Update paper

.#2019-Mascots.org

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-loic@lguegan.1106:1558519162

2019-Mascots.org

@@ -196,7 +196,7 @@ component, formatting, style, styling, insert
    allocated memory for 20 sensors sending data every 10s. Note that red horizontal line represent
    the average energy consumption for sample of energy value. We can see that at each sensing
    interval, server face to peaks of energy consumption. However, VM allocated memory do not
-   influence energy consumption. In fact, simple database requests do not need any particular hudge
+   influence energy consumption. In fact, simple database requests do not need any particular huge
    memory access. Thus, remaining experiments are based on VM allocated memory of 1024MB.
 
    #+BEGIN_EXPORT latex
@@ -215,7 +215,10 @@ component, formatting, style, styling, insert
    \ref{fig:sensorsNumber-WPS} present the average server energy cost per sensors according to the
    number of sensors. These shows a clear linear relation between the number of sensors and the
    server energy consumption. Moreover, we can see that the more sensors we have per server, the
-   more energy we can save.
+   more energy we can save. In fact, since the idle server energy consumption is high, it is more
+   energy efficient to maximze the number of sensors per server. As showed on Figure
+   \ref{fig:sensorsNumber-WPS}, a significant amount of energy can be save when passing from 20
+   sensors to 300 per server.
 
    #+BEGIN_EXPORT latex
    \begin{figure}
@@ -233,6 +236,19 @@ component, formatting, style, styling, insert
      \label{fig:sensorsNumber-cloud}
    \end{figure}
    #+END_EXPORT
+
+   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. 
+
+   #+BEGIN_EXPORT latex
+   \begin{figure}
+  
+     \caption{Freq}
+  
+   \end{figure}
+   #+END_EXPORT
+   
    
    
 ** End-To-End Consumption