From 64b7f630f91f3e30575c2313f41cc9a400295640 Mon Sep 17 00:00:00 2001 From: Michel Salomon Date: Wed, 8 Jul 2015 15:36:51 +0200 Subject: [PATCH 1/1] Final corrections --- PeCO-EO/articleeo.aux | 65 ++++++++--------- PeCO-EO/articleeo.bbl | 18 ++--- PeCO-EO/articleeo.blg | 60 +++++++-------- PeCO-EO/articleeo.log | 126 +++++++++++++++----------------- PeCO-EO/articleeo.pdf | Bin 746415 -> 746329 bytes PeCO-EO/articleeo.tex | 165 +++++++++++++++++++++--------------------- PeCO-EO/biblio.bib | 6 +- PeCO-EO/reponse.tex | 144 ++++++++++++++++++------------------ 8 files changed, 285 insertions(+), 299 deletions(-) diff --git a/PeCO-EO/articleeo.aux b/PeCO-EO/articleeo.aux index 378ac92..7f90674 100644 --- a/PeCO-EO/articleeo.aux +++ b/PeCO-EO/articleeo.aux @@ -13,7 +13,7 @@ \citation{yang2014novel} \citation{HeShibo,kim2013maximum} \citation{Deng2012} -\citation{Huang:2003:CPW:941350.941367} +\citation{huang2005coverage} \@writefile{toc}{\contentsline {section}{\numberline {2}Related Literature}{2}} \newlabel{sec:Literature Review}{{2}{2}} \citation{wang2011coverage} @@ -92,37 +92,36 @@ \bibcite{deschinkel2012column}{{9}{2012}{{Deschinkel}}{{}}} \bibcite{AMPL}{{10}{November 12, 2002}{{Fourer, Gay, and Kernighan}}{{}}} \bibcite{HeShibo}{{11}{2014}{{He et~al.}}{{He, Gong, Zhang, Chen, and Sun}}} -\bibcite{Huang:2003:CPW:941350.941367}{{12}{2005{a}}{{Huang and Tseng}}{{}}} -\bibcite{huang2005coverage}{{13}{2005{b}}{{Huang and Tseng}}{{}}} -\bibcite{doi:10.1155/2010/926075}{{14}{2010}{{Hung and Lui}}{{}}} -\bibcite{idrees2014coverage}{{15}{2014}{{Idrees et~al.}}{{Idrees, Deschinkel, Salomon, and Couturier}}} -\bibcite{Idrees2}{{16}{2015}{{Idrees et~al.}}{{Idrees, Deschinkel, Salomon, and Couturier}}} -\bibcite{jaggi2006}{{17}{2006}{{Jaggi and Abouzeid}}{{}}} -\bibcite{kim2013maximum}{{18}{2013}{{Kim and Cobb}}{{}}} -\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{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{ChinhVu}{{31}{2006}{{Vu et~al.}}{{Vu, Gao, Deshmukh, and Li}}} -\bibcite{chin2007}{{32}{2009}{{Vu}}{{}}} -\bibcite{wang2011coverage}{{33}{2011}{{Wang}}{{}}} -\bibcite{5714480}{{34}{2010}{{Xing, Li, and Wang}}{{}}} -\bibcite{xu2001geography}{{35}{2001}{{Xu, Heidemann, and Estrin}}{{}}} -\bibcite{yan2008design}{{36}{2008}{{Yan et~al.}}{{Yan, Gu, He, and Stankovic}}} -\bibcite{yang2014novel}{{37}{2014{a}}{{Yang and Chin}}{{}}} -\bibcite{yangnovel}{{38}{2014{b}}{{Yang and Chin}}{{}}} -\bibcite{Yang2014}{{39}{2014}{{Yang and Liu}}{{}}} -\bibcite{yick2008wireless}{{40}{2008}{{Yick, Mukherjee, and Ghosal}}{{}}} -\bibcite{Zhang05}{{41}{2005}{{Zhang and Hou}}{{}}} -\bibcite{zhou2009variable}{{42}{2009}{{Zhou, Das, and Gupta}}{{}}} -\bibcite{zorbas2010solving}{{43}{2010}{{Zorbas et~al.}}{{Zorbas, Glynos, Kotzanikolaou, and Douligeris}}} +\bibcite{huang2005coverage}{{12}{2005}{{Huang and Tseng}}{{}}} +\bibcite{doi:10.1155/2010/926075}{{13}{2010}{{Hung and Lui}}{{}}} +\bibcite{idrees2014coverage}{{14}{2014}{{Idrees et~al.}}{{Idrees, Deschinkel, Salomon, and Couturier}}} +\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{ling2009energy}{{20}{2009}{{Ling and Znati}}{{}}} +\bibcite{glpk}{{21}{2012}{{Makhorin}}{{}}} +\bibcite{Misra}{{22}{2011}{{Misra, Kumar, and Obaidat}}{{}}} +\bibcite{pc10}{{23}{2010}{{Padmavathy and Chitra}}{{}}} +\bibcite{puccinelli2005wireless}{{24}{2005}{{Puccinelli and Haenggi}}{{}}} +\bibcite{pujari2011high}{{25}{2011}{{Pujari}}{{}}} +\bibcite{qu2013distributed}{{26}{2013}{{Qu and Georgakopoulos}}{{}}} +\bibcite{rault2014energy}{{27}{2014}{{Rault, Bouabdallah, and Challal}}{{}}} +\bibcite{doi:10.1080/0305215X.2012.687732}{{28}{2013}{{Singh, Rossi, and Sevaux}}{{}}} +\bibcite{varga}{{29}{2003}{{Varga}}{{}}} +\bibcite{ChinhVu}{{30}{2006}{{Vu et~al.}}{{Vu, Gao, Deshmukh, and Li}}} +\bibcite{chin2007}{{31}{2009}{{Vu}}{{}}} +\bibcite{wang2011coverage}{{32}{2011}{{Wang}}{{}}} +\bibcite{5714480}{{33}{2010}{{Xing, Li, and Wang}}{{}}} +\bibcite{xu2001geography}{{34}{2001}{{Xu, Heidemann, and Estrin}}{{}}} +\bibcite{yan2008design}{{35}{2008}{{Yan et~al.}}{{Yan, Gu, He, and Stankovic}}} +\bibcite{yang2014novel}{{36}{2014{a}}{{Yang and Chin}}{{}}} +\bibcite{yangnovel}{{37}{2014{b}}{{Yang and Chin}}{{}}} +\bibcite{Yang2014}{{38}{2014}{{Yang and Liu}}{{}}} +\bibcite{yick2008wireless}{{39}{2008}{{Yick, Mukherjee, and Ghosal}}{{}}} +\bibcite{Zhang05}{{40}{2005}{{Zhang and Hou}}{{}}} +\bibcite{zhou2009variable}{{41}{2009}{{Zhou, Das, and Gupta}}{{}}} +\bibcite{zorbas2010solving}{{42}{2010}{{Zorbas et~al.}}{{Zorbas, Glynos, Kotzanikolaou, and Douligeris}}} \endpage{19} \questionmark{} diff --git a/PeCO-EO/articleeo.bbl b/PeCO-EO/articleeo.bbl index c1025cc..dd24431 100644 --- a/PeCO-EO/articleeo.bbl +++ b/PeCO-EO/articleeo.bbl @@ -1,4 +1,4 @@ -\begin{thebibliography}{43} +\begin{thebibliography}{42} \newcommand{\enquote}[1]{``#1''} \providecommand{\natexlab}[1]{#1} \providecommand{\url}[1]{\normalfont{#1}} @@ -45,8 +45,8 @@ Casta{\~n}o, Fabian, Andr{\'e} Rossi, Marc Sevaux, and Nubia Velasco. 2014. ``A Research} 52 (B): 220--230. \bibitem[CPLEX(2010)]{iamigo:cplex} -CPLEX, Optimizer. 2010. ``{IBM ILOG CPLEX Optimizer}.'' \\url - {http://www-01.ibm.com/software/integration/optimization/cplex-optimizer/}. +CPLEX, Optimizer. 2010. ``IBM ILOG CPLEX Optimizer.'' \emph{Available: + http://www-01.ibm.com/software/integration/optimization/cplex-optimizer/} . \bibitem[Deng, Jiguo~Yu, and Chen(2012)]{Deng2012} Deng, Xiu, Dongxiao~Yu Jiguo~Yu, and Congcong Chen. 2012. ``Transforming Area @@ -69,15 +69,9 @@ He, Shibo, Xiaowen Gong, Junshan Zhang, Jiming Chen, and Youxian Sun. 2014. ``Curve-Based Deployment for Barrier Coverage in Wireless Sensor Networks.'' \emph{IEEE Transactions on Wireless Communications} 13 (2): 724--735. -\bibitem[Huang and Tseng(2005{\natexlab{a}})]{Huang:2003:CPW:941350.941367} -Huang, C.-F., and Y.-C. Tseng. 2005{\natexlab{a}}. ``The Coverage Problem in a - Wireless Sensor Network.'' \emph{Mobile Networks and Applications} 10 (4): - 519--528. - -\bibitem[Huang and Tseng(2005{\natexlab{b}})]{huang2005coverage} -Huang, Chi-Fu, and Yu-Chee Tseng. 2005{\natexlab{b}}. ``The coverage problem in - a wireless sensor network.'' \emph{Mobile Networks and Applications} 10 (4): - 519--528. +\bibitem[Huang and Tseng(2005)]{huang2005coverage} +Huang, Chi-Fu, and Yu-Chee Tseng. 