diff --git a/2019-CloudCom.aux b/2019-CloudCom.aux new file mode 100644 index 0000000..1c0fdc9 --- /dev/null +++ b/2019-CloudCom.aux @@ -0,0 +1,170 @@ +\relax +\providecommand\hyper@newdestlabel[2]{} +\providecommand\HyperFirstAtBeginDocument{\AtBeginDocument} +\HyperFirstAtBeginDocument{\ifx\hyper@anchor\@undefined +\global\let\oldcontentsline\contentsline +\gdef\contentsline#1#2#3#4{\oldcontentsline{#1}{#2}{#3}} +\global\let\oldnewlabel\newlabel +\gdef\newlabel#1#2{\newlabelxx{#1}#2} +\gdef\newlabelxx#1#2#3#4#5#6{\oldnewlabel{#1}{{#2}{#3}}} +\AtEndDocument{\ifx\hyper@anchor\@undefined +\let\contentsline\oldcontentsline +\let\newlabel\oldnewlabel +\fi} +\fi} +\global\let\hyper@last\relax +\gdef\HyperFirstAtBeginDocument#1{#1} +\providecommand\HyField@AuxAddToFields[1]{} +\providecommand\HyField@AuxAddToCoFields[2]{} +\citation{ShiftProject} +\citation{ShiftProject} +\citation{Cisco2019} +\citation{Cisco2019} +\citation{Sandvine2018} +\citation{Sandvine2018} +\citation{li_end--end_2018} +\citation{offloading} +\@writefile{toc}{\contentsline {section}{\numberline {I}Introduction}{1}{section.1}\protected@file@percent } +\citation{Wang2016} +\citation{Ejaz2017} +\citation{Minoli2017} +\citation{Tao2016} +\citation{jalali_fog_2016} +\citation{li_end--end_2018} +\citation{Sarkar2018} +\citation{Wang2016} +\citation{Samie2016} +\citation{Gray2015} +\citation{Nest} +\citation{Samie2016} +\citation{ns3-energywifi} +\citation{Andres2017} +\citation{Gray2015} +\citation{offloading} +\citation{Wang2016} +\citation{Martinez2015} +\citation{ns3-energywifi} +\citation{offloading} +\citation{li_end--end_2018} +\citation{li_end--end_2018} +\citation{Ehsan} +\citation{jalali_fog_2016} +\citation{Sarkar2018} +\citation{li_end--end_2018} +\citation{jalali_fog_2016} +\citation{mahadevan_power_2009} +\citation{li_end--end_2018} +\citation{Ehsan} +\citation{li_end--end_2018} +\@writefile{toc}{\contentsline {section}{\numberline {II}Related Work}{2}{section.2}\protected@file@percent } +\newlabel{sec:orge831050}{{II}{2}{Related Work}{section.2}{}} +\newlabel{sec:sota}{{II}{2}{Related Work}{section.2}{}} +\@writefile{toc}{\contentsline {subsection}{\numberline {\unhbox \voidb@x \hbox {II-A}}Energy consumption of IoT devices}{2}{subsection.2.1}\protected@file@percent } +\newlabel{sec:org77c2591}{{\unhbox \voidb@x \hbox {II-A}}{2}{Energy consumption of IoT devices}{subsection.2.1}{}} +\@writefile{toc}{\contentsline {subsection}{\numberline {\unhbox \voidb@x \hbox {II-B}}Energy consumption of network and cloud infrastructures}{2}{subsection.2.2}\protected@file@percent } +\newlabel{sec:orga15491a}{{\unhbox \voidb@x \hbox {II-B}}{2}{Energy consumption of network and cloud infrastructures}{subsection.2.2}{}} +\@writefile{toc}{\contentsline {section}{\numberline {III}Characterization of low-bandwidth IoT applications}{2}{section.3}\protected@file@percent } +\newlabel{sec:org1da7386}{{III}{2}{Characterization of low-bandwidth IoT applications}{section.3}{}} +\newlabel{sec:usec}{{III}{2}{Characterization of low-bandwidth IoT applications}{section.3}{}} +\citation{Nest} +\citation{Cisco2019} +\citation{halperin_demystifying_nodate} +\citation{li_end--end_2018} +\citation{li_end--end_2018} +\citation{jalali_fog_2016} +\citation{orgerie_simulation_2017} +\citation{sivaraman_profiling_2011} +\citation{Serrano2015} +\citation{cornea_studying_2014-1} +\@writefile{lof}{\contentsline {figure}{\numberline {1}{\ignorespaces Overview of IoT devices.}}{3}{figure.1}\protected@file@percent } +\newlabel{fig:IoTdev}{{1}{3}{Overview of IoT devices}{figure.1}{}} +\@writefile{lof}{\contentsline {figure}{\numberline {2}{\ignorespaces Overview of the IoT architecture.}}{3}{figure.2}\protected@file@percent } +\newlabel{fig:parts}{{2}{3}{Overview of the IoT architecture}{figure.2}{}} +\@writefile{toc}{\contentsline {section}{\numberline {IV}Experimental setup}{3}{section.4}\protected@file@percent } +\newlabel{sec:orgb5f6554}{{IV}{3}{Experimental setup}{section.4}{}} +\newlabel{sec:model}{{IV}{3}{Experimental setup}{section.4}{}} +\@writefile{toc}{\contentsline {subsection}{\numberline {\unhbox \voidb@x \hbox {IV-A}}IoT Part}{3}{subsection.4.1}\protected@file@percent } +\newlabel{sec:orgeb67dd0}{{\unhbox \voidb@x \hbox {IV-A}}{3}{IoT Part}{subsection.4.1}{}} +\@writefile{lot}{\contentsline {table}{\numberline {I}{\ignorespaces Simulations Energy Parameters}}{3}{table.1}\protected@file@percent } +\newlabel{tab:wifi-energy}{{I}{3}{Simulations Energy Parameters}{table.1}{}} +\newlabel{tab:net-energy}{{I(b)}{3}{Subtable I(b)}{subtable.1.2}{}} +\newlabel{sub@tab:net-energy}{{(b)}{3}{Subtable I(b)\relax }{subtable.1.2}{}} +\newlabel{tab:params}{{I}{3}{Simulations Energy Parameters}{subtable.1.2}{}} +\@writefile{lot}{\contentsline {subtable}{\numberline{(a)}{\ignorespaces {IoT part}}}{3}{subtable.1.2}\protected@file@percent } +\@writefile{lot}{\contentsline {subtable}{\numberline{(b)}{\ignorespaces {Network part}}}{3}{subtable.1.2}\protected@file@percent } +\@writefile{toc}{\contentsline {subsection}{\numberline {\unhbox \voidb@x \hbox {IV-B}}Network Part}{3}{subsection.4.2}\protected@file@percent } +\newlabel{sec:orgaeb55ca}{{\unhbox \voidb@x \hbox {IV-B}}{3}{Network Part}{subsection.4.2}{}} +\citation{li_end--end_2018} +\citation{shehabi_united_2016-1} +\@writefile{toc}{\contentsline {subsection}{\numberline {\unhbox \voidb@x \hbox {IV-C}}Cloud Part}{4}{subsection.4.3}\protected@file@percent } +\newlabel{sec:orgfc9ea54}{{\unhbox \voidb@x \hbox {IV-C}}{4}{Cloud Part}{subsection.4.3}{}} +\@writefile{lof}{\contentsline {figure}{\numberline {3}{\ignorespaces Grid'5000 experimental setup.}}{4}{figure.3}\protected@file@percent } +\newlabel{fig:g5kExp}{{3}{4}{Grid'5000 experimental setup}{figure.3}{}} +\@writefile{toc}{\contentsline {section}{\numberline {V}Evaluation}{4}{section.5}\protected@file@percent } +\newlabel{sec:org8201f68}{{V}{4}{Evaluation}{section.5}{}} +\newlabel{sec:eval}{{V}{4}{Evaluation}{section.5}{}} +\@writefile{toc}{\contentsline {subsection}{\numberline {\unhbox \voidb@x \hbox {V-A}}IoT and Network Power Consumption}{4}{subsection.5.1}\protected@file@percent } +\newlabel{sec:org1d05c1b}{{\unhbox \voidb@x \hbox {V-A}}{4}{IoT and Network Power Consumption}{subsection.5.1}{}} +\@writefile{lot}{\contentsline {table}{\numberline {II}{\ignorespaces Sensors transmission interval effects with 15 sensors}}{4}{table.2}\protected@file@percent } +\newlabel{tab:sensorsSendIntervalEffects}{{II}{4}{Sensors transmission interval effects with 15 sensors}{table.2}{}} +\@writefile{toc}{\contentsline {subsection}{\numberline {\unhbox \voidb@x \hbox {V-B}}Cloud Energy Consumption}{4}{subsection.5.2}\protected@file@percent } +\newlabel{sec:org9daa066}{{\unhbox \voidb@x \hbox {V-B}}{4}{Cloud Energy Consumption}{subsection.5.2}{}} +\citation{Ehsan} +\citation{heinrich_predicting_2017} +\citation{shehabi_united_2016-1} +\@writefile{lof}{\contentsline {figure}{\numberline {4}{\ignorespaces Analysis of the variation of the number of sensors on the IoT/Network part energy consumption for a transmission interval of 10s.}}{5}{figure.4}\protected@file@percent } +\newlabel{fig:sensorsNumber}{{4}{5}{Analysis of the variation of the number of sensors on the IoT/Network part energy consumption for a transmission interval of 10s}{figure.4}{}} +\@writefile{toc}{\contentsline {section}{\numberline {VI}End-to-End Consumption Model}{5}{section.6}\protected@file@percent } +\newlabel{sec:orgfd3b6ae}{{VI}{5}{End-to-End Consumption Model}{section.6}{}} +\newlabel{sec:discuss}{{VI}{5}{End-to-End Consumption Model}{section.6}{}} +\citation{Hassidim2013} +\citation{Zhang2016} +\citation{mahadevan_power_2009} +\citation{Hassidim2013} +\citation{orgerie_simulation_2017} +\@writefile{lof}{\contentsline {figure}{\numberline {5}{\ignorespaces Server power consumption multiplied by the PUE (= 1.2) using 20 sensors sending data every 10s for various VM memory sizes}}{6}{figure.5}\protected@file@percent } +\newlabel{fig:vmSize}{{5}{6}{Server power consumption multiplied by the PUE (= 1.2) using 20 sensors sending data every 10s for various VM memory sizes}{figure.5}{}} +\@writefile{lof}{\contentsline {figure}{\numberline {6}{\ignorespaces Average server power consumption multiplied by the PUE (= 1.2) for sensors sending data every 10s}}{6}{figure.6}\protected@file@percent } +\newlabel{fig:sensorsNumber-server}{{6}{6}{Average server power consumption multiplied by the PUE (= 1.2) for sensors sending data every 10s}{figure.6}{}} +\@writefile{lof}{\contentsline {figure}{\numberline {7}{\ignorespaces Average sensors power cost on the server hosting only our VM with PUE (= 1.2) for sensors sending data every 10s}}{6}{figure.7}\protected@file@percent } +\newlabel{fig:sensorsNumber-WPS}{{7}{6}{Average sensors power cost on the server hosting only our VM with PUE (= 1.2) for sensors sending data every 10s}{figure.7}{}} +\@writefile{lof}{\contentsline {figure}{\numberline {8}{\ignorespaces Server energy consumption multiplied by the PUE (= 1.2) for 50 sensors sending requests at different transmission interval.}}{7}{figure.8}\protected@file@percent } +\newlabel{fig:sensorsFrequency}{{8}{7}{Server energy consumption multiplied by the PUE (= 1.2) for 50 sensors sending requests at different transmission interval}{figure.8}{}} +\@writefile{lot}{\contentsline {table}{\numberline {III}{\ignorespaces Network Devices Parameters}}{7}{table.3}\protected@file@percent } +\newlabel{tab:netbidules}{{III}{7}{Network Devices Parameters}{table.3}{}} +\newlabel{fig:end-to-end}{{VI}{7}{End-to-End Consumption Model}{table.3}{}} +\@writefile{lof}{\contentsline {figure}{\numberline {9}{\ignorespaces End-to-end network energy consumption using sensors interval of 10s}}{7}{figure.9}\protected@file@percent } +\bibstyle{IEEEtran} +\bibdata{references} +\bibcite{ShiftProject}{1} +\bibcite{Cisco2019}{2} +\bibcite{Sandvine2018}{3} +\bibcite{li_end--end_2018}{4} +\bibcite{offloading}{5} +\bibcite{Wang2016}{6} +\bibcite{Ejaz2017}{7} +\bibcite{Minoli2017}{8} +\bibcite{Tao2016}{9} +\bibcite{jalali_fog_2016}{10} +\bibcite{Sarkar2018}{11} +\bibcite{Samie2016}{12} +\bibcite{Gray2015}{13} +\bibcite{Nest}{14} +\bibcite{ns3-energywifi}{15} +\bibcite{Andres2017}{16} +\bibcite{Martinez2015}{17} +\bibcite{Ehsan}{18} +\bibcite{mahadevan_power_2009}{19} +\bibcite{halperin_demystifying_nodate}{20} +\bibcite{orgerie_simulation_2017}{21} +\bibcite{sivaraman_profiling_2011}{22} +\bibcite{Serrano2015}{23} +\bibcite{cornea_studying_2014-1}{24} +\bibcite{shehabi_united_2016-1}{25} +\bibcite{heinrich_predicting_2017}{26} +\bibcite{Hassidim2013}{27} +\bibcite{Zhang2016}{28} +\@writefile{toc}{\contentsline {section}{\numberline {VII}Conclusion}{8}{section.7}\protected@file@percent } +\newlabel{sec:org76c5125}{{VII}{8}{Conclusion}{section.7}{}} +\newlabel{sec:cl}{{VII}{8}{Conclusion}{section.7}{}} +\@writefile{toc}{\contentsline {section}{References}{8}{section*.2}\protected@file@percent } diff --git a/2019-CloudCom.bbl b/2019-CloudCom.bbl new file mode 100644 index 0000000..d972e6c --- /dev/null +++ b/2019-CloudCom.bbl @@ -0,0 +1,172 @@ +% Generated by IEEEtran.bst, version: 1.14 (2015/08/26) +\begin{thebibliography}{10} +\providecommand{\url}[1]{#1} +\csname url@samestyle\endcsname +\providecommand{\newblock}{\relax} +\providecommand{\bibinfo}[2]{#2} +\providecommand{\BIBentrySTDinterwordspacing}{\spaceskip=0pt\relax} +\providecommand{\BIBentryALTinterwordstretchfactor}{4} +\providecommand{\BIBentryALTinterwordspacing}{\spaceskip=\fontdimen2\font plus +\BIBentryALTinterwordstretchfactor\fontdimen3\font minus + \fontdimen4\font\relax} +\providecommand{\BIBforeignlanguage}[2]{{% +\expandafter\ifx\csname l@#1\endcsname\relax +\typeout{** WARNING: IEEEtran.bst: No hyphenation pattern has been}% +\typeout{** loaded for the language `#1'. Using the pattern for}% +\typeout{** the default language instead.