Divide by 7 energy on figure 8

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Loic Guegan 2019-07-19 10:51:16 +02:00
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@ -224,39 +224,39 @@ and transmission technologies.
* Characterization of low-bandwidth IoT applications * Characterization of low-bandwidth IoT applications
#+LaTeX: \label{sec:usec} #+LaTeX: \label{sec:usec}
In this section, we detail the characteristics of the considered IoT In this section, we detail the characteristics of the considered IoT
application. While the derived model is more generic, we focus on a application. While the derived model is more generic, we focus on a
given application to obtain a precise use-case with accurate power given application to obtain a precise use-case with accurate power
consumption measurements. consumption measurements.
The Google Nest Thermostat relies on five sensors: temperature, The Google Nest Thermostat relies on five sensors: temperature,
humidity, near-field activity, far-field activity and ambient light humidity, near-field activity, far-field activity and ambient light
\cite{Nest}. Periodical measurements, sent through wireless \cite{Nest}. Periodical measurements, sent through wireless
communications on the Internet, are stored on Google data centers and communications on the Internet, are stored on Google data centers and
processed to learn the home inhabitants habits. The learned behavior processed to learn the home inhabitants habits. The learned behavior
is employed to automatically adjust the home temperature managed by is employed to automatically adjust the home temperature managed by
heating and cooling systems. heating and cooling systems.
#+BEGIN_EXPORT latex #+BEGIN_EXPORT latex
\begin{figure} \begin{figure}
\centering \centering
\includegraphics[width=0.6\linewidth]{./plots/home.png} \includegraphics[width=0.5\linewidth]{./plots/home.png}
\caption{Overview of IoT devices.} \caption{Overview of IoT devices.}
\label{fig:IoTdev} \label{fig:IoTdev}
\end{figure} \end{figure}
#+END_EXPORT #+END_EXPORT
Each IoT device senses periodically its environment. Then, it sends Each IoT device senses periodically its environment. Then, it sends
the produced data through WiFi (in our context) to its gateway or the produced data through WiFi (in our context) to its gateway or
Access Point (AP). The AP is in charge of transmitting the data to the Access Point (AP). The AP is in charge of transmitting the data to the
cloud using the Internet. Figure \ref{fig:IoTdev} illustrates this cloud using the Internet. Figure \ref{fig:IoTdev} illustrates this
architecture. Several IoT devices can share the same AP in a architecture. Several IoT devices can share the same AP in a
home. We consider low-bandwidth applications where devices produces home. We consider low-bandwidth applications where devices produces
several network packets during each sensing period. The transmitting several network packets during each sensing period. The transmitting
frequency can vary from one to several packet sent per minute frequency can vary from one to several packet sent per minute
\cite{Cisco2019}. \cite{Cisco2019}.
#+BEGIN_COMMENT #+BEGIN_COMMENT
The IoT part is composed of an Access Point (AP), connected to several sensors using WIFI. In the The IoT part is composed of an Access Point (AP), connected to several sensors using WIFI. In the
@ -270,37 +270,37 @@ frequency can vary from one to several packet sent per minute
of several network switches and router and it is considered to be a wired network. of several network switches and router and it is considered to be a wired network.
#+END_COMMENT #+END_COMMENT
We consider that the link between the AP and the Cloud is composed of
several network switches and routers using Ethernet as shown in Figure
\ref{fig:parts}. The number of routers on the path depends on the
location of the server, either in a Cloud data center or in a Fog site
at the edge of the network.
We assume that the server hosting the application data for the users We consider that the link between the AP and the Cloud is composed of
belongs to a shared cloud facility with classical service level several network switches and routers using Ethernet as shown in Figure
agreement (SLA). The facility provides redundant storage and computing \ref{fig:parts}. The number of routers on the path depends on the
means as virtual machines (VMs). A server can host several VMs at the location of the server, either in a Cloud data center or in a Fog site
same time. at the edge of the network.