2005. ``The coverage problem in a wireless + sensor network.'' \emph{Mobile Networks and Applications} 10 (4): 519--528. \bibitem[Hung and Lui(2010)]{doi:10.1155/2010/926075} Hung, Ka-Shun, and King-Shan Lui. 2010. ``Perimeter Coverage Scheduling in diff --git a/PeCO-EO/articleeo.blg b/PeCO-EO/articleeo.blg index 5632d0c..d9e03c9 100644 --- a/PeCO-EO/articleeo.blg +++ b/PeCO-EO/articleeo.blg @@ -4,44 +4,44 @@ The top-level auxiliary file: articleeo.aux The style file: gENO.bst Database file #1: biblio.bib Reallocated wiz_functions (elt_size=4) to 6000 items from 3000. -You've used 43 entries, +You've used 42 entries, 3679 wiz_defined-function locations, - 968 strings with 13582 characters, -and the built_in function-call counts, 30343 in all, are: -= -- 2486 -> -- 1565 + 963 strings with 13444 characters, +and the built_in function-call counts, 29694 in all, are: += -- 2431 +> -- 1533 < -- 4 -+ -- 763 -- -- 425 -* -- 2109 -:= -- 4427 -add.period$ -- 97 -call.type$ -- 43 -change.case$ -- 286 -chr.to.int$ -- 50 -cite$ -- 43 -duplicate$ -- 2296 -empty$ -- 2268 -format.name$ -- 532 -if$ -- 6219 -int.to.chr$ -- 3 ++ -- 747 +- -- 417 +* -- 2060 +:= -- 4333 +add.period$ -- 95 +call.type$ -- 42 +change.case$ -- 280 +chr.to.int$ -- 49 +cite$ -- 42 +duplicate$ -- 2249 +empty$ -- 2221 +format.name$ -- 521 +if$ -- 6088 +int.to.chr$ -- 2 int.to.str$ -- 1 -missing$ -- 408 -newline$ -- 140 -num.names$ -- 172 -pop$ -- 1212 +missing$ -- 400 +newline$ -- 137 +num.names$ -- 168 +pop$ -- 1189 preamble$ -- 1 -purify$ -- 284 +purify$ -- 278 quote$ -- 0 -skip$ -- 1072 +skip$ -- 1054 stack$ -- 0 -substring$ -- 1273 -swap$ -- 1060 +substring$ -- 1239 +swap$ -- 1034 text.length$ -- 2 text.prefix$ -- 0 top$ -- 0 -type$ -- 384 +type$ -- 375 warning$ -- 0 -while$ -- 238 +while$ -- 233 width$ -- 0 -write$ -- 480 +write$ -- 469 diff --git a/PeCO-EO/articleeo.log b/PeCO-EO/articleeo.log index f166833..60ac710 100644 --- a/PeCO-EO/articleeo.log +++ b/PeCO-EO/articleeo.log @@ -1,12 +1,11 @@ -This is pdfTeX, Version 3.1415926-2.4-1.40.13 (TeX Live 2012/Debian) (format=pdflatex 2013.9.3) 29 JUN 2015 10:00 +This is pdfTeX, Version 3.14159265-2.6-1.40.15 (TeX Live 2015/dev/Debian) (preloaded format=pdflatex 2015.1.24) 8 JUL 2015 15:36 entering extended mode restricted \write18 enabled. %&-line parsing enabled. **articleeo.tex (./articleeo.tex -LaTeX2e <2011/06/27> -Babel and hyphenation patterns for english, dumylang, nohyphenation, lo -aded. +LaTeX2e <2014/05/01> +Babel <3.9l> and hyphenation patterns for 61 languages loaded. 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Package epstopdf Info: Source file: -(epstopdf) date: 2015-02-20 10:11:12 +(epstopdf) date: 2015-02-20 10:20:43 (epstopdf) size: 358485 bytes (epstopdf) Output file: -(epstopdf) date: 2015-02-20 10:12:43 +(epstopdf) date: 2015-02-20 10:20:45 (epstopdf) size: 78307 bytes (epstopdf) Command: @@ -574,10 +563,10 @@ File: figure1a-eps-converted-to.pdf Graphic file (type pdf) Package pdftex.def Info: figure1a-eps-converted-to.pdf used on input line 268. (pdftex.def) Requested size: 213.39566pt x 202.1362pt. Package epstopdf Info: Source file: -(epstopdf) date: 2015-02-20 10:11:12 +(epstopdf) date: 2015-02-20 10:20:43 (epstopdf) size: 241675 bytes (epstopdf) Output file: -(epstopdf) date: 2015-02-20 10:12:44 +(epstopdf) date: 2015-02-20 10:20:46 (epstopdf) size: 57181 bytes (epstopdf) Command: @@ -640,10 +629,10 @@ Overfull \vbox (701.0pt too high) has occurred while \output is active [] [5 <./figure1a-eps-converted-to.pdf> <./figure1b-eps-converted-to.pdf>] Package epstopdf Info: Source file: -(epstopdf) date: 2015-02-20 10:11:12 +(epstopdf) date: 2015-02-20 10:20:43 (epstopdf) size: 508784 bytes (epstopdf) Output file: -(epstopdf) date: 2015-02-20 10:12:44 +(epstopdf) date: 2015-02-20 10:20:46 (epstopdf) size: 138861 bytes (epstopdf) Command: @@ -657,10 +646,10 @@ File: figure2-eps-converted-to.pdf Graphic file (type pdf) Package pdftex.def Info: figure2-eps-converted-to.pdf used on input line 311. (pdftex.def) Requested size: 398.99872pt x 200.66864pt. Package epstopdf Info: Source file: -(epstopdf) date: 2015-02-20 10:11:12 +(epstopdf) date: 2015-02-20 10:20:43 (epstopdf) size: 196938 bytes (epstopdf) Output file: -(epstopdf) date: 2015-02-20 10:12:45 +(epstopdf) date: 2015-02-20 10:20:47 (epstopdf) size: 48639 bytes (epstopdf) Command: @@ -703,10 +692,10 @@ Overfull \vbox (701.0pt too high) has occurred while \output is active [] [6 <./figure2-eps-converted-to.pdf>] Package epstopdf Info: Source file: -(epstopdf) date: 2015-02-20 10:11:12 +(epstopdf) date: 2015-02-20 10:20:43 (epstopdf) size: 428048 bytes (epstopdf) Output file: -(epstopdf) date: 2015-02-20 10:12:45 +(epstopdf) date: 2015-02-20 10:20:47 (epstopdf) size: 76496 bytes (epstopdf) Command: @@ -897,11 +886,11 @@ Overfull \vbox (701.0pt too high) has occurred while \output is active [] [12] Package epstopdf Info: Source file: -(epstopdf) date: 2015-02-06 11:42:02 +(epstopdf) date: 2015-02-20 10:16:57 (epstopdf) size: 29526 bytes (epstopdf) Output file: -(epstopdf) date: 2015-02-20 10:12:46 -(epstopdf) size: 12638 bytes +(epstopdf) date: 2015-02-20 10:17:32 +(epstopdf) size: 12679 bytes (epstopdf) Command: (epstopdf) \includegraphics on input line 821. @@ -939,11 +928,11 @@ Overfull \vbox (701.0pt too high) has occurred while \output is active [] [13 <./figure5-eps-converted-to.pdf>] Package epstopdf Info: Source file: -(epstopdf) date: 2015-02-06 11:42:02 +(epstopdf) date: 2015-02-20 10:16:57 (epstopdf) size: 29515 bytes (epstopdf) Output file: -(epstopdf) date: 2015-02-20 10:12:46 -(epstopdf) size: 12695 bytes +(epstopdf) date: 2015-02-20 10:17:32 +(epstopdf) size: 12739 bytes (epstopdf) Command: (epstopdf) \includegraphics on input line 840. @@ -956,11 +945,11 @@ File: figure6-eps-converted-to.pdf Graphic file (type pdf) Package pdftex.def Info: figure6-eps-converted-to.pdf used on input line 840. (pdftex.def) Requested size: 242.40503pt x 175.15395pt. Package epstopdf Info: Source file: -(epstopdf) date: 2015-02-06 11:42:02 +(epstopdf) date: 2015-02-20 10:16:57 (epstopdf) size: 24136 bytes (epstopdf) Output file: -(epstopdf) date: 2015-02-20 10:12:46 -(epstopdf) size: 8179 bytes +(epstopdf) date: 2015-02-20 10:17:32 +(epstopdf) size: 8217 bytes (epstopdf) Command: (epstopdf) \includegraphics on input line 864. @@ -973,11 +962,11 @@ File: figure7a-eps-converted-to.pdf Graphic file (type pdf) Package pdftex.def Info: figure7a-eps-converted-to.pdf used on input line 864. (pdftex.def) Requested size: 246.92189pt x 175.15395pt. Package epstopdf Info: Source file: -(epstopdf) date: 2015-02-06 11:42:02 +(epstopdf) date: 2015-02-20 10:16:57 (epstopdf) size: 24138 bytes (epstopdf) Output file: -(epstopdf) date: 2015-02-20 10:12:47 -(epstopdf) size: 8180 bytes +(epstopdf) date: 2015-02-20 10:17:33 +(epstopdf) size: 8218 bytes (epstopdf) Command: (epstopdf) \includegraphics on input line 865. @@ -994,11 +983,11 @@ Package pdftex.def Info: figure7b-eps-converted-to.pdf used on input line 865. LaTeX Warning: `!h' float specifier changed to `!ht'. Package epstopdf Info: Source file: -(epstopdf) date: 2015-02-06 11:42:03 +(epstopdf) date: 2015-02-20 10:16:57 (epstopdf) size: 24103 bytes (epstopdf) Output file: -(epstopdf) date: 2015-02-20 10:12:47 -(epstopdf) size: 8351 bytes +(epstopdf) date: 2015-02-20 10:17:33 +(epstopdf) size: 8390 bytes (epstopdf) Command: (epstopdf) \includegraphics on input line 888. @@ -1010,11 +999,11 @@ File: figure8a-eps-converted-to.pdf