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| -rw-r--r-- | 2019-ICA3PP.org | 3 | ||||
| -rw-r--r-- | 2019-ICA3PP.pdf | bin | 685414 -> 688787 bytes | |||
| -rw-r--r-- | plots/final.png | bin | 22921 -> 21170 bytes |
3 files changed, 1 insertions, 2 deletions
diff --git a/2019-ICA3PP.org b/2019-ICA3PP.org index 4833d84..9ef1151 100644 --- a/2019-ICA3PP.org +++ b/2019-ICA3PP.org @@ -1101,7 +1101,7 @@ applicability of our model. data100=data%>%filter(nbSensors==100)%>%mutate(energy=mean(energy)) %>% slice(1L) data300=data%>%filter(nbSensors==300)%>%mutate(energy=mean(energy)) %>% slice(1L) dataCloud=rbind(data20,data100,data300)%>%mutate(sensorsNumber=nbSensors)%>%mutate(type="Cloud")%>%select(sensorsNumber,energy,type) - + dataCloud=dataCloud%>%mutate(energy=energy/7) # Divide by 7 because 14 core so 1 machine can host 14 vm but we use redundancy (2VM for 1app) # Network data=loadData("./logs/ns3/last/data.csv") @@ -1126,7 +1126,6 @@ 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)) diff --git a/2019-ICA3PP.pdf b/2019-ICA3PP.pdf Binary files differindex 95b669d..b3adb41 100644 --- a/2019-ICA3PP.pdf +++ b/2019-ICA3PP.pdf diff --git a/plots/final.png b/plots/final.png Binary files differindex 31cbb8b..fb4d444 100644 --- a/plots/final.png +++ b/plots/final.png |
