Merge branch 'master' of gitlab.inria.fr:lguegan/paper-lowrate-iot

This commit is contained in:
ORGERIE Anne-Cecile 2019-05-28 16:51:38 +02:00
commit 3aebb53593
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loic@lguegan.1595:1558938768

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@ -36,6 +36,15 @@ Y.~Li, A.-C. Orgerie, I.~Rodero, B.~L. Amersho, M.~Parashar, and J.-M. Menaud,
\url{https://linkinghub.elsevier.com/retrieve/pii/S0167739X17314309} \url{https://linkinghub.elsevier.com/retrieve/pii/S0167739X17314309}
\BIBentrySTDinterwordspacing \BIBentrySTDinterwordspacing
\bibitem{jalali_fog_2016}
\BIBentryALTinterwordspacing
F.~Jalali, K.~Hinton, R.~Ayre, T.~Alpcan, and R.~S. Tucker,
``\BIBforeignlanguage{en}{Fog {Computing} {May} {Help} to {Save} {Energy} in
{Cloud} {Computing}},'' \emph{\BIBforeignlanguage{en}{IEEE Journal on
Selected Areas in Communications}}, vol.~34, no.~5, pp. 1728--1739, May 2016.
[Online]. Available: \url{http://ieeexplore.ieee.org/document/7439752/}
\BIBentrySTDinterwordspacing
\bibitem{orgerie_ecofen:_2011} \bibitem{orgerie_ecofen:_2011}
A.~C. Orgerie, L.~Lefèvre, I.~Guérin-Lassous, and D.~M.~L. Pacheco, A.~C. Orgerie, L.~Lefèvre, I.~Guérin-Lassous, and D.~M.~L. Pacheco,
``{ECOFEN}: {An} {End}-to-end energy {Cost} {mOdel} and simulator {For} ``{ECOFEN}: {An} {End}-to-end energy {Cost} {mOdel} and simulator {For}

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@ -3,33 +3,32 @@
#+EXPORT_EXCLUDE_TAGS: noexport #+EXPORT_EXCLUDE_TAGS: noexport
#+STARTUP: hideblocks #+STARTUP: hideblocks
#+OPTIONS: H:5 author:nil email:nil creator:nil timestamp:nil skip:nil toc:nil ^:nil #+OPTIONS: H:5 author:nil email:nil creator:nil timestamp:nil skip:nil toc:nil ^:nil
#+LATEX_CLASS: IEEEtran #+LATEX_CLASS: llncs
#+LATEX_HEADER: \usepackage{hyperref} #+LATEX_HEADER: \usepackage{hyperref}
#+LATEX_HEADER: \usepackage{booktabs} #+LATEX_HEADER: \usepackage{booktabs}
#+LATEX_HEADER: \usepackage{subfigure} #+LATEX_HEADER: \usepackage{subfigure}
#+LATEX_HEADER: \usepackage{graphicx} #+LATEX_HEADER: \usepackage{graphicx}
#+LATEX_HEADER: \IEEEoverridecommandlockouts #+LATEX_HEADER: \usepackage{xcolor}
#+LATEX_HEADER: \author{\IEEEauthorblockN{1\textsuperscript{st} Anne-Cécile Orgerie} #+LATEX_HEADER: \author{
#+LATEX_HEADER: \IEEEauthorblockA{\textit{Univ Rennes, Inria, CNRS, IRISA, Rennes, France} \\ #+LATEX_HEADER: Loic Guegan\inst{1},
#+LATEX_HEADER: Rennes, France \\ #+LATEX_HEADER: Anne-Cécile Orgerie\inst{2},\\
#+LATEX_HEADER: anne-cecile.orgerie@irisa.fr} #+LATEX_HEADER: }
#+LATEX_HEADER: \and #+LATEX_HEADER: \institute{Univ Rennes, Inria, CNRS, IRISA, Rennes, France\\
#+LATEX_HEADER: \IEEEauthorblockN{2\textsuperscript{nd} Loic Guegan} #+LATEX_HEADER: Emails: anne-cecile.orgerie@irisa.fr\inst{1}, loic.guegan@irisa.fr\inst{2}
#+LATEX_HEADER: \IEEEauthorblockA{\textit{Univ Rennes, Inria, CNRS, IRISA, Rennes, France} \\
#+LATEX_HEADER: Rennes, France \\
#+LATEX_HEADER: loic.guegan@irisa.fr}
#+LATEX_HEADER: } #+LATEX_HEADER: }
#+BEGIN_EXPORT latex
\newcommand{\hl}[1]{\textcolor{red}{#1}}
#+END_EXPORT
#+BEGIN_EXPORT latex #+BEGIN_EXPORT latex
\begin{abstract} \begin{abstract}
Information and Communication Technology takes a growing part in the worldwide energy consumption. One of the root causes of this increase lies in the multiplication of connected devices. Each object of the Internet-of-Things often does not consume much energy by itself. Yet, their number and the infrastructures they require to properly work have leverage. In this paper, we combine simulations and real measurements to study the energy impact of IoT devices. In particular, we analyze the energy consumption of Cloud and telecommunication infrastructures induced by the utilization of connected devices, and we propose an end-to-end energy consumption model for these devices. Information and Communication Technology takes a growing part in the worldwide energy consumption. One of the root causes of this increase lies in the multiplication of connected devices. Each object of the Internet-of-Things often does not consume much energy by itself. Yet, their number and the infrastructures they require to properly work have leverage. In this paper, we combine simulations and real measurements to study the energy impact of IoT devices. In particular, we analyze the energy consumption of Cloud and telecommunication infrastructures induced by the utilization of connected devices, and we propose an end-to-end energy consumption model for these devices.
