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authorLoic Guegan <manzerbredes@mailbox.org>2019-07-19 09:05:39 +0200
committerLoic Guegan <manzerbredes@mailbox.org>2019-07-19 09:05:39 +0200
commit262ab00df2e947f2663780f8a23b440530a35666 (patch)
tree2b48a1898d1fd830c73096154e8f37db32cb7d99 /2019-ICA3PP.org
parent5d4f637da768b2210389ebb049368f64310bd40e (diff)
Update paper remarks
Diffstat (limited to '2019-ICA3PP.org')
-rw-r--r--2019-ICA3PP.org18
1 files changed, 7 insertions, 11 deletions
diff --git a/2019-ICA3PP.org b/2019-ICA3PP.org
index bce8d9d..ecbd534 100644
--- a/2019-ICA3PP.org
+++ b/2019-ICA3PP.org
@@ -415,15 +415,13 @@ In this section, we analyze the experimental results.
** IoT and Network Power Consumption
In a first place, we start by studying the impact of the sensors'
transmission frequency on their energy
- consumption. To this end, we run several simulations in ns3 with different frequencies. The
+ consumption. To this end, we run several simulations in ns3 with 15 sensors using different transmission frequencies. The
results provided by Table \ref{tab:sensorsSendIntervalEffects} show
that the transmission frequency has a very low impact
- on the energy consumption and on the application delay. It has an impact of course, but it is very
+ on the energy consumption and on the cumulative end-to-end 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.
-\hl{TODO: définir le 'application delay' et le nombre de capteurs utilisés pour l'expérience de la table}
-
#+BEGIN_EXPORT latex
% Please add the following required packages to your document preamble:
% \usepackage{booktabs}
@@ -433,10 +431,10 @@ In this section, we analyze the experimental results.
\label{tab:sensorsSendIntervalEffects}
\begin{tabular}{@{}lrrrrr@{}}
\toprule
- Sensors Send Interval & 10s & 30s & 50s & 70s & 90s \\ \midrule
- Sensors Power Consumption & 13.517\hl{94}W & 13.517\hl{67}W & 13.51767W & 13.51767W & 13.517\hl{61}W \\
- Network Power Consumption & 10.441\hl{78}W & 10.441\hl{67}W & 10.44161W & 10.44161W & 10.441\hl{61}W \\
- Average Application Delay & 17.81360s & 5.91265s & 3.53509s & 2.55086s & 1.93848s \\ \bottomrule
+ Sensors Send Interval & 10s & 30s & 50s & 70s & 90s \\ \midrule
+ Sensors Power Consumption & 13.517\hl{94}W & 13.517\hl{67}W & 13.51767W & 13.51767W & 13.517\hl{61}W \\
+ Network Power Consumption & 10.441\hl{78}W & 10.441\hl{67}W & 10.44161W & 10.44161W & 10.441\hl{61}W \\
+ Cumulative Application Delay & 17.81360s & 5.91265s & 3.53509s & 2.55086s & 1.93848s \\ \bottomrule
\end{tabular}
\end{table*}
#+END_EXPORT
@@ -515,8 +513,6 @@ In our case with small and sporadic network traffic, these results show that wit
and are not shared among all the VMs that could be hosted on this
server.
- \hl{Figure 5 n'inclut pas le PUE non? le Pidle est bien à 97 Watts environ?}
-
#+BEGIN_EXPORT latex
\begin{figure}
\centering
@@ -1083,7 +1079,7 @@ applicability of our model.
xlab("Experiment Time (s)")
p=applyTheme(p)
-
+
ggsave("plots/vmSize-cloud.png",dpi=90,height=3,width=6)
#+END_SRC