.
 
-The  energy consumption  and some  other constraints  can easily  be  taken into
-account,  since the  sensors  can  update and  then  exchange their  information
-(including their residual energy) at the beginning of each period.  However, the
-pre-sensing  phases (Information  Exchange, Leader  Election, and  Decision) are
-energy  consuming for some  nodes, even  when they  do not  join the  network to
-monitor the area.
+The  energy consumption  and some  other constraints  can easily  be  taken into account,  since the  sensors  can  update and  then  exchange their  information (including their residual energy) at the beginning of each period.  However, the pre-sensing  phases (Information  Exchange, Leader  Election, and  Decision) are energy  consuming for some  nodes, even  when they  do not  join the  network to monitor the area.
 
 
 These phases can be described in more details as follow:
@@ -71,7 +62,7 @@ The leader election in each subregion is similar to that one which is described
 
 \subsection{Decision phase}
 \label{ch4:sec:02:02:03}
-Each  WSNL will solve  an integer  program to  select which  cover sets  will be
+Each WSNL will solve  an integer  program to  select which  cover sets  will be
 activated in  the following  sensing phase  to cover the  subregion to  which it
 belongs.  The integer  program will produce $T$ cover sets,  one for each round.
 The WSNL will send an Active-Sleep  packet to each sensor in the subregion based
@@ -316,7 +307,9 @@ reduce the advantage  of the optimization. In fact, there  is a balance between
 the  benefit  from the  optimization  and the  execution  time  needed to  solve
 it. Therefore, we have set the number of subregions to 16 rather than 32.
 
-We have used an energy consumption model, which is presented in chapter 1, section \ref{ch1:sec9:subsec2}. The initial energy of each node  is randomly set in the interval $[500;700]$.  A sensor node  will not participate in the  next round if its  remaining energy is less than  $E_{R}=36~\mbox{Joules}$, the minimum  energy needed for the  node to stay alive  during one round.  This value has  been computed by  multiplying the energy consumed in  active state (9.72 mW)  by the time in second  for one round (3600 seconds).  According to the  interval of initial  energy, a sensor  may be alive during at most 20 rounds.
+We used the modeling language and the optimization solver which are mentioned in chapter 3, section \ref{ch3:sec:04:02}. In addition, we employed an energy consumption model, which is presented in chapter 3, section \ref{ch3:sec:04:03}. 
+
+%The initial energy of each node  is randomly set in the interval $[500;700]$.  A sensor node  will not participate in the  next round if its  remaining energy is less than  $E_{R}=36~\mbox{Joules}$, the minimum  energy needed for the  node to stay alive  during one round.  This value has  been computed by  multiplying the energy consumed in  active state (9.72 mW) by the time in second  for one round (3600 seconds). According to the  interval of initial energy, a sensor may be alive during at most 20 rounds.
 
 \subsection{Metrics}
 \label{ch4:sec:03:02}
@@ -349,7 +342,7 @@ where $A_r^t$ is the number of  active sensors in the subregion $r$ during round
 $t$ in the  current sensing phase, $|J|$  is the total number of  sensors in the
 network, and $R$ is the total number of subregions in the network.
 
-\item {{\bf Network Lifetime}:} is described in chapter 3, section \ref{ch3:sec:04:02}.
+\item {{\bf Network Lifetime}:} is described in chapter 3, section \ref{ch3:sec:04:04}.
 
 \item {{\bf  Energy Consumption  (EC)}:} the average energy consumption  can be
   seen as the total energy consumed by the sensors during the $Lifetime_{95}$ or
@@ -373,12 +366,12 @@ factor, corresponds  to the energy consumed  by the sensors  in LISTENING status
 before  receiving   the  decision  to  go   active  or  sleep   in  period  $m$.
 $E^{\scriptsize \mbox{comp}}_m$  refers to the  energy needed by all  the leader
 nodes to solve the integer program during a period. Finally, $E^a_t$ and $E^s_t$
-indicate the energy consummed by the whole network in round $t$.
+indicate the energy consumed by the whole network in round $t$.
 
 
-\item {{\bf Execution Time}:} is described in chapter 3, section \ref{ch3:sec:04:02}.
+\item {{\bf Execution Time}:} is described in chapter 3, section \ref{ch3:sec:04:04}.
   
-\item {{\bf Stopped simulation runs}:} is described in chapter 3, section \ref{ch3:sec:04:02}.
+\item {{\bf Stopped simulation runs}:} is described in chapter 3, section \ref{ch3:sec:04:04}.
 
 \end{enumerate}
 