\end{abstract} \end{abstract}
\begin{IEEEkeywords}
component, formatting, style, styling, insert
\end{IEEEkeywords}
#+END_EXPORT #+END_EXPORT
@ -117,13 +116,15 @@ Smart cities \cite{Ejaz2017}
The network part represents the a network section starting from the AP to the Cloud excluding the The network part represents the a network section starting from the AP to the Cloud excluding the
server. It is also model into ns-3. We consider the server to be 9 hops away from the AP with a server. It is also model into ns-3. We consider the server to be 9 hops away from the AP with a
typical round-trip latency of 100ms from the AP to the server. Each node from the AP to the Cloud typical round-trip latency of 100ms from the AP to the server. Each node from the AP to the Cloud
is assume to be network switches with static and dynamic network energy consumption. ECOFEN is assume to be network switches with static and dynamic network energy consumption. The first 8
\cite{orgerie_ecofen:_2011} is used to model the energy consumption of the network part. ECOFEN hop are edge switches and the last one is consider to be a core switch as mention in
is a ns-3 network energy module dedicated to wired network. It is based on an energy-per-bit \cite{jalali_fog_2016}. ECOFEN \cite{orgerie_ecofen:_2011} is used to model the energy
model including static energy consumption by assuming a linear relation between the amount of consumption of the network part. ECOFEN is a ns-3 network energy module dedicated to wired
data sent to the network interface and its power consumption. The different energy values used to network. It is based on an energy-per-bit model including static energy consumption by assuming a
instantiate the ECOFEN energy model for the network part are shown in Table \ref{tab:net-energy} linear relation between the amount of data sent to the network interface and its power
and come from previous work \cite{cornea_studying_2014-1}. consumption. The different energy values used to instantiate the ECOFEN energy model for the
network part are shown in Table \ref{tab:net-energy} and come from previous work
\cite{cornea_studying_2014-1}.
** Cloud Part ** Cloud Part
Finally, to measure the energy consumed by the server, we used real server from the large-scale Finally, to measure the energy consumed by the server, we used real server from the large-scale
@ -144,39 +145,41 @@ Smart cities \cite{Ejaz2017}
** IoT/Network Consumption ** IoT/Network Consumption
In a first place, we start by studying the impact of the sensors position on their energy In a first place, we start by studying the impact of the sensors position on their energy
consumption. To this end, we run several simulations in ns-3 with different sensors position. The consumption. To this end, we run several simulations in ns-3 with different sensors position. The
results provided by Figure \ref{fig:sensorsPos} show that sensors position have a very low impact results provided by Table \ref{tab:sensorsSendIntervalEffects} show that sensors position have 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 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 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. spread over the time, sensors don't have to contend for accessing to the Wifi channel.
#+BEGIN_EXPORT latex #+BEGIN_EXPORT latex
\begin{figure} % Please add the following required packages to your document preamble:
\centering % \usepackage{booktabs}
\includegraphics[width=0.6\linewidth]{./plots/sensorsPosition-delayenergy.png} \begin{table*}[]
\caption{Effects of sensors position on the application delay and the sensors energy consumption in a cell of 9 sensors.} \centering
\label{fig:sensorsPos} \caption{Sensors send interval effects}
\end{figure} \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 Appplication Delay & 17.81360s & 5.91265s & 3.53509s & 2.55086s & 1.93848s \\ \bottomrule
\end{tabular}
\end{table*}
#+END_EXPORT #+END_EXPORT
Previous work \cite{li_end--end_2018} on similar scenario shows that increasing application
accuracy impact strongly the energy consumption in the context of data stream analysis. However,
in our case, application accuracy is driven by the sensing interval and thus, the transmit
frequency of the sensors. Therefore, we varied the transmission interval of the sensors from 1s
to 60s. Figure \ref{fig:frequency} present the effects of the sensors transmission interval on
the IoT/Network part energy consumption. In case of small and sporadic network traffic, these
results show that with a reasonable transmission interval the energy consumption of the
IoT/Network if almost not affected by the variation of this transmission interval. In fact,
transmitted data are not large enough to leverage the energy consumed by the network.
#+BEGIN_EXPORT latex Previous work \cite{li_end--end_2018} on similar scenario shows that increasing application
\begin{figure} accuracy impact strongly the energy consumption in the context of data stream analysis. However,
\centering in our case, application accuracy is driven by the sensing interval and thus, the transmit
\includegraphics[scale=0.45]{./plots/sendFrequency-energy.png} frequency of the sensors. Therefore, we varied the transmission interval of the sensors from 1s
\caption{Sensors send interval and its influence on the IoT/Network part energy consumption.} to 60s. Some of these results are proposed on Table \ref{tab:sensorsSendIntervalEffects}. In
\label{fig:frequency} case of small and sporadic network traffic, these results show that with a reasonable
\end{figure} transmission interval the energy consumption of the IoT/Network if almost not affected by the
#+END_EXPORT variation of this transmission interval. In fact, transmitted data are not large enough to
leverage the energy consumed by the network.
The number of sensors is a dominant factor that leverage the energy consumption of the The number of sensors is a dominant factor that leverage the energy consumption of the
IoT/Network part. Therefore, we varied the number of sensors in the Wifi cell to analyze its IoT/Network part. Therefore, we varied the number of sensors in the Wifi cell to analyze its
@ -274,7 +277,7 @@ Smart cities \cite{Ejaz2017}
sensors. However, since we are using a single server, large-scale sensors deployment lead to an sensors. However, since we are using a single server, large-scale sensors deployment lead to an
increasing consumption of energy in the IoT part. On the other side, network energy consumption increasing consumption of energy in the IoT part. On the other side, network energy consumption
is stable regarding to the number of sensors since the system use case do not required large data is stable regarding to the number of sensors since the system use case do not required large data
transfert. Thus, it is important to remember that, to save energy, we should maximize the number transfer. Thus, it is important to remember that, to save energy, we should maximize the number
of sensors handle by each cloud server while keeping reasonable sensors request intervals. of sensors handle by each cloud server while keeping reasonable sensors request intervals.
