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@@ -32,19 +32,74 @@ Information and Communication Technology takes a growing part in the worldwide e
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-* Introduction [2 col]
-More and more IoT devices: smart building, smart factories, etc.
-Many sending few data, though taking a lot of bandwidth (Sandvine
-report)
-IoT devices, only top of the iceberg: induced consumption on telco net
-and cloud infra
-In this paper, we estimate the overall energy consumption of an IoT
-device environment by combining simulations and real measurements.
+* Introduction 
+In 2018, Information and Communication Technology (ICT) was estimated
+to absorb around 3% of the global energy consumption, with a growing
+rate of 9% per year \cite{ShiftProject}. This alarming growing rate is
+explained by the emergence of new applications and new ICT devices
+for smart building, smart factories, smart cities, etc. All these
+connected devices constitute the Internet of Things (IoT): connected
+devices with sensors producing data, actuators interacting with their 
+environment and communication means. 
+
+This increase in number of devices implies an increase in the energy
+needed to manufacture and use these devices. Yet, another energy cost is
+directly implied by IoT devices: the cost of computing and
+communication infrastructures they rely on. 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, against 3% in
+2017 \cite{Cisco2019}. The IoT devices have an increasing impact on
+Internet bandwidth.
+
+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. 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}.  
+
+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.
+
+Our main contributions...
+
 Sections...
-* Related Work [1 col]
+
+
+
+* Related Work 
 Smart industry \cite{Wang2016}
 Smart cities \cite{Ejaz2017}
-* Use-Case [1 col]
+* Use-Case 
+
+    #+BEGIN_EXPORT latex
+    \begin{figure}
+      \centering
+      \includegraphics[width=0.85\linewidth]{./plots/parts2.png}
+      \caption{Overview of the IoT architecture.}
+      \label{fig:parts}
+    \end{figure}
+    #+END_EXPORT
+
+
+
 ** Application Characteristic
 
    #+BEGIN_COMMENT
@@ -60,10 +115,20 @@ Smart cities \cite{Ejaz2017}
 
    #+END_COMMENT
 
+
+    #+BEGIN_EXPORT latex
+    \begin{figure}
+      \centering
+      \includegraphics[width=0.6\linewidth]{./plots/home.png}
+      \caption{Overview of IoT devices.}
+      \label{fig:IoTdev}
+    \end{figure}
+    #+END_EXPORT
+   
       
 ** Cloud Infrastructure
 
-* System Model [2 col]
+* System Model 
 
   The system model is divided in two parts. First, the IoT and the Network part are models through
   simulations. Then, the Cloud part is model using real servers connected to watt-meters. In this way,
@@ -141,7 +206,7 @@ Smart cities \cite{Ejaz2017}
    different requests characteristics namely: \textbf{1)} The number request, to virtually
    add/remove sensors \textbf{2)} The requests interval.
 
-* Evaluation [3 col]
+* Evaluation 
 ** IoT/Network Consumption
    In a first place, we start by studying the impact of the sensors position on their energy
    consumption. To this end, we run several simulations in ns-3 with different sensors position. The
@@ -292,9 +357,10 @@ Smart cities \cite{Ejaz2017}
    
 
 
-* Discussion [1 col]
-* Conclusion [1 col]
-* References [1 col]
+* Discussion 
+* Conclusion 
+
+
 \bibliographystyle{IEEEtran}
 \bibliography{references}