Graphic file (type pdf) Package pdftex.def Info: figure8a-eps-converted-to.pdf used on input line 888. (pdftex.def) Requested size: 246.92189pt x 175.15395pt. Package epstopdf Info: Source file: -(epstopdf) date: 2015-02-06 11:42:03 +(epstopdf) date: 2015-02-20 10:16:57 (epstopdf) size: 24855 bytes (epstopdf) Output file: -(epstopdf) date: 2015-02-20 10:12:47 -(epstopdf) size: 8466 bytes +(epstopdf) date: 2015-02-20 10:17:33 +(epstopdf) size: 8505 bytes (epstopdf) Command: (epstopdf) \includegraphics on input line 889. @@ -1056,11 +1045,11 @@ Overfull \vbox (701.0pt too high) has occurred while \output is active [] [14 <./figure6-eps-converted-to.pdf>] Package epstopdf Info: Source file: -(epstopdf) date: 2015-02-06 11:42:03 +(epstopdf) date: 2015-02-20 10:16:57 (epstopdf) size: 27000 bytes (epstopdf) Output file: -(epstopdf) date: 2015-02-20 10:12:48 -(epstopdf) size: 7927 bytes +(epstopdf) date: 2015-02-20 10:17:33 +(epstopdf) size: 7971 bytes (epstopdf) Command: (epstopdf) \includegraphics on input line 909. @@ -1080,9 +1069,6 @@ LaTeX Warning: `!h' float specifier changed to `!ht'. LaTeX Warning: `h' float specifier changed to `ht'. -Underfull \vbox (badness 4144) has occurred while \output is active [] - - Underfull \vbox (badness 10000) has occurred while \output is active [] @@ -1156,7 +1142,13 @@ Overfull \vbox (29.0pt too high) has occurred while \output is active [] Overfull \vbox (701.0pt too high) has occurred while \output is active [] [17] -Underfull \hbox (badness 4024) in paragraph at lines 130--132 +Underfull \hbox (badness 6658) in paragraph at lines 48--50 +[]\OT1/cmr/m/n/10 CPLEX, Op-ti-mizer. 2010. ``IBM ILOG CPLEX Op-ti-mizer.'' \OT +1/cmr/m/it/10 Avail-able: http://www- + [] + + +Underfull \hbox (badness 4024) in paragraph at lines 124--126 []\OT1/cmr/m/n/10 Makhorin, An-drew. 2012. ``The GLPK (GNU Lin-ear Pro-gram-min g Kit).'' \OT1/cmr/m/it/10 Avail-able: [] @@ -1192,7 +1184,7 @@ Overfull \vbox (701.0pt too high) has occurred while \output is active [] Missing character: There is no à in font cmr10! Missing character: There is no © in font cmr10! -Underfull \hbox (badness 10000) in paragraph at lines 171--173 +Underfull \hbox (badness 10000) in paragraph at lines 165--167 []\OT1/cmr/m/n/10 Varga, A. 2003. ``OM-NeT++ Dis-crete Event Sim-u-la-tion Sys- tem.'' \OT1/cmr/m/it/10 Avail-able: [] @@ -1232,13 +1224,13 @@ LaTeX Font Warning: Some font shapes were not available, defaults substituted. ) Here is how much of TeX's memory you used: - 4818 strings out of 495059 - 62762 string characters out of 3182031 - 149121 words of memory out of 3000000 - 7917 multiletter control sequences out of 15000+200000 - 14560 words of font info for 56 fonts, out of 3000000 for 9000 - 14 hyphenation exceptions out of 8191 - 41i,18n,27p,464b,369s stack positions out of 5000i,500n,10000p,200000b,50000s + 4822 strings out of 493221 + 62726 string characters out of 6141266 + 154108 words of memory out of 5000000 + 8172 multiletter control sequences out of 15000+600000 + 14560 words of font info for 56 fonts, out of 8000000 for 9000 + 1119 hyphenation exceptions out of 8191 + 41i,18n,27p,464b,369s stack positions out of 5000i,500n,10000p,200000b,80000s -Output written on articleeo.pdf (19 pages, 746415 bytes). +Output written on articleeo.pdf (19 pages, 746329 bytes). 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b/PeCO-EO/articleeo.tex index 9676c99..1236ff0 100644 --- a/PeCO-EO/articleeo.tex +++ b/PeCO-EO/articleeo.tex @@ -15,7 +15,7 @@ \title{{\itshape Perimeter-based Coverage Optimization \\ to Improve Lifetime in Wireless Sensor Networks}} -\author{Ali Kadhum Idrees$^{a,b}$, Karine Deschinkel$^{a}$$^{\ast}$\thanks{$^\ast$Corresponding author. Email: karine.deschinkel@univ-fcomte.fr}, Michel Salomon$^{a}$ and Rapha\"el Couturier $^{a}$ +\author{Ali Kadhum Idrees$^{a,b}$, Karine Deschinkel$^{a}$$^{\ast}$\thanks{$^\ast$Corresponding author. Email: karine.deschinkel@univ-fcomte.fr}, Michel Salomon$^{a}$, and Rapha\"el Couturier $^{a}$ $^{a}${\em{FEMTO-ST Institute, UMR 6174 CNRS, \\ University Bourgogne Franche-Comt\'e, Belfort, France}} \\ $^{b}${\em{Department of Computer Science, University of Babylon, Babylon, Iraq}} @@ -48,14 +48,14 @@ coverage for WSNs compared to other protocols. \label{sec:introduction} The continuous progress in Micro Electro-Mechanical Systems (MEMS) and wireless -communication hardware has given rise to the opportunity of using large networks +communication hardware has given rise to the opportunity of using large networks of tiny sensors, called Wireless Sensor Networks (WSN)~\citep{akyildiz2002wireless,puccinelli2005wireless}, to fulfill monitoring tasks. A WSN consists of small low-powered sensors working together by communicating with one another through multi-hop radio communications. Each node can send the data it collects in its environment, thanks to its sensor, to the -user by means of sink nodes. The features of a WSN makes it suitable for a wide -range of applications in areas such as business, environment, health, industry, +user by means of sink nodes. The features of a WSN makes it suitable for a wide +range of applications in areas such as business, environment, health, industry, military, and so on~\citep{yick2008wireless}. Typically, a sensor node contains three main components~\citep{anastasi2009energy}: a sensing unit able to measure physical, chemical, or biological phenomena observed in the environment; a @@ -65,13 +65,13 @@ communication unit for data transmission and reception. The energy needed by an active sensor node to perform sensing, processing, and communication is provided by a power supply which is a battery. This battery has a limited energy provision and it may be unsuitable or impossible to replace or -recharge in most applications. Therefore it is necessary to deploy WSN with -high density in order to increase reliability and to exploit node redundancy -thanks to energy-efficient activity scheduling approaches. Indeed, the overlap -of sensing areas can be exploited to schedule alternatively some sensors in a -low power sleep mode and thus save energy. Overall, the main question that must -be answered is: how is it possible to extend the lifetime coverage of a WSN as long as possible -while ensuring a high level of coverage? These past few years many +recharge in most applications. Therefore it is necessary to deploy WSN with high +density in order to increase reliability and to exploit node redundancy thanks +to energy-efficient activity scheduling approaches. Indeed, the overlap of +sensing areas can be exploited to schedule alternatively some sensors in a low +power sleep mode and thus save energy. Overall, the main question that must be +answered is: how is it possible to extend the lifetime coverage of a WSN as long +as possible while ensuring a high level of coverage? These past