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\citation{li2011transforming}
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\bibstyle{gENO}
\bibdata{biblio}
\bibcite{akyildiz2002wireless}{{1}{2002}{{Akyildiz et~al.}}{{Akyildiz, Su, Sankarasubramaniam, and Cayirci}}}
\bibcite{berman04}{{3}{2004}{{Berman and Calinescu}}{{}}}
\bibcite{cardei2005improving}{{4}{2005}{{Cardei and Du}}{{}}}
\bibcite{cardei2005energy}{{5}{2005}{{Cardei et~al.}}{{Cardei, Thai, Li, and Wu}}}
-\newlabel{my-labelx}{{4}{18}}
\bibcite{castano2013column}{{6}{2014}{{Casta{\~n}o et~al.}}{{Casta{\~n}o, Rossi, Sevaux, and Velasco}}}
\bibcite{iamigo:cplex}{{7}{2010}{{CPLEX}}{{}}}
\bibcite{Deng2012}{{8}{2012}{{Deng, Jiguo~Yu, and Chen}}{{}}}
\bibcite{deschinkel2012column}{{9}{2012}{{Deschinkel}}{{}}}
+\newlabel{my-labelx}{{4}{18}}
\bibcite{AMPL}{{10}{November 12, 2002}{{Fourer, Gay, and Kernighan}}{{}}}
\bibcite{HeShibo}{{11}{2014}{{He et~al.}}{{He, Gong, Zhang, Chen, and Sun}}}
\bibcite{huang2005coverage}{{12}{2005}{{Huang and Tseng}}{{}}}
\bibcite{Idrees2}{{15}{2015}{{Idrees et~al.}}{{Idrees, Deschinkel, Salomon, and Couturier}}}
\bibcite{jaggi2006}{{16}{2006}{{Jaggi and Abouzeid}}{{}}}
\bibcite{kim2013maximum}{{17}{2013}{{Kim and Cobb}}{{}}}
-\bibcite{0031-9155-44-1-012}{{18}{1999}{{Lee et~al.}}{{Lee, Gallagher, Silvern, Wuu, and Zaider}}}
-\bibcite{li2013survey}{{19}{2013}{{Li and Vasilakos}}{{}}}
-\bibcite{li2011transforming}{{20}{2011}{{Li et~al.}}{{Li, Vu, Ai, Chen, and Zhao}}}
-\bibcite{ling2009energy}{{21}{2009}{{Ling and Znati}}{{}}}
-\bibcite{glpk}{{22}{2012}{{Makhorin}}{{}}}
-\bibcite{Misra}{{23}{2011}{{Misra, Kumar, and Obaidat}}{{}}}
-\bibcite{pc10}{{24}{2010}{{Padmavathy and Chitra}}{{}}}
-\bibcite{puccinelli2005wireless}{{25}{2005}{{Puccinelli and Haenggi}}{{}}}
-\bibcite{pujari2011high}{{26}{2011}{{Pujari}}{{}}}
-\bibcite{qu2013distributed}{{27}{2013}{{Qu and Georgakopoulos}}{{}}}
-\bibcite{rault2014energy}{{28}{2014}{{Rault, Bouabdallah, and Challal}}{{}}}
-\bibcite{doi:10.1080/0305215X.2012.687732}{{29}{2013}{{Singh, Rossi, and Sevaux}}{{}}}
-\bibcite{varga}{{30}{2003}{{Varga}}{{}}}
-\bibcite{vu2009universal}{{31}{2009}{{Vu et~al.}}{{Vu, Chen, Zhao, and Li}}}
+\bibcite{1279193}{{18}{2004}{{Kumagai}}{{}}}
+\bibcite{0031-9155-44-1-012}{{19}{1999}{{Lee et~al.}}{{Lee, Gallagher, Silvern, Wuu, and Zaider}}}
+\bibcite{li2013survey}{{20}{2013}{{Li and Vasilakos}}{{}}}
+\bibcite{li2011transforming}{{21}{2011}{{Li et~al.}}{{Li, Vu, Ai, Chen, and Zhao}}}
+\bibcite{ling2009energy}{{22}{2009}{{Ling and Znati}}{{}}}
+\bibcite{glpk}{{23}{2012}{{Makhorin}}{{}}}
+\bibcite{Misra}{{24}{2011}{{Misra, Kumar, and Obaidat}}{{}}}
+\bibcite{pc10}{{25}{2010}{{Padmavathy and Chitra}}{{}}}
+\bibcite{puccinelli2005wireless}{{26}{2005}{{Puccinelli and Haenggi}}{{}}}
+\bibcite{pujari2011high}{{27}{2011}{{Pujari}}{{}}}
+\bibcite{qu2013distributed}{{28}{2013}{{Qu and Georgakopoulos}}{{}}}
+\bibcite{rault2014energy}{{29}{2014}{{Rault, Bouabdallah, and Challal}}{{}}}
+\bibcite{doi:10.1080/0305215X.2012.687732}{{30}{2013}{{Singh, Rossi, and Sevaux}}{{}}}
+\bibcite{varga}{{31}{2003}{{Varga}}{{}}}
\bibcite{ChinhVu}{{32}{2006}{{Vu et~al.}}{{Vu, Gao, Deshmukh, and Li}}}
\bibcite{chin2007}{{33}{2009}{{Vu}}{{}}}
\bibcite{wang2011coverage}{{34}{2011}{{Wang}}{{}}}
barrier-coverage in Wireless Sensor Networks.'' In \emph{19th IEEE
International Conference on Networks (ICON), 2013,} 1--6.