}% +\else +\language=\csname l@#1\endcsname +\fi +#2}} +\providecommand{\BIBdecl}{\relax} +\BIBdecl + +\bibitem{ShiftProject} +{The Shift Project}, ``{Lean ICT, Pour une sobri\'et\'e num\'erique},'' + https://theshiftproject.org/article/pour-une-sobriete-numerique-rapport-shift/, + Oct. 2018. + +\bibitem{Cisco2019} +Cisco, ``{Cisco Visual Networking Index: Forecast and Trends, 2017–2022},'' + White paper, Feb. 2019. + +\bibitem{Sandvine2018} +Sandvine, ``{The Global Internet Phenomena Report},'' + \url{https://www.sandvine.com/phenomena}, Oct. 2018. + +\bibitem{li_end--end_2018} +Y.~Li, A.-C. Orgerie, I.~Rodero, B.~L. Amersho, M.~Parashar, and J.-M. Menaud, + ``\BIBforeignlanguage{en}{End-to-end energy models for {Edge} {Cloud}-based + {IoT} platforms: {Application} to data stream analysis in {IoT}},'' + \emph{\BIBforeignlanguage{en}{Future Generation Computer Systems}}, vol.~87, + pp. 667--678, Oct. 2018. + +\bibitem{offloading} +K.~{Kumar} and Y.~{Lu}, ``{Cloud Computing for Mobile Users: Can Offloading + Computation Save Energy?}'' \emph{Computer}, vol.~43, no.~4, pp. 51--56, + 2010. + +\bibitem{Wang2016} +K.~{Wang}, Y.~{Wang}, Y.~{Sun}, S.~{Guo}, and J.~{Wu}, ``{Green Industrial + Internet of Things Architecture: An Energy-Efficient Perspective},'' + \emph{IEEE Communications Magazine}, vol.~54, no.~12, pp. 48--54, 2016. + +\bibitem{Ejaz2017} +W.~Ejaz, M.~Naeem, A.~Shahid, A.~Anpalagan, and M.~Jo, ``Efficient energy + management for the internet of things in smart cities,'' \emph{IEEE + Communications Magazine}, vol.~55, no.~1, pp. 84--91, 2017. + +\bibitem{Minoli2017} +D.~{Minoli}, K.~{Sohraby}, and B.~{Occhiogrosso}, ``{IoT Considerations, + Requirements, and Architectures for Smart Buildings—Energy Optimization and + Next-Generation Building Management Systems},'' \emph{IEEE Internet of Things + Journal}, vol.~4, no.~1, pp. 269--283, 2017. + +\bibitem{Tao2016} +F.~Tao, Y.~Wang, Y.~Zuo, H.~Yang, and M.~Zhang, ``{Internet of Things in + product life-cycle energy management},'' \emph{Journal of Industrial + Information Integration}, vol.~1, pp. 26 -- 39, 2016. + +\bibitem{jalali_fog_2016} +F.~Jalali, K.~Hinton, R.~Ayre, T.~Alpcan, and R.~S. Tucker, + ``\BIBforeignlanguage{en}{Fog {Computing} {May} {Help} to {Save} {Energy} in + {Cloud} {Computing}},'' \emph{\BIBforeignlanguage{en}{IEEE J. on Selected + Areas in Communications}}, vol.~34, no.~5, pp. 1728--1739, 2016. + +\bibitem{Sarkar2018} +S.~{Sarkar}, S.~{Chatterjee}, and S.~{Misra}, ``{Assessment of the Suitability + of Fog Computing in the Context of Internet of Things},'' \emph{IEEE + Transactions on Cloud Computing}, vol.~6, no.~1, pp. 46--59, 2018. + +\bibitem{Samie2016} +F.~Samie, L.~Bauer, and J.~Henkel, ``Iot technologies for embedded computing: A + survey,'' in \emph{IEEE/ACM/IFIP CODES}, 2016. + +\bibitem{Gray2015} +C.~{Gray}, R.~{Ayre}, K.~{Hinton}, and R.~S. {Tucker}, ``{Power consumption of + IoT access network technologies},'' in \emph{IEEE International Conference on + Communication Workshop (ICCW)}, 2015, pp. 2818--2823. + +\bibitem{Nest} +Google, ``{Nest Learning Thermostat -- Spec Sheet},'' + \url{https://nest.com/-downloads/press/documents/nest-thermostat-fact-sheet_2017.pdf}, + 2017. + +\bibitem{ns3-energywifi} +H.~Wu, S.~Nabar, and R.~Poovendran, ``{An Energy Framework for the Network + Simulator 3 (NS-3)},'' in \emph{International ICST Conference on Simulation + Tools and Techniques (SIMUTools)}, 2011, pp. 222--230. + +\bibitem{Andres2017} +P.~{Andres-Maldonado}, P.~{Ameigeiras}, J.~{Prados-Garzon}, J.~J. + {Ramos-Munoz}, and J.~M. {Lopez-Soler}, ``{Optimized LTE data transmission + procedures for IoT: Device side energy consumption analysis},'' in \emph{IEEE + International Conference on Communications Workshops (ICC Workshops)}, 2017, + pp. 540--545. + +\bibitem{Martinez2015} +B.~{Martinez}, M.~{Montón}, I.~{Vilajosana}, and J.~D. {Prades}, ``{The Power + of Models: Modeling Power Consumption for IoT Devices},'' \emph{IEEE Sensors + Journal}, vol.~15, no.~10, pp. 5777--5789, 2015. + +\bibitem{Ehsan} +E.~{Ahvar}, A.-C. {Orgerie}, and A.~{Lebre}, ``Estimating energy consumption of + cloud, fog and edge computing infrastructures,'' \emph{IEEE Trans. on Sust. + Comp.}, 2019. + +\bibitem{mahadevan_power_2009} +P.~Mahadevan, P.~Sharma, S.~Banerjee, and P.~Ranganathan, ``A {Power} + {Benchmarking} {Framework} for {Network} {Devices},'' in \emph{{NETWORKING}}, + ser. Lecture {Notes} in {Computer} {Science}, 2009, pp. 795--808. + +\bibitem{halperin_demystifying_nodate} +D.~Halperin, B.~Greenstein, A.~Sheth, and D.~Wetherall, + ``\BIBforeignlanguage{en}{Demystifying 802.11n {Power} {Consumption}},'' in + \emph{\BIBforeignlanguage{en}{International Conference on Power Aware + Computing and Systems (HotPower)}}, 2010, p.~5. + +\bibitem{orgerie_simulation_2017} +A.-C. Orgerie, B.~L. Amersho, T.~Haudebourg, M.~Quinson, M.~Rifai, D.~L. + Pacheco, and L.~Lefèvre, ``Simulation {Toolbox} for {Studying} {Energy} + {Consumption} in {Wired} {Networks},'' in \emph{{CNSM}: {International} + {Conference} on {Network} and {Service} {Management}}, 2017, pp. 1--5. + +\bibitem{sivaraman_profiling_2011} +V.~Sivaraman, A.~Vishwanath, Z.~Zhao, and C.~Russell, ``Profiling per-packet + and per-byte energy consumption in the {NetFPGA} {Gigabit} router,'' in + \emph{IEEE INFOCOM Workshops}, 2011, pp. 331--336. + +\bibitem{Serrano2015} +P.~{Serrano}, A.~{Garcia-Saavedra}, G.~{Bianchi}, A.~{Banchs}, and + A.~{Azcorra}, ``{Per-Frame Energy Consumption in 802.11 Devices and Its + Implication on Modeling and Design},'' \emph{IEEE/ACM Trans. on Net.}, + vol.~23, no.~4, pp. 1243--1256, 2015. + +\bibitem{cornea_studying_2014-1} +B.~F. Cornea, A.~C. Orgerie, and L.~Lefèvre, ``Studying the energy consumption + of data transfers in {Clouds}: the {Ecofen} approach,'' in \emph{2014 {IEEE} + 3rd {International} {Conference} on {Cloud} {Networking} ({CloudNet})}, Oct. + 2014, pp. 143--148. + +\bibitem{shehabi_united_2016-1} +A.~Shehabi, S.~Smith, D.~Sartor, R.~Brown, M.~Herrlin, J.~Koomey, E.~Masanet, + N.~Horner, I.~Azevedo, and W.~Lintner, ``\BIBforeignlanguage{en}{United + {States} {Data} {Center} {Energy} {Usage} {Report}},'' LBNL, Tech. Rep. + LBNL--1005775, 1372902, Jun. 2016. + +\bibitem{heinrich_predicting_2017} +F.~C. Heinrich, T.~Cornebize, A.~Degomme, A.~Legrand, A.~Carpen-Amarie, + S.~Hunold, A.-C. Orgerie, and M.~Quinson, ``Predicting the + {Energy}-{Consumption} of {MPI} {Applications} at {Scale} {Using} {Only} a + {Single} {Node},'' in \emph{IEEE Cluster Conference}, 2017, pp. 92--102. + +\bibitem{Hassidim2013} +A.~{Hassidim}, D.~{Raz}, M.~{Segalov}, and A.~{Shaqed}, ``{Network utilization: + The flow view},'' in \emph{IEEE INFOCOM}, 2013, pp. 1429--1437. + +\bibitem{Zhang2016} +Z.~{Zhang}, Y.~{Bejerano}, and S.~{Antonakopoulos}, ``{Energy-Efficient IP Core + Network Configuration Under General Traffic Demands},'' \emph{IEEE/ACM Trans. + on Networking}, vol.~24, no.~2, pp. 745--758, 2016. + +\end{thebibliography} diff --git a/2019-CloudCom.blg b/2019-CloudCom.blg new file mode 100644 index 0000000..c78397f --- /dev/null +++ b/2019-CloudCom.blg @@ -0,0 +1,56 @@ +This is BibTeX, Version 0.99d (TeX Live 2019/Arch Linux) +Capacity: max_strings=100000, hash_size=100000, hash_prime=85009 +The top-level auxiliary file: 2019-CloudCom.aux +The style file: IEEEtran.bst +Reallocated singl_function (elt_size=8) to 100 items from 50. +Reallocated singl_function (elt_size=8) to 100 items from 50. +Reallocated singl_function (elt_size=8) to 100 items from 50. +Reallocated wiz_functions (elt_size=8) to 6000 items from 3000. +Reallocated singl_function (elt_size=8) to 100 items from 50. +Database file #1: references.bib +-- IEEEtran.bst version 1.14 (2015/08/26) by Michael Shell. +-- http://www.michaelshell.org/tex/ieeetran/bibtex/ +-- See the "IEEEtran_bst_HOWTO.pdf" manual for usage information. + +Done. +You've used 28 entries, + 4087 wiz_defined-function locations, + 991 strings with 13141 characters, +and the built_in function-call counts, 22722 in all, are: += -- 1768 +> -- 618 +< -- 188 ++ -- 339 +- -- 112 +* -- 1115 +:= -- 3266 +add.period$ -- 56 +call.type$ -- 28 +change.case$ -- 28 +chr.to.int$ -- 438 +cite$ -- 28 +duplicate$ -- 1612 +empty$ -- 1834 +format.name$ -- 136 +if$ -- 5344 +int.to.chr$ -- 0 +int.to.str$ -- 28 +missing$ -- 301 +newline$ -- 107 +num.names$ -- 28 +pop$ -- 713 +preamble$ -- 1 +purify$ -- 0 +quote$ -- 2 +skip$ -- 1744 +stack$ -- 0 +substring$ -- 1051 +swap$ -- 1345 +text.length$ -- 42 +text.prefix$ -- 0 +top$ -- 5 +type$ -- 28 +warning$ -- 0 +while$ -- 98 +width$ -- 30 +write$ -- 289 diff --git a/2019-CloudCom.log b/2019-CloudCom.log new file mode 100644 index 0000000..0cac42a --- /dev/null +++ b/2019-CloudCom.log @@ -0,0 +1,622 @@ +This is pdfTeX, Version 3.14159265-2.6-1.40.20 (TeX Live 2019/Arch Linux) (preloaded format=pdflatex 2019.8.25) 16 OCT 2019 15:06 +entering extended mode + restricted \write18 enabled. + %&-line parsing enabled. +**/home/loic/Documents/Git/manzerbredes/paper-lowrate-iot/2019-CloudCom.tex +(/home/loic/Documents/Git/manzerbredes/paper-lowrate-iot/2019-CloudCom.tex +LaTeX2e <2018-12-01> +(/usr/share/texmf-dist/tex/latex/IEEEtran/IEEEtran.cls +Document Class: IEEEtran 2015/08/26 V1.8b by Michael Shell +-- See the "IEEEtran_HOWTO" manual for usage information. +-- http://www.michaelshell.org/tex/ieeetran/ +\@IEEEtrantmpdimenA=\dimen102 +\@IEEEtrantmpdimenB=\dimen103 +\@IEEEtrantmpdimenC=\dimen104 +\@IEEEtrantmpcountA=\count80 +\@IEEEtrantmpcountB=\count81 +\@IEEEtrantmpcountC=\count82 +\@IEEEtrantmptoksA=\toks14 +LaTeX Font Info: Try loading font information for OT1+ptm on input line 503. + +(/usr/share/texmf-dist/tex/latex/psnfss/ot1ptm.fd +File: ot1ptm.fd 2001/06/04 font definitions for OT1/ptm. +) +-- Using 8.5in x 11in (letter) paper. +-- Using PDF output. +\@IEEEnormalsizeunitybaselineskip=\dimen105 +-- This is a 10 point document. +\CLASSINFOnormalsizebaselineskip=\dimen106 +\CLASSINFOnormalsizeunitybaselineskip=\dimen107 +\IEEEnormaljot=\dimen108 +LaTeX Font Info: Font shape `OT1/ptm/bx/n' in size <5> not available +(Font) Font shape `OT1/ptm/b/n' tried instead on input line 1090. +LaTeX Font Info: Font shape `OT1/ptm/bx/it' in size <5> not available +(Font) Font shape `OT1/ptm/b/it' tried instead on input line 1090. + +LaTeX Font Info: Font shape `OT1/ptm/bx/n' in size <7> not available +(Font) Font shape `OT1/ptm/b/n' tried instead on input line 1090. +LaTeX Font Info: Font shape `OT1/ptm/bx/it' in size <7> not available +(Font) Font shape `OT1/ptm/b/it' tried instead on input line 1090. + +LaTeX Font Info: Font shape `OT1/ptm/bx/n' in size <8> not available +(Font) Font shape `OT1/ptm/b/n' tried instead on input line 1090. +LaTeX