few years many energy-efficient mechanisms have been suggested to retain energy and extend the lifetime of the WSNs~\citep{rault2014energy}. @@ -88,13 +88,13 @@ This paper makes the following contributions : architecture. \item A new mathematical optimization model is proposed. Instead of trying to cover a set of specified points/targets as in most of the methods proposed in - the literature, we formulate a mixed-integer program based on the perimeter coverage of - each sensor. The model involves integer variables to capture the deviations - between the actual level of coverage and the required level. Hence, an - optimal schedule will be obtained by minimizing a weighted sum of these - deviations. + the literature, we formulate a mixed-integer program based on the perimeter + coverage of each sensor. The model involves integer variables to capture the + deviations between the actual level of coverage and the required level. + Hence, an optimal schedule will be obtained by minimizing a weighted sum of + these deviations. \item Extensive simulation experiments are conducted using the discrete event - simulator OMNeT++, to demonstrate the efficiency of our protocol. We have + simulator OMNeT++, to demonstrate the efficiency of our protocol. We have compared the PeCO protocol to two approaches found in the literature: DESK~\citep{ChinhVu} and GAF~\citep{xu2001geography}, and also to our previous protocol DiLCO published in~\citep{Idrees2}. DiLCO uses the same framework as @@ -125,12 +125,12 @@ to the objective of coverage for a finite number of discrete points called targets, and barrier coverage~\citep{HeShibo,kim2013maximum} focuses on preventing intruders from entering into the region of interest. In \citep{Deng2012} authors transform the area coverage problem into the target -coverage one, taking into account the intersection points among disks of sensors -nodes or between disks of sensor nodes and boundaries. In -\citep{Huang:2003:CPW:941350.941367} authors prove that if the perimeters of the -sensors are sufficiently covered it will be the case for the whole area. They -provide an algorithm in $O(nd~log~d)$ time to compute the perimeter-coverage of -each sensor. $d$ denotes the maximum number of sensors that are neighbors to a +coverage one, taking into account the intersection points among disks of sensors +nodes or between disks of sensor nodes and boundaries. In +\citep{huang2005coverage} authors prove that if the perimeters of the sensors +are sufficiently covered it will be the case for the whole area. They provide an +algorithm in $O(nd~log~d)$ time to compute the perimeter-coverage of each +sensor. $d$ denotes the maximum number of sensors that are neighbors to a sensor, and $n$ is the total number of sensors in the network. {\it In PeCO protocol, instead of determining the level of coverage of a set of discrete points, our optimization model is based on checking the perimeter-coverage of @@ -162,22 +162,22 @@ algorithms~\citep{ChinhVu,qu2013distributed,yangnovel} each sensor decides of its own activity scheduling after an information exchange with its neighbors. The main interest of such an approach is to avoid long range communications and thus to reduce the energy dedicated to the communications. Unfortunately, since -each node has information on its immediate neighbors only (usually the one-hop -ones), it may make a bad decision leading to a global suboptimal solution. +each node has information on its immediate neighbors only (usually the one-hop +ones), it may make a bad decision leading to a global suboptimal solution. Conversely, centralized algorithms~\citep{cardei2005improving,zorbas2010solving,pujari2011high} always -provide nearly optimal solutions since the algorithm has a global -view of the whole network. The disadvantage of a centralized method is obviously -its high cost in communications needed to transmit to a single node, the base -station which will globally schedule nodes' activities, data from all the other -sensor nodes in the area. The price in communications can be huge since long -range communications will be needed. In fact the larger the WSN, the higher the +provide nearly optimal solutions since the algorithm has a global view of the +whole network. The disadvantage of a centralized method is obviously its high +cost in communications needed to transmit to a single node, the base station +which will globally schedule nodes' activities, data from all the other sensor +nodes in the area. The price in communications can be huge since long range +communications will be needed. In fact the larger the WSN, the higher the communication energy cost. {\it In order to be suitable for large-scale - networks, in the PeCO protocol the area of interest is divided into several + networks, in the PeCO protocol the area of interest is divided into several smaller subregions, and in each one, a node called the leader is in charge of - selecting the active sensors for the current period. Thus the PeCO protocol is - scalable and a globally distributed method, whereas it is centralized in each - subregion.} + selecting the active sensors for the current period. Thus the PeCO protocol + is scalable and a globally distributed method, whereas it is centralized in + each subregion.} Various coverage scheduling algorithms have been developed these past few years. Many of them, dealing with the maximization of the number of cover sets, are @@ -202,20 +202,20 @@ The authors in \citep{Idrees2} propose a Distributed Lifetime Coverage Optimization (DiLCO) protocol, which maintains the coverage and improves the lifetime in WSNs. It is an improved version of a research work presented in~\citep{idrees2014coverage}. First, the area of interest is partitioned into -subregions using a divide-and-conquer method. The DiLCO protocol is then distributed -on the sensor nodes in each subregion in a second step. Hence this protocol -combines two techniques: a leader election in each subregion, followed by an -optimization-based node activity scheduling performed by each elected +subregions using a divide-and-conquer method. The DiLCO protocol is then +distributed on the sensor nodes in each subregion in a second step. Hence this +protocol combines two techniques: a leader election in each subregion, followed +by an optimization-based node activity scheduling performed by each elected leader. The proposed DiLCO protocol is a periodic protocol where each period is decomposed into 4 phases: information exchange, leader election, decision, and sensing. The simulations show that DiLCO is able to increase the WSN lifetime and provides improved coverage performance. {\it In the PeCO protocol, a new mathematical optimization model is proposed. Instead of trying to cover a set - of specified points/targets as in the DiLCO protocol, we formulate an integer - program based on the perimeter coverage of each sensor. The model involves integer - variables to capture the deviations between the actual level of coverage and - the required level. The idea is that an optimal scheduling will be obtained by - minimizing a weighted sum of these deviations.