Merge branch 'master' of gitlab.inria.fr:lguegan/paper-lowrate-iot

2019-ICA3PP.org

@@ -224,39 +224,39 @@ and transmission technologies.
 
 
 * 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
-application. While the derived model is more generic, we focus on a
-given application to obtain a precise use-case with accurate power
-consumption measurements.  
+   In this section, we detail the characteristics of the considered IoT
+   application. While the derived model is more generic, we focus on a
+   given application to obtain a precise use-case with accurate power
+   consumption measurements.  
 
-The Google Nest Thermostat relies on five sensors: temperature,
-humidity, near-field activity, far-field activity and ambient light
-\cite{Nest}. Periodical measurements, sent through wireless
-communications on the Internet, are stored on Google data centers and
-processed to learn the home inhabitants habits. The learned behavior
-is employed to automatically adjust the home temperature managed by
-heating and cooling systems.
+   The Google Nest Thermostat relies on five sensors: temperature,
+   humidity, near-field activity, far-field activity and ambient light
+   \cite{Nest}. Periodical measurements, sent through wireless
+   communications on the Internet, are stored on Google data centers and
+   processed to learn the home inhabitants habits. The learned behavior
+   is employed to automatically adjust the home temperature managed by
+   heating and cooling systems.
 
-    #+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
-     
-Each IoT device senses periodically its environment. Then, it sends
-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
-cloud using the Internet. Figure \ref{fig:IoTdev} illustrates this
-architecture. Several IoT devices can share the same AP in a
-home. We consider low-bandwidth applications where devices produces
-several network packets during each sensing period. The transmitting
-frequency can vary from one to several packet sent per minute
-\cite{Cisco2019}. 
+       #+BEGIN_EXPORT latex
+       \begin{figure}
+         \centering
+         \includegraphics[width=0.5\linewidth]{./plots/home.png}
+         \caption{Overview of IoT devices.}
+         \label{fig:IoTdev}
+       \end{figure}
+       #+END_EXPORT
+
+   Each IoT device senses periodically its environment. Then, it sends
+   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
+   cloud using the Internet. Figure \ref{fig:IoTdev} illustrates this
+   architecture. Several IoT devices can share the same AP in a
+   home. We consider low-bandwidth applications where devices produces
+   several network packets during each sensing period. The transmitting
+   frequency can vary from one to several packet sent per minute
+   \cite{Cisco2019}. 
 
    #+BEGIN_COMMENT
    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.
 
    #+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
-belongs to a shared cloud facility with classical service level
-agreement (SLA). The facility provides redundant storage and computing
-means as virtual machines (VMs). A server can host several VMs at the
-same time.
+   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.
 
-    #+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
+   We assume that the server hosting the application data for the users
+   belongs to a shared cloud facility with classical service level
+   agreement (SLA). The facility provides redundant storage and computing
+   means as virtual machines (VMs). A server can host several VMs at the
+   same time.
 
-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}. 
+   #+BEGIN_EXPORT latex
+   \begin{figure}
+     \centering
+     \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 
-\hl{Ajouter \% de bande passante utilisé par les applis low-rate}
-#+Latex: \label{sec:model}
+  \hl{Ajouter \% de bande passante utilisé par les applis low-rate}
+  #+Latex: \label{sec:model}
   In this section, we describe the experimental setup employed to
   acquire energy measurements for each of the three parts of our
   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{figure}
      \centering
-     \includegraphics[width=0.5\linewidth]{./plots/g5k-xp.png}
+     \includegraphics[width=0.45\linewidth]{./plots/g5k-xp.png}
      \caption{Grid'5000 experimental setup.}
      \label{fig:g5kExp}
    \end{figure}
@@ -664,7 +664,7 @@ In our case with small and sporadic network traffic, these results show that wit
    \begin{figure}
      \centering
      \hspace{1cm}
-     \includegraphics[scale=0.3]{plots/final.png}
+     \includegraphics[scale=0.4]{plots/final.png}
      \label{fig:end-to-end}
      \caption{End-to-end network energy consumption using sensors interval of 10s}
    \end{figure}
@@ -1152,6 +1152,7 @@ applicability of our model.
       fakeData$type=factor(fakeData$type,ordered=TRUE,levels=c("Sensors","Network","Cloud"))
 
       # 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")+ 
       xlab("Sensors Number")+ylab("Power Consumption (W)")+guides(fill=guide_legend(title="System Part"))
       p=applyTheme(p)+theme(text = element_text(size=16))