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 \newlabel{figure6}{{6}{14}}
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diff --git a/PeCO-EO/articleeo.pdf b/PeCO-EO/articleeo.pdf
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diff --git a/PeCO-EO/articleeo.tex b/PeCO-EO/articleeo.tex
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@@ -507,7 +507,7 @@ in  the current  period.   Each  sensor node  determines  its  position and  its
 subregion using an  embedded GPS or a location discovery  algorithm. After that,
 all the sensors collect position  coordinates, remaining energy, sensor node ID,
 and the number of their one-hop  live neighbors during the information exchange.
-\textcolor{blue}{Both INFO packet and ActiveSleep packet contain two parts: header and data payload. The sensor ID is included in the header, where the header size is 8 bits. The data part includes position coordinates (64 bits), remaining energy (32 bits), and the number of one-hop live neighbors (8 bits). Therefore the size of the INFO packet is 112 bits. The ActiveSleep packet is 16 bits size, 8 bits for the header and 8 bits for data part that includes only sensor status (0 or 1).}
+\textcolor{green}{Both INFO packet and ActiveSleep packet contain two parts: header and data payload. The sensor ID is included in the header, where the header size is 8 bits. The data part includes position coordinates (64 bits), remaining energy (32 bits), and the number of one-hop live neighbors (8 bits). Therefore the size of the INFO packet is 112 bits. The ActiveSleep packet is 16 bits size, 8 bits for the header and 8 bits for data part that includes only sensor status (0 or 1).}
 The sensors  inside a same  region cooperate to  elect a leader.   The selection
 criteria for the leader are (in order  of priority):
 \begin{enumerate}
@@ -719,8 +719,8 @@ approach.
   sensing period~$p$, $R$  is the number of subregions, and  $|J|$ is the number
   of sensors in the network.
   
-\item {\bf \textcolor{blue}{Energy Saving Ratio (ESR)}}:  
-\textcolor{blue}{this metric, which shows the ability of a protocol to save energy, is defined by:
+\item {\bf \textcolor{green}{Energy Saving Ratio (ESR)}}:  
+\textcolor{green}{this metric, which shows the ability of a protocol to save energy, is defined by:
 \begin{equation*}
 \scriptsize
 \mbox{ESR}(\%) = \frac{\mbox{Number of alive sensors during this round}}
@@ -853,12 +853,10 @@ keeping a greater coverage ratio as shown in Figure \ref{figure5}.
 \label{figure6}
 \end{figure} 
 
-\subsubsection{\textcolor{blue}{Energy Saving Ratio}} 
+\subsubsection{\textcolor{green}{Energy Saving Ratio}} 
 
-%\textcolor{blue}{In this experiment, we study the energy saving ratio, see Figure~\ref{fig5}, for 200 deployed nodes. 
-%The larger the ratio  is,  the more  redundant sensor  nodes are switched off, and consequently  the longer the  network may  liv%e. }
 
-\textcolor{blue}{The  simulation  results  show  that our  protocol  PeCO  saves
+\textcolor{green}{The  simulation  results  show  that our  protocol  PeCO  saves
   efficiently energy by  turning off some sensors during the  sensing phase.  As
   shown in  Figure~\ref{fig5}, GAF provides  better energy saving than  PeCO for
   the  first fifty  rounds. Indeed  GAF  balances the  energy consumption  among
@@ -934,14 +932,12 @@ for  different   coverage  ratios.   We  denote  by   Protocol/70,  Protocol/80,
 Protocol/85, Protocol/90,  and Protocol/95 the  amount of time during  which the
 network  can satisfy  an  area  coverage greater  than  $70\%$, $80\%$,  $85\%$,
 $90\%$, and  $95\%$ respectively,  where the  term Protocol  refers to  DiLCO or
-PeCO.  \textcolor{blue}{Indeed there are applications that do not require a 100\% coverage of the
+PeCO.  \textcolor{green}{Indeed there are applications that do not require a 100\% coverage of the
 area to be  monitored. For example, forest
 fire application might require complete coverage
 in summer seasons while only require 80$\%$ of the area to be covered in rainy seasons~\citep{li2011transforming}. As another example, birds habit study requires only 70$\%$-coverage at nighttime when the birds are sleeping while requires 100$\%$-coverage at daytime when the birds are active~\citep{1279193}. 
-%Mudflows monitoring applications may require part of the area to be covered in sunny days. Thus, to extend network lifetime, the coverage quality can be decreased if it is acceptable~\citep{wang2014keeping}}. 
  PeCO always  outperforms DiLCO  for the  three  lower coverage  ratios, moreover  the
 improvements grow  with the network  size. DiLCO outperforms PeCO when the coverage ratio is required to be $>90\%$, but PeCO extends the network lifetime significantly when coverage ratio can be relaxed.}
-%DiLCO  is better for  coverage ratios near 100\%, but  in that case PeCO  is not ineffective for  the smallest network sizes.
 
 \begin{figure}[h!]
 \centering \includegraphics[scale=0.55]{figure9.eps}
@@ -966,7 +962,7 @@ $\beta=0.4$ seems to  achieve the best compromise between  lifetime and coverage
 ratio.   That explains  why  we have  chosen this  setting  for the  experiments
 presented in the previous subsections.
 
