Update with adding reponse.tex file

diff --git a/article.bib b/article.bib
index 60609ba8247af6d00cac860b162ecad09f2cf64d..4f8a67170a0465330cc93d511bde7a0cb9c543d2 100644 (file)
--- a/article.bib
+++ b/article.bib
@@ -528,4 +528,20 @@ ISSN={1536-1276},
   year={2012}
 }
 
   year={2012}
 }
 

+@BOOK{AMPL,
+  AUTHOR =       "Robert Fourer and David M. Gay and Brian W. Kernighan",
+  TITLE =        "AMPL: A Modeling Language for Mathematical Programming",
+  PUBLISHER =    "Cengage Learning",
+  YEAR =         "November 12, 2002",
+  edition =      "2nd",
+ 
+}
+
+@ARTICLE{glpk,
+author = {Andrew Makhorin},
+title = {The GLPK (GNU Linear Programming Kit)},
+journal = {Available: https://www.gnu.org/software/glpk/},
+year = {2012}
+}
+

 
 

diff --git a/article.tex b/article.tex
index f156c3617f4dcc2e9893cf66c79328d35c8475c2..16831f35887418d8667d80bcfe0ab9073093720a 100644 (file)
--- a/article.tex
+++ b/article.tex
@@ -521,8 +521,7 @@ active nodes.
 Instead  of working  with a  continuous coverage  area, we  make it  discrete by
 considering for each sensor a set of points called primary points. Consequently,
 we assume  that the sensing disk  defined by a sensor  is covered if  all of its
 Instead  of working  with a  continuous coverage  area, we  make it  discrete by
 considering for each sensor a set of points called primary points. Consequently,
 we assume  that the sensing disk  defined by a sensor  is covered if  all of its

-primary points are covered. The choice of number and locations of primary points
-is the subject of another study not presented here.
+primary points are covered. The choice of number and locations of primary points is the subject of another study not presented here.

 
 %By  knowing the  position (point  center: ($p_x,p_y$))  of  a wireless
 %sensor node  and its $R_s$,  we calculate the primary  points directly
 
 %By  knowing the  position (point  center: ($p_x,p_y$))  of  a wireless
 %sensor node  and its $R_s$,  we calculate the primary  points directly


@@ -859,7 +858,7 @@ Sensing time for one round & 60 Minutes \\
 $E_{R}$ & 36 Joules\\
 $R_s$ & 5~m   \\     
 %\hline
 $E_{R}$ & 36 Joules\\
 $R_s$ & 5~m   \\     
 %\hline

-$W_{\Theta}$ & 1   \\
+$W_{\theta}$ & 1   \\

 % [1ex] adds vertical space
 %\hline
 $W_{U}$ & $|P|^2$
 % [1ex] adds vertical space
 %\hline
 $W_{U}$ & $|P|^2$


@@ -948,7 +947,7 @@ 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
 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 $0.2575~mW$.
+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
 
 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


@@ -1011,7 +1010,7 @@ network, and $R$ is the total number of subregions in the network.
   % New version with global loops on period
   \begin{equation*}
     \scriptsize
   % New version with global loops on period
   \begin{equation*}
     \scriptsize

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

   \end{equation*}
 
 
   \end{equation*}
 
 


@@ -1057,9 +1056,9 @@ indicate the energy consumed by the whole network in round $t$.
 
 \end{enumerate}
 
 
 \end{enumerate}
 

-\section{Results and analysis}
+\subsection{Results and analysis}

 
 

-\subsection{Coverage ratio} 
+\subsubsection{Coverage ratio} 

 
 Figure~\ref{fig3} shows  the average coverage  ratio for 150 deployed  nodes. We
 can notice that for the first thirty rounds both DESK and GAF provide a coverage
 
 Figure~\ref{fig3} shows  the average coverage  ratio for 150 deployed  nodes. We
 can notice that for the first thirty rounds both DESK and GAF provide a coverage


@@ -1085,7 +1084,7 @@ rounds, and thus should extend the network lifetime.
 \label{fig3}
 \end{figure} 
 
 \label{fig3}
 \end{figure} 
 

-\subsection{Active sensors ratio} 
+\subsubsection{Active sensors ratio} 

 
 It is crucial to have as few active nodes as possible in each round, in order to
 minimize    the    communication    overhead    and   maximize    the    network
 
 It is crucial to have as few active nodes as possible in each round, in order to
 minimize    the    communication    overhead    and   maximize    the    network


@@ -1106,7 +1105,7 @@ nodes in a more efficient manner.
 \label{fig4}
 \end{figure} 
 
 \label{fig4}
 \end{figure} 
 

-\subsection{Stopped simulation runs}
+\subsubsection{Stopped simulation runs}

 %The results presented in this experiment, is to show the comparison of our MuDiLCO protocol with other two approaches from the point of view the stopped simulation runs per round. Figure~\ref{fig6} illustrates the percentage of stopped simulation
 %runs per round for 150 deployed nodes. 
 
