X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/JournalMultiPeriods.git/blobdiff_plain/f7dcdff7f2151372dfabe5d5a70f4f4e3d13324b..851c4bad39e11ad78c3f12eb0b7324fcaa29f60b:/article.tex?ds=sidebyside

diff --git a/article.tex b/article.tex
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@@ -149,10 +149,10 @@ in~\cite{idrees2015distributed}.
 %more  interesting  to  divide  the  area  into  several  subregions,  given  the
 %computation complexity.
 
-\textcolor{blue}{ Compared  to our  previous paper~\cite{idrees2015distributed},
-  in  this one  we study  the  possibility of  dividing the  sensing phase  into
-  multiple rounds.   In fact, in this  paper we make a  multiround optimization,
-  while it was a single round optimization in our previous work.  The idea is to
+\textcolor{blue}{ 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
   take advantage  of the  pre-sensing phase  to plan  the sensor's  activity for
   several  rounds instead  of one,  thus saving  energy. In  addition, when  the
   optimization problem becomes  more complex, its resolution is  stopped after a
@@ -291,34 +291,13 @@ Indeed, each sensor  maintains its own timer and its  wake-up time is randomized
 \subsection{Assumptions and primary points}
 \label{pp}
 
-\textcolor{blue}{Assumptions and coverage model are identical to those presented
-  in~\cite{idrees2015distributed}.}
-
-\iffalse
-We  consider a  randomly and  uniformly  deployed network  consisting of  static
-wireless sensors.  The sensors are  deployed in high density to ensure initially
-a high  coverage ratio  of the interested  area.  We  assume that all  nodes are
-homogeneous  in   terms  of  communication  and   processing  capabilities,  and
-heterogeneous  from the  point  of view  of  energy provision.   Each sensor  is
-supposed  to get information  on its  location either  through hardware  such as
-embedded GPS or through location discovery algorithms.
-   
-To model  a sensor node's coverage  area, we consider the  boolean disk coverage
-model   which  is  the   most  widely   used  sensor   coverage  model   in  the
-literature. Thus, each  sensor has a constant sensing range  $R_s$ and all space
-points within  the disk centered  at the sensor  with the radius of  the sensing
-range  is  said  to  be  covered  by  this sensor.   We  also  assume  that  the
-communication   range  satisfies   $R_c  \geq   2R_s$.   In   fact,   Zhang  and
-Zhou~\cite{Zhang05} proved that if  the transmission range fulfills the previous
-hypothesis, a complete coverage of  a convex area implies connectivity among the
-active nodes.\fi
-
-\textcolor{blue}{We  consider a  scenario where  sensors are  deployed in  high
-  density to ensure initially a high coverage ratio of the interested area. Each
+\textcolor{blue}{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
   (eventually different  from each other)  and is  supposed to be  equipped with
-  module for  locating its geographical  positions. All space points  within the
-  disk centered at the sensor with the radius of the sensing range is said to be
+  a module to  locate its geographical  positions. All space points  within the
+  disk centered at the sensor with the radius of the sensing range are said to be
   covered by this sensor.}
 
 \indent Instead of working with the coverage area, we consider for each sensor a
@@ -377,8 +356,8 @@ 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 protocol
-  DiLCO described in~\cite{idrees2015distributed},} each sensing phase is itself
+Leader~Election,  Decision, and  Sensing. \textcolor{blue}{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
@@ -503,8 +482,8 @@ 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 extension of that
-  formulated  in~\cite{idrees2015distributed},  variables  are  now  indexed  in
+\textcolor{blue}{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 $t$.}
 
 For a  primary point  $p$, let $\alpha_{j,p}$  denote the indicator  function of
@@ -611,15 +590,6 @@ integer program contains  $A*T$ variables of type  $X_{t,j}$, $P*T$ overcoverage
 variables and $P*T$ undercoverage variables.  The number of constraints is equal
 to $P*T$ (for constraints (\ref{eq16})) $+$ $A$ (for constraints (\ref{eq144})).
 
