modif mineure

[Sensornets15.git] / Example.tex

diff --git a/Example.tex b/Example.tex
index 4907bf5cf8633c1fadb9c9682a0f01537821121c..fe40099f5d95860411e50fb73a31cc2e353e036e 100644 (file)
--- a/Example.tex
+++ b/Example.tex
@@ -44,8 +44,7 @@ the  coverage  and  to improve  the  lifetime  in  wireless sensor  networks  is
 proposed.   The  area of  interest  is first  divided  into  subregions using  a
 divide-and-conquer  method and  then the  DiLCO protocol  is distributed  on the
 sensor nodes  in each  subregion. The DiLCO  combines two  efficient techniques:
 proposed.   The  area of  interest  is first  divided  into  subregions using  a
 divide-and-conquer  method and  then the  DiLCO protocol  is distributed  on the
 sensor nodes  in each  subregion. The DiLCO  combines two  efficient techniques:

-leader election  for each subregion, followed by  an optimization-based planning
-of activity  scheduling decisions for  each subregion. The proposed  DiLCO works
+leader election  for each subregion, followed by  an optimization-based  activity  scheduling for  each subregion. The proposed  DiLCO works

 into periods during which a small  number of nodes, remaining active for sensing,
 is selected to ensure coverage so as to maximize the lifetime of wireless sensor
 network.   Each  period  consists   of  four  phases:  (i)~Information  Exchange,
 into periods during which a small  number of nodes, remaining active for sensing,
 is selected to ensure coverage so as to maximize the lifetime of wireless sensor
 network.   Each  period  consists   of  four  phases:  (i)~Information  Exchange,


@@ -99,7 +98,7 @@ problem. By using this model, they are proposed  an  Energy-Efficient central-Sc
 
 The work in~\cite{cheng2014achieving} presented a unified sensing architecture for duty cycled sensor networks, called uSense, which comprises three ideas: Asymmetric Architecture, Generic Switching and Global Scheduling. The objective is to  provide a flexible and efficient coverage in sensor networks.
 
 
 The work in~\cite{cheng2014achieving} presented a unified sensing architecture for duty cycled sensor networks, called uSense, which comprises three ideas: Asymmetric Architecture, Generic Switching and Global Scheduling. The objective is to  provide a flexible and efficient coverage in sensor networks.
 

- In~\cite{ling2009energy}, The lifetime of
+ In~\cite{ling2009energy}, the lifetime of

 a sensor node is divided into epochs. At each epoch, the
 base station deduces the current sensing coverage requirement
 from application or user request. It then applies the heuristic algorithm in order to produce the set of active nodes which take the mission of sensing during the current epoch.  After that, the produced schedule is sent to the sensor nodes in the network. 
 a sensor node is divided into epochs. At each epoch, the
 base station deduces the current sensing coverage requirement
 from application or user request. It then applies the heuristic algorithm in order to produce the set of active nodes which take the mission of sensing during the current epoch.  After that, the produced schedule is sent to the sensor nodes in the network. 


@@ -289,7 +288,7 @@ There are five status for each sensor node in the network :
 %\end{enumerate}
 %Below, we describe each phase in more details.
 Algorithm 1 gives a brief description of the protocol applied by each sensor node (denoted by $s_j$ for a sensor node indexed by $j$).
 %\end{enumerate}
 %Below, we describe each phase in more details.
 Algorithm 1 gives a brief description of the protocol applied by each sensor node (denoted by $s_j$ for a sensor node indexed by $j$).

-Initially, the sensor node checks its remaining energy in order to participate in the current period. Each sensor node determines its position and its subregion based Embedded GPS  or Location Discovery Algorithm. After that, all the sensors collect position coordinates, remaining energy $RE_j$, sensor node id, and the number of its one-hop live neighbors during the information exchange. 
+Initially, the sensor node checks its remaining energy in order to participate in the current period. After that, all the sensors collect position coordinates, remaining energy $RE_j$, sensor node id, and the number of its one-hop live neighbors during the information exchange. 

 Then all the sensor nodes in the same subregion will select the leader based on the received informations. The selection criteria for the leader in order  of priority  are: larger number  of neighbours,  larger remaining  energy, and  then in  case of equality, larger index. After that, if the sensor node is leader, it will execute the integer program algorithm (see section~\ref{cp}) which provides a set of sensors planned to be active in the sensing round. As leader, it will send an Active-Sleep packet to each sensor in the same subregion to indicate it if it has to be active or not. On the contrary, if the sensor is not the leader, it will wait for the Active-Sleep packet to know its state for the sensing round.
 
 
 Then all the sensor nodes in the same subregion will select the leader based on the received informations. The selection criteria for the leader in order  of priority  are: larger number  of neighbours,  larger remaining  energy, and  then in  case of equality, larger index. After that, if the sensor node is leader, it will execute the integer program algorithm (see section~\ref{cp}) which provides a set of sensors planned to be active in the sensing round. As leader, it will send an Active-Sleep packet to each sensor in the same subregion to indicate it if it has to be active or not. On the contrary, if the sensor is not the leader, it will wait for the Active-Sleep packet to know its state for the sensing round.
 