-%As can be seen in Table~\ref{my-labelx},  it is obvious and clear that when $\alpha$ decreased and $\beta$ increased by any step, the network lifetime for $Lifetime_{50}$ increased and the $Lifetime_{95}$ decreased. Therefore, selecting the values of $\alpha$ and $\beta$ depend on the application type used in the sensor nework. In PeCO protocol, $\alpha$ and $\beta$ are chosen based on the largest value of network lifetime for $Lifetime_{95}$.
+
 
 \begin{table}[h]
 \centering

diff --git a/PeCO-EO/articleeo.tex~ b/PeCO-EO/articleeo.tex~
index 5ba7f55932dd982a40e034a21050950216875f02..4faafaa6a289a7d2b84086dab2f19b696422a210 100644 (file)
--- a/PeCO-EO/articleeo.tex~
+++ b/PeCO-EO/articleeo.tex~
@@ -507,7 +507,7 @@ in  the current  period.   Each  sensor node  determines  its  position and  its
 subregion using an  embedded GPS or a location discovery  algorithm. After that,
 all the sensors collect position  coordinates, remaining energy, sensor node ID,
 and the number of their one-hop  live neighbors during the information exchange.
-\textcolor{blue}{Both INFO packet and ActiveSleep packet contain two parts: header and data payload. The sensor ID is included in the header, where the header size is 8 bits. The data part includes position coordinates (64 bits), remaining energy (32 bits), and the number of one-hop live neighbors (8 bits). Therefore the size of the INFO packet is 112 bits. The ActiveSleep packet is 16 bits size, 8 bits for the header and 8 bits for data part that includes only sensor status (0 or 1).}
+\textcolor{green}{Both INFO packet and ActiveSleep packet contain two parts: header and data payload. The sensor ID is included in the header, where the header size is 8 bits. The data part includes position coordinates (64 bits), remaining energy (32 bits), and the number of one-hop live neighbors (8 bits). Therefore the size of the INFO packet is 112 bits. The ActiveSleep packet is 16 bits size, 8 bits for the header and 8 bits for data part that includes only sensor status (0 or 1).}
 The sensors  inside a same  region cooperate to  elect a leader.   The selection
 criteria for the leader are (in order  of priority):
 \begin{enumerate}
@@ -719,8 +719,8 @@ approach.
   sensing period~$p$, $R$  is the number of subregions, and  $|J|$ is the number
   of sensors in the network.
   
-\item {\bf \textcolor{blue}{Energy Saving Ratio (ESR)}}:  
-\textcolor{blue}{this metric, which shows the ability of a protocol to save energy, is defined by:
+\item {\bf \textcolor{green}{Energy Saving Ratio (ESR)}}:  
+\textcolor{green}{this metric, which shows the ability of a protocol to save energy, is defined by:
 \begin{equation*}
 \scriptsize
 \mbox{ESR}(\%) = \frac{\mbox{Number of alive sensors during this round}}
@@ -853,26 +853,20 @@ keeping a greater coverage ratio as shown in Figure \ref{figure5}.
 \label{figure6}
 \end{figure} 
 
-\subsubsection{\textcolor{blue}{Energy Saving Ratio (ESR)}} 
-
-%\textcolor{blue}{In this experiment, we study the energy saving ratio, see Figure~\ref{fig5}, for 200 deployed nodes. 
-%The larger the ratio  is,  the more  redundant sensor  nodes are switched off, and consequently  the longer the  network may  liv%e. }
-
-\textcolor{blue}{The simulation  results show that  our protocol PeCO  allows to
-  efficiently save energy by turning off  some sensors during the sensing phase.
-  As shown in Figure~\ref{fig5}, GAF provides better energy saving than PeCO for
-  the  first fifty  rounds, because  GAF  balances the  energy consumption  among
-  sensor nodes inside each  small fixed grid and thus permits to  extend the life of
-  sensors in  each grid  fairly but  in the same  time turn  on large  number of
-  sensors during sensing  that lead later to quickly  deplete sensor's batteries
-  together. After that  GAF  provide  less energy  saving  compared with  other
-  approaches because of the large number of dead nodes. DESK algorithm shows less
-  energy saving compared with other approaches  due to activate a large number of
-  sensors during the  sensing. DiLCO protocol provides less  energy saving ratio
-  compared with  PeCO because it generally  activate a larger number  of sensor
-  nodes during sensing.  Note that again as the number  of rounds increases PeCO
-  becomes the most  performing one, since it consumes less  energy compared with
-  other approaches.}
+\subsubsection{\textcolor{green}{Energy Saving Ratio}} 
+
+
+\textcolor{green}{The  simulation  results  show  that our  protocol  PeCO  saves
+  efficiently energy by  turning off some sensors during the  sensing phase.  As
+  shown in  Figure~\ref{fig5}, GAF provides  better energy saving than  PeCO for
+  the  first fifty  rounds. Indeed  GAF  balances the  energy consumption  among
+  sensor nodes inside each small fixed grid  and thus permits to extend the life
+  of sensors in each grid fairly. However, at  the same time it turns on a large
+  number of sensors and that leads  later to quickly deplete sensor's batteries.
+  DESK algorithm  shows less energy  saving compared with other  approaches.  In
+  comparison  with PeCO,  DiLCO protocol  usually provides  lower energy  saving
+  ratios. Moreover,  it can  be noticed  that after  round fifty,  PeCO protocol
+  exhibits the slowest decrease among all the considered protocols.}
 
