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 #+BEGIN_EXPORT latex
 \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. 
+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}
 #+END_EXPORT
 
 
-* 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.
-Sections...
-* Related Work [1 col]
+* Introduction 
+In 2018, Information and Communication Technology (ICT) was estimated
+to absorb around 3% of the global energy consumption
+\cite{ShiftProject}. This consumption grows at a rate of 9% per year
+\cite{ShiftProject}. This alarming increase is explained by the fast
+emergence of numerous new applications and new ICT devices. These
+devices supply services for smart building, smart factories and smart
+cities for instance, allowing for optimized decisions. 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 utilize all these devices. 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, 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 applications 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.
+
+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:
+- 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
+  telecommunication infrastructures;
+- an end-to-end energy model for low-bandwidth IoT applications.
+
+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 using 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. 
+
+
+
+* Related Work 
+#+LaTeX: \label{sec:sota}
 Smart industry \cite{Wang2016}
 Smart cities \cite{Ejaz2017}
-* Use-Case [1 col]
+* Use-Case 
+#+LaTeX: \label{sec:usec}
+
+
+
 ** Application Characteristic
 
    #+BEGIN_COMMENT
@@ -60,11 +156,31 @@ 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]
 
+    #+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
+
+* System Model 
+#+LaTeX: \label{sec: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,
   it is possible to evaluate the end-to-end energy consumption of the system.
@@ -141,7 +257,8 @@ 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 
+#+LaTeX: \label{sec:eval}
 ** 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 +409,12 @@ Smart cities \cite{Ejaz2017}
    
 
 
-* Discussion [1 col]
-* Conclusion [1 col]
-* References [1 col]
+* Discussion 
+#+LaTeX: \label{sec:discuss}
+
+* Conclusion 
+#+LaTeX: \label{sec:cl}
+
 \bibliographystyle{IEEEtran}
 \bibliography{references}