paper-lowrate-iot/2019-Mascots.org

#+TITLE: Estimating the end-to-end energy consumption of IoT devices along with their impact on Cloud and telecommunication infrastructures

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#+LATEX_HEADER: \author{\IEEEauthorblockN{1\textsuperscript{st} Anne-Cécile Orgerie}
#+LATEX_HEADER: \IEEEauthorblockA{\textit{Univ Rennes, Inria, CNRS, IRISA, Rennes, France} \\
#+LATEX_HEADER: Rennes, France \\
#+LATEX_HEADER: anne-cecile.orgerie@irisa.fr}
#+LATEX_HEADER: \and
#+LATEX_HEADER: \IEEEauthorblockN{2\textsuperscript{nd} Loic Guegan}
#+LATEX_HEADER: \IEEEauthorblockA{\textit{Univ Rennes, Inria, CNRS, IRISA, Rennes, France} \\
#+LATEX_HEADER: Rennes, France \\
#+LATEX_HEADER: loic.guegan@irisa.fr}
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\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}

\begin{IEEEkeywords}
component, formatting, style, styling, insert
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* Introduction [2 col]
* Related Work [1 col]
* Use-Case [1 col]
** Application Characteristic

   The IoT part is composed of an Access Point (AP), connected to several sensors using WIFI. In the
   system, the IoT part is considered as the part where the system data are created. In fact, the
   data life cycle start when the sensors records their respective local temperature at a frequency
   $f$ and the local timestamp. Then, these data are transmitted through the network along with an
   arbitrary sensor id of 128 bits. Finally, the AP is in charge to transmit the data to the cloud
   using the network part.

   The network part is considered as the medium that link the IoT part to the cloud. It is composed
   of several network switches and router and it is considered to be a wired network.
   
** Cloud Infrastructure

* System Model [2 col]
  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.

** IoT Part
   In the first place, the IoT part is composed of several sensors connected to an AP which forms a
   cell. It is model using the ns-3 network simulator. Thus, we setup between 5 and 20 sensors
   connected to the AP using WIFI 5GHz 802.11n. The node are placed randomly in a square of 30
   meters around the AP which correspond to a typical real use case. All the nodes of the cell are
   setup with the default WIFI energy model provided by ns-3.  The different energy values used by
   the energy model come from the literature and are provided on Table \ref{tab:wifi-energy}. Note
   that we suppose that the energy source of the cell nodes are unlimited and thus every nodes can
   communicate for all the simulation duration.

   As a scenario, sensors send to the AP packets of 192 bits that include: \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 time. The data are transmitted immediately at each
   sensing interval $I$ varied from 1s to 60s. Finally, the AP is in charge to relay data to the
   cloud using the network part.
   
   
   #+BEGIN_EXPORT latex
   \begin{table}[]
     \centering
     \caption{Wifi Energy Settings}
     \label{tab:wifi-energy}
     \begin{tabular}{|l|l|l|}
       \hline
       & Value  & Reference(s) \\ \hline
       Supply Voltage & 3.3V   & TODO         \\ \hline
       Tx             & 0.38A  & TODO         \\ \hline
       Rx             & 0.313A & TODO         \\ \hline
       Idle           & 0.273A & TODO         \\ \hline
     \end{tabular}
   \end{table}  
   #+END_EXPORT


** Network Part
   The network part represents the network starting from the AP to the Cloud excluding the server.
   It is also model into ns-3. We consider the server to be 9 hops aways from the AP with a typical
   round-trip latency of 100ms from the AP to the server. ECOFEN \cite{orgerie_ecofen:_2011} is used
   to model the energy consumption of the network part. ECOFEN is a ns-3 network energy module for
   ns-3 dedicated to wired network energy estimation. The different energy values used in the
   network part are from the literature and shown in Table \ref{tab:net-energy}.

   #+BEGIN_EXPORT latex
   \begin{table}[]
     \centering
     \caption{Network Part Energy Settings}
     \label{tab:net-energy}
     \begin{tabular}{|l|l|l|}
       \hline
       & Value  & Reference(s) \\ \hline
       Idle & 1J   & TODO         \\ \hline
       Bytes (Tx/Rx)             & 3.4nJ  & TODO         \\ \hline
       Pkt (Tx/Rx)             & 192.0nJ & TODO         \\ \hline
     \end{tabular}
   \end{table}  
   #+END_EXPORT

** Cloud Part
   Finally, to measure the energy consumption of the server, we used real server from the
   large-scale test-beds Grid5000 (G5K). In fact, G5K has a cluster called Nova composed of several
   nodes which are connected to watt-meters. In this way, we can benefit from real energy
   measurements. The server is configured to use KVM for virtualization. Virtual Machines (VM)


* Evaluation [3 col]
** IoT/Network Consumption
** Cloud Energy Consumption
** Virtual Machine Size Impact
** Application Accuracy
   Refresh frequency etc...
** End-To-End Consumption
* Discussion [1 col]
* Conclusion [1 col]
* References [1 col]
\bibliographystyle{IEEEtran}
\bibliography{references}

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