 %The results presented in this experiment, is to show the comparison of our MuDiLCO protocol with other two approaches from the point of view the stopped simulation runs per round. Figure~\ref{fig6} illustrates the percentage of stopped simulation
 %runs per round for 150 deployed nodes. 
 


@@ -1128,7 +1127,7 @@ still connected.
 \label{fig6}
 \end{figure} 
 
 \label{fig6}
 \end{figure} 
 

-\subsection{Energy consumption} \label{subsec:EC}
+\subsubsection{Energy consumption} \label{subsec:EC}

 
 We  measure  the  energy  consumed  by the  sensors  during  the  communication,
 listening, computation, active, and sleep status for different network densities
 
 We  measure  the  energy  consumed  by the  sensors  during  the  communication,
 listening, computation, active, and sleep status for different network densities


@@ -1162,11 +1161,11 @@ sensors to consider in the integer program.
 %In fact,  a distributed optimization decision, which produces T rounds, on the subregions is  greatly reduced the cost of communications and the time of listening as well as the energy needed for sensing phase and computation so thanks to the partitioning of the initial network into several independent subnetworks and producing T rounds for each subregion periodically. 
 
 
 %In fact,  a distributed optimization decision, which produces T rounds, on the subregions is  greatly reduced the cost of communications and the time of listening as well as the energy needed for sensing phase and computation so thanks to the partitioning of the initial network into several independent subnetworks and producing T rounds for each subregion periodically. 
 
 

-\subsection{Execution time}
+\subsubsection{Execution time}

 
 We observe  the impact of the  network size and of  the number of  rounds on the
 computation  time.   Figure~\ref{fig77} gives  the  average  execution times  in
 
 We observe  the impact of the  network size and of  the number of  rounds on the
 computation  time.   Figure~\ref{fig77} gives  the  average  execution times  in

-seconds (needed to solve optimization problem) for different values of $T$.  The
+seconds (needed to solve optimization problem) for different values of $T$. The modeling language for Mathematical Programming (AMPL)~\cite{AMPL} is  employed to generate the Mixed Integer Linear Program instance  in a  standard format, which  is then read  and solved  by the optimization solver  GLPK (GNU  linear Programming Kit  available in  the public domain) \cite{glpk} through a Branch-and-Bound method. The

 original execution time  is computed on a laptop  DELL with Intel Core~i3~2370~M
 (2.4 GHz)  processor (2  cores) and the  MIPS (Million Instructions  Per Second)
 rate equal to 35330. To be consistent  with the use of a sensor node with Atmels
 original execution time  is computed on a laptop  DELL with Intel Core~i3~2370~M
 (2.4 GHz)  processor (2  cores) and the  MIPS (Million Instructions  Per Second)
 rate equal to 35330. To be consistent  with the use of a sensor node with Atmels


@@ -1195,7 +1194,7 @@ optimization problem.
 
 %While MuDiLCO-1, 3, and 5 solves the optimization process with suitable execution times to be used on wireless sensor network because it distributed on larger number of small subregions as well as it is used acceptable number of round(s) T.  We think that in distributed fashion the solving of the optimization problem to produce T rounds in a subregion can be tackled by sensor nodes. Overall, to be able to deal with very large networks, a distributed method is clearly required.
 
 
 %While MuDiLCO-1, 3, and 5 solves the optimization process with suitable execution times to be used on wireless sensor network because it distributed on larger number of small subregions as well as it is used acceptable number of round(s) T.  We think that in distributed fashion the solving of the optimization problem to produce T rounds in a subregion can be tackled by sensor nodes. Overall, to be able to deal with very large networks, a distributed method is clearly required.
 

-\subsection{Network lifetime}
+\subsubsection{Network lifetime}

 
 The next  two figures,  Figures~\ref{fig8}(a) and \ref{fig8}(b),  illustrate the
 network lifetime  for different network sizes,  respectively for $Lifetime_{95}$
 
 The next  two figures,  Figures~\ref{fig8}(a) and \ref{fig8}(b),  illustrate the
 network lifetime  for different network sizes,  respectively for $Lifetime_{95}$


@@ -1252,7 +1251,7 @@ scheduling.
 The activity  scheduling in each subregion  works in periods,  where each period
 consists of four  phases: (i) Information Exchange, (ii)  Leader Election, (iii)
 Decision Phase to plan the activity  of the sensors over $T$ rounds, (iv) Sensing
 The activity  scheduling in each subregion  works in periods,  where each period
 consists of four  phases: (i) Information Exchange, (ii)  Leader Election, (iii)
 Decision Phase to plan the activity  of the sensors over $T$ rounds, (iv) Sensing

-Phase itself divided into T rounds.
+Phase itself divided into $T$ rounds.