#+BEGIN_EXPORT latex #+BEGIN_EXPORT latex
@ -307,7 +310,7 @@ Smart cities \cite{Ejaz2017}
simple plot function for them. simple plot function for them.
#+NAME: RUtils #+NAME: RUtils
#+BEGIN_SRC R :eval never #+BEGIN_SRC R :eval never
library("tidyverse") library("tidyverse")
# Fell free to update the following # Fell free to update the following
@ -321,6 +324,7 @@ Smart cities \cite{Ejaz2017}
if("sensorsEnergy"%in%colnames(data)){ # If it is ns3 logs if("sensorsEnergy"%in%colnames(data)){ # If it is ns3 logs
data=data%>%mutate(sensorsEnergy=sensorsEnergy/ns3SimTime) # Convert to watts data=data%>%mutate(sensorsEnergy=sensorsEnergy/ns3SimTime) # Convert to watts
data=data%>%mutate(networkEnergy=networkEnergy/ns3SimTime) data=data%>%mutate(networkEnergy=networkEnergy/ns3SimTime)
data=data%>%mutate(networkEnergy=networkEnergy+getSwitchesIDLE(sensorsNumber,sensorsSendInterval)) # Add Idle conso of switches
data=data%>%mutate(totalEnergy=totalEnergy/ns3SimTime) data=data%>%mutate(totalEnergy=totalEnergy/ns3SimTime)
} }
else{ # Log from g5k else{ # Log from g5k
@ -329,6 +333,32 @@ Smart cities \cite{Ejaz2017}
} }
} }
getSwitchesIDLE=function(nbSensors, sendInterval){
pktSize=192
nEdgeRouter=8
nCoreRouter=1
EdgeIdle=4095
EdgeMax=4550
EdgeTraffic=560*10^9
CoreIdle=11070
CoreMax=12300
CoreTraffic=4480*10^9
# Apply 0.6 factor
EdgeTraffic=EdgeTraffic*0.6
CoreTraffic=CoreTraffic*0.6
totalTraffic=pktSize/sendInterval*nbSensors
EdgeConso=EdgeIdle*(totalTraffic/EdgeTraffic)
CoreConso=CoreIdle*(totalTraffic/CoreTraffic)
return(EdgeConso+CoreConso)
}
# Get label according to varName # Get label according to varName
getLabel=function(varName){ getLabel=function(varName){
if(is.na(labels[varName])){ if(is.na(labels[varName])){
@ -345,7 +375,11 @@ Smart cities \cite{Ejaz2017}
scale_colour_manual(values=palette) scale_colour_manual(values=palette)
return(plot) return(plot)
} }
#+END_SRC #+END_SRC
**** Bash **** Bash
***** Plots -> PDF ***** Plots -> PDF
Merge all plots in plots/ folder into a pdf file. Merge all plots in plots/ folder into a pdf file.
@ -474,10 +508,59 @@ Smart cities \cite{Ejaz2017}
*** Plot Scripts *** Plot Scripts
**** Random R Scripts **** Random R Scripts
Table sensorsSendInterval~Sensors+NetEnergyconsumption
#+BEGIN_SRC R :noweb yes :results output
<<RUtils>>
data=loadData("logs/ns3/last/data.csv")
sensorsE=data%>%filter(simKey=="SENDINTERVAL",sensorsNumber==15) %>%select(sensorsSendInterval,sensorsEnergy)%>%arrange(sensorsSendInterval)
delay=data%>%filter(simKey=="SENDINTERVAL",sensorsNumber==15) %>%select(sensorsSendInterval,avgDelay)%>%arrange(sensorsSendInterval)
netE=data%>%filter(simKey=="SENDINTERVAL",sensorsNumber==15) %>%select(sensorsSendInterval,networkEnergy)%>%arrange(sensorsSendInterval)
formatData=right_join(sensorsE,netE)%>%right_join(delay)%>%filter(((sensorsSendInterval/10)%%2)!=0)
print(t(formatData))
#+END_SRC
#+RESULTS:
: [,1] [,2] [,3] [,4] [,5]
: sensorsSendInterval 10.00000 30.00000 50.00000 70.00000 90.00000
: sensorsEnergy 13.51794 13.51767 13.51767 13.51767 13.51761
: networkEnergy 10.44178 10.44167 10.44161 10.44161 10.44161
: avgDelay 17.81360 5.91265 3.53509 2.55086 1.93848
Figure Sensors Position ~ Energy/Delay
#+BEGIN_SRC R :noweb yes :results graphics :file plots/sensorsPosition-delayenergy.png
<<RUtils>>
tr=11 # Offset to center delay plot
data=loadData("logs/ns3/last/data.csv")
data=data%>%filter(simKey=="SENSORSPOS",sensorsNumber==9)
p=ggplot(data,aes(y=sensorsEnergy,x=positionSeed,color="Energy"))+xlab(getLabel("Sensors Position Seed"))+ylab(getLabel("Sensors Power Consumption (W)"))+
geom_line()+geom_point()+geom_line(aes(y=(avgDelay-tr),color="Delay"))+geom_point(aes(y=(avgDelay-tr),color="Delay"))+expand_limits(y=c(0,15))+
scale_y_continuous(sec.axis = sec_axis(~.+tr, name = "Application Delay (s)")) +
guides(color=guide_legend(title="Curves"))
p=applyTheme(p)
p=p+theme(axis.title.y.right = element_text(margin = margin(t = 0, r = -8, b = 0, l = 10)))
ggsave("plots/sensorsPosition-delayenergy.png",dpi=80, width=4, height=3.2)
#+END_SRC
#+RESULTS:
[[file:plots/sensorsPosition-delayenergy.png]]