Font Info: Font shape `OT1/ptm/bx/it' in size <8> not available +(Font) Font shape `OT1/ptm/b/it' tried instead on input line 1090. + +LaTeX Font Info: Font shape `OT1/ptm/bx/n' in size <9> not available +(Font) Font shape `OT1/ptm/b/n' tried instead on input line 1090. +LaTeX Font Info: Font shape `OT1/ptm/bx/it' in size <9> not available +(Font) Font shape `OT1/ptm/b/it' tried instead on input line 1090. + +LaTeX Font Info: Font shape `OT1/ptm/bx/n' in size <10> not available +(Font) Font shape `OT1/ptm/b/n' tried instead on input line 1090. +LaTeX Font Info: Font shape `OT1/ptm/bx/it' in size <10> not available +(Font) Font shape `OT1/ptm/b/it' tried instead on input line 1090. + +LaTeX Font Info: Font shape `OT1/ptm/bx/n' in size <11> not available +(Font) Font shape `OT1/ptm/b/n' tried instead on input line 1090. +LaTeX Font Info: Font shape `OT1/ptm/bx/it' in size <11> not available +(Font) Font shape `OT1/ptm/b/it' tried instead on input line 1090. + +LaTeX Font Info: Font shape `OT1/ptm/bx/n' in size <12> not available +(Font) Font shape `OT1/ptm/b/n' tried instead on input line 1090. +LaTeX Font Info: Font shape `OT1/ptm/bx/it' in size <12> not available +(Font) Font shape `OT1/ptm/b/it' tried instead on input line 1090. + +LaTeX Font Info: Font shape `OT1/ptm/bx/n' in size <17> not available +(Font) Font shape `OT1/ptm/b/n' tried instead on input line 1090. +LaTeX Font Info: Font shape `OT1/ptm/bx/it' in size <17> not available +(Font) Font shape `OT1/ptm/b/it' tried instead on input line 1090. + +LaTeX Font Info: Font shape `OT1/ptm/bx/n' in size <20> not available +(Font) Font shape `OT1/ptm/b/n' tried instead on input line 1090. +LaTeX Font Info: Font shape `OT1/ptm/bx/it' in size <20> not available +(Font) Font shape `OT1/ptm/b/it' tried instead on input line 1090. + +LaTeX Font Info: Font shape `OT1/ptm/bx/n' in size <24> not available +(Font) Font shape `OT1/ptm/b/n' tried instead on input line 1090. +LaTeX Font Info: Font shape `OT1/ptm/bx/it' in size <24> not available +(Font) Font shape `OT1/ptm/b/it' tried instead on input line 1090. + +\IEEEquantizedlength=\dimen109 +\IEEEquantizedlengthdiff=\dimen110 +\IEEEquantizedtextheightdiff=\dimen111 +\IEEEilabelindentA=\dimen112 +\IEEEilabelindentB=\dimen113 +\IEEEilabelindent=\dimen114 +\IEEEelabelindent=\dimen115 +\IEEEdlabelindent=\dimen116 +\IEEElabelindent=\dimen117 +\IEEEiednormlabelsep=\dimen118 +\IEEEiedmathlabelsep=\dimen119 +\IEEEiedtopsep=\skip41 +\c@section=\count83 +\c@subsection=\count84 +\c@subsubsection=\count85 +\c@paragraph=\count86 +\c@IEEEsubequation=\count87 +\abovecaptionskip=\skip42 +\belowcaptionskip=\skip43 +\c@figure=\count88 +\c@table=\count89 +\@IEEEeqnnumcols=\count90 +\@IEEEeqncolcnt=\count91 +\@IEEEsubeqnnumrollback=\count92 +\@IEEEquantizeheightA=\dimen120 +\@IEEEquantizeheightB=\dimen121 +\@IEEEquantizeheightC=\dimen122 +\@IEEEquantizeprevdepth=\dimen123 +\@IEEEquantizemultiple=\count93 +\@IEEEquantizeboxA=\box27 +\@IEEEtmpitemindent=\dimen124 +\IEEEPARstartletwidth=\dimen125 +\c@IEEEbiography=\count94 +\@IEEEtranrubishbin=\box28 +) (/usr/share/texmf-dist/tex/latex/hyperref/hyperref.sty +Package: hyperref 2018/11/30 v6.88e Hypertext links for LaTeX + +(/usr/share/texmf-dist/tex/generic/oberdiek/hobsub-hyperref.sty +Package: hobsub-hyperref 2016/05/16 v1.14 Bundle oberdiek, subset hyperref (HO) + + +(/usr/share/texmf-dist/tex/generic/oberdiek/hobsub-generic.sty +Package: hobsub-generic 2016/05/16 v1.14 Bundle oberdiek, subset generic (HO) +Package: hobsub 2016/05/16 v1.14 Construct package bundles (HO) +Package: infwarerr 2016/05/16 v1.4 Providing info/warning/error messages (HO) +Package: ltxcmds 2016/05/16 v1.23 LaTeX kernel commands for general use (HO) +Package: ifluatex 2016/05/16 v1.4 Provides the ifluatex switch (HO) +Package ifluatex Info: LuaTeX not detected. +Package: ifvtex 2016/05/16 v1.6 Detect VTeX and its facilities (HO) +Package ifvtex Info: VTeX not detected. +Package: intcalc 2016/05/16 v1.2 Expandable calculations with integers (HO) +Package: ifpdf 2018/09/07 v3.3 Provides the ifpdf switch +Package: etexcmds 2016/05/16 v1.6 Avoid name clashes with e-TeX commands (HO) +Package: kvsetkeys 2016/05/16 v1.17 Key value parser (HO) +Package: kvdefinekeys 2016/05/16 v1.4 Define keys (HO) +Package: pdftexcmds 2018/09/10 v0.29 Utility functions of pdfTeX for LuaTeX (HO +) +Package pdftexcmds Info: LuaTeX not detected. +Package pdftexcmds Info: \pdf@primitive is available. +Package pdftexcmds Info: \pdf@ifprimitive is available. +Package pdftexcmds Info: \pdfdraftmode found. +Package: pdfescape 2016/05/16 v1.14 Implements pdfTeX's escape features (HO) +Package: bigintcalc 2016/05/16 v1.4 Expandable calculations on big integers (HO +) +Package: bitset 2016/05/16 v1.2 Handle bit-vector datatype (HO) +Package: uniquecounter 2016/05/16 v1.3 Provide unlimited unique counter (HO) +) +Package hobsub Info: Skipping package `hobsub' (already loaded). +Package: letltxmacro 2016/05/16 v1.5 Let assignment for LaTeX macros (HO) +Package: hopatch 2016/05/16 v1.3 Wrapper for package hooks (HO) +Package: xcolor-patch 2016/05/16 xcolor patch +Package: atveryend 2016/05/16 v1.9 Hooks at the very end of document (HO) +Package atveryend Info: \enddocument detected (standard20110627). +Package: atbegshi 2016/06/09 v1.18 At begin shipout hook (HO) +Package: refcount 2016/05/16 v3.5 Data extraction from label references (HO) +Package: hycolor 2016/05/16 v1.8 Color options for hyperref/bookmark (HO) +) +(/usr/share/texmf-dist/tex/latex/graphics/keyval.sty +Package: keyval 2014/10/28 v1.15 key=value parser (DPC) +\KV@toks@=\toks15 +) +(/usr/share/texmf-dist/tex/generic/ifxetex/ifxetex.sty +Package: ifxetex 2010/09/12 v0.6 Provides ifxetex conditional +) +(/usr/share/texmf-dist/tex/latex/oberdiek/auxhook.sty +Package: auxhook 2016/05/16 v1.4 Hooks for auxiliary files (HO) +) +(/usr/share/texmf-dist/tex/latex/oberdiek/kvoptions.sty +Package: kvoptions 2016/05/16 v3.12 Key value format for package options (HO) +) +\@linkdim=\dimen126 +\Hy@linkcounter=\count95 +\Hy@pagecounter=\count96 + +(/usr/share/texmf-dist/tex/latex/hyperref/pd1enc.def +File: pd1enc.def 2018/11/30 v6.88e Hyperref: PDFDocEncoding definition (HO) +Now handling font encoding PD1 ... +... no UTF-8 mapping file for font encoding PD1 +) +\Hy@SavedSpaceFactor=\count97 + +(/usr/share/texmf-dist/tex/latex/latexconfig/hyperref.cfg +File: hyperref.cfg 2002/06/06 v1.2 hyperref configuration of TeXLive +) +Package hyperref Info: Hyper figures OFF on input line 4519. +Package hyperref Info: Link nesting OFF on input line 4524. +Package hyperref Info: Hyper index ON on input line 4527. +Package hyperref Info: Plain pages OFF on input line 4534. +Package hyperref Info: Backreferencing OFF on input line 4539. +Package hyperref Info: Implicit mode ON; LaTeX internals redefined. +Package hyperref Info: Bookmarks ON on input line 4772. +\c@Hy@tempcnt=\count98 + +(/usr/share/texmf-dist/tex/latex/url/url.sty +\Urlmuskip=\muskip10 +Package: url 2013/09/16 ver 3.4 Verb mode for urls, etc. +) +LaTeX Info: Redefining \url on input line 5125. +\XeTeXLinkMargin=\dimen127 +\Fld@menulength=\count99 +\Field@Width=\dimen128 +\Fld@charsize=\dimen129 +Package hyperref Info: Hyper figures OFF on input line 6380. +Package hyperref Info: Link nesting OFF on input line 6385. +Package hyperref Info: Hyper index ON on input line 6388. +Package hyperref Info: backreferencing OFF on input line 6395. +Package hyperref Info: Link coloring OFF on input line 6400. +Package hyperref Info: Link coloring with OCG OFF on input line 6405. +Package hyperref Info: PDF/A mode OFF on input line 6410. +LaTeX Info: Redefining \ref on input line 6450. +LaTeX Info: Redefining \pageref on input line 6454. +\Hy@abspage=\count100 +\c@Item=\count101 +\c@Hfootnote=\count102 +) +Package hyperref Info: Driver (autodetected): hpdftex. + +(/usr/share/texmf-dist/tex/latex/hyperref/hpdftex.def +File: hpdftex.def 2018/11/30 v6.88e Hyperref driver for pdfTeX +\Fld@listcount=\count103 +\c@bookmark@seq@number=\count104 + +(/usr/share/texmf-dist/tex/latex/oberdiek/rerunfilecheck.sty +Package: rerunfilecheck 2016/05/16 v1.8 Rerun checks for auxiliary files (HO) +Package uniquecounter Info: New unique counter `rerunfilecheck' on input line 2 +82. +) +\Hy@SectionHShift=\skip44 +) +(/usr/share/texmf-dist/tex/latex/booktabs/booktabs.sty +Package: booktabs 2016/04/27 v1.618033 publication quality tables +\heavyrulewidth=\dimen130 +\lightrulewidth=\dimen131 +\cmidrulewidth=\dimen132 +\belowrulesep=\dimen133 +\belowbottomsep=\dimen134 +\aboverulesep=\dimen135 +\abovetopsep=\dimen136 +\cmidrulesep=\dimen137 +\cmidrulekern=\dimen138 +\defaultaddspace=\dimen139 +\@cmidla=\count105 +\@cmidlb=\count106 +\@aboverulesep=\dimen140 +\@belowrulesep=\dimen141 +\@thisruleclass=\count107 +\@lastruleclass=\count108 +\@thisrulewidth=\dimen142 +) +(/usr/share/texmf-dist/tex/latex/subfigure/subfigure.sty +Package: subfigure 2002/03/15 v2.1.5 subfigure package +\subfigtopskip=\skip45 +\subfigcapskip=\skip46 +\subfigcaptopadj=\dimen143 +\subfigbottomskip=\skip47 +\subfigcapmargin=\dimen144 +\subfiglabelskip=\skip48 +\c@subfigure=\count109 +\c@lofdepth=\count110 +\c@subtable=\count111 +\c@lotdepth=\count112 + +**************************************** +* Local config file subfigure.cfg used * +**************************************** +(/usr/share/texmf-dist/tex/latex/subfigure/subfigure.cfg) +\subfig@top=\skip49 +\subfig@bottom=\skip50 +) +(/usr/share/texmf-dist/tex/latex/graphics/graphicx.sty +Package: graphicx 2017/06/01 v1.1a Enhanced LaTeX Graphics (DPC,SPQR) + +(/usr/share/texmf-dist/tex/latex/graphics/graphics.sty +Package: graphics 2017/06/25 v1.2c Standard LaTeX Graphics (DPC,SPQR) + +(/usr/share/texmf-dist/tex/latex/graphics/trig.sty +Package: trig 2016/01/03 v1.10 sin cos tan (DPC) +) +(/usr/share/texmf-dist/tex/latex/graphics-cfg/graphics.cfg +File: graphics.cfg 2016/06/04 v1.11 sample graphics configuration +) +Package graphics Info: Driver file: pdftex.def on input line 99. + +(/usr/share/texmf-dist/tex/latex/graphics-def/pdftex.def +File: pdftex.def 2018/01/08 v1.0l Graphics/color driver for pdftex +)) +\Gin@req@height=\dimen145 +\Gin@req@width=\dimen146 +) +(/usr/share/texmf-dist/tex/latex/xcolor/xcolor.sty +Package: xcolor 2016/05/11 v2.12 LaTeX color extensions (UK) + +(/usr/share/texmf-dist/tex/latex/graphics-cfg/color.cfg +File: color.cfg 2016/01/02 v1.6 sample color configuration +) +Package xcolor Info: Driver file: pdftex.def on input line 225. +Package xcolor Info: Model `cmy' substituted by `cmy0' on input line 1348. +Package xcolor Info: Model `hsb' substituted by `rgb' on input line 1352. +Package xcolor Info: Model `RGB' extended on input line 1364. +Package xcolor Info: Model `HTML' substituted by `rgb' on input line 1366. +Package xcolor Info: Model `Hsb' substituted by `hsb' on input line 1367. +Package xcolor Info: Model `tHsb' substituted by `hsb' on input line 1368. +Package xcolor Info: Model `HSB' substituted by `hsb' on input line 1369. +Package xcolor Info: Model `Gray' substituted by `gray' on input line 1370. +Package xcolor Info: Model `wave' substituted by `hsb' on input line 1371. +) +(/usr/share/texmf-dist/tex/latex/multirow/multirow.sty +Package: multirow 2019/01/01 v2.4 Span multiple rows of