 


@@ -348,7 +347,7 @@ we first show the pseudo-code of DiLCO protocol, which is executed by each senso
   \BlankLine
   %\emph{Initialize the sensor node and determine it's position and subregion} \; 
   
   \BlankLine
   %\emph{Initialize the sensor node and determine it's position and subregion} \; 
   

-  \If{ $RE_j \geq E_{R}$ }{
+  \If{ $RE_j \geq E_{th}$ }{

       \emph{$s_j.status$ = COMMUNICATION}\;
       \emph{Send $INFO()$ packet to other nodes in the subregion}\;
       \emph{Wait $INFO()$ packet from other nodes in the subregion}\; 
       \emph{$s_j.status$ = COMMUNICATION}\;
       \emph{Send $INFO()$ packet to other nodes in the subregion}\;
       \emph{Wait $INFO()$ packet from other nodes in the subregion}\; 


@@ -629,7 +628,7 @@ transmit information on an event in the area that it monitors.
  Energy Consumption (EC) can be seen as the total energy consumed by the sensors during the $Lifetime95$ or $Lifetime50$ divided by the number of periods. The EC can be computed as follow: \\
  \begin{equation*}
 \scriptsize
  Energy Consumption (EC) can be seen as the total energy consumed by the sensors during the $Lifetime95$ or $Lifetime50$ divided by the number of periods. The EC can be computed as follow: \\
  \begin{equation*}
 \scriptsize

-\mbox{EC} = \frac{\sum\limits_{m=1}^{M_L} \left( E^{\mbox{com}}_m+E^{\mbox{list}}_m+E^{\mbox{comp}}_m  + E^{a}+E^{s} \right)}{M_L},
+\mbox{EC} = \frac{\sum\limits_{m=1}^{M} \left( E^{\mbox{com}}_m+E^{\mbox{list}}_m+E^{\mbox{comp}}_m  + E^{a}+E^{s} \right)}{M_L},

 \end{equation*}
 
 %\begin{equation*}
 \end{equation*}
 
 %\begin{equation*}


@@ -637,7 +636,7 @@ transmit information on an event in the area that it monitors.
 %\mbox{EC} =  \frac{\mbox{$\sum\limits_{d=1}^D E^c_d$}}{\mbox{$D$}} + \frac{\mbox{$\sum\limits_{d=1}^D %E^l_d$}}{\mbox{$D$}} + \frac{\mbox{$\sum\limits_{d=1}^D E^a_d$}}{\mbox{$D$}} + %\frac{\mbox{$\sum\limits_{d=1}^D E^s_d$}}{\mbox{$D$}}.
 %\end{equation*}
 
 %\mbox{EC} =  \frac{\mbox{$\sum\limits_{d=1}^D E^c_d$}}{\mbox{$D$}} + \frac{\mbox{$\sum\limits_{d=1}^D %E^l_d$}}{\mbox{$D$}} + \frac{\mbox{$\sum\limits_{d=1}^D E^a_d$}}{\mbox{$D$}} + %\frac{\mbox{$\sum\limits_{d=1}^D E^s_d$}}{\mbox{$D$}}.
 %\end{equation*}
 

-where $M_L$ corresponds to the number of  periods.  The total  energy consumed by  the sensors
+where $M$ corresponds to the number of  periods.  The total  energy consumed by  the sensors

 (EC) comes through taking into consideration four main energy factors. The first
 one ,  denoted $E^{\scriptsize \mbox{com}}_m$, represent  the energy consumption
 spent  by  all  the  nodes   for  wireless  communications  during  period  $m$.
 (EC) comes through taking into consideration four main energy factors. The first
 one ,  denoted $E^{\scriptsize \mbox{com}}_m$, represent  the energy consumption
 spent  by  all  the  nodes   for  wireless  communications  during  period  $m$.


@@ -645,7 +644,7 @@ $E^{\scriptsize  \mbox{list}}_m$, the  next  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
 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, $E^a_{m}$ and $E^s_{m}$  indicate the energy consummed by the whole network in the sensing round.
+period. Finally, $E^a_{m}$ and $E^s_{m}$  indicate the energy consumed by the whole network in the sensing round.

 
 \iffalse 
 \item {{\bf Execution Time}:} a  sensor  node has  limited  energy  resources  and computing  power,
 
 \iffalse 
 \item {{\bf Execution Time}:} a  sensor  node has  limited  energy  resources  and computing  power,


@@ -673,7 +672,7 @@ Our method is compared with other two approaches. The first approach, called DES
 
 
 \subsubsection{Coverage Ratio} 
 
 
 \subsubsection{Coverage Ratio} 

-In this experiment, Figure~\ref{fig3} shows the average coverage ratio for 150 deployed nodes.  
+Figure~\ref{fig3} shows the average coverage ratio for 150 deployed nodes.  

 \parskip 0pt    
 \begin{figure}[h!]
 \centering
 \parskip 0pt    
 \begin{figure}[h!]
 \centering