} + of specified points/targets as in the DiLCO protocol, we formulate an integer + program based on the perimeter coverage of each sensor. The model involves + integer variables to capture the deviations between the actual level of + coverage and the required level. The idea is that an optimal scheduling will + be obtained by minimizing a weighted sum of these deviations.} \section{ The P{\scshape e}CO Protocol Description} \label{sec:The PeCO Protocol Description} @@ -741,14 +741,14 @@ approach. \subsection{Simulation Results} In order to assess and analyze the performance of our protocol we have -implemented the PeCO protocol in OMNeT++~\citep{varga} simulator. The simulations -were run on a DELL laptop with an Intel Core~i3~2370~M (1.8~GHz) processor (2 -cores) whose MIPS (Million Instructions Per Second) rate is equal to 35330. To -be consistent with the use of a sensor node based on Atmels AVR ATmega103L -microcontroller (6~MHz) having a MIPS rate equal to 6, the original execution -time on the laptop is multiplied by 2944.2 $\left(\frac{35330}{2} \times -\frac{1}{6} \right)$. Energy consumption is calculated according to the power -consumption values, in milliWatt per second, given in Table~\ref{tab:EC}. +implemented the PeCO protocol in OMNeT++~\citep{varga} simulator. The +simulations were run on a DELL laptop with an Intel Core~i3~2370~M (1.8~GHz) +processor (2 cores) whose MIPS (Million Instructions Per Second) rate is equal +to 35330. To be consistent with the use of a sensor node based on Atmels AVR +ATmega103L microcontroller (6~MHz) having a MIPS rate equal to 6, the original +execution time on the laptop is multiplied by 2944.2 $\left(\frac{35330}{2} +\times \frac{1}{6} \right)$. Energy consumption is calculated according to the +power consumption values, in milliWatt per second, given in Table~\ref{tab:EC}, based on the energy model proposed in \citep{ChinhVu}. \begin{table}[h] @@ -780,7 +780,7 @@ consuming and more efficient, or implement a lightweight heuristic. For example, for a WSN of 200 sensor nodes, a leader node has to deal with constraints induced by about 12 sensor nodes. In that case, to solve the optimization problem a memory consumption of more than 1~MB can be observed with GLPK, -whereas less than 300~kB would be needed with CPLEX. +whereas less than 300~KB would be needed with CPLEX. Besides PeCO, three other protocols will be evaluated for comparison purposes. The first one, called DESK, is a fully distributed coverage algorithm @@ -789,17 +789,17 @@ GAF~\citep{xu2001geography}, consists in dividing the monitoring area into fixed squares. Then, during the decision phase, in each square, one sensor is chosen to remain active during the sensing phase. The last one, the DiLCO protocol~\citep{Idrees2}, is an improved version of a research work we presented -in~\citep{idrees2014coverage}. Let us notice that the PeCO and DiLCO protocols are -based on the same framework. In particular, the choice for the simulations of a -partitioning in 16~subregions was made because it corresponds to the +in~\citep{idrees2014coverage}. Let us notice that the PeCO and DiLCO protocols +are based on the same framework. In particular, the choice for the simulations +of a partitioning in 16~subregions was made because it corresponds to the configuration producing the best results for DiLCO. Of course, this number of -subregions should be adapted according to the size of the area of interest and +subregions should be adapted according to the size of the area of interest and the number of sensors. The protocols are distinguished from one another by the formulation of the integer program providing the set of sensors which have to be -activated in each sensing phase. The DiLCO protocol tries to satisfy the coverage of -a set of primary points, whereas the objective of the PeCO protocol is to reach a desired -level of coverage for each sensor perimeter. In our experimentations, we chose a -level of coverage equal to one ($l=1$). +activated in each sensing phase. The DiLCO protocol tries to satisfy the +coverage of a set of primary points, whereas the objective of the PeCO protocol +is to reach a desired level of coverage for each sensor perimeter. In our +experimentations, we chose a level of coverage equal to one ($l=1$). \subsubsection{Coverage Ratio} @@ -807,9 +807,9 @@ Figure~\ref{figure5} shows the average coverage ratio for 200 deployed nodes obtained with the four protocols. DESK, GAF, and DiLCO provide a slightly better coverage ratio with respectively 99.99\%, 99.91\%, and 99.02\%, compared to the 98.76\% produced by PeCO for the first periods. This is due to the fact that at -the beginning the DiLCO and PeCO protocols put more redundant -sensors to sleep status (which slightly decreases the coverage ratio), while the two other -protocols activate more sensor nodes. Later, when the number of periods is +the beginning the DiLCO and PeCO protocols put more redundant sensors to sleep +status (which slightly decreases the coverage ratio), while the two other +protocols activate more sensor nodes. Later, when the number of periods is beyond~70, it clearly appears that PeCO provides a better coverage ratio and keeps a coverage ratio greater than 50\% for longer periods (15 more compared to DiLCO, 40 more compared to DESK). The energy saved by PeCO in the early periods @@ -848,7 +848,7 @@ The effect of the energy consumed by the WSN during the communication, computation, listening, active, and sleep status is studied for different network densities and the four approaches compared. Figures~\ref{figure7}(a) and (b) illustrate the energy consumption for different network sizes and for -$Lifetime95$ and $Lifetime50$. The results show that the PeCO protocol is the most +$Lifetime_{95}$ and $Lifetime_{50}$. The results show that the PeCO protocol is the most competitive from the energy consumption point of view. As shown by both figures, PeCO consumes much less energy than the other methods. One might think that the resolution of the integer program is too costly in energy, but the results show @@ -872,7 +872,7 @@ size is the lowest with PeCO. We observe the superiority of both the PeCO and DiLCO protocols in comparison with the two other approaches in prolonging the network lifetime. In -Figures~\ref{figure8}(a) and (b), $Lifetime95$ and $Lifetime50$ are shown for +Figures~\ref{figure8}(a) and (b), $Lifetime_{95}$ and $Lifetime_{50}$ are shown for different network sizes. As can be seen in these figures, the lifetime increases with the size of the network, and it is clearly larger for the DiLCO