etat de l'art un peu avancé

4 files changed, 111 insertions, 35 deletions

diff --git a/2019-ICA3PP.bbl b/2019-ICA3PP.bbl
index 87991f5..58562b8 100644
--- a/2019-ICA3PP.bbl
+++ b/2019-ICA3PP.bbl
@@ -36,30 +36,68 @@ Cisco, ``{Cisco Visual Networking Index: Forecast and Trends, 2017–2022,
 Sandvine, ``{The Global Internet Phenomena Report},''
   \url{https://www.sandvine.com/phenomena}, Oct. 2018.
 
+\bibitem{li_end--end_2018}
+\BIBentryALTinterwordspacing
+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. [Online]. Available:
+  \url{https://linkinghub.elsevier.com/retrieve/pii/S0167739X17314309}
+\BIBentrySTDinterwordspacing
+
 \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{Samie2016}
+F.~Samie, L.~Bauer, and J.~Henkel, ``Iot technologies for embedded computing: A
+  survey,'' in \emph{IEEE/ACM/IFIP International Conference on
+  Hardware/Software Codesign and System Synthesis (CODES)}, 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{halperin_demystifying_nodate}
-D.~Halperin, B.~Greenstein, A.~Sheth, and D.~Wetherall,
-  ``\BIBforeignlanguage{en}{Demystifying 802.11n {Power} {Consumption}},''
-  p.~5.
+\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{li_end--end_2018}
-\BIBentryALTinterwordspacing
-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. [Online]. Available:
-  \url{https://linkinghub.elsevier.com/retrieve/pii/S0167739X17314309}
-\BIBentrySTDinterwordspacing
+\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{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{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{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{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{jalali_fog_2016}
 \BIBentryALTinterwordspacing
@@ -70,6 +108,11 @@ F.~Jalali, K.~Hinton, R.~Ayre, T.~Alpcan, and R.~S. Tucker,
   [Online]. Available: \url{http://ieeexplore.ieee.org/document/7439752/}
 \BIBentrySTDinterwordspacing
 
+\bibitem{halperin_demystifying_nodate}
+D.~Halperin, B.~Greenstein, A.~Sheth, and D.~Wetherall,
+  ``\BIBforeignlanguage{en}{Demystifying 802.11n {Power} {Consumption}},''
+  p.~5.
+
 \bibitem{orgerie_ecofen:_2011}
 A.~C. Orgerie, L.~Lefèvre, I.~Guérin-Lassous, and D.~M.~L. Pacheco,
   ``{ECOFEN}: {An} {End}-to-end energy {Cost} {mOdel} and simulator {For}
diff --git a/2019-ICA3PP.org b/2019-ICA3PP.org
index 5d34f0b..14d3981 100644
--- a/2019-ICA3PP.org
+++ b/2019-ICA3PP.org
@@ -46,17 +46,16 @@ 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 new applications and new ICT
+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, providing optimized decisions
-based on data produced by smart devices. All these connected devices
-constitute the Internet of Things (IoT): connected devices with
-sensors producing data, actuators interacting with their environment
-and communication means. 
- 
+factories and smart cities for instance. Through connected devices,
+with 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 all these devices. Yet, the overall energy
-bill of IoT also comprises indirect costs as it relies on computing and
+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.  
@@ -94,20 +93,20 @@ 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 applications send few
+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 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.
+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
+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 
@@ -117,8 +116,8 @@ effects.
 Our contributions include:
 - a characterization of low-bandwidth IoT applications;
 - an analysis of the energy consumption of a low-bandwidth IoT
-  application including the energy consumption of the IoT device and
-  the consumption induced by its utilization on the Cloud and
+  application including the energy consumption of the WiFi IoT device
+  and the consumption induced by its utilization on the Cloud and
   telecommunication infrastructures;
 - an end-to-end energy model for low-bandwidth IoT applications.
 
@@ -136,9 +135,36 @@ this work and presents future work.
 * Related Work 
 #+LaTeX: \label{sec:sota}
 ** Energy consumption of IoT devices
-Smart apps and devices everywhere
-
-Smart industry \cite{Wang2016} : archi with sensing devices, cloud
+The multiplication of smart devices and smart applications pushes the
+limits of Internet: IoT is now used everywhere for home automation,
+smart agriculture, smart industry, e-health, smart cities, logistics,
+smart grids, smart buildings,
+etc. \cite{Wang2016,Ejaz2017,Minoli2017}. IoT devices are typically
+used to optimize processes and the envisionned application domains
+include the energy domain, like for instance the energy management of 
+product life-cycle \cite{Tao2016}. Yet, few studies adress 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 like
+Ethernet or wireless: WiFi, Bluetooth, Near Field Communication (NFC),
+ZigBee, celular 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}. 
+
+
+Smart industry \cite{Wang2016} : Archi with sensing devices, cloud
 server, user applications and networks
 
 IoT archi : devices, gateways, fog and clouds \cite{Samie2016}
@@ -166,7 +192,7 @@ CO2 impact of IoT and fog computing architectures vs Cloud
 \cite{Sarkar2018} 
 
 
-Fog archi to use more renewable energy \cite{li_end--end_2018} or
+Fog archi to use more renewable energy \cite{li_end--end_2018} Or
 reduce communication costs \cite{jalali_fog_2016}
 
 ** Energy consumption of network and cloud infrastructures
diff --git a/2019-ICA3PP.pdf b/2019-ICA3PP.pdf
index 65f8abe..b95e4f3 100644
--- a/2019-ICA3PP.pdf
+++ b/2019-ICA3PP.pdf
diff --git a/references.bib b/references.bib
index 58de2d3..cd3c9c7 100644
--- a/references.bib
+++ b/references.bib
@@ -2482,3 +2482,10 @@ pages = "26 - 39",
 year = "2016",
 author = "Fei Tao and Yiwen Wang and Ying Zuo and Haidong Yang and Meng Zhang",
 }
+
+@misc{Nest,
+title={{Nest Learning Thermostat -- Spec Sheet}},
+year = {2017},
+howpublished = {\url{https://nest.com/-downloads/press/documents/nest-thermostat-fact-sheet_2017.pdf}},
+author = {Google}
+}