Watt per sensor on server Watt per sensor on server
#+BEGIN_SRC R :noweb yes :results output #+BEGIN_SRC R :noweb yes :results output
<<RUtils>> <<RUtils>>
@ -508,7 +591,7 @@ Smart cities \cite{Ejaz2017}
data=data%>%group_by(vmSize)%>%mutate(energy=mean(energy))%>%slice(1L)%>%ungroup() data=data%>%group_by(vmSize)%>%mutate(energy=mean(energy))%>%slice(1L)%>%ungroup()
data=data%>%mutate(vmSize=as.character(vmSize)) 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)")+ ggplot(data) + geom_bar(aes(x=vmSize,y=energy),stat="identity")+expand_limits(y=c(75,100))+ylab("Server Power Consumption (W)")+
xlab("Experiment Time (s)")+scale_y_log10() xlab("Experiment Time (s)")+scale_y_log10()
@ -558,7 +641,7 @@ Smart cities \cite{Ejaz2017}
#+END_SRC #+END_SRC
#+BEGIN_SRC R :results graphics :noweb yes :file plot-final.png :session *R* #+BEGIN_SRC R :results graphics :noweb yes :file plots/plot-final.png :session *R*
<<NS3-RUtils>> <<NS3-RUtils>>
simTime=1800 simTime=1800
@ -577,203 +660,148 @@ Smart cities \cite{Ejaz2017}
data=rbind(dataNet,dataS)%>%mutate(sensorsNumber=as.character(sensorsNumber)) data=rbind(dataNet,dataS)%>%mutate(sensorsNumber=as.character(sensorsNumber))
ggplot(data)+geom_bar(aes(x=sensorsNumber,y=energy,fill=type),stat="identity")+xlab("Sensors Number")+ylab("Power Consumption (W)")+guides(fill=guide_legend(title="Part")) ggplot(data)+geom_bar(aes(x=sensorsNumber,y=energy,fill=type),stat="identity")+xlab("Sensors Number")+ylab("Power Consumption (W)")+guides(fill=guide_legend(title="Part"))
ggsave("plot-final.png",dpi=80) ggsave("plots/plot-final.png",dpi=80)
#+END_SRC #+END_SRC
**** Plot In Paper **** Plot In Paper
Figure Power sensors vs network
#+BEGIN_SRC R :noweb yes :results graphics :file plots/sendFrequency-energy.png #+BEGIN_SRC R :noweb yes :results graphics :file plots/numberSensors-WIFINET.png :session *R*
<<RUtils>>
data=loadData("logs/ns3/last/data.csv")
data=data%>%filter(simKey=="NBSENSORS")
dataW=data%>%mutate(energy=sensorsEnergy)%>% mutate(type="Sensors") %>% select(sensorsNumber,energy,type)
dataN=data%>%mutate(energy=networkEnergy)%>% mutate(type="Network") %>% select(sensorsNumber,energy,type)
data=rbind(dataN,dataW)
data=data%>%mutate(sensorsNumber=as.character(sensorsNumber))
data=data%>%mutate(sensorsNumber=fct_reorder(sensorsNumber,as.numeric(sensorsNumber)))
data=data%>%filter(sensorsNumber%in%c(2,4,6,8,10))
p=ggplot(data)+geom_bar(aes(x=sensorsNumber,y=energy,fill=type),position="dodge",stat="identity")+
xlab(getLabel("sensorsNumber"))+ ylab("Power Consumption (W)") + guides(fill=guide_legend(title=""))
p=applyTheme(p)+theme(text = element_text(size=15))
size=5
ggsave("plots/numberSensors-WIFINET.png",dpi=90,width=size,height=size-1)
#+END_SRC
#+RESULTS:
[[file:plots/numberSensors-WIFINET.png]]
Final plot: Energy cloud, network and sensors
#+BEGIN_SRC R :noweb yes :results graphics :file plots/final.png
<<RUtils>> <<RUtils>>
data=loadData("logs/ns3/last/data.csv") # Linear Approx
data=data%>%filter(simKey=="SENDINTERVAL",sensorsNumber==15) approx=function(data1, data2,nbSensors){
x1=data1$sensorsNumber
y1=data1$energy
p=ggplot(data,aes(y=totalEnergy,x=sensorsSendInterval))+ x2=data2$sensorsNumber
xlab(getLabel("sensorsSendInterval"))+ylab(getLabel("Sensors And Network\nEnergy Consumption (W)"))+ y2=data2$energy
geom_line()+geom_point()+expand_limits(y=c(0,50))+
guides(color=guide_legend(title="Curves"))+
theme(axis.title.y.right = element_text(margin = margin(t = 0, r = -13, b = 0, l = 7)))
p=applyTheme(p)
ggsave("plots/sendFrequency-energy.png",dpi=100, width=3, height=2.8) a=((y2-y1)/(x2-x1))
#+END_SRC b=y1-a*x1
#+RESULTS: return(a*nbSensors+b)
[[file:plots/sendFrequency-energy.png]]
}
# Load data
data=loadData("./logs/g5k/last/data.csv")
data=data%>%filter(state=="sim",simKey=="nbSensors")
Figure Sensors Position ~ Energy/Delay # Cloud
#+BEGIN_SRC R :noweb yes :results graphics :file plots/sensorsPosition-delayenergy.png data20=data%>%filter(nbSensors==20)%>%mutate(energy=mean(energy)) %>% slice(1L)
<<RUtils>> data100=data%>%filter(nbSensors==100)%>%mutate(energy=mean(energy)) %>% slice(1L)