a table +\multirow@colwidth=\skip51 +\multirow@cntb=\count113 +\multirow@dima=\skip52 +\bigstrutjot=\dimen147 +) +(/usr/share/texmf-dist/tex/latex/amsmath/amsmath.sty +Package: amsmath 2018/12/01 v2.17b AMS math features +\@mathmargin=\skip53 + +For additional information on amsmath, use the `?' option. +(/usr/share/texmf-dist/tex/latex/amsmath/amstext.sty +Package: amstext 2000/06/29 v2.01 AMS text + +(/usr/share/texmf-dist/tex/latex/amsmath/amsgen.sty +File: amsgen.sty 1999/11/30 v2.0 generic functions +\@emptytoks=\toks16 +\ex@=\dimen148 +)) +(/usr/share/texmf-dist/tex/latex/amsmath/amsbsy.sty +Package: amsbsy 1999/11/29 v1.2d Bold Symbols +\pmbraise@=\dimen149 +) +(/usr/share/texmf-dist/tex/latex/amsmath/amsopn.sty +Package: amsopn 2016/03/08 v2.02 operator names +) +\inf@bad=\count114 +LaTeX Info: Redefining \frac on input line 223. +\uproot@=\count115 +\leftroot@=\count116 +LaTeX Info: Redefining \overline on input line 385. +\classnum@=\count117 +\DOTSCASE@=\count118 +LaTeX Info: Redefining \ldots on input line 482. +LaTeX Info: Redefining \dots on input line 485. +LaTeX Info: Redefining \cdots on input line 606. +\Mathstrutbox@=\box29 +\strutbox@=\box30 +\big@size=\dimen150 +LaTeX Font Info: Redeclaring font encoding OML on input line 729. +LaTeX Font Info: Redeclaring font encoding OMS on input line 730. +\macc@depth=\count119 +\c@MaxMatrixCols=\count120 +\dotsspace@=\muskip11 +\c@parentequation=\count121 +\dspbrk@lvl=\count122 +\tag@help=\toks17 +\row@=\count123 +\column@=\count124 +\maxfields@=\count125 +\andhelp@=\toks18 +\eqnshift@=\dimen151 +\alignsep@=\dimen152 +\tagshift@=\dimen153 +\tagwidth@=\dimen154 +\totwidth@=\dimen155 +\lineht@=\dimen156 +\@envbody=\toks19 +\multlinegap=\skip54 +\multlinetaggap=\skip55 +\mathdisplay@stack=\toks20 +LaTeX Info: Redefining \[ on input line 2844. +LaTeX Info: Redefining \] on input line 2845. +) (./2019-CloudCom.aux) +\openout1 = `2019-CloudCom.aux'. + +LaTeX Font Info: Checking defaults for OML/cmm/m/it on input line 28. +LaTeX Font Info: ... okay on input line 28. +LaTeX Font Info: Checking defaults for T1/cmr/m/n on input line 28. +LaTeX Font Info: ... okay on input line 28. +LaTeX Font Info: Checking defaults for OT1/cmr/m/n on input line 28. +LaTeX Font Info: ... okay on input line 28. +LaTeX Font Info: Checking defaults for OMS/cmsy/m/n on input line 28. +LaTeX Font Info: ... okay on input line 28. +LaTeX Font Info: Checking defaults for OMX/cmex/m/n on input line 28. +LaTeX Font Info: ... okay on input line 28. +LaTeX Font Info: Checking defaults for U/cmr/m/n on input line 28. +LaTeX Font Info: ... okay on input line 28. +LaTeX Font Info: Checking defaults for PD1/pdf/m/n on input line 28. +LaTeX Font Info: ... okay on input line 28. + +-- Lines per column: 56 (exact). +\AtBeginShipoutBox=\box31 +Package hyperref Info: Link coloring OFF on input line 28. +(/usr/share/texmf-dist/tex/latex/hyperref/nameref.sty +Package: nameref 2016/05/21 v2.44 Cross-referencing by name of section + +(/usr/share/texmf-dist/tex/generic/oberdiek/gettitlestring.sty +Package: gettitlestring 2016/05/16 v1.5 Cleanup title references (HO) +) +\c@section@level=\count126 +) +LaTeX Info: Redefining \ref on input line 28. +LaTeX Info: Redefining \pageref on input line 28. +LaTeX Info: Redefining \nameref on input line 28. + +(./2019-CloudCom.out) (./2019-CloudCom.out) +\@outlinefile=\write3 +\openout3 = `2019-CloudCom.out'. + + +(/usr/share/texmf-dist/tex/context/base/mkii/supp-pdf.mkii +[Loading MPS to PDF converter (version 2006.09.02).] +\scratchcounter=\count127 +\scratchdimen=\dimen157 +\scratchbox=\box32 +\nofMPsegments=\count128 +\nofMParguments=\count129 +\everyMPshowfont=\toks21 +\MPscratchCnt=\count130 +\MPscratchDim=\dimen158 +\MPnumerator=\count131 +\makeMPintoPDFobject=\count132 +\everyMPtoPDFconversion=\toks22 +) (/usr/share/texmf-dist/tex/latex/oberdiek/epstopdf-base.sty +Package: epstopdf-base 2016/05/15 v2.6 Base part for package epstopdf + +(/usr/share/texmf-dist/tex/latex/oberdiek/grfext.sty +Package: grfext 2016/05/16 v1.2 Manage graphics extensions (HO) +) +Package epstopdf-base Info: Redefining graphics rule for `.eps' on input line 4 +38. +Package grfext Info: Graphics extension search list: +(grfext) [.pdf,.png,.jpg,.mps,.jpeg,.jbig2,.jb2,.PDF,.PNG,.JPG,.JPE +G,.JBIG2,.JB2,.eps] +(grfext) \AppendGraphicsExtensions on input line 456. + +(/usr/share/texmf-dist/tex/latex/latexconfig/epstopdf-sys.cfg +File: epstopdf-sys.cfg 2010/07/13 v1.3 Configuration of (r)epstopdf for TeX Liv +e +)) +LaTeX Font Info: Try loading font information for OMS+ptm on input line 31. + +(/usr/share/texmf-dist/tex/latex/psnfss/omsptm.fd +File: omsptm.fd +) +LaTeX Font Info: Font shape `OMS/ptm/m/n' in size <10> not available +(Font) Font shape `OMS/cmsy/m/n' tried instead on input line 31. + +Underfull \hbox (badness 1917) in paragraph at lines 129--133 +[]\OT1/ptm/m/n/10 an anal-y-sis of the en-ergy con-sump-tion of a low- + [] + +[1{/var/lib/texmf/fonts/map/pdftex/updmap/pdftex.map} + + +] [2] +<./plots/home.png, id=144, 314.76749pt x 247.48161pt> +File: ./plots/home.png Graphic file (type png) + +Package pdftex.def Info: ./plots/home.png used on input line 273. +(pdftex.def) Requested size: 151.20154pt x 118.88045pt. +<./plots/parts2.png, id=149, 456.43202pt x 136.297pt> +File: ./plots/parts2.png Graphic file (type png) + +Package pdftex.def Info: ./plots/parts2.png used on input line 301. +(pdftex.def) Requested size: 214.20154pt x 63.96393pt. + [3 <./plots/home.png> <./plots/parts2.png>] +<./plots/g5k-xp.png, id=177, 167.73541pt x 172.33615pt> +File: ./plots/g5k-xp.png Graphic file (type png) + +Package pdftex.def Info: ./plots/g5k-xp.png used on input line 408. +(pdftex.def) Requested size: 151.20154pt x 155.34827pt. +<./plots/numberSensors-WIFINET.png, id=184, 361.35pt x 289.08pt> +File: ./plots/numberSensors-WIFINET.png Graphic file (type png) + +Package pdftex.def Info: ./plots/numberSensors-WIFINET.png used on input line +497. +(pdftex.def) Requested size: 163.79846pt x 131.03757pt. + [4 <./plots/g5k-xp.png>] +<./plots/vmSize-cloud.png, id=199, 433.62pt x 216.81pt> +File: ./plots/vmSize-cloud.png Graphic file (type png) + +Package pdftex.def Info: ./plots/vmSize-cloud.png used on input line 516. +(pdftex.def) Requested size: 309.60315pt x 154.80954pt. +<./plots/sensorsNumberLine-cloud.png, id=207, 289.08pt x 325.215pt> +File: ./plots/sensorsNumberLine-cloud.png Graphic file (type png) + +Package pdftex.def Info: ./plots/sensorsNumberLine-cloud.png used on input lin +e 566. +(pdftex.def) Requested size: 138.60077pt x 155.92278pt. +<./plots/WPS-cloud.png, id=208, 289.08pt x 289.08pt> +File: ./plots/WPS-cloud.png Graphic file (type png) + +Package pdftex.def Info: ./plots/WPS-cloud.png used on input line 574. +(pdftex.def) Requested size: 138.60077pt x 138.59802pt. + +File: plots/sendInterval-cloud.png Graphic file (type png) + +Package pdftex.def Info: plots/sendInterval-cloud.png used on input line 590. +(pdftex.def) Requested size: 309.60315pt x 154.80954pt. + +Overfull \hbox (6.35864pt too wide) detected at line 631 +[] + [] + +[5 <./plots/numberSensors-WIFINET.png (PNG copy)>] [6 <./plots/vmSize-cloud.png + (PNG copy)> <./plots/sensorsNumberLine-cloud.png> <./plots/WPS-cloud.png>] +Underfull \hbox (badness 3492) in paragraph at lines 709--717 +[]\OT1/ptm/m/n/10 Where $\OML/cmm/m/it/10 P[]$ \OT1/ptm/m/n/10 is the static po +wer con-sump-tion of + [] + + +File: plots/final.png Graphic file (type png) + +Package pdftex.def Info: plots/final.png used on input line 733. +(pdftex.def) Requested size: 226.79846pt x 155.92223pt. +[7 <./plots/sendInterval-cloud.png (PNG copy)> <./plots/final.png (PNG copy)>] +(./2019-CloudCom.bbl +Underfull \hbox (badness 4266) in paragraph at lines 25--28 +[]\OT1/ptm/m/n/8 The Shift Project, ``Lean ICT, Pour une so-bri[]et[]e num[]eri +que,'' + [] + + +Underfull \hbox (badness 10000) in paragraph at lines 25--28 +\OT1/ptm/m/n/8 https://theshiftproject.org/article/pour-une-sobriete-numerique- +rapport- + [] + + +Underfull \hbox (badness 4886) in paragraph at lines 30--32 +[]\OT1/ptm/m/n/8 Cisco, ``Cisco Vi-sual Net-work-ing In-dex: Fore-cast and Tren +ds, + [] + + +Underfull \hbox (badness 1389) in paragraph at lines 34--36 +[]\OT1/ptm/m/n/8 Sandvine, ``The Global In-ter-net Phe-nom-ena Re-port,'' []$ht +tps : / / www . + [] + +** WARNING: IEEEtran.bst: No hyphenation pattern has been +** loaded for the language `en'. Using the pattern for +** the default language instead. +** WARNING: IEEEtran.bst: No hyphenation pattern has been +** loaded for the language `en'. Using the pattern for +** the default language instead. +** WARNING: IEEEtran.bst: No hyphenation pattern has been +** loaded for the language `en'. Using the pattern for +** the default language instead. +** WARNING: IEEEtran.bst: No hyphenation pattern has been +** loaded for the language `en'. Using the pattern for +** the default language instead. + +Underfull \hbox (badness 2809) in paragraph at lines 91--94 +[]\OT1/ptm/m/n/8 Google, ``Nest Learn-ing Ther-mo-stat -- Spec Sheet,'' []$http +s : / / nest . + [] + + +Underfull \hbox (badness 10000) in paragraph at lines 91--94 +\OT1/ptm/m/n/8 com / -[]downloads / press / documents / nest-[]thermostat-[]fac +t-[]sheet[]2017 . pdf$[], + [] + +** WARNING: IEEEtran.bst: No hyphenation pattern has been +** loaded for the language `en'. Using the pattern for +** the default language instead. +** WARNING: IEEEtran.bst: No hyphenation pattern has been +** loaded for the language `en'. Using the pattern for +** the default language instead. +** WARNING: IEEEtran.bst: No hyphenation pattern has been +** loaded for the language `en'. Using the pattern for +** the default language instead. +) + +** Conference Paper ** +Before submitting the final camera ready copy, remember to: + + 1. Manually equalize the lengths of two columns on the last page + of your paper; + + 2. Ensure that any PostScript and/or PDF output post-processing + uses only Type 1 fonts and that every step in the generation + process uses the appropriate paper size. + +Package atveryend Info: Empty hook `BeforeClearDocument' on input line 811. +[8] +Package atveryend Info: Empty hook `AfterLastShipout' on input line 811. + (./2019-CloudCom.aux) +Package atveryend Info: Executing hook `AtVeryEndDocument' on input line 811. +Package atveryend Info: Executing hook `AtEndAfterFileList' on input line 811. +Package rerunfilecheck Info: File `2019-CloudCom.out' has not changed. +(rerunfilecheck) Checksum: 14EDF505A77B0488CA6C90929BF4F9E7;955. +Package atveryend Info: Empty hook `AtVeryVeryEnd' on input line 811. + ) +Here is how much of TeX's memory you used: + 7329 strings out of 492623 + 109553 string characters out of 6135669 + 220918 words of memory out of 5000000 + 11096 multiletter control sequences out of 15000+600000 + 40208 words of font info for 77 fonts, out of 8000000 for 9000 + 1141 hyphenation exceptions out of 8191 + 28i,10n,35p,337b,391s stack positions out of 5000i,500n,10000p,200000b,80000s +{/usr/share/texmf-dist/fonts/enc/dvips/base/8r.enc} +Output written on 2019-CloudCom.pdf (8 pages, 696467 bytes). +PDF statistics: + 329 PDF objects out of 1000 (max. 8388607) + 288 compressed objects within 3 object streams + 70 named destinations out