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etat de l'art un peu avancé
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@ -36,21 +36,6 @@ Cisco, ``{Cisco Visual Networking Index: Forecast and Trends, 2017–2022,
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Sandvine, ``{The Global Internet Phenomena Report},''
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\url{https://www.sandvine.com/phenomena}, Oct. 2018.
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\bibitem{Wang2016}
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K.~{Wang}, Y.~{Wang}, Y.~{Sun}, S.~{Guo}, and J.~{Wu}, ``{Green Industrial
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Internet of Things Architecture: An Energy-Efficient Perspective},''
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\emph{IEEE Communications Magazine}, vol.~54, no.~12, pp. 48--54, 2016.
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\bibitem{Ejaz2017}
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W.~Ejaz, M.~Naeem, A.~Shahid, A.~Anpalagan, and M.~Jo, ``Efficient energy
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management for the internet of things in smart cities,'' \emph{IEEE
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Communications Magazine}, vol.~55, no.~1, pp. 84--91, 2017.
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\bibitem{halperin_demystifying_nodate}
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D.~Halperin, B.~Greenstein, A.~Sheth, and D.~Wetherall,
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``\BIBforeignlanguage{en}{Demystifying 802.11n {Power} {Consumption}},''
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p.~5.
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\bibitem{li_end--end_2018}
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\BIBentryALTinterwordspacing
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Y.~Li, A.-C. Orgerie, I.~Rodero, B.~L. Amersho, M.~Parashar, and J.-M. Menaud,
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@ -61,6 +46,59 @@ Y.~Li, A.-C. Orgerie, I.~Rodero, B.~L. Amersho, M.~Parashar, and J.-M. Menaud,
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\url{https://linkinghub.elsevier.com/retrieve/pii/S0167739X17314309}
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\BIBentrySTDinterwordspacing
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\bibitem{Wang2016}
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K.~{Wang}, Y.~{Wang}, Y.~{Sun}, S.~{Guo}, and J.~{Wu}, ``{Green Industrial
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Internet of Things Architecture: An Energy-Efficient Perspective},''
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\emph{IEEE Communications Magazine}, vol.~54, no.~12, pp. 48--54, 2016.
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\bibitem{Samie2016}
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F.~Samie, L.~Bauer, and J.~Henkel, ``Iot technologies for embedded computing: A
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survey,'' in \emph{IEEE/ACM/IFIP International Conference on
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Hardware/Software Codesign and System Synthesis (CODES)}, 2016.
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\bibitem{Ejaz2017}
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W.~Ejaz, M.~Naeem, A.~Shahid, A.~Anpalagan, and M.~Jo, ``Efficient energy
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management for the internet of things in smart cities,'' \emph{IEEE
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Communications Magazine}, vol.~55, no.~1, pp. 84--91, 2017.
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\bibitem{Minoli2017}
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D.~{Minoli}, K.~{Sohraby}, and B.~{Occhiogrosso}, ``{IoT Considerations,
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Requirements, and Architectures for Smart Buildings—Energy Optimization and
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Next-Generation Building Management Systems},'' \emph{IEEE Internet of Things
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Journal}, vol.~4, no.~1, pp. 269--283, 2017.
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\bibitem{Tao2016}
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F.~Tao, Y.~Wang, Y.~Zuo, H.~Yang, and M.~Zhang, ``{Internet of Things in
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product life-cycle energy management},'' \emph{Journal of Industrial
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Information Integration}, vol.~1, pp. 26 -- 39, 2016.
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\bibitem{Gray2015}
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C.~{Gray}, R.~{Ayre}, K.~{Hinton}, and R.~S. {Tucker}, ``{Power consumption of
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IoT access network technologies},'' in \emph{IEEE International Conference on
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Communication Workshop (ICCW)}, 2015, pp. 2818--2823.
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\bibitem{Andres2017}
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P.~{Andres-Maldonado}, P.~{Ameigeiras}, J.~{Prados-Garzon}, J.~J.
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{Ramos-Munoz}, and J.~M. {Lopez-Soler}, ``{Optimized LTE data transmission
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procedures for IoT: Device side energy consumption analysis},'' in \emph{IEEE
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International Conference on Communications Workshops (ICC Workshops)}, 2017,
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pp. 540--545.