and PeCO protocols. For instance, for a network of 300~sensors and coverage ratio @@ -916,17 +916,17 @@ sizes. Table~\ref{my-labelx} shows network lifetime results for different values of $\alpha$ and $\beta$, and a network size equal to 200 sensor nodes. On the one -hand, the choice of $\beta \gg \alpha$ prevents the overcoverage, and also limits -the activation of a large number of sensors, but as $\alpha$ is low, some areas -may be poorly covered. This explains the results obtained for {\it Lifetime50} -with $\beta \gg \alpha$: a large number of periods with low coverage ratio. On -the other hand, when we choose $\alpha \gg \beta$, we favor the coverage even if -some areas may be overcovered, so ahigh coverage ratio is reached, but a large -number of sensors are activated to achieve this goal. Therefore the network -lifetime is reduced. The choice $\alpha=0.6$ and $\beta=0.4$ 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. +hand, the choice of $\beta \gg \alpha$ prevents the overcoverage, and also +limits the activation of a large number of sensors, but as $\alpha$ is low, some +areas may be poorly covered. This explains the results obtained for +$Lifetime_{50}$ with $\beta \gg \alpha$: a large number of periods with low +coverage ratio. On the other hand, when we choose $\alpha \gg \beta$, we favor +the coverage even if some areas may be overcovered, so a high coverage ratio is +reached, but a large number of sensors are activated to achieve this goal. +Therefore the network lifetime is reduced. The choice $\alpha=0.6$ and +$\beta=0.4$ 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 $Lifetime_{95}$. @@ -973,18 +973,17 @@ lifetime, coverage ratio, active sensors ratio, and energy consumption. We plan to extend our framework so that the schedules are planned for multiple sensing periods. We also want to improve the integer program to take into account heterogeneous sensors from both energy and node characteristics point of -views. Finally, it would be interesting to implement the PeCO protocol using a +views. Finally, it would be interesting to implement the PeCO protocol using a sensor-testbed to evaluate it in real world applications. - -\subsection*{Acknowledgements} +\subsection*{Acknowledgments} The authors are deeply grateful to the anonymous reviewers for their constructive advice, which improved the technical quality of the paper. As a -Ph.D. student, Ali Kadhum IDREES would like to gratefully acknowledge the +Ph.D. student, Ali Kadhum Idrees would like to gratefully acknowledge the University of Babylon - Iraq for financial support and Campus France for the received support. This work is also partially funded by the Labex ACTION program -(contract ANR-11-LABX-01-01). - +(contract ANR-11-LABX-01-01). + \bibliographystyle{gENO} \bibliography{biblio} %articleeo diff --git a/PeCO-EO/biblio.bib b/PeCO-EO/biblio.bib index 1b5b487..880b361 100644 --- a/PeCO-EO/biblio.bib +++ b/PeCO-EO/biblio.bib @@ -1,8 +1,8 @@ -@misc{iamigo:cplex, +@article{iamigo:cplex, author = {Optimizer CPLEX}, - howpublished = {\\url {http://www-01.ibm.com/software/integration/optimization/cplex-optimizer/}}, - title = {{IBM ILOG CPLEX Optimizer}}, + title = {IBM ILOG CPLEX Optimizer}, + journal = {Available: http://www-01.ibm.com/software/integration/optimization/cplex-optimizer/}, year = {2010} } diff --git a/PeCO-EO/reponse.tex b/PeCO-EO/reponse.tex index 1fb3f07..f35e844 100644 --- a/PeCO-EO/reponse.tex +++ b/PeCO-EO/reponse.tex @@ -19,7 +19,7 @@ \today \end{flushright}% -\vspace{-0.5cm}\hspace{-2cm}FEMTO-ST Institute, UMR 6714 CNRS +\vspace{-0.5cm}\hspace{-2cm}FEMTO-ST Institute, UMR 6174 CNRS \hspace{-2cm}University Bourgogne Franche-Comt\'e @@ -33,7 +33,7 @@ Detailed changes and addressed issues in the revision of the article ``Perimeter-based Coverage Optimization \\ to Improve Lifetime in Wireless Sensor Networks''\\ -by Ali Kadhum Idrees, Karine Deschinkel, Michel Salomon, and Raph\"ael Couturier +by Ali Kadhum Idrees, Karine Deschinkel, Michel Salomon and Raph\"ael Couturier \medskip @@ -86,9 +86,9 @@ application of these methods for the coverage scheduling problem.\\ assumption made on the selection criteria for the leader seems too vague. \\ \textcolor{blue}{\textbf{\textsc{Answer:} The selection criteria for the leader - inside each subregion is explained page~9, at the end of Section~3.3 - After the information exchange among the sensor nodes in the subregion, each - node will have all the information needed to decide if it will be the leader or + inside each subregion is explained page~9, at the end of Section~3.3. After + the information exchange among the sensor nodes in the subregion, each node + will have all the information needed to decide if it will be the leader or not. The decision is based on selecting the sensor node that has the larger number of one-hop neighbors. If this value is the same for many sensors, the node that has the largest remaining energy will be selected as a leader. If @@ -103,7 +103,7 @@ cooperate and make these decisions was not discussed.\\ \textcolor{blue}{\textbf{\textsc{Answer:} The communication and information sharing required to cooperate and make these decisions is discussed at the - end of page 8. Position coordinates, remaining energy, sensor node ID and + end of page 8. Position coordinates, remaining energy, sensor node ID, and number of one-hop neighbors are exchanged.}}\\ \noindent {\bf 4.} The definitions of the undercoverage and overcoverage @@ -140,22 +140,22 @@ results showing how the algorithm performs with different alphas and betas.\\ 200~sensor nodes. It explains the value chosen for the simulation settings in Table~2. \\ \indent The choice of alpha and beta should be made according to the needs of the application. Alpha should be large enough to prevent - undercoverage and thus to reach the highest possible coverage ratio. Beta - should be enough large to prevent overcoverage and thus to activate a minimum - number of sensors. The values of $\alpha_{i}^{j}$ can be identical for all - coverage intervals $i$ of one sensor $j$ in order to express that the - perimeter of each sensor should be uniformly covered, but $\alpha_{i}^{j}$ - values can be differentiated between sensors to force some regions to be - better covered than others. The choice of $\beta \gg \alpha$ prevents the - overcoverage, and so limit the activation of a large number of sensors, but - as $\alpha$ is low, some areas may be poorly covered. This explains the - results obtained for $Lifetime_{50}$ with $\beta \gg \alpha$: a large number - of periods with low coverage ratio. With $\alpha \gg \beta$, we favor the - coverage even if some areas may be overcovered, so a high coverage ratio is - reached, but a large number of sensors are activated to achieve this goal. - Therefore the network lifetime is reduced. The choice $\alpha=0.6$ and - $\beta=0.4$ seems to achieve the best compromise between lifetime and - coverage ratio.