of 1000 (max. 500000) + 166 words of extra memory for PDF output out of 10000 (max. 10000000) + diff --git a/2019-CloudCom.out b/2019-CloudCom.out new file mode 100644 index 0000000..1231205 --- /dev/null +++ b/2019-CloudCom.out @@ -0,0 +1,15 @@ +\BOOKMARK [1][-]{section.1}{Introduction}{}% 1 +\BOOKMARK [1][-]{section.2}{Related Work}{}% 2 +\BOOKMARK [2][-]{subsection.2.1}{Energy consumption of IoT devices}{section.2}% 3 +\BOOKMARK [2][-]{subsection.2.2}{Energy consumption of network and cloud infrastructures}{section.2}% 4 +\BOOKMARK [1][-]{section.3}{Characterization of low-bandwidth IoT applications}{}% 5 +\BOOKMARK [1][-]{section.4}{Experimental setup}{}% 6 +\BOOKMARK [2][-]{subsection.4.1}{IoT Part}{section.4}% 7 +\BOOKMARK [2][-]{subsection.4.2}{Network Part}{section.4}% 8 +\BOOKMARK [2][-]{subsection.4.3}{Cloud Part}{section.4}% 9 +\BOOKMARK [1][-]{section.5}{Evaluation}{}% 10 +\BOOKMARK [2][-]{subsection.5.1}{IoT and Network Power Consumption}{section.5}% 11 +\BOOKMARK [2][-]{subsection.5.2}{Cloud Energy Consumption}{section.5}% 12 +\BOOKMARK [1][-]{section.6}{End-to-End Consumption Model}{}% 13 +\BOOKMARK [1][-]{section.7}{Conclusion}{}% 14 +\BOOKMARK [1][-]{section*.2}{References}{}% 15 diff --git a/2019-CloudCom.pdf b/2019-CloudCom.pdf new file mode 100644 index 0000000..68a1d22 Binary files /dev/null and b/2019-CloudCom.pdf differ diff --git a/2019-ICA3PP.org b/2019-ICA3PP.org index dd4b734..a87c9fc 100644 --- a/2019-ICA3PP.org +++ b/2019-ICA3PP.org @@ -1196,7 +1196,7 @@ Our usecase: for one sensor data300=data%>%filter(nbSensors==300)%>%mutate(energy=mean(energy)) %>% slice(1L) dataCloud=rbind(data20,data100,data300)%>%mutate(sensorsNumber=nbSensors)%>%mutate(type="Cloud")%>%select(sensorsNumber,energy,type) dataCloud=bind_rows(dataCloud,tibble(sensorsNumber=1,energy=approx(data20,data100,1),type="Cloud")) - dataCloud=dataCloud%>%mutate(energy=energy/7) # Divide by 7 because 14 core so 1 machine can host 14 vm but we use redundancy (2VM for 1app) + dataCloud=dataCloud%>%mutate(energy=energy/8) # Divide by 8 because 16 core so 1 machine can host 16 vm but we use redundancy (2VM for 1app) # Network data=loadData("./logs/ns3/last/data.csv") @@ -1225,12 +1225,16 @@ Our usecase: for one sensor xlab("Sensors Number")+ylab("Power Consumption (W)")+guides(fill=guide_legend(title="System Part")) p=applyTheme(p)+theme(text = element_text(size=16)) ggsave("plots/final.png",dpi=90,width=8,height=5.5) + write.csv(last_plot()$data,file=paste0("/home/loic/aa",".csv")) #+END_SRC #+RESULTS: [[file:plots/final.png]] + + + Impact of vm size #+BEGIN_SRC R :noweb yes :results graphics :noweb yes :file plots/vmSize-cloud.png <> @@ -1343,7 +1347,7 @@ Our usecase: for one sensor p=applyTheme(p) ggsave("plots/sendInterval-cloud.png",dpi=120,height=3,width=6) #+END_SRC - + #+RESULTS: [[file:plots/sendInterval-cloud.png]] diff --git a/2019-ICA3PP.tex b/2019-ICA3PP.tex new file mode 100644 index 0000000..e4de9ce --- /dev/null +++ b/2019-ICA3PP.tex @@ -0,0 +1,717 @@ +% Intended LaTeX compiler: pdflatex +\documentclass[conference]{llncs} + \usepackage{hyperref} +\usepackage{booktabs} +\usepackage{subfigure} +\usepackage{graphicx} +\usepackage{xcolor} +\author{ +Loic Guegan and +Anne-Cécile Orgerie\\ +} +\institute{Univ Rennes, Inria, CNRS, IRISA, Rennes, France\\ +Emails: loic.guegan@irisa.fr, anne-cecile.orgerie@irisa.fr +} +\date{\today} +\title{Estimating the end-to-end energy consumption of low-bandwidth IoT applications for WiFi devices} +\hypersetup{ + pdfauthor={}, + pdftitle={Estimating the end-to-end energy consumption of low-bandwidth IoT applications for WiFi devices}, + pdfkeywords={}, + pdfsubject={}, + pdfcreator={Emacs 26.2 (Org mode 9.1.9)}, + pdflang={English}} +\begin{document} + +\maketitle +\newcommand{\hl}[1]{\textcolor{red}{#1}} + +\begin{abstract} +Information and Communication Technology takes a growing part in the +worldwide energy consumption. One of the root causes of this increase +lies in the multiplication of connected devices. Each object of the +Internet-of-Things often does not consume much energy by itself. Yet, +their number and the infrastructures they require to properly work +have leverage. In this paper, we combine simulations and real +measurements to study the energy impact of IoT devices. In particular, +we analyze the energy consumption of Cloud and telecommunication +infrastructures induced by the utilization of connected devices, And +we propose an end-to-end energy consumption model for these devices. +\end{abstract} + + +\section{Introduction} +\label{sec:org3cd850c} +In 2018, Information and Communication Technology (ICT) was estimated +to absorb around 3\% of the global energy consumption +\cite{ShiftProject}. This consumption is estimated to grow at a rate +of 9\% per year \cite{ShiftProject}. This alarming growth is explained +by the fast emergence of numerous applications and new ICT +devices. These devices supply services for smart building, smart +factories and smart cities for instance. Through connected sensors +producing data, actuators interacting with their environment and +communication means -- all being parts of the Internet of Things (IoT) +-- they provide optimized decisions. + +This increase in number of devices implies an increase in the energy +needed to manufacture and utilize them. Yet, the overall energy bill +of IoT also comprises indirect costs, as it relies on computing and +networking infrastructures that consume energy to enable smart +services. Indeed, IoT devices communicate with Cloud computing +infrastructures to store, analyze and share their data. + +In February 2019, a report by Cisco stated that ``IoT connections will +represent more than half (14.6 billion) of all global connected +devices and connections (28.5 billion) by 2022" \cite{Cisco2019}. This +will represent more than 6\% of global IP traffic in 2022, against 3\% +in 2017 \cite{Cisco2019}. This increasing impact of IoT devices on +Internet connections induces a growing weight on ICT energy +consumption. + +The energy consumption of IoT devices themselves is only the top of +the iceberg: their use induce energy costs in communication and cloud +infrastructures. In this paper, we estimate the overall energy +consumption of an IoT device environment by combining simulations and +real measurements. We focus on a given application with low bandwidth +requirement and we evaluate its overall energy consumption: from the +device, through telecommunication networks, and up to the Cloud data +center hosting the application. From this analysis, we derive an +end-to-end energy consumption model that can be used to assess the +consumption of other IoT devices. + +While some IoT devices produce a lot of data, like smart vehicles for +instance, many others generate only a small amount of data, like smart +meters. However, the scale matters here: many small devices can end up +producing big data volumes. As an example, according to a report +published by Sandvine in October 2018, the Google Nest Thermostat is +the most significant IoT device in terms of worldwide connections: it +represents 0.16\% of all connections, ranging 55th on the list of +connections \cite{Sandvine2018}. As a comparison, the voice assistants +Alexa and Siri are respectively 97th and 102nd with 0.05\% of all +connections \cite{Sandvine2018}. This example highlights the growing +importance of low-bandwidth IoT applications on Internet +infrastructures, and consequently on their energy consumption. + +In this paper, we focus on IoT devices for low-bandwidth applications +such as smart meters or smart sensors. These devices send few +data periodically to cloud servers, either to store them or to get +computing power and take decisions. This is a first step towards a +comprehensive characterization of the global IoT energy +footprint. While few studies address the energy consumption of +high-bandwidth IoT applications \cite{li_end--end_2018}, to the best +of our knowledge, none of them targets low-bandwidth applications, +despite their growing importance on the Internet infrastructures. + +Low-bandwidth IoT applications, such as the Nest Thermostat, often +relies on sensors powered by batteries. For such sensors, reducing +their energy consumption is a critical target. Yet, we argue that +end-to-end energy models are required to estimate the overall impact +of IoT devices, and to understand how to reduce their complete energy +consumption. Without such models, one could optimize the consumption +of on-battery devices at a heavier cost for cloud servers and +networking infrastructures, resulting on an higher overall energy +consumption. Using end-to-end models could prevent these unwanted +effects. + +Our contributions include: +\begin{itemize} +\item a characterization of low-bandwidth IoT applications; +\item an analysis of the energy consumption of a low-bandwidth IoT +application including the energy consumption of the WiFi IoT device +and the consumption induced by its utilization on the Cloud and +telecommunication infrastructures; +\item an end-to-end energy model for low-bandwidth IoT applications +relying on WiFi devices. +\end{itemize} + +The paper is organized as follows. Section \ref{sec:sota} presents the +state of the art. The low-bandwidth IoT application is characterized +in Section \ref{sec:usec}, and details on its architecture are +provided in Section \ref{sec:model}. Section \ref{sec:eval} provides +our experimental results combining real measurements and +simulations. Section \ref{sec:discuss} discusses the key findings an +the end-to-end energy model. Finally, Section \ref{sec:cl} concludes +this work and presents future work. + + + +\section{Related Work} +\label{sec:org78a494a} +\label{sec:sota} +\subsection{Energy consumption of IoT devices} +\label{sec:orgb12df93} +The multiplication of smart devices and smart applications pushes the +limits of Internet: IoT is now used everywhere for home automation, +smart agriculture, e-health, smart cities, logistics, smart grids, +smart buildings, etc. \cite{Wang2016,Ejaz2017,Minoli2017}. IoT devices +are typically used to optimize processes and the envisioned +application domains include the energy distribution and management. It +can for instance help the energy management of product life-cycle +\cite{Tao2016}. Yet, few studies address the impact of IoT itself on +global energy consumption \cite{jalali_fog_2016,li_end--end_2018} or +CO2 emissions \cite{Sarkar2018}. + +The underlying architecture of these smart applications usually +includes sensing devices, cloud servers, user applications and +telecommunication networks. Concerning the computing part, the cloud +servers can either be located on Cloud data centers, on Fog +infrastructures located at the network edge, or on home gateways +\cite{Wang2016}. Various network technologies are employed by IoT +devices to communicate with their nearby gateway; either wired +networks with Ethernet or wireless networks: WiFi, Bluetooth, Near +Field Communication (NFC), ZigBee, cellular network (like 3G, LTE, 4G), +Low Power Wide Area Network (LPWAN), +etc. \cite{Samie2016,Gray2015}. The chosen technology depends on the +smart device characteristics and the targeted communication +performance. The