#+BEGIN_EXPORT latex We assume that the server hosting the application data for the users
\begin{figure} belongs to a shared cloud facility with classical service level
\centering agreement (SLA). The facility provides redundant storage and computing
\includegraphics[width=0.85\linewidth]{./plots/parts2.png} means as virtual machines (VMs). A server can host several VMs at the
\caption{Overview of the IoT architecture.} same time.
\label{fig:parts}
\end{figure}
#+END_EXPORT
In the following, we describe the experimental setup, the results and #+BEGIN_EXPORT latex
the end-to-end model. For all these steps, we decompose the overall \begin{figure}
IoT architecture into three parts: the IoT device part, the networking \centering
part and the cloud part, as displayed on Figure \ref{fig:parts}. \includegraphics[width=0.6\linewidth]{./plots/parts2.png}
\caption{Overview of the IoT architecture.}
\label{fig:parts}
\end{figure}
#+END_EXPORT
In the following, we describe the experimental setup, the results and
the end-to-end model. For all these steps, we decompose the overall
IoT architecture into three parts: the IoT device part, the networking
part and the cloud part, as displayed on Figure \ref{fig:parts}.
* Experimental setup * Experimental setup
\hl{Ajouter \% de bande passante utilisé par les applis low-rate} \hl{Ajouter \% de bande passante utilisé par les applis low-rate}
#+Latex: \label{sec:model} #+Latex: \label{sec:model}
In this section, we describe the experimental setup employed to In this section, we describe the experimental setup employed to
acquire energy measurements for each of the three parts of our acquire energy measurements for each of the three parts of our
system model. The IoT and the network parts are modeled system model. The IoT and the network parts are modeled
@ -388,7 +388,7 @@ part and the cloud part, as displayed on Figure \ref{fig:parts}.
#+BEGIN_EXPORT latex #+BEGIN_EXPORT latex
\begin{figure} \begin{figure}
\centering \centering
\includegraphics[width=0.5\linewidth]{./plots/g5k-xp.png} \includegraphics[width=0.45\linewidth]{./plots/g5k-xp.png}
\caption{Grid'5000 experimental setup.} \caption{Grid'5000 experimental setup.}
\label{fig:g5kExp} \label{fig:g5kExp}
\end{figure} \end{figure}
@ -596,7 +596,7 @@ In our case with small and sporadic network traffic, these results show that wit
\begin{figure} \begin{figure}
\centering \centering
\hspace{1cm} \hspace{1cm}
\includegraphics[scale=0.3]{plots/final.png} \includegraphics[scale=0.4]{plots/final.png}
\label{fig:end-to-end} \label{fig:end-to-end}
\caption{End-to-end network energy consumption using sensors interval of 10s} \caption{End-to-end network energy consumption using sensors interval of 10s}
\end{figure} \end{figure}
@ -1084,6 +1084,7 @@ applicability of our model.
fakeData$type=factor(fakeData$type,ordered=TRUE,levels=c("Sensors","Network","Cloud")) fakeData$type=factor(fakeData$type,ordered=TRUE,levels=c("Sensors","Network","Cloud"))
# Plot # Plot
fakeData=fakeData%>%mutate(energy=energy/7) # Divide by 7 because 14 core so 1 machine can host 14 vm but we use redundancy (2VM for 1app)
p=ggplot(fakeData)+geom_bar(position="dodge2",colour="black",aes(x=sensorsNumber,y=energy,fill=type),stat="identity")+ p=ggplot(fakeData)+geom_bar(position="dodge2",colour="black",aes(x=sensorsNumber,y=energy,fill=type),stat="identity")+
xlab("Sensors Number")+ylab("Power Consumption (W)")+guides(fill=guide_legend(title="System Part")) xlab("Sensors Number")+ylab("Power Consumption (W)")+guides(fill=guide_legend(title="System Part"))
p=applyTheme(p)+theme(text = element_text(size=16)) p=applyTheme(p)+theme(text = element_text(size=16))

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