-\iffalse
-\subsection{Sensing phase}
-
-The sensing phase consists of $T$ rounds. Each sensor node in the subregion will
-receive an Active-Sleep packet from WSNL, informing it to stay awake or to go to
-sleep for each  round of the sensing  phase.  Algorithm~\ref{alg:MuDiLCO}, which
-will  be executed  by  each sensor  node~$s_j$  at the  beginning  of a  period,
-explains how the Active-Sleep packet is obtained.
-\fi
 
 \section{Experimental framework}
 \label{exp}
@@ -695,67 +665,7 @@ the following  we have  set the number  of subregions  to~16 \textcolor{blue}{as
   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
-  values.}   \textcolor{red}{Est-ce qu'il  faut en  ecrire plus  et redonner  le
-  tableau de valeurs?}
-
-\iffalse
-\subsection{Energy model}
-
-We  use an  energy consumption  model  proposed by~\cite{ChinhVu}  and based  on
-\cite{raghunathan2002energy} with slight  modifications.  The energy consumption
-for  sending/receiving the packets  is added,  whereas the  part related  to the
-sensing range is removed because we consider a fixed sensing range.
-
-For our  energy consumption model, we  refer to the sensor  node Medusa~II which
-uses an Atmels  AVR ATmega103L microcontroller~\cite{raghunathan2002energy}. The
-typical  architecture  of a  sensor  is composed  of  four  subsystems: the  MCU
-subsystem which is capable of computation, communication subsystem (radio) which
-is responsible  for transmitting/receiving messages, the  sensing subsystem that
-collects  data, and  the  power supply  which  powers the  complete sensor  node
-\cite{raghunathan2002energy}. Each  of the first three subsystems  can be turned
-on or  off depending on  the current status  of the sensor.   Energy consumption
-(expressed in  milliWatt per second) for  the different status of  the sensor is
-summarized in Table~\ref{table4}.
-
-\begin{table}[ht]
-\caption{The Energy Consumption Model}
-\centering
-\begin{tabular}{|c|c|c|c|c|}
-  \hline
-Sensor status & MCU & Radio & Sensing & Power (mW) \\ [0.5ex]
-\hline
-LISTENING & on & on & on & 20.05 \\
-\hline
-ACTIVE & on & off & on & 9.72 \\
-\hline
-SLEEP & off & off & off & 0.02 \\
-\hline
-COMPUTATION & on & on & on & 26.83 \\
-\hline
-\end{tabular}
-
-\label{table4}
-\end{table}
-
-For the sake of simplicity we ignore the  energy needed to turn on the radio, to
-start up the sensor node, to move from one status to another, etc.
-Thus, when a sensor becomes active (i.e.,  it has already chosen its status), it
-can turn its radio  off to save battery.  MuDiLCO uses two  types of packets for
-communication. The size of the INFO  packet and Active-Sleep packet are 112~bits
-and 24~bits  respectively.  The value  of energy  spent to send  a 1-bit-content
-message is  obtained by using  the equation in  ~\cite{raghunathan2002energy} to
-calculate the  energy cost  for transmitting  messages and  we propose  the same
-value for receiving  the packets. The energy  needed to send or  receive a 1-bit
-packet is equal to 0.2575~mW.
-
-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.
-\fi
+  values.}  
 
 \subsection{Metrics}
 
@@ -828,21 +738,7 @@ indicate the energy consumed by the whole network in round $t$.
 %nodes  have  been drained  of  their  energy  or each  sensor  network monitoring  an area has become  disconnected.
 \end{enumerate}
 
-\iffalse
-\begin{enumerate}
- \setcounter{5}
-\item {{\bf  Execution Time}:}  a sensor node  has limited energy  resources and
-  computing power, therefore it is important that the proposed algorithm has the
-  shortest possible execution  time. The energy of a sensor  node must be mainly
-  used for the sensing phase, not for the pre-sensing ones.
-  
-\item {{\bf Stopped simulation runs}:} a simulation ends when the sensor network
-  becomes disconnected (some nodes are dead and are not able to send information
-  to the base station). We report the number of simulations that are stopped due
-  to network disconnections and for which round it occurs.
 
-\end{enumerate}
-\fi
 
 \section{Experimental results and analysis}
 \label{analysis}
@@ -856,7 +752,8 @@ 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  that results
+Model-9, Model-13,  Model-17, and  Model-21. \textcolor{blue}{Note
+  that the results
   presented in~\cite{idrees2015distributed}  correspond to Model-13  (13 primary
   points)}.
 