Google Nest Thermostat can for instance use WiFi, +802.15.4 and Bluetooth \cite{Nest}. In this paper, we focus on WiFi as +it is broadly available and employed by IoT devices +\cite{Samie2016,ns3-energywifi}. + +Several works aim at reducing the energy consumption of the device +transmission \cite{Andres2017} or improving the energy efficiency of +the access network technologies \cite{Gray2015}. An extensive +literature exists on increasing the lifetime of battery-based wireless +sensor networks \cite{Wang2016}. Yet, IoT devices present more +diversity than typical wireless sensors in terms of hardware +characteristics, communication means and data production patterns. + +Based on real measurements, previous studies have proposed energy +models for IoT devices. Yet, these models are specific to a given kind +of IoT device or a given transmission technology. +Martinez et al. provide energy consumption measurements for wireless +sensor networks using SIGFOX transmissions and employed for +smart-parking systems \cite{Martinez2015}. Wu et al. implement an +energy model for WiFi devices in the well-known ns3 network simulator +\cite{ns3-energywifi}. + + +\subsection{Energy consumption of network and cloud infrastructures} +\label{sec:org40352c8} +IoT architecture rely on telecommunication networks and Cloud +infrastructures to provide services. The data produced by IoT devices +are stored and exploited by servers located either in Cloud data +centers or Fog edge sites. While studies exist on the energy +consumption of network and cloud infrastructures in general +\cite{Ehsan}, they do not consider the specific case of IoT devices. +To the best of our knowledge, no study estimates the direct impact of +IoT applications on the energy consumption of these infrastructures. + +Most work focusing on energy consumption, Cloud architecture and IoT +applications tries to answer the question: where to locate data +processing in order to save energy +\cite{jalali_fog_2016}, to reduce the CO2 impact \cite{Sarkar2018}, or +to optimize renewable energy consumption \cite{li_end--end_2018}. + +In both cases, the network and cloud infrastructures, attributing the +energy consumption to a given user or application is a challenging +task. The complexity comes from the shared nature of these +infrastructures: a given Ethernet port in the core of the network +processes many packets coming from a high number of sources +\cite{jalali_fog_2016}. Moreover, the employed equipment is not power +proportional: servers and routers consume consequent amounts of +energy while being idle +\cite{mahadevan_power_2009,li_end--end_2018}. +The power consumed by a device is divided into two parts: a dynamic +part that varies with traffic or amount of computation to process, and +a static part that is constant and dissipated even while being idle +\cite{Ehsan}. This static part implies that a consequent energy cost +of running an application on a server is due to the device being +simply powered on. Consequently, sharing these static energy costs +among all the concerned users requires an end-to-end model +\cite{li_end--end_2018}. + +In this paper, we focus on IoT devices using WiFi transmission and +generating low data volumes. Our model, extracted from real +measurements and simulations, can be adapted to other kinds of devices +and transmission technologies. + + + +\section{Characterization of low-bandwidth IoT applications} +\label{sec:orgfab80c8} +\label{sec:usec} + +In this section, we detail the characteristics of the considered IoT +application. While the derived model is more generic, we focus on a +given application to obtain a precise use-case with accurate power +consumption measurements. + +The Google Nest Thermostat relies on five sensors: temperature, +humidity, near-field activity, far-field activity and ambient light +\cite{Nest}. Periodical measurements, sent through wireless +communications on the Internet, are stored on Google data centers and +processed to learn the home inhabitants habits. The learned behavior +is employed to automatically adjust the home temperature managed by +heating and cooling systems. + +\begin{figure} + \centering + \includegraphics[width=0.5\linewidth]{./plots/home.png} + \caption{Overview of IoT devices.} + \label{fig:IoTdev} +\end{figure} + +Each IoT device senses periodically its environment. Then, it sends +the produced data through WiFi (in our context) to its gateway or +Access Point (AP). The AP is in charge of transmitting the data to the +cloud using the Internet. Figure \ref{fig:IoTdev} illustrates this +architecture. Several IoT devices can share the same AP in a +home. We consider low-bandwidth applications where devices produces +several network packets during each sensing period. The transmitting +frequency can vary from one to several packet sent per minute +\cite{Cisco2019}. + +We consider that the link between the AP and the Cloud is composed of +several network switches and routers using Ethernet as shown in Figure +\ref{fig:parts}. The number of routers on the path depends on the +location of the server, either in a Cloud data center or in a Fog site +at the edge of the network. + +We assume that the server hosting the application data for the users +belongs to a shared cloud facility with classical service level +agreement (SLA). The facility provides redundant storage and computing +means as virtual machines (VMs). A server can host several VMs at the +same time. + +\begin{figure} + \centering + \includegraphics[width=0.6\linewidth]{./plots/parts2.png} + \caption{Overview of the IoT architecture.} + \label{fig:parts} +\end{figure} + +In the following, we describe the experimental setup, the results and +the end-to-end model. For all these steps, we decompose the overall +IoT architecture into three parts: the IoT device part, the networking +part and the cloud part, as displayed on Figure \ref{fig:parts}. + + +\section{Experimental setup} +\label{sec:org7832488} +\label{sec:model} +In this section, we describe the experimental setup employed to +acquire energy measurements for each of the three parts of our +system model. The IoT and the network parts are modeled +through simulations. The Cloud part is modeled using real +servers connected to wattmeters. In this way, it is possible to +evaluate the end-to-end energy consumption of the system. + +\subsection{IoT Part} +\label{sec:org844d4c9} +In the first place, the IoT part is composed of several sensors connected to an Access Point (AP) +which form a cell. This cell is studied using the ns3 network +simulator. In the experimental scenario, we setup +between 5 and 15 sensors connected to the AP using WiFi 5GHz 802.11n. The node are placed +randomly in a rectangle of \(400m^2\) around the AP which corresponds +to a typical use case for a home environment. All +the cell nodes employ the default WIFI energy model provided by ns3. The different +energy values used by the energy model are provided in Table \ref{tab:params}. These parameters +were extracted from previous work\cite{halperin_demystifying_nodate,li_end--end_2018} On +IEEE 802.11n. Besides, we suppose that the energy source of each +nodes is not limited during the experiments. Thus each node +can communicate until the end of all the simulations. + +As a scenario, sensors send 192 bits packets to the AP composed of: \textbf{1)} A 128 bits +sensors id \textbf{2)} A 32 bits integer representing the temperature \textbf{3)} An integer +timestamp representing the temperature sensing date. They are stored as time series. The data are +transmitted immediately at each sensing interval \(I\) that we vary from 1s to 60s. Finally, the AP is in +charge of relaying data to the cloud via the network part. + +\begin{table}[] + \centering + \caption{Simulations Energy Parameters} + \label{tab:wifi-energy} + \subtable[IoT part]{ + \begin{tabular}{@{}lr@{}} + Parameter & Value \\ \midrule + Supply Voltage & 3.3V \\ + Tx & 0.38A \\ + Rx & 0.313A \\ + Idle & 0.273A \\ \bottomrule + \end{tabular}} + \hspace{0.3cm} + \subtable[Network part]{ + \label{tab:net-energy} + \begin{tabular}{@{}lr@{}} + Parameter & Value \\ \midrule + Idle & 0.00001W \\ + Bytes (Tx/Rx) & 3.4nJ \\ + Pkt (Tx/Rx) & 192.0nJ \\ \bottomrule + \end{tabular} + } + \label{tab:params} +\end{table} + +\subsection{Network Part} +\label{sec:org2f479bf} +The network part represents the a network section starting from the AP to the Cloud excluding the +server. It is also modeled into ns3. We consider the server to be 9 hops away from the AP with a +typical round-trip latency of 100ms from the AP to the server +\cite{li_end--end_2018}. Each node from the AP to the Cloud +is a network switch with static and dynamic network energy consumption. The first 8 +hops are edge switches and the last one is consider to be a core router as mentioned in +\cite{jalali_fog_2016}. ECOFEN \cite{orgerie_ecofen:_2011} is used to model the energy +consumption of the network part. ECOFEN is an ns3 network energy module dedicated to wired +networks. It is based on an energy-per-bit and energy-per-packet +model for the dynamic energy consumption +\cite{sivaraman_profiling_2011,Serrano2015}, and it includes also a static energy consumption. +The different values used to instantiate the ECOFEN energy model for the +network part are shown in left part of Table \ref{tab:params} and come from previous work +\cite{cornea_studying_2014-1}. + +\subsection{Cloud Part} +\label{sec:orgeacf775} +Finally, to measure the energy consumed by the Cloud part, we use a real server from the large-scale +test-bed Grid'5000. Grid'5000 provides clusters composed of several nodes which +are connected to wattmeters. The wattmeters provide 50 +instantaneous power measurements per second and per server. This +way, we can benefit from real energy measurements. The server used +in the experiment embeds two Intel Xeon E5-2620 v4 processors with +64 GB of RAM and 600GB +of disk space on a Linux based operating system. This server is configured to use KVM as +virtualization mechanism. We deploy a classical Debian x86\_64 distribution on the Virtual Machine +(VM) along with a MySQL database. We use different amounts of allocated memory for the VM namely +1024MB/2048MB/4096MB to highlight its effects on the server energy +consumption. The server only hosts this VM in order to easily isolate its +power consumption. + +\begin{figure} + \centering + \includegraphics[width=0.45\linewidth]{./plots/g5k-xp.png} + \caption{Grid'5000 experimental setup.