paper-lowrate-iot/g5k/logs/analysis.org

• Logs Analysis
  • R Scripts
    • Plots script
      • Final plot
    • R Utils
  • Plots -> PDF
  • CSVs -> CSV
  • Custom Plots

Logs Analysis

R Scripts

Plots script

  <<RUtils>>
  dataOrig=loadData("./second-final/data.csv")

  data=dataOrig%>%filter(simKey=="nbSensors")%>%filter(state=="sim",nbSensors==100)
  dataIDLE=dataOrig%>%filter(simKey=="nbSensors")%>%filter(state!="sim",nbSensors==100)
  data=data%>%mutate(meanEnergy=mean(energy))
  dataIDLE=dataIDLE%>%mutate(meanEnergy=mean(energy))
  data=rbind(data,dataIDLE)
  ggplot(data,aes(x=time,y=energy))+geom_point(position="jitter")+xlab(getLabel("time"))+expand_limits(y=0)+facet_wrap(~state)+geom_hline(aes(color=state,yintercept=mean(meanEnergy)))
  ggsave("./second-final/plot.png",dpi=180)

# A tibble: 3,050 x 8
            ts energy simKey    vmSize nbSensors   time state meanEnergy
         <dbl>  <dbl> <chr>      <dbl>     <dbl>  <dbl> <chr>      <dbl>
 1 1558429001.   90.2 nbSensors   2048       100 0      IDLE        90.8
 2 1558429001.   89   nbSensors   2048       100 0.0199 IDLE        90.8
 3 1558429001.   89   nbSensors   2048       100 0.0399 IDLE        90.8
 4 1558429001.   90.8 nbSensors   2048       100 0.0599 IDLE        90.8
 5 1558429001.   91   nbSensors   2048       100 0.0799 IDLE        90.8
 6 1558429001.   90.5 nbSensors   2048       100 0.1000 IDLE        90.8
 7 1558429001.   89.9 nbSensors   2048       100 0.120  IDLE        90.8
 8 1558429001.   88.6 nbSensors   2048       100 0.140  IDLE        90.8
 9 1558429001.   88.6 nbSensors   2048       100 0.160  IDLE        90.8
10 1558429001.   90.5 nbSensors   2048       100 0.180  IDLE        90.8
# … with 3,040 more rows

Final plot

  <<RUtils>>
  data=loadData("./second-final/data.csv")
  data=data%>%filter(state=="sim",simKey=="nbSensors")


  # Cloud
  data10=data%>%filter(nbSensors==20)%>%mutate(meanEnergy=mean(energy)) %>% slice(1L)
  data100=data%>%filter(nbSensors==100)%>%mutate(meanEnergy=mean(energy)) %>% slice(1L)
  data300=data%>%filter(nbSensors==300)%>%mutate(meanEnergy=mean(energy)) %>% slice(1L)
  dataCloud=rbind(data10,data100,data300)%>%mutate(nbSensors=as.character(nbSensors))

  # Network
  dataNet=loadData("../../ns3-simulations/logs/data.csv")
  dataNet=dataNet%>%filter(simKey=="NBSENSORS")
  data5=dataNet%>%filter(sensorsNumber==5)%>%select(networkEnergy,sensorsNumber)
  data10=dataNet%>%filter(sensorsNumber==10)%>%select(networkEnergy,sensorsNumber)
  
  print(data20)

  ggplot(dataCloud)+geom_bar(aes(x=nbSensors,y=meanEnergy),stat="identity")+xlab("Sensors Number")+ylab("Power Consumption (W)")
  ggsave("./second-final/plot-final.png",dpi=80)

  <<RUtils>>


  data=loadData("./second-final/data.csv")
  data=data%>%filter(state=="sim",simKey=="nbSensors")

  # Cloud
  data10=data%>%filter(nbSensors==20)%>%mutate(energy=mean(energy)) %>% slice(1L)
  data100=data%>%filter(nbSensors==100)%>%mutate(energy=mean(energy)) %>% slice(1L)
  data300=data%>%filter(nbSensors==300)%>%mutate(energy=mean(energy)) %>% slice(1L)
  dataCloud=rbind(data10,data100,data300)%>%mutate(sensorsNumber=nbSensors)%>%mutate(type="Cloud")%>%select(sensorsNumber,energy,type)



  approx=function(data1, data2,nbSensors){
    x1=data1$sensorsNumber
    y1=data1$energy

    x2=data2$sensorsNumber
    y2=data2$energy

    a=((y2-y1)/(x2-x1))
    b=y1-a*x1

    return(a*nbSensors+b)

  }


  simTime=1800

  # Network
  data=read_csv("../../ns3-simulations/logs/data.csv")
  data=data%>%filter(simKey=="NBSENSORS")
  dataC5=data%>%filter(sensorsNumber==5)%>% mutate(energy=networkEnergy/simTime) %>%select(energy,sensorsNumber)
  dataC10=data%>%filter(sensorsNumber==10)%>%mutate(energy=networkEnergy/simTime) %>%select(energy,sensorsNumber)
  dataNet=rbind(dataC5,dataC10)%>%mutate(type="Network")

