X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/JournalMultiPeriods.git/blobdiff_plain/82118333bcdd1e2615611a6f72996c619397d3f0..refs/heads/master:/article.tex

diff --git a/article.tex b/article.tex
index eb65d9f..ed70b52 100644
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+++ b/article.tex
@@ -149,7 +149,7 @@ in~\cite{idrees2015distributed}.
 %more  interesting  to  divide  the  area  into  several  subregions,  given  the
 %computation complexity.
 
-\textcolor{blue}{ Compared  to our  previous work~\cite{idrees2015distributed},
+\textcolor{black}{ Compared  to our  previous work~\cite{idrees2015distributed},
   in  this paper  we study  the  possibility of  dividing the  sensing phase  into
   multiple rounds.   We make a  multiround optimization,
   while previously it was a single round optimization.  The idea is to
@@ -291,7 +291,7 @@ Indeed, each sensor  maintains its own timer and its  wake-up time is randomized
 \subsection{Assumptions and primary points}
 \label{pp}
 
-\textcolor{blue}{The assumptions and the coverage model are identical to those presented
+\textcolor{black}{The assumptions and the coverage model are identical to those presented
   in~\cite{idrees2015distributed}. We  consider a  scenario in which  sensors are  deployed in  high
   density to  initially ensure a high coverage ratio of the interested area. Each
   sensor  has  a  predefined  sensing  range $R_s$,  an  initial  energy  supply
@@ -356,14 +356,14 @@ inside a subregion is less than or equal to 3.
 
 As can  be seen  in Figure~\ref{fig2},  our protocol  works in  periods fashion,
 where   each   period   is    divided   into   4~phases:   Information~Exchange,
-Leader~Election,  Decision, and  Sensing. \textcolor{blue}{Compared  to 
+Leader~Election,  Decision, and  Sensing. \textcolor{black}{Compared  to 
  the DiLCO protocol described in~\cite{idrees2015distributed},} each sensing phase is itself
 divided into $T$ rounds of equal duration 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 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. \textcolor{blue}{Algorithm~\ref{alg:MuDiLCO} is  executed by each sensor
+rounds. \textcolor{black}{Algorithm~\ref{alg:MuDiLCO} is  executed by each sensor
   node~$s_j$ (with enough remaining energy) at the beginning of a period.}
 \begin{figure}[t!]
 \centering \includegraphics[width=125mm]{Modelgeneral.pdf} % 70mm
@@ -400,7 +400,7 @@ rounds. \textcolor{blue}{Algorithm~\ref{alg:MuDiLCO} is  executed by each sensor
 \label{alg:MuDiLCO}
 \end{algorithm}
 
-\textcolor{blue}{As  already   described  in~\cite{idrees2015distributed}},  two
+\textcolor{black}{As  already   described  in~\cite{idrees2015distributed}},  two
 types of packets are used by the proposed protocol:
 \begin{enumerate}[(a)] 
 \item INFO  packet: such a packet  will be sent by  each sensor node to  all the
@@ -482,7 +482,7 @@ determine the possibility  of activating sensor $j$ during round  $t$ of a given
 sensing phase.  We also consider primary  points as targets.  The set of primary
 points is denoted by $P$ and the set  of sensors by $J$. Only sensors able to be
 alive  during  at  least  one  round   are  involved  in  the  integer  program.
-\textcolor{blue}{Note that the proposed integer  program is an
+\textcolor{black}{Note that the proposed integer  program is an
   extension of the one   formulated  in~\cite{idrees2015distributed},  variables  are  now  indexed  in
   addition with the number of round $t$.}
 
@@ -657,11 +657,11 @@ lifetime. Moreover,  it makes  the MuDiLCO protocol  more robust  against random
 network  disconnection due  to node  failures.  However,  too many  subdivisions
 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. In
-the following  we have  set the number  of subregions  to~16 \textcolor{blue}{as
+the following  we have  set the number  of subregions  to~16 \textcolor{black}{as
   recommended in~\cite{idrees2015distributed}}.
 
 \subsection{Energy model}
-\textcolor{blue}{The      energy     consumption      model     is      detailed
+\textcolor{black}{The      energy     consumption      model     is      detailed
   in~\cite{raghunathan2002energy}.   It  is   based   on   the  model   proposed
   by~\cite{ChinhVu}. We refer to the sensor  node Medusa~II which uses an Atmels
   AVR ATmega103L  microcontroller~\cite{raghunathan2002energy} to  use numerical
@@ -669,7 +669,7 @@ the following  we have  set the number  of subregions  to~16 \textcolor{blue}{as
 
 \subsection{Metrics}
 
-\textcolor{blue}{To evaluate  our approach  we consider the  performance metrics
+\textcolor{black}{To evaluate  our approach  we consider the  performance metrics
   detailed in~\cite{idrees2015distributed},  which are: Coverage  Ratio, Network
   Lifetime  and  Energy  Consumption.   Compared to  the  previous  definitions,
   formulations of  Coverage Ratio and  Energy Consumption are enriched  with the
@@ -752,7 +752,7 @@ points. The  objective of this  comparison is to  select the suitable  number of
 primary points to be used by  a MuDiLCO protocol.  In this comparison, MuDiLCO-1
 protocol is used  with five primary point models, each  model corresponding to a
 number of primary  points, which are called Model-5 (it  uses 5 primary points),
-Model-9, Model-13,  Model-17, and  Model-21. \textcolor{blue}{Note
+Model-9, Model-13,  Model-17, and  Model-21. \textcolor{black}{Note
   that the results
   presented in~\cite{idrees2015distributed}  correspond to Model-13  (13 primary
   points)}.
@@ -915,7 +915,7 @@ Figure~\ref{fig77} for different network sizes.
 
 \begin{figure}[ht!]
 \centering
-\includegraphics[scale=0.5]{F/T.pdf}  
+\includegraphics[scale=0.5]{FT.pdf}  
 \caption{Execution Time (in seconds)}
 \label{fig77}
 \end{figure} 
@@ -963,9 +963,9 @@ metrics, MuDiLCO-5 seems to be the best suited method compared to MuDiLCO-7.
 \begin{figure}[t!]
   \centering
   \begin{tabular}{cl}
-    \parbox{9.5cm}{\includegraphics[scale=0.5125]{F/LT95.pdf}} & (a) \\
+    \parbox{9.5cm}{\includegraphics[scale=0.5125]{FLT95.pdf}} & (a) \\
     \verb+ + \\
-    \parbox{9.5cm}{\includegraphics[scale=0.5125]{F/LT50.pdf}} & (b)
+    \parbox{9.5cm}{\includegraphics[scale=0.5125]{FLT50.pdf}} & (b)
   \end{tabular}
   \caption{Network lifetime for (a) $Lifetime_{95}$ and 
     (b) $Lifetime_{50}$}