+\bibitem[Kumagai(2004)]{1279193}
+Kumagai, J. 2004. ``Life of birds [wireless sensor network for bird study].''
+ \emph{Spectrum, IEEE} 41 (4): 42--49.
+
\bibitem[Lee et~al.(1999)Lee, Gallagher, Silvern, Wuu, and
Zaider]{0031-9155-44-1-012}
Lee, Eva~K, Richard~J Gallagher, David Silvern, Cheng-Shie Wuu, and Marco
Varga, A. 2003. ``OMNeT++ Discrete Event Simulation System.'' \emph{Available:
http://www.omnetpp.org} .
-\bibitem[Vu et~al.(2009)Vu, Chen, Zhao, and Li]{vu2009universal}
-Vu, Chinh, Guantao Chen, Yi~Zhao, and Yingshu Li. 2009. ``A universal framework
- for partial coverage in Wireless Sensor Networks.'' In \emph{Performance
- Computing and Communications Conference (IPCCC), 2009 IEEE 28th
- International,} 1--8. IEEE.
-
\bibitem[Vu et~al.(2006)Vu, Gao, Deshmukh, and Li]{ChinhVu}
Vu, Chinh, Shan Gao, Wiwek Deshmukh, and Yingshu Li. 2006. ``Distributed
Energy-Efficient Scheduling Approach for K-Coverage in Wireless Sensor
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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
+ 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
\end{figure}
Figure~\ref{figure9} compares the lifetime coverage of the DiLCO and PeCO protocols
-for different coverage ratios. We denote by Protocol/50, Protocol/80,
+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 $50\%$, $80\%$, $85\%$,
+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
area to be monitored. For example, forest
fire application might require complete coverage
-in summer seasons while only requires 80$\%$ of the area to be covered in rainy seasons \cite{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 \cite{vu2009universal}. 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\cite{wang2014keeping}}. PeCO might be an interesting method since it achieves a good balance between a high level coverage ratio and network lifetime. PeCO
-always outperforms DiLCO for the three lower coverage ratios, moreover the
-improvements grow with the network size. \textcolor{blue}{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.}
+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!]
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}{We suppose that 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 their 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)}
+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).}
The sensors inside a same region cooperate to elect a leader. The selection
criteria for the leader are (in order of priority):
\begin{enumerate}
of sensors in the network.
\item {\bf \textcolor{blue}{Energy Saving Ratio (ESR)}}:
-\textcolor{blue}{we consider a performance metric linked to energy. This metric, called Energy Saving Ratio (ESR), is defined by:
+\textcolor{blue}{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}}
\subsubsection{\textcolor{blue}{Energy Saving Ratio (ESR)}}
-\textcolor{blue}{In this experiment, we consider an Energy Saving Ratio (see Figure~\ref{fig5}) for 200 deployed nodes.
-The longer the ratio is, the more redundant sensor nodes are switched off, and consequently the longer the network may live. }
+%\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.}
\begin{figure}[h!]
%\centering
\label{fig5}
\end{figure}
-\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 balance the energy consumption among sensor nodes inside each small fixed grid that 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 togehter. After that GAF provide less energy saving compared with other approches because of the large number of dead nodes. DESK algorithm shows less energy saving compared with other approaches due to activate a larg number of sensors during the sensing. DiLCO protocol provides less energy saving ratio commpared 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{Energy Consumption}
\end{figure}
Figure~\ref{figure9} compares the lifetime coverage of the DiLCO and PeCO protocols
-for different coverage ratios. We denote by Protocol/50, Protocol/80,
+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 $50\%$, $80\%$, $85\%$,
+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
area to be monitored. For example, forest
fire application might require complete coverage
-in summer seasons while only requires 80$\%$ of the area to be covered in rainy seasons \cite{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 \cite{vu2009universal}. 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\cite{wang2014keeping}}. PeCO might be an interesting method since it achieves a good balance between a high level coverage ratio and network lifetime. PeCO
-always outperforms DiLCO for the three lower coverage ratios, moreover the
-improvements grow with the network size. \textcolor{blue}{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.}
+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!]