  # Sensors
  dataS5=data%>%filter(sensorsNumber==5)%>% mutate(energy=sensorsEnergy/simTime) %>%select(energy,sensorsNumber) 
  dataS10=data%>%filter(sensorsNumber==10)%>%mutate(energy=sensorsEnergy/simTime) %>%select(energy,sensorsNumber) 
  dataS=rbind(dataS5,dataS10)%>%mutate(type="Sensors")

  fakeNetS=tibble(
    sensorsNumber=c(20,100,300,20,100,300),
    energy=c(dataC10$energy,approx(dataC5,dataC10,100),approx(dataC5,dataC10,300),dataS10$energy,approx(dataS5,dataS10,100),approx(dataS5,dataS10,300)),
    type=c("Network","Network","Network","Sensors","Sensors","Sensors")
  )

  fakeNetS=fakeNetS%>%mutate(sensorsNumber=as.character(sensorsNumber))
  dataCloud=dataCloud%>%mutate(sensorsNumber=as.character(sensorsNumber))

  data=rbind(fakeNetS,dataCloud)%>%mutate(sensorsNumber=as.character(sensorsNumber))


  data=data%>%mutate(sensorsNumber=fct_reorder(sensorsNumber,as.numeric(sensorsNumber)))

  ggplot(data)+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="Part"))
  ggsave("final.png",dpi=80)

R Utils

RUtils is intended to load logs (data.csv) and providing simple plot function for them.

  library("tidyverse")

  # Fell free to update the following
  labels=c(time="Time (s)")

  loadData=function(path){
    data=read_csv(path)
  }

  # Get label according to varName
  getLabel=function(varName){
    if(is.na(labels[varName])){
      return(varName)
    }
    return(labels[varName])
  }

Plots -> PDF

Merge all plots in plots/ folder into a pdf file.

  orgFile="plots/plots.org"
  <<singleRun>> # To get all default arguments

  # Write helper function
  function write {
      echo "$1" >> $orgFile
  }

  echo "#+TITLE: Analysis" > $orgFile
  write "#+LATEX_HEADER: \usepackage{fullpage}"
  write "#+OPTIONS: toc:nil"
  # Default arguments
  write '\begin{center}'
  write '\begin{tabular}{lr}'
  write 'Parameters & Values\\'
  write '\hline'
  write "sensorsPktSize & ${sensorsPktSize} bytes\\\\"
  write "sensorsSendInterval & ${sensorsSendInterval}s\\\\"
  write "sensorsNumber & ${sensorsNumber}\\\\"
  write "nbHop & ${nbHop}\\\\"
  write "linksBandwidth & ${linksBandwidth}Mbps\\\\"
  write "linksLatency & ${linksLatency}ms\\\\"
  write '\end{tabular}'
  write '\newline'
  write '\end{center}'

  for plot in $(find plots/ -type f -name "*.png")
  do
      write "\includegraphics[width=0.5\linewidth]{$(basename ${plot})}"
  done

  # Export to pdf
  emacs $orgFile --batch -f org-latex-export-to-pdf --kill

CSVs -> CSV

Merge all energy file into one (and add additional fields).

  #!/bin/bash

  whichLog="second-final"


  logFile="$(dirname $(readlink -f $0))"/$whichLog/simLogs.txt
  dataFile=$(dirname "$logFile")/data.csv


  getValue () {
      line=$(echo "$1" | grep "Simulation para"|sed "s/Simulation parameters: //g")
      key=$2
      echo "$line"|awk 'BEGIN{RS=" ";FS=":"}"'$key'"==$1{gsub("\n","",$0);print $2}'
  }

  ##### Add extract info to energy #####
  IFS=$'\n'
  for cmd in $(cat $logFile|grep "Simulation parameters")
  do
      nodeName=$(getValue $cmd serverNodeName)
      from=$(getValue $cmd simStart)
      to=$(getValue $cmd simEnd)
      vmSize=$(getValue $cmd vmSize)
      nbSensors=$(getValue $cmd nbSensors)
      simKey=$(getValue $cmd simKey)
      csvFile="$whichLog/${simKey}_${vmSize}VMSIZE_${nbSensors}NBSENSORS_${from}${to}.csv"
      csvFileIDLE="$whichLog/${simKey}_${vmSize}VMSIZE_${nbSensors}NBSENSORS_${from}${to}_IDLE.csv"
      tmpFile=${csvFile}_tmp
      echo ts,energy,simKey,vmSize,nbSensors,time,state > $tmpFile
      minTs=$(tail -n+2 $csvFile|awk -F"," 'BEGIN{min=0}$1<min||min==0{min=$1}END{print(min)}') # To compute ts field
      minTsIDLE=$(tail -n+2 $csvFileIDLE|awk -F"," 'BEGIN{min=0}$1<min||min==0{min=$1}END{print(min)}') # To compute ts field
      tail -n+2 ${csvFile} | awk -F"," '{print $0",'$simKey','$vmSize','$nbSensors',"$1-'$minTs'",sim"}' >> $tmpFile
      tail -n+2 ${csvFileIDLE} | awk -F"," '{print $0",'$simKey','$vmSize','$nbSensors',"$1-'$minTsIDLE'",IDLE"}' >> $tmpFile
  done


  ##### Fill dataFile #####
  echo ts,energy,simKey,vmSize,nbSensors,time,state > $dataFile
  for tmpFile in $(find ${whichLog}/*_tmp -type f)
  do
      tail -n+2 $tmpFile >> $dataFile
      rm $tmpFile # Pay attention to this line :D
  done

Custom Plots

  <<RUtils>>

  data%>%filter(simKey=="SENDINTERVAL",sensorsNumber==20) %>% ggplot(aes(x=sensorsSendInterval,y=networkEnergy))+xlab(getLabel("sensorsSendInterval"))+ylab(getLabel("networkEnergy"))+
  geom_line()+labs(title="For 20 sensors")
  ggsave("plots/sensorsSendInterval-net.png",dpi=80)

  <<RUtils>>
  data%>%filter(simKey=="SENDINTERVAL",sensorsNumber==20) %>% ggplot(aes(x=sensorsSendInterval,y=sensorsEnergy))+xlab(getLabel("sensorsSendInterval"))+ylab(getLabel("sensorsEnergy"))+
  geom_line() +     geom_line()+labs(title="For 20 sensors")
  ggsave("plots/sensorsSendInterval-wifi.png",dpi=80)