tr=171 # Offset to center delay plot data300=data%>%filter(nbSensors==300)%>%mutate(energy=mean(energy)) %>% slice(1L)
data=loadData("logs/ns3/last/data.csv") dataCloud=rbind(data20,data100,data300)%>%mutate(sensorsNumber=nbSensors)%>%mutate(type="Cloud")%>%select(sensorsNumber,energy,type)
data=data%>%filter(simKey=="SENSORSPOS",sensorsNumber==9)
p=ggplot(data,aes(y=sensorsEnergy,x=positionSeed,color="Energy"))+xlab(getLabel("Sensors Position Seed"))+ylab(getLabel("Sensors Energy Consumption (W)"))+
geom_line()+geom_point()+geom_line(aes(y=(avgDelay-tr),color="Delay"))+geom_point(aes(y=(avgDelay-tr),color="Delay"))+expand_limits(y=c(0,15))+
scale_y_continuous(sec.axis = sec_axis(~.+tr, name = "Application Delay (s)")) +
guides(color=guide_legend(title="Curves"))
p=applyTheme(p)
p=p+theme(axis.title.y.right = element_text(margin = margin(t = 0, r = -8, b = 0, l = 10)))
# Network
ggsave("plots/sensorsPosition-delayenergy.png",dpi=80, width=4, height=3.2) data=loadData("./logs/ns3/last/data.csv")
#+END_SRC
#+RESULTS:
[[file:plots/sensorsPosition-delayenergy.png]]
#+BEGIN_SRC R :noweb yes :results graphics :file plots/numberSensors-WIFINET.png :session *R*
<<RUtils>>
data=loadData("logs/ns3/last/data.csv")
data=data%>%filter(simKey=="NBSENSORS") data=data%>%filter(simKey=="NBSENSORS")
dataW=data%>%mutate(energy=sensorsEnergy)%>% mutate(type="Sensors") %>% select(sensorsNumber,energy,type) dataN5=data%>%filter(sensorsNumber==5)%>% mutate(energy=networkEnergy) %>%select(energy,sensorsNumber)
dataN=data%>%mutate(energy=networkEnergy)%>% mutate(type="Network") %>% select(sensorsNumber,energy,type) dataN10=data%>%filter(sensorsNumber==10)%>%mutate(energy=networkEnergy) %>%select(energy,sensorsNumber)
dataNet=rbind(dataN5,dataN10)
fakeNet=tibble(sensorsNumber=c(20,100,300))
fakeNet=fakeNet%>%mutate(energy=approx(dataN5,dataN10,sensorsNumber),type="Network")
data=rbind(dataN,dataW) # Sensors
data=data%>%mutate(sensorsNumber=as.character(sensorsNumber)) dataS5=data%>%filter(sensorsNumber==5)%>% mutate(energy=sensorsEnergy) %>%select(energy,sensorsNumber)
data=data%>%mutate(sensorsNumber=fct_reorder(sensorsNumber,as.numeric(sensorsNumber))) dataS10=data%>%filter(sensorsNumber==10)%>%mutate(energy=sensorsEnergy) %>%select(energy,sensorsNumber)
data=data%>%filter(sensorsNumber%in%c(2,4,6,8,10)) dataS=rbind(dataS5,dataS10)
fakeS=tibble(sensorsNumber=c(20,100,300))
fakeS=fakeNet%>%mutate(energy=approx(dataS5,dataS10,sensorsNumber),type="Sensors")
p=ggplot(data)+geom_bar(aes(x=sensorsNumber,y=energy,fill=type),position="dodge",stat="identity")+ # Combine Net/Sensors/Cloud and order factors
xlab(getLabel("sensorsNumber"))+ ylab("Energy Consumption (W)") + guides(fill=guide_legend(title="")) fakeData=rbind(fakeNet,fakeS,dataCloud)
p=applyTheme(p)+theme(text = element_text(size=15)) fakeData=fakeData%>%mutate(sensorsNumber=as.character(sensorsNumber))
fakeData=fakeData%>%mutate(sensorsNumber=fct_reorder(sensorsNumber,as.numeric(sensorsNumber)))
fakeData$type=factor(fakeData$type,ordered=TRUE,levels=c("Sensors","Network","Cloud"))
# Plot
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))
ggsave("plots/final.png",dpi=90,width=8,height=5.5)
size=5
ggsave("plots/numberSensors-WIFINET.png",dpi=90,width=size,height=size-1)
#+END_SRC #+END_SRC
#+RESULTS: #+RESULTS:
[[file:plots/numberSensors-WIFINET.png]] [[file:plots/final.png]]
Impact of vm size
#+BEGIN_SRC R :noweb yes :results graphics :noweb yes :file plots/vmSize-cloud.png
<<RUtils>>
# Load data
data=loadData("./logs/g5k/last/data.csv")
data=data%>%filter(state=="sim",simKey=="vmSize")%>%filter(time<=300)
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 Power Consumption (W)")+
xlab("Experiment Time (s)")
p=applyTheme(p)
ggsave("plots/vmSize-cloud.png",dpi=90,height=3,width=6)
#+END_SRC
#+RESULTS:
[[file:plots/vmSize-cloud.png]]
Impact of sensors number
#+BEGIN_SRC R :noweb yes :results graphics :file plots/sensorsNumber-cloud.png
<<RUtils>>
# Load data
data=loadData("./logs/g5k/last/data.csv")
data=data%>%filter(state=="sim",simKey=="nbSensors")%>%ungroup()
Final plot: Energy cloud, network and sensors data=data%>%mutate(nbSensorsSort=nbSensors)