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\bibitem{Martinez2015}
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B.~{Martinez}, M.~{Montón}, I.~{Vilajosana}, and J.~D. {Prades}, ``{The Power
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of Models: Modeling Power Consumption for IoT Devices},'' \emph{IEEE Sensors
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Journal}, vol.~15, no.~10, pp. 5777--5789, 2015.
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\bibitem{ns3-energywifi}
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H.~Wu, S.~Nabar, and R.~Poovendran, ``{An Energy Framework for the Network
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Simulator 3 (NS-3)},'' in \emph{International ICST Conference on Simulation
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Tools and Techniques (SIMUTools)}, 2011, pp. 222--230.
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\bibitem{Sarkar2018}
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S.~{Sarkar}, S.~{Chatterjee}, and S.~{Misra}, ``{Assessment of the Suitability
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of Fog Computing in the Context of Internet of Things},'' \emph{IEEE
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Transactions on Cloud Computing}, vol.~6, no.~1, pp. 46--59, 2018.
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\bibitem{jalali_fog_2016}
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\BIBentryALTinterwordspacing
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F.~Jalali, K.~Hinton, R.~Ayre, T.~Alpcan, and R.~S. Tucker,
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@ -70,6 +108,11 @@ F.~Jalali, K.~Hinton, R.~Ayre, T.~Alpcan, and R.~S. Tucker,
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[Online]. Available: \url{http://ieeexplore.ieee.org/document/7439752/}
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\BIBentrySTDinterwordspacing
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\bibitem{halperin_demystifying_nodate}
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D.~Halperin, B.~Greenstein, A.~Sheth, and D.~Wetherall,
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``\BIBforeignlanguage{en}{Demystifying 802.11n {Power} {Consumption}},''
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p.~5.
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\bibitem{orgerie_ecofen:_2011}
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A.~C. Orgerie, L.~Lefèvre, I.~Guérin-Lassous, and D.~M.~L. Pacheco,
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``{ECOFEN}: {An} {End}-to-end energy {Cost} {mOdel} and simulator {For}
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@ -46,17 +46,16 @@ In 2018, Information and Communication Technology (ICT) was estimated
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to absorb around 3% of the global energy consumption
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\cite{ShiftProject}. This consumption is estimated to grow at a rate
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of 9% per year \cite{ShiftProject}. This alarming growth is explained
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by the fast emergence of numerous new applications and new ICT
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by the fast emergence of numerous applications and new ICT
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devices. These devices supply services for smart building, smart
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factories and smart cities for instance, providing optimized decisions
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based on data produced by smart devices. All these connected devices
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constitute the Internet of Things (IoT): connected devices with
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sensors producing data, actuators interacting with their environment
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and communication means.
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factories and smart cities for instance. Through connected devices,
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with sensors producing data, actuators interacting with their
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environment and communication means -- all being parts of the Internet of
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Things (IoT) -- they provide optimized decisions.
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This increase in number of devices implies an increase in the energy
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needed to manufacture and utilize all these devices. Yet, the overall energy
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bill of IoT also comprises indirect costs as it relies on computing and
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needed to manufacture and utilize them. Yet, the overall energy bill
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of IoT also comprises indirect costs, as it relies on computing and
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networking infrastructures that consume energy to enable smart
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services. Indeed, IoT devices communicate with Cloud computing
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infrastructures to store, analyze and share their data.
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@ -94,20 +93,20 @@ importance of low-bandwidth IoT applications on Internet
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infrastructures, and consequently on their energy consumption.
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In this paper, we focus on IoT devices for low-bandwidth applications
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such as smart meters or smart sensors. These applications send few
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such as smart meters or smart sensors. These devices send few
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data periodically to cloud servers, either to store them or to get
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computing power and take decisions. This is a first step towards a
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comprehensive characterization of the IoT energy footprint. While few
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studies address the energy consumption of high-bandwidth IoT
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applications \cite{li_end--end_2018}, to the best of our knowledge,
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none of them targets low-bandwidth applications, despite their growing
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importance on the Internet infrastructures.