}}\\ + undercoverage and thus to reach the highest possible coverage ratio. Beta + should be large enough to prevent overcoverage and thus to activate a + minimum number of sensors. The values of $\alpha_{i}^{j}$ can be identical + for all coverage intervals $i$ of one sensor $j$ in order to express that + the perimeter of each sensor should be uniformly covered, but + $\alpha_{i}^{j}$ values can be differentiated between sensors to force some + regions to be better covered than others. The choice of $\beta \gg \alpha$ + prevents the overcoverage, and so limit the activation of a large number of + sensors, but as $\alpha$ is low, some areas may be poorly covered. This + explains the results obtained for $Lifetime_{50}$ with $\beta \gg \alpha$: a + large number of periods with low coverage ratio. With $\alpha \gg \beta$, + we favor the coverage even if some areas may be overcovered, so a high + coverage ratio is reached, but a large number of sensors are activated to + achieve this goal. Therefore the network lifetime is reduced. The choice + $\alpha=0.6$ and $\beta=0.4$ seems to achieve the best compromise between + lifetime and coverage ratio.}}\\ \noindent {\bf 6.} The authors have performed a thorough review of existing coverage methodologies. However, the clarity in the literature review is a @@ -166,10 +166,12 @@ suggest using the journals template to adjust them for overall consistency.\\ \textcolor{blue}{\textbf{\textsc{Answer:} References have been carefully checked and seem to be consistent with the journal template. In Section~2, ``Related literature'', we refer to papers dealing with coverage and lifetime in - WSN. Each paragraph of this Section discusses the literature related to a + WSN. Each paragraph of this section discusses the literature related to a particular aspect of the problem : 1. types of coverage, 2. types of scheme, 3. centralized versus distributed protocols, 4. optimization method. At the - end of each paragraph we position our approach. We have also added a last paragraph about our previous work on DilCO protocol to explain the difference with PeCO. }}\\ + end of each paragraph we position our approach. We have also added a last + paragraph about our previous work on DiLCO protocol to explain the + difference with PeCO. }}\\ \noindent {\bf 7.} The methodology is implemented in OMNeT++ (network simulator) and tested against 2 existing algorithms and a previously developed method by @@ -208,12 +210,12 @@ coverage ratio. \\ every Section is indented in the new version. }}\\ \noindent {\ding{90} You seem to be writing in the first person. I suggest - rewriting sentences that include “we” “our” or “I” in the third person. (There + rewriting sentences that include ``we'' ``our'' or ``I'' in the third person. (There are too many instances to list them all. They are easily found using the find tool.) } \\ \textcolor{blue}{\textbf{\textsc{Answer:} It is very common to find sentences - with "we" and "our" in scientific papers to explain the work made by the + with ``we'' and ``our'' in scientific papers to explain the work made by the authors. Nevertheless we agree with the reviewer and we reformulated some sentences in the paper to avoid too many uses of the first person. }}\\ @@ -224,19 +226,19 @@ coverage ratio. \\ \noindent {\ding{90} Add an “and” after the comma on page 3 line 34.} \\ -\textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed }}\\ +\textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed.}}\\ \noindent {\ding{90} “model as” instead of “Than” on page 10 line 12.} \\ -\textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed }}\\ +\textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed.}}\\ \noindent {\ding{90} “no longer” instead of “no more” on page 10 line 31.} \\ -\textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed }}\\ +\textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed.}}\\ \noindent {\ding{90} “in the active state” add the on page 10 line 34. } \\ -\textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed }}\\ +\textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed.}}\\ \noindent { \ding{90} Lots of English and grammar mistakes. I recommend rereading the paper line by line and adjusting the sentences that do not make @@ -279,16 +281,16 @@ how should this common duration should be chosen?\\ between any pairs of sensors inside a subregion is less than or equal to~3. Concerning the choice of the sensing period duration, it is correlated with the types of applications, with the amount of initial energy in sensors - batteries and also with the duration of the exchange phase. All applications - do not have the same Quality of Service requirements. In our case, - information exchange is executed every hour, but the length of the sensing - period could be reduced and adapted dynamically. On the one hand, a small - sensing period would allow the network to be more reliable but would have higher - communication costs. On the other hand, the choice of a long duration may - cause problems in case of nodes failure during the sensing period. - Several explanations on these points are given throughout the paper. In - particular, we discuss the number of subregions in Section 5.2 and the - sensing duration in the second paragraph of Section 5.1.}}\\ + batteries, and also with the duration of the exchange phase. All + applications do not have the same Quality of Service requirements. In our + case, information exchange is executed every hour, but the length of the + sensing period could be reduced and adapted dynamically. On the one hand, a + small sensing period would allow the network to be more reliable but would + have higher communication costs. On the other hand, the choice of a long + duration may cause problems in case of nodes failure during the sensing + period. Several explanations on these points are given throughout the + paper. In particular, we discuss the number of subregions in Section 5.2 and + the sensing duration in the second paragraph of Section 5.1.}}\\ \noindent {\bf 2.}Page 9, Section 4, is the Perimeter-based coverage problem NP-hard? This question is important for justifying the use of a Mixed Integer @@ -296,13 +298,13 @@ Linear Programming model.\\ \textcolor{blue}{\textbf{\textsc{Answer:} The perimeter scheduling coverage problem is NP-hard in general, it has been proved in the paper entitled - "Perimeter Coverage Scheduling in Wireless Sensor Networks Using Sensors - with a Single Continuous Cover Range" from Ka-Shun Hung and King-Shan Lui + ``Perimeter Coverage Scheduling in Wireless Sensor Networks Using Sensors + with a Single Continuous Cover Range'' from Ka-Shun Hung and King-Shan Lui (EURASIP Journal on Wireless Communications and Networking 2010, 2010:926075 doi:10.1155/2010/926075). In this paper, authors study the coverage of the perimeter of a large object requiring to be monitored. In our study, the large object to be monitored is the sensor itself (or more precisely its - sensing area). This point has been highlighted at the beginning of + sensing area). This point has been highlighted at the beginning of Section~4.