#+BEGIN_SRC R :noweb yes :results output graphics :file plots/final.png data=data%>%mutate(nbSensors=paste0(nbSensors," Sensors"))
<<RUtils>> data$nbSensors=fct_reorder(data$nbSensors, data$nbSensorsSort)
# Load data data=data%>%group_by(nbSensors)%>%mutate(avgEnergy=mean(energy))%>%ungroup()
data=loadData("./logs/g5k/last/data.csv") p=ggplot(data,aes(x=time, y=energy)) + geom_line()+facet_wrap(~nbSensors)+expand_limits(y=c(0,40))+ylab("Server Power Consumption (W)")+
data=data%>%filter(state=="sim",simKey=="nbSensors") xlab("Experiment Time (s)")+geom_hline(aes(yintercept=avgEnergy),color="Red",size=1.0)
# Cloud
data10=data%>%filter(nbSensors==20)%>%mutate(energy=mean(energy)) %>% slice(1L)
data100=data%>%filter(nbSensors==100)%>%mutate(energy=mean(energy)) %>% slice(1L)
data300=data%>%filter(nbSensors==300)%>%mutate(energy=mean(energy)) %>% slice(1L)
dataCloud=rbind(data10,data100,data300)%>%mutate(sensorsNumber=nbSensors)%>%mutate(type="Cloud")%>%select(sensorsNumber,energy,type)
approx=function(data1, data2,nbSensors){
x1=data1$sensorsNumber
y1=data1$energy
x2=data2$sensorsNumber
y2=data2$energy
a=((y2-y1)/(x2-x1))
b=y1-a*x1
return(a*nbSensors+b)
}
simTime=1800
# Network
data=read_csv("./logs/ns3/last/data.csv")
data=data%>%filter(simKey=="NBSENSORS")
dataC5=data%>%filter(sensorsNumber==5)%>% mutate(energy=networkEnergy/simTime) %>%select(energy,sensorsNumber)
dataC10=data%>%filter(sensorsNumber==10)%>%mutate(energy=networkEnergy/simTime) %>%select(energy,sensorsNumber)
dataNet=rbind(dataC5,dataC10)%>%mutate(type="Network")
# Sensors
dataS5=data%>%filter(sensorsNumber==5)%>% mutate(energy=sensorsEnergy/simTime) %>%select(energy,sensorsNumber)
dataS10=data%>%filter(sensorsNumber==10)%>%mutate(energy=sensorsEnergy/simTime) %>%select(energy,sensorsNumber)
dataS=rbind(dataS5,dataS10)%>%mutate(type="Sensors")
fakeNetS=tibble(
sensorsNumber=c(20,100,300,20,100,300),
energy=c(dataC10$energy,approx(dataC5,dataC10,100),approx(dataC5,dataC10,300),dataS10$energy,approx(dataS5,dataS10,100),approx(dataS5,dataS10,300)),
type=c("Network","Network","Network","Sensors","Sensors","Sensors")
)
fakeNetS=fakeNetS%>%mutate(sensorsNumber=as.character(sensorsNumber))
dataCloud=dataCloud%>%mutate(sensorsNumber=as.character(sensorsNumber))
data=rbind(fakeNetS,dataCloud)%>%mutate(sensorsNumber=as.character(sensorsNumber))
data=data%>%mutate(sensorsNumber=fct_reorder(sensorsNumber,as.numeric(sensorsNumber)))
data$type=factor(data$type,ordered=TRUE,levels=c("Sensors","Network","Cloud"))
p=ggplot(data)+geom_bar(position="dodge2",colour="black",aes(x=sensorsNumber,y=energy,fill=type),stat="identity")+
xlab("Sensors Number")+ylab("Energy Consumption (W)")+guides(fill=guide_legend(title="System Part"))
p=applyTheme(p)+theme(text = element_text(size=16))
ggsave("plots/final.png",dpi=90,width=8,height=5.5)
#+END_SRC
#+RESULTS:
[[file:plots/final.png]]
Impact of vm size
#+BEGIN_SRC R :noweb yes :results graphics :noweb yes :file plots/vmSize-cloud.png
<<RUtils>>
# Load data
data=loadData("./logs/g5k/last/data.csv")
data=data%>%filter(state=="sim",simKey=="vmSize")%>%filter(time<=300)
data=data%>%mutate(vmSize=paste0(vmSize," MB"))
data=data%>%group_by(vmSize)%>%mutate(avgEnergy=mean(energy))%>%ungroup()
p=ggplot(data,aes(x=time, y=energy)) + geom_line()+facet_wrap(~vmSize)+geom_hline(aes(yintercept=avgEnergy),color="Red",size=1.0)+expand_limits(y=c(0,40))+ylab("Server Energy Consumption (W)")+
xlab("Experiment Time (s)")
p=applyTheme(p)
ggsave("plots/vmSize-cloud.png",dpi=90,height=3,width=6)
#+END_SRC
#+RESULTS:
[[file:plots/vmSize-cloud.png]]
Impact of sensors number
#+BEGIN_SRC R :noweb yes :results graphics :file plots/sensorsNumber-cloud.png
<<RUtils>>
# Load data
data=loadData("./logs/g5k/last/data.csv")
data=data%>%filter(state=="sim",simKey=="nbSensors")%>%ungroup()
data=data%>%mutate(nbSensorsSort=nbSensors)
data=data%>%mutate(nbSensors=paste0(nbSensors," Sensors"))
data$nbSensors=fct_reorder(data$nbSensors, data$nbSensorsSort)
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("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)
#+END_SRC
#+RESULTS:
[[file:plots/sensorsNumber-cloud.png]]