 
 Simulations  results show the  relevance of  the proposed  protocol in  terms of
 lifetime, coverage  ratio, active  sensors ratio, energy  consumption, execution
 
 Simulations  results show the  relevance of  the proposed  protocol in  terms of
 lifetime, coverage  ratio, active  sensors ratio, energy  consumption, execution

diff --git a/reponse.tex b/reponse.tex
new file mode 100644 (file)
index 0000000..dda571f
--- /dev/null
+++ b/reponse.tex
@@ -0,0 +1,217 @@
+\documentclass[14]{article}
+
+\usepackage{color}
+\usepackage{times}
+\usepackage{titlesec}
+\usepackage{pifont}
+%\usepackage[T1]{fontenc}
+%\usepackage[latin1]{inputenc}
+
+\renewcommand{\labelenumii}{\labelenumi\arabic{enumii}}
+%\titleformat*{\section}{\Large\bfseries}
+
+%\title{Response to the reviewers of \bf "Perimeter-based Coverage Optimization to Improve Lifetime in Wireless Sensor Networks"}
+%\author{Ali Kadhum Idrees, Karine Deschinkela, Michel Salomon and Raphael Couturier}
+
+\begin{document}
+
+\begin{flushright}
+\today
+\end{flushright}%
+
+\vspace{-0.5cm}\hspace{-2cm}FEMTO-ST Institute, UMR 6714 CNRS
+
+\hspace{-2cm}University Bourgogne Franche-Comt\'e
+
+\hspace{-2cm}IUT Belfort-Montb\'eliard, BP 527, 90016 Belfort Cedex, France.
+
+\bigskip
+
+\begin{center}
+Detailed changes and addressed issues in the revision of the article
+
+``Multiround Distributed Lifetime Coverage Optimization \\
+ Protocol in Wireless Sensor Networks''\\
+  
+
+by Ali Kadhum Idrees, Karine Deschinkel, Michel Salomon, and Raph\"ael Couturier
+
+\medskip
+
+\end{center}
+Dear Editor and Reviewers,
+
+First of all, we would like to thank you very much for your kind help to improve
+our article  named: `` Multiround Distributed Lifetime Coverage Optimization
+Protocol in Wireless Sensor Networks
+''.  We  highly  appreciate the  detailed  valuable
+comments of the reviewers on our  article. The suggestions are quite helpful for
+us and we incorporate them in the revised article. We are happy to submit to you
+a revised version that considers most of your remarks and suggestions to improve
+the quality of our article.
+
+As below, we  would like to clarify  some of the points raised  by the reviewers
+and we hope the reviewers and the  editors will be satisfied by our responses to
+the comments and the revision for the original manuscript.
+
+
+
+\section*{Response to Reviewer No. 1 Comments}
+
+The paper entitled "Multiround Distributed Lifetime Coverage Optimization
+Protocol in Wireless Sensor Networks" introduces MuDiLCO, a distributed protocol
+to enhance the use of WSN by splitting the network lifetime into periods, and by
+breaking each sensing activity of a period into a series of rounds. A sensor
+called the leader is elected, and based on local data, solves a Mixed Integer
+Linear Program in order to schedule the activity of its neighbors over the
+sensing rounds of the current period.
+
+The contribution of this paper is interesting, but probably needs to be deepened
+in order to reach the standards of a publication in Ad Hoc Networks.\\
+
+
+\noindent\textcolor{black}{\textbf{MAJOR COMMENTS:}} \\
+
+\noindent {\bf  1.}     Page 6, Section 3.2
+The author didn't explain how subregions are created. This is an important
+point, as clustering may have a significant impact on solution quality. Not only
+the size of the subregion should be discussed and analyzed, but also the
+clustering strategy.\\
+
+\textcolor{blue}{\textbf{\textsc{Answer:}      }}\\
+
+
+\noindent {\bf  2.}     Page 8
+The objective function (5) of the Mixed Integer Linear Program appears to be
+very questionable. Indeed overcoverage and undercoverage may compensate each
+other, so the same objective value may represent two incomparable situations. It
+seems that the semantic of the objective function is not well defined, as one
+may wonder what exactly is (quantitatively speaking) the problem objective.
+Coverage breach is obviously an issue in WSN, but why penalizing overcoverage? A
+two-phase approach where breach is minimized first, and then overcoverage is
+minimized would probably make more sense.
+    \\
+
+\textcolor{blue}{\textbf{\textsc{Answer:}      }}\\
+
+
+
+\noindent {\bf 3.}   Page 9
+In the MILP formulation, it is possible that some point p is never covered at
+all, which means that some part of the area to monitor may never be monitored by
