From 827d9925334c6df0614808ba2860b75f32d76926 Mon Sep 17 00:00:00 2001
From: Loic Guegan <manzerberdes@gmx.com>
Date: Sat, 25 May 2019 11:11:08 +0200
Subject: Update paper

---
 2019-Mascots.org              |  25 +++++++++++++++----------
 2019-Mascots.pdf              | Bin 146523 -> 189465 bytes
 plots/sendInterval-cloud.png  | Bin 30886 -> 42686 bytes
 plots/sensorsNumber-cloud.png | Bin 46435 -> 46221 bytes
 plots/vmSize-cloud.png        | Bin 31363 -> 31130 bytes
 5 files changed, 15 insertions(+), 10 deletions(-)

diff --git a/2019-Mascots.org b/2019-Mascots.org
index 4d2044b..5c248c3 100644
--- a/2019-Mascots.org
+++ b/2019-Mascots.org
@@ -128,7 +128,7 @@ component, formatting, style, styling, insert
    The sensors requests are simulated using another server. This server is in charge to send hundred
    of requests to the VM in order to fill the database. Consequently, it is easy to vary the
    different requests characteristics namely: \textbf{1)} The number request, to virtually
-   add/remove sensors \textbf{2)} The requests frequency.
+   add/remove sensors \textbf{2)} The requests interval.
 
 * Evaluation [3 col]
 ** IoT/Network Consumption
@@ -239,13 +239,17 @@ component, formatting, style, styling, insert
 
    A last parameter can leverage server energy consumption namely sensors send frequency. In
    addition to increasing the application accuracy, sensors send frequency increase network traffic
-   and database accesses. 
+   and database accesses. Figure \ref{fig:sensorsFrequency} present the impact on the server energy
+   consumption of changing the send interval of 50 sensors to 1s, 10s and 30s. We can see that, the
+   more sensors send interval is low, the more server energy consumption peaks occurs. Therefore, it
+   leads to an increase in the server energy consumption.
 
    #+BEGIN_EXPORT latex
    \begin{figure}
-  
-     \caption{Freq}
-  
+     \centering
+     \includegraphics[scale=0.5]{plots/sendInterval-cloud.png}
+     \label{fig:sensorsFrequency}
+     \caption{Server energy consumption for 50 sensors sending request at different interval.}
    \end{figure}
    #+END_EXPORT
    
@@ -472,7 +476,7 @@ component, formatting, style, styling, insert
        data=data%>%mutate(vmSize=as.character(vmSize))
 
        ggplot(data) + geom_bar(aes(x=vmSize,y=energy),stat="identity")+expand_limits(y=c(75,100))+ylab("Server Energy Consumption (W)")+
-       xlab("Simulation Time (s)")+scale_y_log10()
+       xlab("Experiment Time (s)")+scale_y_log10()
 
 
        ggsave("plots/vmSizeBar-cloud.png",dpi=90,height=3,width=6)  
@@ -703,7 +707,7 @@ component, formatting, style, styling, insert
     data=data%>%mutate(vmSize=paste0(vmSize," MB"))
     data=data%>%group_by(vmSize)%>%mutate(avgEnergy=mean(energy))%>%ungroup()
     p=ggplot(data,aes(x=time, y=energy)) + geom_line()+facet_wrap(~vmSize)+geom_hline(aes(yintercept=avgEnergy),color="Red",size=1.0)+expand_limits(y=c(0,40))+ylab("Server Energy Consumption (W)")+
-    xlab("Simulation Time (s)")
+    xlab("Experiment Time (s)")
 
     p=applyTheme(p)
 
@@ -728,7 +732,7 @@ component, formatting, style, styling, insert
 
     data=data%>%group_by(nbSensors)%>%mutate(avgEnergy=mean(energy))%>%ungroup()
     p=ggplot(data,aes(x=time, y=energy)) + geom_line()+facet_wrap(~nbSensors)+expand_limits(y=c(0,40))+ylab("Server Energy Consumption (W)")+
-    xlab("Simulation Time (s)")+geom_hline(aes(yintercept=avgEnergy),color="Red",size=1.0)
+    xlab("Experiment Time (s)")+geom_hline(aes(yintercept=avgEnergy),color="Red",size=1.0)
 
     p=applyTheme(p)
     ggsave("plots/sensorsNumber-cloud.png",dpi=90,height=3,width=6)  
@@ -804,11 +808,12 @@ component, formatting, style, styling, insert
     data$sendInterval=fct_reorder(data$sendInterval,oldSendInterval)
 
     data=data%>%group_by(sendInterval)%>%mutate(avgEnergy=mean(energy))%>%ungroup()
+        print(data)
     p=ggplot(data,aes(x=time, y=energy)) + geom_line()+facet_wrap(~sendInterval)+expand_limits(y=c(0,40))+ylab("Server Energy Consumption (W)")+
-    xlab("Simulation Time (s)")+geom_hline(aes(yintercept=avgEnergy),color="Red",size=1.0)
+    xlab("Experiment Time (s)")+geom_hline(aes(yintercept=avgEnergy),color="Red",size=1.0)
 
     p=applyTheme(p)
-    ggsave("plots/sendInterval-cloud.png",dpi=90,height=3,width=6)  
+    ggsave("plots/sendInterval-cloud.png",dpi=120,height=3,width=6)  
   #+END_SRC
 
   #+RESULTS:
diff --git a/2019-Mascots.pdf b/2019-Mascots.pdf
index 917d242..19c258f 100644
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diff --git a/plots/sendInterval-cloud.png b/plots/sendInterval-cloud.png
index c6c5877..799ad30 100644
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diff --git a/plots/sensorsNumber-cloud.png b/plots/sensorsNumber-cloud.png
index 75def52..ff00c92 100644
Binary files a/plots/sensorsNumber-cloud.png and b/plots/sensorsNumber-cloud.png differ
diff --git a/plots/vmSize-cloud.png b/plots/vmSize-cloud.png
index 2f16e6a..7eea89d 100644
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