From: Karine Deschinkel Date: Mon, 5 Oct 2015 14:25:01 +0000 (+0200) Subject: ok X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/Sensornets15.git/commitdiff_plain/c5d35ebf9a8ac33354f3f6514280bce5ec92a729 ok --- diff --git a/Example.aux b/Example.aux index 4af5b0e..5cc252b 100644 --- a/Example.aux +++ b/Example.aux @@ -43,13 +43,13 @@ \@writefile{toc}{\contentsline {section}{\numberline {3}\uppercase {Description of the DiLCO protocol}}{3}} \newlabel{sec:The DiLCO Protocol Description}{{3}{3}} \@writefile{toc}{\contentsline {subsection}{\numberline {3.1}Assumptions and models}{3}} -\citation{pedraza2006} -\citation{idrees2014coverage} \@writefile{toc}{\contentsline {subsection}{\numberline {3.2}Main idea}{4}} \newlabel{main_idea}{{3.2}{4}} \@writefile{lof}{\contentsline {figure}{\numberline {1}{\ignorespaces DiLCO protocol\relax }}{4}} \providecommand*\caption@xref[2]{\@setref\relax\@undefined{#1}} \newlabel{fig2}{{1}{4}} +\citation{pedraza2006} +\citation{idrees2014coverage} \@writefile{loa}{\contentsline {algocf}{\numberline {1}{\ignorespaces DiLCO($s_j$)\relax }}{5}} \newlabel{alg:DiLCO}{{1}{5}} \@writefile{toc}{\contentsline {section}{\numberline {4}\uppercase {Coverage problem formulation}}{5}} @@ -69,12 +69,12 @@ \newlabel{table3}{{1}{6}} \@writefile{lot}{\contentsline {table}{\numberline {2}{\ignorespaces Energy consumption model\relax }}{7}} \newlabel{table4}{{2}{7}} -\@writefile{toc}{\contentsline {subsection}{\numberline {5.2}Performance analysis}{7}} -\newlabel{sub1}{{5.2}{7}} \citation{ChinhVu} \citation{xu2001geography} \@writefile{lof}{\contentsline {figure}{\numberline {2}{\ignorespaces Coverage ratio\relax }}{8}} \newlabel{fig3}{{2}{8}} +\@writefile{toc}{\contentsline {subsection}{\numberline {5.2}Performance analysis}{8}} +\newlabel{sub1}{{5.2}{8}} \@writefile{toc}{\contentsline {subsubsection}{\numberline {5.2.1}Coverage ratio}{8}} \@writefile{toc}{\contentsline {subsubsection}{\numberline {5.2.2}Energy consumption}{8}} \@writefile{lof}{\contentsline {figure}{\numberline {3}{\ignorespaces Energy consumption per period\relax }}{9}} @@ -89,37 +89,34 @@ \newlabel{sec:Conclusion and Future Works}{{6}{10}} \bibstyle{plain} \bibdata{Example} -\bibcite{ref17}{1} -\bibcite{ref19}{2} -\bibcite{berman04}{3} -\bibcite{cardei2005improving}{4} -\bibcite{cardei2005energy}{5} -\bibcite{castano2013column}{6} -\bibcite{conti2014mobile}{7} -\bibcite{Deng2012}{8} -\bibcite{deschinkel2012column}{9} -\bibcite{idrees2014coverage}{10} -\bibcite{jaggi2006}{11} -\bibcite{kim2013maximum}{12} -\bibcite{Kumar:2005}{13} -\bibcite{li2013survey}{14} -\bibcite{ling2009energy}{15} -\bibcite{pujari2011high}{16} -\bibcite{Misra}{17} -\bibcite{Nayak04}{18} -\bibcite{pc10}{19} -\bibcite{pedraza2006}{20} -\bibcite{qu2013distributed}{21} -\bibcite{raghunathan2002energy}{22} -\bibcite{ref22}{23} -\bibcite{rossi2012exact}{24} -\bibcite{varga}{25} -\bibcite{chin2007}{26} -\bibcite{ChinhVu}{27} -\bibcite{5714480}{28} -\bibcite{xu2001geography}{29} -\bibcite{yang2014novel}{30} -\bibcite{yangnovel}{31} -\bibcite{Yang2014}{32} -\bibcite{Zhang05}{33} -\bibcite{zorbas2010solving}{34} +\bibcite{berman04}{Berman and Calinescu, 2004} +\bibcite{cardei2005improving}{Cardei and Du, 2005} +\bibcite{cardei2005energy}{Cardei et\nobreakspace {}al., 2005} +\bibcite{castano2013column}{Casta{\~n}o et\nobreakspace {}al., 2013} +\bibcite{conti2014mobile}{Conti and Giordano, 2014} +\bibcite{Deng2012}{Deng et\nobreakspace {}al., 2012} +\bibcite{deschinkel2012column}{Deschinkel, 2012} +\bibcite{idrees2014coverage}{Idrees et\nobreakspace {}al., 2014} +\bibcite{jaggi2006}{Jaggi and Abouzeid, 2006} +\bibcite{kim2013maximum}{Kim and Cobb, 2013} +\bibcite{Kumar:2005}{Kumar et\nobreakspace {}al., 2005} +\bibcite{li2013survey}{Li and Vasilakos, 2013} +\bibcite{ling2009energy}{Ling and Znati, 2009} +\bibcite{pujari2011high}{Manju and Pujari, 2011} +\bibcite{Misra}{Misra et\nobreakspace {}al., 2011} +\bibcite{Nayak04}{Nayak and Stojmenovic, 2010} +\bibcite{pc10}{Padmavathy and Chitra, 2010} +\bibcite{pedraza2006}{Pedraza et\nobreakspace {}al., 2006} +\bibcite{qu2013distributed}{Qu and Georgakopoulos, 2013} +\bibcite{raghunathan2002energy}{Raghunathan et\nobreakspace {}al., 2002} +\bibcite{rossi2012exact}{Rossi et\nobreakspace {}al., 2012} +\bibcite{varga}{Varga, 2003} +\bibcite{ChinhVu}{Vu et\nobreakspace {}al., 2006} +\bibcite{chin2007}{Vu, 2009} +\bibcite{5714480}{Xing et\nobreakspace {}al., 2010} +\bibcite{xu2001geography}{Xu et\nobreakspace {}al., 2001} +\bibcite{yang2014novel}{Yang and Chin, 2014a} +\bibcite{yangnovel}{Yang and Chin, 2014b} +\bibcite{Yang2014}{Yang and Liu, 2014} +\bibcite{Zhang05}{Zhang and Hou, 2005} +\bibcite{zorbas2010solving}{Zorbas et\nobreakspace {}al., 2010} diff --git a/Example.tex b/Example.tex index cef7ad1..c30cff5 100644 --- a/Example.tex +++ b/Example.tex @@ -91,7 +91,7 @@ means of recharging or replacing, usually due to environmental (hostile or unpractical environments) or cost reasons. Therefore, it is desired that the WSNs are