 \begin{figure}[h!]
 %\centering
@@ -881,9 +875,7 @@ keeping a greater coverage ratio as shown in Figure \ref{figure5}.
 \includegraphics[scale=0.5]{ESR.eps} %\\~ ~ ~(a)
 \caption{Energy Saving Ratio for 200 deployed nodes}
 \label{fig5}
-\end{figure} 
-
-
+\end{figure}
 
 \subsubsection{Energy Consumption}
 
@@ -940,14 +932,12 @@ for  different   coverage  ratios.   We  denote  by   Protocol/70,  Protocol/80,
 Protocol/85, Protocol/90,  and Protocol/95 the  amount of time during  which the
 network  can satisfy  an  area  coverage greater  than  $70\%$, $80\%$,  $85\%$,
 $90\%$, and  $95\%$ respectively,  where the  term Protocol  refers to  DiLCO or
-PeCO.  \textcolor{blue}{Indeed there are applications that do not require a 100\% coverage of the
+PeCO.  \textcolor{green}{Indeed there are applications that do not require a 100\% coverage of the
 area to be  monitored. For example, forest
 fire application might require complete coverage
 in summer seasons while only require 80$\%$ of the area to be covered in rainy seasons~\citep{li2011transforming}. As another example, birds habit study requires only 70$\%$-coverage at nighttime when the birds are sleeping while requires 100$\%$-coverage at daytime when the birds are active~\citep{1279193}. 
-%Mudflows monitoring applications may require part of the area to be covered in sunny days. Thus, to extend network lifetime, the coverage quality can be decreased if it is acceptable~\citep{wang2014keeping}}. 
  PeCO always  outperforms DiLCO  for the  three  lower coverage  ratios, moreover  the
-improvements grow  with the network  size. DiLCO outperforms PeCO when the coverage ratio is required to be $>90\%$, but PeCo extends the network lifetime significantly when coverage ratio can be relaxed.}
-%DiLCO  is better for  coverage ratios near 100\%, but  in that case PeCO  is not ineffective for  the smallest network sizes.
+improvements grow  with the network  size. DiLCO outperforms PeCO when the coverage ratio is required to be $>90\%$, but PeCO extends the network lifetime significantly when coverage ratio can be relaxed.}
 
 \begin{figure}[h!]
 \centering \includegraphics[scale=0.55]{figure9.eps}

diff --git a/PeCO-EO/reponse2.tex b/PeCO-EO/reponse2.tex
index c695a984f922d91cb0acca0aa4134c0453eb2466..2c4b47d7e004e005eb776b0c959e436fff205416 100644 (file)
--- a/PeCO-EO/reponse2.tex
+++ b/PeCO-EO/reponse2.tex
@@ -28,20 +28,15 @@
 \bigskip
 
 \begin{center}
-Detailed changes and addressed issues in the revision of the article
-
-``Perimeter-based Coverage Optimization \\
-to Improve Lifetime in Wireless Sensor Networks''\\
+Revision of the manuscript ``Perimeter-based Coverage Optimization to Improve Lifetime in Wireless Sensor Networks''\\
 
 by Ali Kadhum Idrees, Karine Deschinkel, Michel Salomon and Raph\"ael Couturier
 
 \medskip
 
 \end{center}
-Dear Editor and Reviewers,
-
-
-Comments (here in red color) raised by the reviewer n\textsuperscript{o}1  after a first revision have been carefully considered. Please find below our answers highlighted in green. We did our best to satisfy your requests.
+Dear Editor and Reviewers,\\
+Comments (here in red color) raised by the reviewer n\textsuperscript{o}1  after a first revision have been carefully considered. Please find below our answers highlighted in green. We also highlighted the changes we made in the manuscript by using coloured text. We did our best to satisfy your requests.
 
 %Journal: Engineering Optimization
 %Reviewer's Comment to the Author Manuscript id GENO-2015-0094