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comprehensive characterization of the global IoT energy
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footprint. While few studies address the energy consumption of
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high-bandwidth IoT applications \cite{li_end--end_2018}, to the best
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of our knowledge, none of them targets low-bandwidth applications,
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despite their growing importance on the Internet infrastructures.
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Low-bandwidth IoT applications, such as the Nest Thermostat, often
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relies on sensors powered by batteries. For such sensors, reducing
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their energy consumption is a critical target. Yet, we argue that
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end-to-end energy models are required to estimate the overall impact
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of IoT devices and to understand how to reduce their complete energy
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of IoT devices, and to understand how to reduce their complete energy
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consumption. Without such models, one could optimize the consumption
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of on-battery devices at a heavier cost for cloud servers and
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networking infrastructures, resulting on an higher overall energy
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@ -117,8 +116,8 @@ effects.
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Our contributions include:
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- a characterization of low-bandwidth IoT applications;
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- an analysis of the energy consumption of a low-bandwidth IoT
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application including the energy consumption of the IoT device and
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the consumption induced by its utilization on the Cloud and
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application including the energy consumption of the WiFi IoT device
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and the consumption induced by its utilization on the Cloud and
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telecommunication infrastructures;
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- an end-to-end energy model for low-bandwidth IoT applications.
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@ -136,9 +135,36 @@ this work and presents future work.
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* Related Work
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#+LaTeX: \label{sec:sota}
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** Energy consumption of IoT devices
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Smart apps and devices everywhere
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The multiplication of smart devices and smart applications pushes the
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limits of Internet: IoT is now used everywhere for home automation,
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smart agriculture, smart industry, e-health, smart cities, logistics,
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smart grids, smart buildings,
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etc. \cite{Wang2016,Ejaz2017,Minoli2017}. IoT devices are typically
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used to optimize processes and the envisionned application domains
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include the energy domain, like for instance the energy management of
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product life-cycle \cite{Tao2016}. Yet, few studies adress the impact
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of IoT itself on global energy consumption
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\cite{jalali_fog_2016,li_end--end_2018} or CO2 emissions
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\cite{Sarkar2018}.
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Smart industry \cite{Wang2016} : archi with sensing devices, cloud
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The underlying architecture of these smart applications usually
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includes sensing devices, cloud servers, user applications and
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telecommunication networks. Concerning the computing part, the cloud
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servers can either be located on Cloud data centers, on Fog
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infrastructures located at the network edge or on home gateways
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\cite{Wang2016}. Various network technologies are employed by IoT
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devices to communicate with their nearby gateway; either wired like
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Ethernet or wireless: WiFi, Bluetooth, Near Field Communication (NFC),
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ZigBee, celular network (like 3G, LTE, 4G), Low Power Wide Area
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Network (LPWAN), etc. \cite{Samie2016,Gray2015}. The chosen technology
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depends on the smart device characteristics and the targeted
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communication performance. The Google Nest Thermostat can for instance
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use WiFi, 802.15.4 and bluetooth \cite{Nest}. In this paper, we focus
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on WiFi as it is broadly available and employed by IoT devices
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\cite{Samie2016,ns3-energywifi}.
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Smart industry \cite{Wang2016} : Archi with sensing devices, cloud
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server, user applications and networks
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IoT archi : devices, gateways, fog and clouds \cite{Samie2016}
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@ -166,7 +192,7 @@ CO2 impact of IoT and fog computing architectures vs Cloud
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\cite{Sarkar2018}
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Fog archi to use more renewable energy \cite{li_end--end_2018} or
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Fog archi to use more renewable energy \cite{li_end--end_2018} Or
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reduce communication costs \cite{jalali_fog_2016}
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** Energy consumption of network and cloud infrastructures
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@ -2482,3 +2482,10 @@ pages = "26 - 39",
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year = "2016",
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author = "Fei Tao and Yiwen Wang and Ying Zuo and Haidong Yang and Meng Zhang",
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}
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@misc{Nest,
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title={{Nest Learning Thermostat -- Spec Sheet}},
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year = {2017},
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howpublished = {\url{https://nest.com/-downloads/press/documents/nest-thermostat-fact-sheet_2017.pdf}},
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author = {Google}
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}
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