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2019-ICA3PP.org
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2019-ICA3PP.org
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@ -224,39 +224,39 @@ and transmission technologies.
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* Characterization of low-bandwidth IoT applications
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* Characterization of low-bandwidth IoT applications
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#+LaTeX: \label{sec:usec}
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#+LaTeX: \label{sec:usec}
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In this section, we detail the characteristics of the considered IoT
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In this section, we detail the characteristics of the considered IoT
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application. While the derived model is more generic, we focus on a
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application. While the derived model is more generic, we focus on a
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given application to obtain a precise use-case with accurate power
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given application to obtain a precise use-case with accurate power
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consumption measurements.
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consumption measurements.
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The Google Nest Thermostat relies on five sensors: temperature,
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The Google Nest Thermostat relies on five sensors: temperature,
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humidity, near-field activity, far-field activity and ambient light
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humidity, near-field activity, far-field activity and ambient light
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\cite{Nest}. Periodical measurements, sent through wireless
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\cite{Nest}. Periodical measurements, sent through wireless
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communications on the Internet, are stored on Google data centers and
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communications on the Internet, are stored on Google data centers and
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processed to learn the home inhabitants habits. The learned behavior
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processed to learn the home inhabitants habits. The learned behavior
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is employed to automatically adjust the home temperature managed by
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is employed to automatically adjust the home temperature managed by
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heating and cooling systems.
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heating and cooling systems.
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#+BEGIN_EXPORT latex
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#+BEGIN_EXPORT latex
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\begin{figure}
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\begin{figure}
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\centering
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\centering
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\includegraphics[width=0.6\linewidth]{./plots/home.png}
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\includegraphics[width=0.5\linewidth]{./plots/home.png}
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\caption{Overview of IoT devices.}
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\caption{Overview of IoT devices.}
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\label{fig:IoTdev}
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\label{fig:IoTdev}
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\end{figure}
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\end{figure}
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#+END_EXPORT
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#+END_EXPORT
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Each IoT device senses periodically its environment. Then, it sends
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Each IoT device senses periodically its environment. Then, it sends
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the produced data through WiFi (in our context) to its gateway or
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the produced data through WiFi (in our context) to its gateway or
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Access Point (AP). The AP is in charge of transmitting the data to the
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Access Point (AP). The AP is in charge of transmitting the data to the
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cloud using the Internet. Figure \ref{fig:IoTdev} illustrates this
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cloud using the Internet. Figure \ref{fig:IoTdev} illustrates this
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architecture. Several IoT devices can share the same AP in a
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architecture. Several IoT devices can share the same AP in a
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home. We consider low-bandwidth applications where devices produces
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home. We consider low-bandwidth applications where devices produces
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several network packets during each sensing period. The transmitting
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several network packets during each sensing period. The transmitting
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frequency can vary from one to several packet sent per minute
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frequency can vary from one to several packet sent per minute
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\cite{Cisco2019}.
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\cite{Cisco2019}.
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#+BEGIN_COMMENT
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#+BEGIN_COMMENT
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The IoT part is composed of an Access Point (AP), connected to several sensors using WIFI. In the
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The IoT part is composed of an Access Point (AP), connected to several sensors using WIFI. In the
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@ -270,37 +270,37 @@ frequency can vary from one to several packet sent per minute
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of several network switches and router and it is considered to be a wired network.
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of several network switches and router and it is considered to be a wired network.
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#+END_COMMENT
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#+END_COMMENT
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We consider that the link between the AP and the Cloud is composed of
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several network switches and routers using Ethernet as shown in Figure
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\ref{fig:parts}. The number of routers on the path depends on the
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location of the server, either in a Cloud data center or in a Fog site
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at the edge of the network.
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We assume that the server hosting the application data for the users
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We consider that the link between the AP and the Cloud is composed of
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belongs to a shared cloud facility with classical service level
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several network switches and routers using Ethernet as shown in Figure
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agreement (SLA). The facility provides redundant storage and computing
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\ref{fig:parts}. The number of routers on the path depends on the
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means as virtual machines (VMs). A server can host several VMs at the
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location of the server, either in a Cloud data center or in a Fog site
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same time.