} + \label{fig:g5kExp} +\end{figure} + +The data sent by the IoT devices are simulated using another +server from the same cluster. This server is in charge of sending +the data packets to the VM hosting the application in order to fill +its database. In the following, each data packet coming from an IoT +device and addressed to the application VM is called a request. Consequently, it is easy to vary the +different application characteristics namely: \textbf{1)} The number +of requests, to virtually +add/remove sensors \textbf{2)} The requests interval, to study the +impact of the transmitting frequency. Figure \ref{fig:g5kExp} presents this simulation +setup. + + + + +\section{Evaluation} +\label{sec:org21ac4f0} +\label{sec:eval} + +\subsection{IoT and Network Power Consumption} +\label{sec:org5a488af} +In this section, we analyze the experimental results. + In a first place, we start by studying the impact of the sensors' transmission frequency on their + energy consumption. To this end, we run several simulations in ns3 with 15 sensors using + different transmission frequencies. The results provided by Table + \ref{tab:sensorsSendIntervalEffects} show that the transmission frequency has a very low impact + on the energy consumption and on the average end-to-end application delay. It has an impact of + course, but it is very limited. This due to the fact that in such a scenario with very small + number of communications spread over the time, sensors don't have to contend for accessing to the + Wifi channel. + +% Please add the following required packages to your document preamble: +% \usepackage{booktabs} +\begin{table*}[] +\centering +\caption{Sensors transmission interval effects with 15 sensors} +\label{tab:sensorsSendIntervalEffects} +\begin{tabular}{@{}lrrrrr@{}} +\toprule +Transmission Interval & 10s & 30s & 50s & 70s & 90s \\ \midrule +Sensor Power & 13.517\hl{94}W & 13.517\hl{67}W & 13.51767W & 13.51767W & 13.517\hl{61}W \\ +Network Power & 0.441\hl{88}W & 0.441\hl{77}W & 0.44171W & 0.44171W & 0.441\hl{71}W \\ +Application Delay & 0.09951s & 0.10021s & 0.10100s & 0.10203s & 0.10202s \\ \bottomrule +\end{tabular} +\end{table*} + + + Previous work \cite{li_end--end_2018} on a similar scenario shows that increasing application + accuracy impacts strongly the energy consumption in the context of data stream analysis. However, + in our case, application accuracy is driven by the sensing interval and thus, the transmission + frequency of the sensors. +In our case with small and sporadic network traffic, these results show that with a reasonable + transmission interval, the energy consumption of the IoT and the + network parts are almost not affected by the + variation of this transmission interval. In fact, transmitted data are not large enough to + leverage the energy consumed by the network. + +We then vary the number of sensors in the Wifi cell. +The Figure \ref{fig:sensorsNumber} represents the energy consumed by each simulated part +according to the number of sensors. It is clear that the energy consumed by the network is the +dominant part. However, if the number of sensors is increasing, the energy consumed by the +network can become smaller than the sensors part. In fact, deploying new +sensors in the cell do not introduce much network load. To this end, sensors energy consumption +can become dominant. + +\begin{figure} + \centering + \includegraphics[width=0.5\linewidth]{./plots/numberSensors-WIFINET.png} + \caption{Analysis of the variation of the number of sensors on the IoT/Network part energy consumption for a transmission interval of 10s.} + \label{fig:sensorsNumber} +\end{figure} + + +\subsection{Cloud Energy Consumption} +\label{sec:orgf1c1df0} +In this end-to-end energy consumption study, cloud accounts for a huge part of the overall energy +consumption. According a report \cite{shehabi_united_2016-1} On United States data center energy +usage, the average Power Usage Effectiveness (PUE) of an hyper-scale data center is 1.2. Thus, in +our analysis, all energy measurement on cloud server will account +for this PUE. It means that the power consumption of the server is multiplied by +the PUE to include the external energy costs like server cooling +and data center facilities \cite{Ehsan}. + +\begin{figure} + \centering + \includegraphics[width=0.8\linewidth]{./plots/vmSize-cloud.png} + \caption{Server power consumption multiplied by the PUE (= 1.2) using 20 sensors sending data every 10s for various VM memory sizes} + \label{fig:vmSize} +\end{figure} + + +Firstly, we analyze the impact of the VM allocated memory on the server energy +consumption. Figure \ref{fig:vmSize} depicts the server energy consumption according to the VM +allocated memory for 20 sensors sending data every 10s. Note that +the horizontal red line represents +the average energy consumption for the considered sample of energy values. We can see that at +each transmission interval, the server faces spikes of energy +consumption. However, the amount of allocated memory to the VM +does not significantly influence the server energy consumption. In +fact, simple database requests do not need any particular +heavy memory accesses and processing time. Thus, remaining experiments are based on VM with 1024MB +of allocated memory. + +Next, we study the effects of increasing the number of sensors on the server energy consumption. +Figure \ref{fig:sensorsNumber-server} presents the results of the average server energy +consumption when varying the number of sensors from 20 to 500, while Figure +\ref{fig:sensorsNumber-WPS} presents the average server energy cost per sensor according to the +number of sensors. These results show a clear linear relation between the number of sensors and +the server energy consumption. Moreover, we can see that the more sensors we have per VM, the +more energy we can save. In fact, since the server's idle power +consumption is high (around 97 Watts), it is more +energy efficient to maximize the number of sensors per server. As shown on Figure +\ref{fig:sensorsNumber-WPS}, a significant amount of energy can be save when passing from 20 to +300 sensors per VM. Note that these measurements are not the row +measurements taken from the wattmeters: they include the PUE +but they are not shared among all the VMs that could be hosted on this +server. So, for the studied server, its static power consumption +(also called idle consumption) is around 83.2 Watts and we consider +a PUE of 1.2, this value is taken from \cite{shehabi_united_2016-1}\}. + +\begin{figure} + \centering + \subfigure[Average server energy consumption multiplied by the PUE (= 1.2)]{ + \includegraphics[width=0.4\linewidth]{./plots/sensorsNumberLine-cloud.png} + \label{fig:sensorsNumber-server} + } + \hspace{0.5cm} + \subfigure[Average sensors energy cost on the server hosting only our VM]{ + \includegraphics[width=0.4\linewidth]{./plots/WPS-cloud.png} + \label{fig:sensorsNumber-WPS} + } + \caption{Server energy consumption multiplied by the PUE (= 1.2) for sensors sending data every 10s} + \label{fig:sensorsNumber-cloud} +\end{figure} + +A last parameter can leverage server energy consumption, namely +sensors transmission interval. In addition +to increasing the application accuracy, sensors transmission frequency increases network traffic and +database accesses. Figure \ref{fig:sensorsFrequency} presents the impact on the server energy +consumption when changing the transmission interval of 50 sensors +to 1s, 10s and 30s. We can see that, the lower sensors transmission +interval is, the more server energy consumption peaks +occur. Therefore, it leads to an increase of the server energy consumption. + +\begin{figure} + \centering + \includegraphics[scale=0.5]{plots/sendInterval-cloud.png} + \caption{Server energy consumption multiplied by the PUE (= 1.2) for 50 sensors sending requests at different transmission interval.} + \label{fig:sensorsFrequency} +\end{figure} + +\section{End-To-End Consumption Model} +\label{sec:org75005f9} +\label{sec:discuss} + +To have an overview of the energy consumed by the overall system, it is important to consider the +end-to-end energy consumption. +We detail here the model used to attribute the energy +consumption of our application for each part of the +architecture. For a given IoT device, we have: +\begin{enumerate} +\item For the IoT part, the entire consumption of the IoT device +belongs to the system's accounted consumption. +\item For the network part, the data packets generated by the IoT +device travel through network switches, routers and ports that +are shared with other traffic. +\item For the cloud part, the VM hosting the data is shared with +other IoT devices belonging to the same application and the +server hosting the VM also hosts other VMs. Furthermore, the +server belongs to a data center and takes part in the overall +energy drawn to cool the server room. +\end{enumerate} + +Concerning the IoT part, we include the entire IoT device power +consumption. Indeed, in our targeted low-bandwidth IoT application, +the sensor is dedicated to this application. From Table \ref{tab:params}, one can +derive that the static power +consumption of one IoT sensor is around 0.9 Watts. Its dynamic part +depends on the transmission frequency. + +Concerning the sharing of the network costs, for each router, we +consider its aggregate bandwidth (on all the ports), its average +link utilization and the share taken by our IoT application. For a +given network device, we compute our share of the static energy +part as follows: + +\[P_{static}^{netdevice} = \frac{P_{static}^{device} \times Bandwidth^{application}}{AggregateBandwidth^{device} +\times LinkUtilization^{device}}\] + +where \(P_{static}^{device}\) is the static power consumption of the +network device (switch fabrics for instance or gateway), +\(Bandwidth^{application }\) Is the bandwidth used by our IoT application, +\(AggregateBandwidth^{device }\) is the overall aggregated bandwidth of the +network device on all its ports, and \(LinkUtilization^{device}\) is the +effective link utilization percentage. The \(Bandwidth^{application }\) +depends on the transmission frequency in our use-case. +The formula includes the +link utilization in order to charge for the effective energy cost +per trafic and not for the theoretical upper bound which is the +link bandwidth. Indeed, using such an upper bound leads to greatly +underestimate our energy part, since link utilization typically +varies between 5 to 40\% \cite{Hassidim2013,Zhang2016}. + +Similarly, for each network port, we take the share attributable to +our application: the ratio of our bandwidth utilization over the +port bandwidth multiplied by the link utilization and the overall +static power consumption of the port. Table \ref{tab:netbidules} +summarizes the parameters used in our model, they are taken from +\cite{mahadevan_power_2009,Hassidim2013}. These are the parameters +used in our formula to compute the values that we used in the +simulations and that are presented in left part of Table \ref{tab:params}. + + + +\begin{table}[] + \centering + \caption{Network Devices Parameters} + \label{tab:netbidules} + \begin{tabular}{l|l} + Device & ~Parameters \\ \midrule + Gateway & ~Static power = 8.3 Watts, Bandwidth = 54Mbps, Utilization = 10\% \\ + Core router & ~Static power = 555 Watts, 48 ports of 1 Gbps, Utilization = 25\% \\ + Edge switch~ & ~Static power = 150 Watts, 48 ports of 1 Gbps, Utilization = 25\% \\ + \bottomrule + \end{tabular} +\end{table} + + + +For the sharing of the Cloud costs, we take into account the number +of VMs that a server can host, the CPU utilization of a VM and the +PUE. For a given Cloud server hosting our IoT application, we +compute our share of the static energy part as follows: + +\[P_{static}^{Cloudserver} = \frac{P_{static}^{server} \times PUE^{DataCenter}}{HostedVMs^{server}}\] + +Where \(P_{static}^{server}\) is the static power consumption of the +server, \(PUE^{DataCenter}\) is the data center PUE, and +\(HostedVMs^{server}\) is the number of VMs a server can host. This last +parameter should be adjusted in the case of VMs with multiple +virtual CPUs. We do not +consider here over-commitment of Cloud servers. Yet, the dynamic +energy part is computed with the real dynamic measurements, so it +accounts for VM over-provisioning and resource under-utilization. + +In our case, the Cloud server has 14 cores, which corresponds to +the potential hosting of 14 small VMs with one virtual CPU each, +and each vCPU is pinned to a server core. We consider that for +fault-tolerance purpose, the IoT application has a replication +factor of 2, meaning that two cloud servers store its database. + +The Figure \ref{fig:end-to-end} represents the end-to-end system +energy consumption using the model described above while varying +the number of sensors for a transmission interval of 10 +seconds. The values are extracted from the experiments presented in +the previous section. + +\begin{figure} + \centering + \hspace{1cm} + \includegraphics[scale=0.35]{plots/final.png} + \label{fig:end-to-end} + \caption{End-to-end network energy consumption using sensors interval of 10s} +\end{figure} + + +Note that, for small-scale systems, with WiFi IoT devices, the IoT +sensor part is dominant in the overall energy consumption. Indeed, +the IoT application induces a very small cost on Cloud and network +infrastructures compared to the IoT device cost. But, our model +assumes that a single VM is handling multiple users (up to 300 +sensors), thus being energy-efficient. Conclusions would be +different with one VM per user in the case of no over-commitment on +the Cloud side. For the network infrastructure, in our case of +low-bandwidth utilization (one data packet every 10 seconds), the +impact is almost negligible. + +Another way of looking at these results is to observe that only for +a high number of sensors (more than 300), the power consumption of Cloud and +network parts start to be negligible (few percent). It means that, +if IoT applications handle clients one by one (i.e. one VM per +client), the impact is high on cloud and network part if they have +only few sensors. The energy efficiency is really poor for only few +devices: with 20 IoT sensors, the overall energy cost to handle these +devices is almost doubled compared to the energy consumption of the IoT devices +themselves. Instead of increasing the number of sensors, which +would result in a higher overall energy consumption, one should +focus on reducing the energy consumption of IoT devices, especially +WiFi devices which are common due to WiFi availability +everywhere. One could also focus on improving the energy cost of +Cloud and network infrastructure for low-bandwidth applications and +few devices. + + + +\section{Conclusion} +\label{sec:orgb2daa12} +\label{sec:cl} + +Information and Communication Technology takes a growing part in the +worldwide energy consumption. One of the root causes of this increase +lies in the multiplication of connected devices. Each object of the +Internet-of-Things often does not consume much energy by itself. Yet, +their number and the infrastructures they require to properly work +have leverage. + +In this paper, we combine simulations and real +measurements to study the energy impact of IoT devices. In particular, +we analyze the energy consumption of Cloud and telecommunication +infrastructures induced by the utilization of connected devices. +Through the fine-grain analysis of a given low-bandwidth IoT device +periodically sending data to a Cloud server using WiFi, +we propose an end-to-end energy consumption model. +This model provides insights on the hidden part of the iceberg: the +impact of IoT devices on the energy consumption of Cloud and network +infrastructures. On our use-case, we show that for a given sensor, its +larger energy consumption is on the sensor part. But the impact on the +Cloud and network part is huge when using only few sensors with +low-bandwidth applications. +Consequently, with the +IoT exploding growth, it becomes necessary to improve the energy +efficiency of applications hosted on Cloud infrastructures and of IoT devices. +Our future work includes studying other types of IoT wireless +transmission techniques that would be more energy-efficient. We also +plan to study other +IoT applications in order to increase the applicability of our model +and provide advice for increasing the energy-efficiency of IoT infrastructures. + + + +\bibliographystyle{IEEEtran} +\bibliography{references} +\end{document} diff --git a/logs/ns3/logs-on-g5k-try1/plots/plots.tex b/logs/ns3/logs-on-g5k-try1/plots/plots.tex new file mode 100644 index 0000000..ea553c6 --- /dev/null +++ b/logs/ns3/logs-on-g5k-try1/plots/plots.tex @@ -0,0 +1,47 @@ +% Created 2019-05-06 lun. 12:03 +% Intended LaTeX compiler: pdflatex +\documentclass[11pt]{article} +\usepackage[utf8]{inputenc} +\usepackage[T1]{fontenc} +\usepackage{graphicx} +\usepackage{grffile} +\usepackage{longtable} +\usepackage{wrapfig} +\usepackage{rotating} +\usepackage[normalem]{ulem} +\usepackage{amsmath} +\usepackage{textcomp} +\usepackage{amssymb} +\usepackage{capt-of} +\usepackage{hyperref} +\usepackage{fullpage} +\date{\today} +\title{Analysis} +\hypersetup{ + pdfauthor={}, + pdftitle={Analysis}, + pdfkeywords={}, + pdfsubject={}, + pdfcreator={Emacs 26.2 (Org mode 9.1.9)}, + pdflang={English}} +\begin{document} + +\maketitle +\begin{center} +\begin{tabular}{lr} +Parameters & Values\\ +\hline +sensorsPktSize & 5 bytes\\ +sensorsSendInterval & 10s\\ +sensorsNumber & 10\\ +nbHop & 10\\ +linksBandwidth & 10Mbps\\ +linksLatency & 2ms\\ +\end{tabular} +\newline +\end{center} +\includegraphics[width=0.5\linewidth]{BW-linksBandwidth_totalEnergy.png} +\includegraphics[width=0.5\linewidth]{NBSENSORS-sensorsNumber_totalEnergy.png} +\includegraphics[width=0.5\linewidth]{LATENCY-linksLatency_totalEnergy.png} +\includegraphics[width=0.5\linewidth]{NBHOP-nbHop_totalEnergy.png} +\end{document} diff --git a/logs/ns3/logs-on-my-machine-try1/plots/plots.tex b/logs/ns3/logs-on-my-machine-try1/plots/plots.tex new file mode 100644 index 0000000..3b7f228 --- /dev/null +++ b/logs/ns3/logs-on-my-machine-try1/plots/plots.tex @@ -0,0 +1,47 @@ +% Created 2019-05-06 lun. 11:10 +% Intended LaTeX compiler: pdflatex +\documentclass[11pt]{article} +\usepackage[utf8]{inputenc} +\usepackage[T1]{fontenc} +\usepackage{graphicx} +\usepackage{grffile} +\usepackage{longtable} +\usepackage{wrapfig} +\usepackage{rotating} +\usepackage[normalem]{ulem} +\usepackage{amsmath} +\usepackage{textcomp} +\usepackage{amssymb} +\usepackage{capt-of} +\usepackage{hyperref} +\usepackage{fullpage} +\date{\today} +\title{Analysis} +\hypersetup{ + pdfauthor={}, + pdftitle={Analysis}, + pdfkeywords={}, + pdfsubject={}, + pdfcreator={Emacs 26.2 (Org mode 9.1.9)}, + pdflang={English}} +\begin{document} + +\maketitle +\begin{center} +\begin{tabular}{lr} +Parameters & Values\\ +\hline +sensorsPktSize & 5 bytes\\ +sensorsSendInterval & 10s\\ +sensorsNumber & 10\\ +nbHop & 10\\ +linksBandwidth & 10Mbps\\ +linksLatency & 2ms\\ +\end{tabular} +\newline +\end{center} +\includegraphics[width=0.5\linewidth]{BW-linksBandwidth_totalEnergy.png} +\includegraphics[width=0.5\linewidth]{NBSENSORS-sensorsNumber_totalEnergy.png} +\includegraphics[width=0.5\linewidth]{LATENCY-linksLatency_totalEnergy.png} +\includegraphics[width=0.5\linewidth]{NBHOP-nbHop_totalEnergy.png} +\end{document} diff --git a/plots/WPS-cloud.png b/plots/WPS-cloud.png index 88a4a99..8f5908d 100644 Binary files a/plots/WPS-cloud.png and b/plots/WPS-cloud.png differ diff --git a/plots/final.png b/plots/final.png index a49be18..fce0002 100644 Binary files a/plots/final.png and b/plots/final.png differ diff --git a/plots/plots.tex b/plots/plots.tex new file mode 100644 index 0000000..3e63623 --- /dev/null +++ b/plots/plots.tex @@ -0,0 +1,51 @@ +% Created 2019-05-22 mer. 09:13 +% Intended LaTeX compiler: pdflatex +\documentclass[11pt]{article} +\usepackage[utf8]{inputenc} +\usepackage[T1]{fontenc} +\usepackage{graphicx} +\usepackage{grffile} +\usepackage{longtable} +\usepackage{wrapfig} +\usepackage{rotating} +\usepackage[normalem]{ulem} +\usepackage{amsmath} +\usepackage{textcomp} +\usepackage{amssymb} +\usepackage{capt-of} +\usepackage{hyperref} +\usepackage{fullpage} +\date{\today} +\title{Analysis} +\hypersetup{ + pdfauthor={}, + pdftitle={Analysis}, + pdfkeywords={}, + pdfsubject={}, + pdfcreator={Emacs 26.2 (Org mode 9.1.9)}, + pdflang={English}} +\begin{document} + +\maketitle +\begin{center} +\begin{tabular}{lr} +Parameters & Values\\ +\hline +sensorsPktSize & bytes\\ +sensorsSendInterval & s\\ +sensorsNumber & \\ +nbHop & \\ +linksBandwidth & Mbps\\ +linksLatency & ms\\ +\end{tabular} +\newline +\end{center} +\includegraphics[width=0.5\linewidth]{SENDINTERVAL-sensorsSendInterval_networkEnergy.png} +\includegraphics[width=0.5\linewidth]{SENDINTERVAL-sensorsSendInterval_sensorsEnergy.png} +\includegraphics[width=0.5\linewidth]{SENSORSPOS-positionSeed_avgDelay.png} +\includegraphics[width=0.5\linewidth]{NBSENSORS-sensorsNumber_totalEnergy.png} +\includegraphics[width=0.5\linewidth]{sensorsSendInterval-net.png} +\includegraphics[width=0.5\linewidth]{SENSORSPOS-positionSeed_totalEnergy.png} +\includegraphics[width=0.5\linewidth]{final.png} +\includegraphics[width=0.5\linewidth]{sensorsSendInterval-wifi.png} +\end{document} diff --git a/src/ns3/plots/plots.tex b/src/ns3/plots/plots.tex new file mode 100644 index 0000000..074d33c --- /dev/null +++ b/src/ns3/plots/plots.tex @@ -0,0 +1,52 @@ +% Created 2019-05-15 mer. 15:24 +% Intended LaTeX compiler: pdflatex +\documentclass[11pt]{article} +\usepackage[utf8]{inputenc} +\usepackage[T1]{fontenc} +\usepackage{graphicx} +\usepackage{grffile} +\usepackage{longtable} +\usepackage{wrapfig} +\usepackage{rotating} +\usepackage[normalem]{ulem} +\usepackage{amsmath} +\usepackage{textcomp} +\usepackage{amssymb} +\usepackage{capt-of} +\usepackage{hyperref} +\usepackage{fullpage} +\date{\today} +\title{Analysis} +\hypersetup{ + pdfauthor={}, + pdftitle={Analysis}, + pdfkeywords={}, + pdfsubject={}, + pdfcreator={Emacs 26.2 (Org mode 9.1.9)}, + pdflang={English}} +\begin{document} + +\maketitle +\begin{center} +\begin{tabular}{lr} +Parameters & Values\\ +\hline +sensorsPktSize & 5 bytes\\ +sensorsSendInterval & 10s\\ +sensorsNumber & 10\\ +nbHop & 10\\ +linksBandwidth & 10Mbps\\ +linksLatency & 2ms\\ +\end{tabular} +\newline +\end{center} +\includegraphics[width=0.5\linewidth]{SENDINTERVAL-sensorsSendInterval_networkEnergy.png} +\includegraphics[width=0.5\linewidth]{SENDINTERVAL-sensorsSendInterval_sensorsEnergy.png} +\includegraphics[width=0.5\linewidth]{SENSORSPOS-positionSeed_avgDelay.png} +\includegraphics[width=0.5\linewidth]{NBSENSORS-sensorsNumber_totalEnergy.png} +\includegraphics[width=0.5\linewidth]{SENDINTERVAL-sensorsSendInterval_totalEnergy.png} +\includegraphics[width=0.5\linewidth]{SENDINTERVAL-sensorsSendInterval_energyWifi.png} +\includegraphics[width=0.5\linewidth]{sensorsSendInterval-net.png} +\includegraphics[width=0.5\linewidth]{SENSORSPOS-positionSeed_totalEnergy.png} +\includegraphics[width=0.5\linewidth]{sensorsSendInterval-wifi.png} +\end{document}