Update paper

.#2019-Mascots.org

@@ -1 +0,0 @@
-loic@lguegan.13218:1558336539

2019-Mascots.org

@@ -93,14 +93,14 @@ component, formatting, style, styling, insert
 
 ** 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
+   It is also model into ns-3. We consider the server to be 9 hops away from the AP with a typical
    round-trip latency of 100ms from the AP to the server. Each node from the AP to the Cloud is
    assume to be network switches with static and dynamic network energy consumption. 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. It is
    based on an energy-per-bit model including static consumption by assuming a linear relation
    between the amount of data sent to the network interface and the power consumption. The different
-   energy values used to instanciate the ECOFEN energy model for the network part are shown in Table
+   energy values used to instantiate the ECOFEN energy model for the network part are shown in Table
    \ref{tab:net-energy} and come from previous work \cite{cornea_studying_2014-1}.
 
    #+BEGIN_EXPORT latex
@@ -123,7 +123,7 @@ component, formatting, style, styling, insert
    nodes which are connected to watt-meters. In this way, we can benefit from real energy
    measurements. The server used in the experiment is composed of Intel Xeon E5-2620 processor with
    64 GB of RAM and 600GB of disk space on a Linux based distribution. This server is configured to
-   use KVM as virtualization mechanism. We deploy a classical Linux x86_64 disctribution on the
+   use KVM as virtualization mechanism. We deploy a classical Linux x86_64 distribution on the
    Virtual Machines (VM) along with a MySQL database. We different amount of allocated memory for
    the VM namely 1024MB/2048MB/4096MB to highlight its effects on the server energy consumption.
 
@@ -134,29 +134,37 @@ component, formatting, style, styling, insert
 
 * Evaluation [3 col]
 ** IoT/Network Consumption
-   In a first place, we first start by studying the impact of the sensors position on their energy
+   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
-   results show that sensors position have a very low impact on the energy consumption and on the
-   application delay.
-   
+   results provided by Figure \ref{fig:sensorsPos} show that sensors position have a very low impact
+   on the energy consumption and on the application delay. It has an impact of course but it is very
+   limited. This due to the fact that in such a scenario with very small number of communications
+   spread over the time, sensors don't have to contend for accessing to the Wifi channel.
 
+   #+BEGIN_EXPORT latex
+   \begin{figure}
+     \centering
+     \includegraphics[width=0.6\linewidth]{./plots/sensorsPosition-delayenergy.png}
+     \caption{Sensors Position}
+     \label{fig:sensorsPos}
+   \end{figure}
+   #+END_EXPORT
+
+
+   The number of sensors it the dominant factor that leverage the energy consumption of the
+   IoT/Network part. Therefore, we varied the number of sensors in the Wifi cell to analyze its
+   impact. The figure \ref{fig:sensorsNumber} represents the energy consumption of each simulated
+   part. It is clear that the energy consume by the network is the dominant part. However, since the
+   number of sensors is increasing the energy consume by the network will become negligible face to
+   the energy consume by the sensors.
+   
+   
     #+BEGIN_EXPORT latex
     \begin{figure}
       \centering
-      \includegraphics[width=0.6\linewidth]{./plots/sensorsPosition-delayenergy.png}
-      \caption{Sensors Position}
-      \label{fig:sensorsPos}
-    \end{figure}
-    #+END_EXPORT
-
-
-    
-
-    #+BEGIN_EXPORT latex
-    \begin{figure}
-      \label{fig:sensorsFrequency}
-      \caption{Sensors Sensing Frequency}
-
+      \includegraphics[width=0.6\linewidth]{./plots/numberSensors-WIFINET.png}
+      \caption{Sensors Number}
+      \label{fig:sensorsNumber}
     \end{figure}
     #+END_EXPORT
 
@@ -328,12 +336,7 @@ component, formatting, style, styling, insert
        simTime=1800
 