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at the edge of the network.
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#+BEGIN_EXPORT latex
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We assume that the server hosting the application data for the users
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\begin{figure}
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belongs to a shared cloud facility with classical service level
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\centering
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agreement (SLA). The facility provides redundant storage and computing
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\includegraphics[width=0.85\linewidth]{./plots/parts2.png}
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means as virtual machines (VMs). A server can host several VMs at the
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\caption{Overview of the IoT architecture.}
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same time.
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\label{fig:parts}
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\end{figure}
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#+END_EXPORT
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In the following, we describe the experimental setup, the results and
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#+BEGIN_EXPORT latex
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the end-to-end model. For all these steps, we decompose the overall
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\begin{figure}
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IoT architecture into three parts: the IoT device part, the networking
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\centering
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part and the cloud part, as displayed on Figure \ref{fig:parts}.
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\includegraphics[width=0.6\linewidth]{./plots/parts2.png}
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\caption{Overview of the IoT architecture.}
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\label{fig:parts}
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\end{figure}
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#+END_EXPORT
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In the following, we describe the experimental setup, the results and
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the end-to-end model. For all these steps, we decompose the overall
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IoT architecture into three parts: the IoT device part, the networking
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part and the cloud part, as displayed on Figure \ref{fig:parts}.
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* Experimental setup
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* Experimental setup
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\hl{Ajouter \% de bande passante utilisé par les applis low-rate}
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\hl{Ajouter \% de bande passante utilisé par les applis low-rate}
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#+Latex: \label{sec:model}
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#+Latex: \label{sec:model}
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In this section, we describe the experimental setup employed to
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In this section, we describe the experimental setup employed to
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acquire energy measurements for each of the three parts of our
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acquire energy measurements for each of the three parts of our
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system model. The IoT and the network parts are modeled
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system model. The IoT and the network parts are modeled
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@ -388,7 +388,7 @@ part and the cloud part, as displayed on Figure \ref{fig:parts}.
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#+BEGIN_EXPORT latex
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#+BEGIN_EXPORT latex
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\begin{figure}
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\begin{figure}
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\centering
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\centering
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\includegraphics[width=0.5\linewidth]{./plots/g5k-xp.png}
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\includegraphics[width=0.45\linewidth]{./plots/g5k-xp.png}
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\caption{Grid'5000 experimental setup.}
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\caption{Grid'5000 experimental setup.}
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\label{fig:g5kExp}
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\label{fig:g5kExp}
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\end{figure}
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\end{figure}
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@ -664,7 +664,7 @@ In our case with small and sporadic network traffic, these results show that wit
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\begin{figure}
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\begin{figure}
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\centering
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\centering
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\hspace{1cm}
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\hspace{1cm}
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\includegraphics[scale=0.3]{plots/final.png}
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\includegraphics[scale=0.4]{plots/final.png}
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\label{fig:end-to-end}
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\label{fig:end-to-end}
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\caption{End-to-end network energy consumption using sensors interval of 10s}
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\caption{End-to-end network energy consumption using sensors interval of 10s}
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\end{figure}
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\end{figure}
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@ -1152,6 +1152,7 @@ applicability of our model.
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fakeData$type=factor(fakeData$type,ordered=TRUE,levels=c("Sensors","Network","Cloud"))
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fakeData$type=factor(fakeData$type,ordered=TRUE,levels=c("Sensors","Network","Cloud"))
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# Plot
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# Plot
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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)
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p=ggplot(fakeData)+geom_bar(position="dodge2",colour="black",aes(x=sensorsNumber,y=energy,fill=type),stat="identity")+
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p=ggplot(fakeData)+geom_bar(position="dodge2",colour="black",aes(x=sensorsNumber,y=energy,fill=type),stat="identity")+
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xlab("Sensors Number")+ylab("Power Consumption (W)")+guides(fill=guide_legend(title="System Part"))
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xlab("Sensors Number")+ylab("Power Consumption (W)")+guides(fill=guide_legend(title="System Part"))
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p=applyTheme(p)+theme(text = element_text(size=16))
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p=applyTheme(p)+theme(text = element_text(size=16))
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