p=applyTheme(p)
ggsave("plots/sensorsNumber-cloud.png",dpi=90,height=3,width=6)
#+END_SRC
#+RESULTS:
[[file:plots/sensorsNumber-cloud.png]]
#+BEGIN_SRC R :noweb yes :results graphics :file plots/sensorsNumberLine-cloud.png :session *R:2* #+BEGIN_SRC R :noweb yes :results graphics :file plots/sensorsNumberLine-cloud.png :session *R:2*
<<RUtils>> <<RUtils>>
@ -788,77 +816,69 @@ Smart cities \cite{Ejaz2017}
data=data%>%mutate(WPS=(avgEnergy/nbSensors)) data=data%>%mutate(WPS=(avgEnergy/nbSensors))
p=ggplot(data,aes(x=nbSensors, y=avgEnergy)) + geom_point() +geom_line()+ p=ggplot(data,aes(x=nbSensors, y=avgEnergy)) + geom_point() +geom_line()+
xlab(getLabel("sensorsNumber"))+ylab("Average Server Energy (W)") xlab(getLabel("sensorsNumber"))+ylab("Average server power consumption (W)")
p=applyTheme(p)+theme(text = element_text(size=14))+ expand_limits(y=108) p=applyTheme(p)+theme(text = element_text(size=14))+ expand_limits(y=108)
ggsave("plots/sensorsNumberLine-cloud.png",dpi=90,height=4,width=4) ggsave("plots/sensorsNumberLine-cloud.png",dpi=90,height=4.5,width=4)
#+END_SRC #+END_SRC
#+RESULTS: #+RESULTS:
[[file:plots/sensorsNumberLine-cloud.png]] [[file:plots/sensorsNumberLine-cloud.png]]
#+BEGIN_SRC R :noweb yes :results graphics :file plots/WPS-cloud.png :session *R:2*
<<RUtils>>
# Load data
data=loadData("./logs/g5k/last/data.csv")
data=data%>%filter(state=="sim",simKey=="nbSensors")%>%ungroup()
#+BEGIN_SRC R :noweb yes :results graphics :file plots/WPS-cloud.png :session *R:2* data=data%>%group_by(nbSensors)%>%mutate(avgEnergy=mean(energy))%>%distinct()%>%ungroup()
<<RUtils>> data=data%>%distinct(nbSensors,.keep_all=TRUE)
# Load data data=data%>%mutate(WPS=(avgEnergy/nbSensors))
data=loadData("./logs/g5k/last/data.csv")
data=data%>%filter(state=="sim",simKey=="nbSensors")%>%ungroup() oldNb=data$nbSensors
data=data%>%mutate(nbSensors=as.character(nbSensors))
data$nbSensors=fct_reorder(data$nbSensors,oldNb)
p=ggplot(data,aes(x=nbSensors, y=WPS)) + geom_bar(stat="identity")+
xlab(getLabel("sensorsNumber"))+ylab("Server power cost per sensors (W)")
p=applyTheme(p)+theme(text = element_text(size=14))+ theme(axis.title.y = element_text(margin = margin(t = 0, r = 8, b = 0, l = 0)))
ggsave("plots/WPS-cloud.png",dpi=90,height=4,width=4)
#+END_SRC
data=data%>%group_by(nbSensors)%>%mutate(avgEnergy=mean(energy))%>%distinct()%>%ungroup() #+RESULTS:
data=data%>%distinct(nbSensors,.keep_all=TRUE) [[file:plots/WPS-cloud.png]]
data=data%>%mutate(WPS=(avgEnergy/nbSensors))
oldNb=data$nbSensors #+BEGIN_SRC R :noweb yes :results graphics :file plots/sendInterval-cloud.png
data=data%>%mutate(nbSensors=as.character(nbSensors)) <<RUtils>>
data$nbSensors=fct_reorder(data$nbSensors,oldNb) # Load data
p=ggplot(data,aes(x=nbSensors, y=WPS)) + geom_bar(stat="identity")+ data=loadData("./logs/g5k/last/data.csv")
xlab(getLabel("sensorsNumber"))+ylab("Server energy cost per sensors (W)")
p=applyTheme(p)+theme(text = element_text(size=14))+ theme(axis.title.y = element_text(margin = margin(t = 0, r = 8, b = 0, l = 0))) data=data%>%filter(state=="sim",simKey=="sendInterval")%>%ungroup()
ggsave("plots/WPS-cloud.png",dpi=90,height=4,width=4)
#+END_SRC
#+RESULTS: oldSendInterval=data$sendInterval
[[file:plots/WPS-cloud.png]] data=data%>%mutate(sendInterval=paste0(sendInterval,"s"))
data$sendInterval=fct_reorder(data$sendInterval,oldSendInterval)
#+BEGIN_SRC R :noweb yes :results graphics :file plots/sendInterval-cloud.png
<<RUtils>>
# Load data
data=loadData("./logs/g5k/last/data.csv")
data=data%>%filter(state=="sim",simKey=="sendInterval")%>%ungroup()
oldSendInterval=data$sendInterval
data=data%>%mutate(sendInterval=paste0(sendInterval,"s"))
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("Experiment Time (s)")+geom_hline(aes(yintercept=avgEnergy),color="Red",size=1.0)
p=applyTheme(p)
ggsave("plots/sendInterval-cloud.png",dpi=120,height=3,width=6)
#+END_SRC
#+RESULTS:
[[file:plots/sendInterval-cloud.png]]
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 power consumption (W)")+
xlab("Experiment Time (s)")+geom_hline(aes(yintercept=avgEnergy),color="Red",size=1.0)