+the WSN. The authors are referred to "alpha-coverage to extend network lifetime
+on wireless sensor networks", Optim. Lett. 7, No. 1, 157-172 (2013) by Gentilli
+et al to enforce a constraint on the minimum coverage of each point.  \\
+
+\textcolor{blue}{\textbf{\textsc{Answer:}       }}\\
+
+
+\noindent {\bf 4.}  Page 13
+The criterion "Energy Consumption" is the average consumption per round. But the
+duration of a round is a feature that can be arbitrarily set in the algorithm.
+Computing the average energy consumption per unit of time over the network
+lifetime would be better, as it is independent from the number and duration of
+rounds.  \\
+
+\textcolor{blue}{\textbf{\textsc{Answer :}        }}
+
+
+
+\noindent {\bf 5.}    Page 15-18
+Figures 2-6 mention four different versions of MuDiLCO. The performance of these
+different versions should be analyzed with more details for each figure.
+Alternatively, the authors may remove some versions of MuDiLCO if they do not
+bring any valuable insight. \\
+
+
+\textcolor{blue}{\textbf{\textsc{Answer :}        }}
+
+
+\noindent {\bf 6.}   Page 19 (most major point)
+The authors state that solving the Mixed Integer Linear Program is
+time-consuming, and use this point for explaining why MuDiLCO-7 is not as
+efficient as other versions. Why not using a heuristic (or a metaheuristic) for
+addressing the problem instead of using an exact solver? A straightforward and
+easily implementable idea to cut CPU time would be to return the best feasible
+solution found by the solver after a given time threshold for example. Doing so
+is very likely to save time and energy, and to improve the results of MuDiLCO-7
+in particular.  \\
+
+
+\textcolor{blue}{\textbf{\textsc{Answer :}        }}
+
+
+\bigskip
+
+\noindent\textcolor{black}{\textbf{MINOR COMMENTS:}} \\
+
+\noindent  {\ding{90}    Page 2
+The paragraph that begins with "The remainder of the paper is organized as
+follows" should mention the content of Section 5.    }  \\
+
+\textcolor{blue}{\textbf{\textsc{Answer:}  Right, fixed.  Section 5 is included as a subsection 4.4 within section 4.    }}\\
+
+\noindent  {\ding{90}   Page 3
+The sentence "the centralized approaches usually suffer from the scalability
+problem, making them less competitive as the network size increase" should
+probably be tempered: heuristics and metaheuristics can handle very large and
+centralized problems (even if exact approaches can't), and these approaches are
+very popular in WSN.     } \\
+
+\textcolor{blue}{\textbf{\textsc{Answer:}    }}\\
+
+\noindent  {\ding{90}    Page 5
+"The choice of number and locations of primary points is the subject of another
+study not presented here". The authors should provide at least one reference
+about the aforementioned study.      }  \\
+
+\textcolor{blue}{\textbf{\textsc{Answer:}          }}\\
+
+\noindent {\ding{90}     Page 6, Figure 1:
+All rounds seem to have the same duration. This should be stated explicitly, and
+justified (in column generation based approaches, "rounds" to not have the same
+duration).           }  \\
+
+\textcolor{blue}{\textbf{\textsc{Answer:}                }}\\
+
+\noindent  {\ding{90}  Page 11 in Table 1
+$W_\Theta$ should be replaced with $W_\theta$
+              } \\
+
+\textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed }}.\\
+
+\noindent {\ding{90}    Page 12
+Don't italicize "mW" in "equal to 02575 mW"            } \\
+
+\textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed }}.\\
+
+\noindent {\ding{90}  Page 14
+ML is not defined (see the denominator of the large, unnumbered formula that
+defines EC).          }  \\
+
+\textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed }}.\\
+
+\noindent {\ding{90}  Page 19 Section 6
+
+"Sensing phase itself divided into T rounds" -> T should be italic.           } 
+\\
+
+\textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed }}.\\
+
+\noindent {\ding{90}  Page 18 Section 5.5
+The name of the solver used to solve the Mixed Integer Linear Program should be
+given.   }  \\
+
+\textcolor{blue}{\textbf{\textsc{Answer:}   Right, fixed         }}.\\
+
+
+We are very grateful to the  reviewers who, by their recommendations, allowed us
+to improve the quality of our article.
+\begin{flushright}
+Best regards\\
+The authors
+\end{flushright} 
+ 
+
+
+\end{document}