deployed with high densities so as to exploit the overlapping sensing regions of some sensor nodes to save energy by turning off some of them during -the sensing phase to prolong the network lifetime. \textcolor{blue}{A WSN can use various types of sensors such as \cite{ref17,ref19}: thermal, seismic, magnetic, visual, infrared, acoustic, and radar. These sensors are capable of observing different physical conditions such as: temperature, humidity, pressure, speed, direction, movement, light, soil makeup, noise levels, presence or absence of certain kinds of objects, and mechanical stress levels on attached objects. Consequently, a wide range of WSN applications such as~\cite{ref22}: health-care, environment, agriculture, public safety, military, transportation systems, and industry applications.} +the sensing phase to prolong the network lifetime. \textcolor{blue}{A WSN can use various types of sensors such as \cite{ref17,ref19}: thermal, seismic, magnetic, visual, infrared, acoustic, and radar. These sensors are capable of observing different physical conditions such as: temperature, humidity, pressure, speed, direction, movement, light, soil makeup, noise levels, presence or absence of certain kinds of objects, and mechanical stress levels on attached objects. Consequently, there is a wide range of WSN applications such as~\cite{ref22}: health-care, environment, agriculture, public safety, military, transportation systems, and industry applications.} In this paper we design a protocol that focuses on the area coverage problem with the objective of maximizing the network lifetime. Our proposition, the @@ -116,8 +116,7 @@ framework of the DiLCO approach and the coverage problem formulation. In this paper we made more realistic simulations by taking into account the characteristics of a Medusa II sensor ~\cite{raghunathan2002energy} to measure the energy consumption and the computation time. We have implemented two other -existing approaches (a distributed one, DESK ~\cite{ChinhVu}, and a centralized -one called GAF ~\cite{xu2001geography}) in order to compare their performances +existing \textcolor{blue}{and distributed approaches}(DESK ~\cite{ChinhVu}, and GAF ~\cite{xu2001geography}) in order to compare their performances with our approach. We also focus on performance analysis based on the number of subregions. % MODIF - END @@ -244,7 +243,8 @@ less accurate according to the number of primary points. \label{main_idea} \noindent We start by applying a divide-and-conquer algorithm to partition the area of interest into smaller areas called subregions and then our protocol is -executed simultaneously in each subregion. +executed simultaneously in each subregion. \textcolor{blue}{Sensor nodes are assumed to +be deployed almost uniformly over the region and the subdivision of the area of interest is regular.} \begin{figure}[ht!] \centering @@ -257,7 +257,9 @@ As shown in Figure~\ref{fig2}, the proposed DiLCO protocol is a periodic protocol where each period is decomposed into 4~phases: Information Exchange, Leader Election, Decision, and Sensing. For each period there will be exactly one cover set in charge of the sensing task. A periodic scheduling is -interesting because it enhances the robustness of the network against node failures. \textcolor{blue}{Many WSN applications have communication requirements that are periodic and known previously such as collecting temperature statistics at regular intervals. This periodic nature can be used to provide a regular schedule to sensor nodes and thus avoid a sensor failure. If the period time increases, the reliability and energy consumption are decreased and vice versa}. First, a node that has not enough energy to complete a period, or +interesting because it enhances the robustness of the network against node failures. +% \textcolor{blue}{Many WSN applications have communication requirements that are periodic and known previously such as collecting temperature statistics at regular intervals. This periodic nature can be used to provide a regular schedule to sensor nodes and thus avoid a sensor failure. If the period time increases, the reliability and energy consumption are decreased and vice versa}. +First, a node that has not enough energy to complete a period, or which fails before the decision is taken, will be excluded from the scheduling process. Second, if a node fails later, whereas it was supposed to sense the region of interest, it will only affect the quality of the coverage until the diff --git a/reponse.tex b/reponse.tex index 4b131be..6a2dea7 100644 --- a/reponse.tex +++ b/reponse.tex @@ -77,6 +77,7 @@ The paper present a new system to optimize sensord detections. The work present \textcolor{blue}{\textbf{\textsc{Answer:} Right. We have included a paragraph on the examples and practical applications of WSNs in section~1. }} +\textcolor{red}Je pense que la question porte sur un exemple d'application de notre protocole?} \section*{Response to Reviewer $\#$3 Comments}