 
-cbPalette <- c("#0000B0", "#E69F00", "#56B4E9", "#009E73", "#F0E442", "#0072B2", "#D55E00", "#CC79A7")
-
-# To use for fills, add
- 
-
-# To use for line and point colors, add
+       cbPalette <- c("#0000B0", "#E69F00", "#56B4E9", "#009E73", "#F0E442", "#0072B2", "#D55E00", "#CC79A7")
 
        # Load Data
         data=read_csv("logs/ns3/last/data.csv")
@@ -594,7 +597,65 @@ cbPalette <- c("#0000B0", "#E69F00", "#56B4E9", "#009E73", "#F0E442", "#0072B2",
      #+RESULTS: mergeCSV
 *** Final Plots
 
+
+    Figure Sensors Position ~ Energy/Delay
+    #+BEGIN_SRC R :noweb yes :results graphics :file plots/sensorsPosition-delayenergy.png
+      <<NS3-RUtils>>
+      simTime=1800
+
+
+
+      cbPalette <- c("#00AFBB", "#E7B800", "#FC4E07","#0abb00")
+      # Load Data
+       data=read_csv("logs/ns3/last/data.csv")
+       data=data%>%mutate(sensorsEnergyW=sensorsEnergy/simTime)
+
+      data%>%filter(simKey=="SENSORSPOS",sensorsNumber==10) %>% ggplot(aes(y=sensorsEnergyW,x=positionSeed,color="Energy"))+xlab(getLabel("Sensors Position Seed"))+ylab(getLabel("Sensors Energy Consumption (W)"))+
+      geom_line()+geom_point()+geom_line(aes(y=(avgDelay+5),color="Delay"))+geom_point(aes(y=(avgDelay+5),color="Delay"))+expand_limits(y=c(0,15))+scale_y_continuous(sec.axis = sec_axis(~.-5, name = "Application Delay (s)")) +theme_bw() +  scale_fill_manual(values=cbPalette) +   scale_colour_manual(values=cbPalette)+guides(color=guide_legend(title="Curves"))
+      ggsave("plots/sensorsPosition-delayenergy.png",dpi=80, width=4, height=3.2)
+    #+END_SRC
+
+    #+RESULTS:
+    [[file:plots/sensorsPosition-delayenergy.png]]
     
+
+
+
+    #+BEGIN_SRC R :noweb yes :results graphics  :file plots/numberSensors-WIFINET.png :session *R*
+      <<NS3-RUtils>>
+      simTime=1800
+
+
+      cbPalette <- c("#00AFBB", "#E7B800", "#FC4E07","#0abb00")
+
+      # Load Data
+      data=read_csv("logs/ns3/last/data.csv")
+      data=data%>%filter(simKey=="NBSENSORS")
+      dataW=data%>%mutate(energy=sensorsEnergy/simTime)%>% mutate(type="Sensors") %>% select(sensorsNumber,energy,type) 
+      dataN=data%>%mutate(energy=networkEnergy/simTime)%>% mutate(type="Network") %>% select(sensorsNumber,energy,type)
+
+      data=rbind(dataN,dataW)
+      data=data%>%mutate(sensorsNumber=as.character(sensorsNumber))
+      data=data%>%mutate(sensorsNumber=fct_reorder(sensorsNumber,as.numeric(sensorsNumber)))
+      data=data%>%filter(sensorsNumber%in%c(2,4,6,8,10))
+
+      ggplot(data)+geom_bar(aes(x=sensorsNumber,y=energy,fill=type),position="identity",stat="identity")+
+      theme_bw()+
+          theme(text = element_text(size=16))+
+      scale_fill_manual(values=cbPalette) +   scale_colour_manual(values=cbPalette)+
+      xlab(getLabel("sensorsNumber"))+ ylab("Energy Consumption (W)") + guides(fill=guide_legend(title="")) +coord_flip()
+
+      size=5
+     ggsave("plots/numberSensors-WIFINET.png",dpi=90,width=size,height=size-1)
+    #+END_SRC
+
+    #+RESULTS:
+    [[file:plots/numberSensors-WIFINET.png]]
+
+
+
+
+
      #+BEGIN_SRC R :noweb yes :results graphics :file plots/final.png :session *R*
        library("tidyverse")