}}\\ \noindent {\bf 3.} Page 9, the major problem with the present paper is, in my @@ -318,10 +320,11 @@ performance metrics list given in Section 5.1 is exhaustive, then the authors should mention at the beginning of the paper what are the aims of the protocol, and explain how the protocol is built to optimize these objectives. \\ -\textcolor{blue}{\textbf{\textsc{Answer:} Right. The mixed Integer Linear +\textcolor{blue}{\textbf{\textsc{Answer:} Right. The Mixed Integer Linear Program adresses a multiobjective problem, where the goal is to minimize - overcoverage and undercoverage for each coverage interval of a sensor. To the best of our knowledge, representing the objective function as a weighted sum of - criteria to be minimized in case of multicriteria optimization is a + overcoverage and undercoverage for each coverage interval of a sensor. To + the best of our knowledge, representing the objective function as a weighted + sum of criteria to be minimized in case of multicriteria optimization is a classical method. In Section 5, the comparison of protocols with a large variety of performance metrics allows to select the most appropriate method according to the QoS requirement of the application.}}\\ @@ -376,25 +379,24 @@ constraints. Total number & S & I & GLPK IP & GLPK LP & nodes&CPLEX\\ of nodes &&&&relaxation &B\&B tree &\\ \hline -100 & 6.25& 5&0.2 MB & 0.2 Mb &1 & 64 kB\\ +100 & 6.25& 5&0.2 MB & 0.2 MB &1 & 64 KB\\ \hline -200 & 12.5& 11&1.7 MB & 1.6 Mb &1 & 281 kB\\ +200 & 12.5& 11&1.7 MB & 1.6 MB &1 & 281 KB\\ \hline -300 &18.5 & 17&3.6 MB & 3.5 Mb & 3 &644 kB\\ +300 &18.5 & 17&3.6 MB & 3.5 MB & 3 &644 KB\\ \hline \end{tabular} -\medskip \\ -It is noteworthy that the difference of memory used with GLPK between the -resolution of the IP and its LP-relaxation is very weak (not more than 0.1 -MB). The size of the branch and bound tree does not exceed 3 nodes. This result -leads one to believe that the memory use with CPLEX\textregistered for solving -the IP would be very close to that for the LP-relaxation, that is to say around -100 Kb for a subregion containing $S=10$ sensors. Moreover the IP seems to have -some specifities that encourage us to develop our own solver (coefficents matrix -is very sparse) or to use an existing heuristic to find good approximate -solutions (Reference : ``A feasibility pump heuristic for general mixed-integer -problems", Livio Bertacco and Matteo Fischetti and Andrea Lodi, Discrete -Optimization, issn 1572-5286). +\medskip \\ It is noteworthy that the difference of memory used with GLPK +between the resolution of the IP and its LP-relaxation is very weak (not more +than 0.1 MB). The size of the branch and bound tree does not exceed 3 +nodes. This result leads one to believe that the memory use with +CPLEX\textregistered for solving the IP would be very close to that for the +LP-relaxation, that is to say less than 300 KB for a subregion containing $S=12$ +sensors. Moreover the IP seems to have some specifities that encourage us to +develop our own solver (coefficents matrix is very sparse) or to use an existing +heuristic to find good approximate solutions (Reference : ``A feasibility pump +heuristic for general mixed-integer problems", Livio Bertacco and Matteo +Fischetti and Andrea Lodi, Discrete Optimization, issn 1572-5286). \item the subdivision of the region of interest. To make the resolution of integer programming tractable by a leader sensor, we need to limit the number of nodes in each subregion (the number of variables and constraints of the @@ -448,36 +450,36 @@ A discussion about memory consumption has been added in Section 5.2}} \noindent {\ding{90} Page 5, lines 34 and 37, replace [0, $2\pi$] with [0, $2\pi$) } \\ -\textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed }}.\\ +\textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed.}}\\ \noindent {\ding{90} Page 5, line 36 and 43, replace ``figure 2" with ``Figure 2" } \\ -\textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed }}.\\ +\textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed.}}\\ \noindent {\ding{90} Page 5, line 50, replace ``section 4" with ``Section 4" } \\ -\textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed }}.\\ +\textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed.}}\\ \noindent {\ding{90} Page 5, line 51, replace ``figure 3" with ``Figure 3"} \\ -\textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed }}.\\ +\textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed.}}\\ \noindent {\ding{90} Page 7, line 20 ``regular homogeneous subregions" is too vague. } \\ \textcolor{blue}{\textbf{\textsc{Answer:} As mentioned in the previous remark, the spatial subdivision was not clearly explained in the paper. We added a discussion about this question in the article. Thank you for highlighting - it. }}.\\ + it. }}\\ \noindent {\ding{90} Page 7, line 24, replace ``figure 4" with ``Figure 4"} \\ -\textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed }}.\\ +\textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed.}}\\ \noindent {\ding{90} Page 7, line 47, replace ``Five status" with ``Five statuses" } \\ -\textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed }}.\\ +\textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed.}}\\ \noindent {\ding{90} Page 9, the constraints of the Mixed Integer Linear Program (2) are not numbered. There are two inequalities for overcoverage and @@ -500,7 +502,7 @@ A discussion about memory consumption has been added in Section 5.2}} connected". In order to assess this, the communication range should be known, but it is not given in Table 2. } \\ -\textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed}}.\\ +\textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed.}}\\ \noindent {\ding{90} Page 10, line 53, the ``Coverage ratio" definition is provided for a given period p? Then in the formula on top of page 11, N is set @@ -516,12 +518,12 @@ A discussion about memory consumption has been added in Section 5.2}} \noindent {\ding{90} Page 11, line 17 in the formula of ASR, |S| should be replaced with J (where J is defined page 4 line 16). } \\ -\textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed }}.\\ +\textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed.}}\\ \noindent {\ding{90} Page 13, line 41 and 43, replace ``figure 8" with ``Figure 8" } \\ -\textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed }}.\\ +\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. -- 2.39.5