(contract ANR-11-LABX-01-01).
\bibliographystyle{gENO}
-\bibliography{biblio} % biblio
+\bibliography{biblio} %articleeo
\end{document}
year={2014}
}
+@ARTICLE{1279193,
+author={Kumagai, J.},
+journal={Spectrum, IEEE},
+title={Life of birds [wireless sensor network for bird study]},
+year={2004},
+volume={41},
+number={4},
+pages={42-49},
+month={April}
+}
+
Dear Editor and Reviewers,
-Comments (here in red color) raised by the reviewer n°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.
+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.
%Journal: Engineering Optimization
%Reviewer's Comment to the Author Manuscript id GENO-2015-0094
-\noindent {\bf 3.} The communication and information sharing required to
+\noindent {\textbf{3. \textsc{Reviewer's comment:} } } The communication and information sharing required to
cooperate and make these decisions was not discussed.\\
\textcolor{blue}{\textbf{\textsc{Answer:} The communication and information
\textcolor{red}{\textbf{\textsc{Reviewer's response:} I see at the end of page 8 the description of the INFO packet. However, you are not including any description of the position coordinates, remaining energy, sensor node ID, etc. in the write up. I suggest adding this into the write up to make the communication clear.}}\\
-\textcolor{green}{\textbf{\textsc{Answer:} Right, we have included more description about the INFO packet and the ActiveSleep packet into the write up at the end of section~3.}}\\
+\textcolor{green}{\textbf{\textsc{Answer:} Right, we have included more description about the INFO packet and the ActiveSleep packet at the end of section~3.}}\\
-\noindent {\bf 7.} The methodology is implemented in OMNeT++ (network simulator)
+\noindent {\textbf{7. \textsc{Reviewer's comment:}}} The methodology is implemented in OMNeT++ (network simulator)
and tested against 2 existing algorithms and a previously developed method by
the authors. The simulation results are thorough and show that the proposed
method improves the coverage and network lifetime compared with the 3 existing
contribution but it's less convincing since the results are slightly better if not the same for the two
methodologies you have developed. Could you include some other measure that shows that the
PeCO is better? Maybe include computation time or something that is as convincing as the energy
-consumed per sensor.}}
+consumed per sensor.}}\\
\textcolor{green}{\textbf{\textsc{Answer:} In fact, we defined in section 5.1 a new performance metric linked to the energy, called Energy Saving Ratio (ESR). We added a new section (5.2.3) in the result part related to this performance metric which shows that our PeCO protocol provides better energy saving compared with other approaches.}}\\
-\noindent {\bf 8.} Since this paper is attacking the coverage problem, I would
+\noindent {8. \textbf{\textsc{Reviewer's comment:}}} Since this paper is attacking the coverage problem, I would
like to see more information on the amount of coverage the algorithm is
achieving. It seems that there is a tradeoff in this algorithm that allows the
network to increase its lifetime but does not improve the coverage ratio. This
you would want to have a coverage ratio of $50\%$? This seems like a very small ratio and as you
increase it, DiLCO becomes the methodology that has the maximum network lifetime. If you don't
include application examples, your statement "Indeed there are applications that do not require a
-100$\%$ coverage of the area to be monitored." stronger. }}
+100$\%$ coverage of the area to be monitored." stronger. }}\\
-\textcolor{green}{\textbf{\textsc{Answer:} Thank you so much to your suggestion for adjusting the sentence in the end of Section 5.2.5. (previously Section 5.2.4.), It is done.
-For the applications, we added some applications examples in the end of the sentence "Indeed there are applications that do not require a 100$\%$ coverage of the area to be monitored." as well as we changed the figure 10 (previously figure 9) by adding DilCO/70 and PecO/70 instead of DilCO/50 and PeCO/50 }}\\
+\textcolor{green}{\textbf{\textsc{Answer:} Thank you so much for your suggestion, we modified the sentence at the end of Section 5.2.5. (previously Section 5.2.4.). As recommended, we added some applications examples. We also changed the figure 10 (previously figure 9) by replacing DilCO/50 and PecO/50 by DilCO/70 and PeCO/70.}}\\