p=applyTheme(p)
ggsave("plots/sendInterval-cloud.png",dpi=120,height=3,width=6)
#+END_SRC
#+RESULTS:
[[file:plots/sendInterval-cloud.png]]
* Emacs settings :noexport: * Emacs settings :noexport:
# Local Variables: # Local Variables:
# eval: (unless (boundp 'org-latex-classes) (setq org-latex-classes nil)) # eval: (unless (boundp 'org-latex-classes) (setq org-latex-classes nil))
# eval: (add-to-list 'org-latex-classes # eval: (add-to-list 'org-latex-classes
# '("IEEEtran" "\\documentclass[conference]{IEEEtran}\n \[NO-DEFAULT-PACKAGES]\n \[EXTRA]\n" ("\\section{%s}" . "\\section*{%s}") ("\\subsection{%s}" . "\\subsection*{%s}") ("\\subsubsection{%s}" . "\\subsubsection*{%s}") ("\\paragraph{%s}" . "\\paragraph*{%s}") ("\\subparagraph{%s}" . "\\subparagraph*{%s}"))) # '("llncs" "\\documentclass[conference]{llncs}\n \[NO-DEFAULT-PACKAGES]\n \[EXTRA]\n" ("\\section{%s}" . "\\section*{%s}") ("\\subsection{%s}" . "\\subsection*{%s}") ("\\subsubsection{%s}" . "\\subsubsection*{%s}") ("\\paragraph{%s}" . "\\paragraph*{%s}") ("\\subparagraph{%s}" . "\\subparagraph*{%s}")))
# End: # End:

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@ -1,986 +0,0 @@
sensorsSendInterval,sensorsPktSize,sensorsNumber,nbHop,linksBandwidth,linksLatency,totalEnergy,nbPacketCloud,nbNodes,avgDelay,ns3Version,simKey,positionSeed,sensorsEnergy,networkEnergy
60,5,20,10,10,2,66465.3,580,30,0.591748,3.29,SENDINTERVAL,5,32442.4,34022.9
10,5,15,10,10,2,58355.1,2685,25,3.35431,3.29,SENSORSPOS,5,24332.1,34023
100,5,15,10,10,2,58354.6,255,25,0.361198,3.29,SENDINTERVAL,5,24331.7,34022.9
10,5,15,10,10,2,58355.1,2685,25,3.35431,3.29,SENDINTERVAL,5,24332.1,34023
10,5,20,10,10,2,66466,3580,30,3.36277,3.29,SENSORSPOS,2,32443,34023
10,5,10,10,10,2,50244.2,1790,20,3.35197,3.29,SENSORSPOS,10,16221.3,34022.9
70,5,15,10,10,2,58354.6,375,25,0.530476,3.29,SENDINTERVAL,5,24331.7,34022.9
100,5,10,10,10,2,50244,170,20,0.35825,3.29,SENDINTERVAL,5,16221.1,34022.9
10,5,20,10,10,2,66466,3580,30,3.36149,3.29,SENSORSPOS,6,32443,34023
80,5,20,10,10,2,66465.3,440,30,0.470471,3.29,SENDINTERVAL,5,32442.4,34022.9
10,5,5,10,10,2,42133.5,895,15,3.34757,3.29,SENSORSPOS,7,8110.6,34022.9
10,5,10,10,10,2,50244.2,1790,20,3.35204,3.29,SENSORSPOS,8,16221.3,34022.9
10,5,10,10,10,2,50244.2,1790,20,3.35214,3.29,SENSORSPOS,3,16221.3,34022.9
10,5,10,10,10,2,50244.2,1790,20,3.35204,3.29,SENSORSPOS,1,16221.3,34022.9
80,5,5,10,10,2,42133.5,110,15,0.458482,3.29,SENDINTERVAL,5,8110.55,34022.9
10,5,15,10,10,2,58355.1,2685,25,3.35482,3.29,SENSORSPOS,10,24332.1,34023
30,5,10,10,10,2,50244,590,20,1.14582,3.29,SENDINTERVAL,5,16221.1,34022.9
10,5,5,10,10,2,42133.5,895,15,3.34757,3.29,SENDINTERVAL,5,8110.6,34022.9
10,5,5,10,10,2,42133.5,895,15,3.34757,3.29,SENSORSPOS,9,8110.6,34022.9
70,5,5,10,10,2,42133.5,125,15,0.525334,3.29,SENDINTERVAL,5,8110.55,34022.9
10,5,15,10,10,2,58355.1,2685,25,3.35414,3.29,SENSORSPOS,4,24332.1,34023
10,5,15,10,10,2,58355.1,2685,25,3.35479,3.29,SENSORSPOS,8,24332.1,34023
10,5,10,10,10,2,50244.2,1790,20,3.35267,3.29,SENSORSPOS,4,16221.3,34022.9
10,5,1,10,10,2,35645,179,11,3.34319,3.29,NBSENSORS,5,1622.11,34022.9
80,5,15,10,10,2,58354.6,330,25,0.46359,3.29,SENDINTERVAL,5,24331.7,34022.9
10,5,4,10,10,2,40511.4,716,14,3.34588,3.29,NBSENSORS,5,6488.44,34022.9
10,5,5,10,10,2,42133.5,895,15,3.34757,3.29,SENSORSPOS,1,8110.6,34022.9
20,5,15,10,10,2,58354.7,1335,25,1.7017,3.29,SENDINTERVAL,5,24331.8,34022.9
60,5,15,10,10,2,58354.6,435,25,0.585288,3.29,SENDINTERVAL,5,24331.7,34022.9
40,5,5,10,10,2,42133.5,220,15,0.861025,3.29,SENDINTERVAL,5,8110.55,34022.9
10,5,8,10,10,2,46999.9,1432,18,3.36006,3.29,NBSENSORS,5,12977,34022.9
10,5,15,10,10,2,58355.1,2685,25,3.35439,3.29,SENSORSPOS,7,24332.1,34023
40,5,10,10,10,2,50244,440,20,0.8645,3.29,SENDINTERVAL,5,16221.1,34022.9
70,5,10,10,10,2,50244,250,20,0.529365,3.29,SENDINTERVAL,5,16221.1,34022.9
100,5,5,10,10,2,42133.5,85,15,0.356905,3.29,SENDINTERVAL,5,8110.55,34022.9
50,5,5,10,10,2,42133.5,175,15,0.701508,3.29,SENDINTERVAL,5,8110.55,34022.9
60,5,10,10,10,2,50244,290,20,0.585039,3.29,SENDINTERVAL,5,16221.1,34022.9
10,5,5,10,10,2,42133.5,895,15,3.34757,3.29,SENSORSPOS,6,8110.6,34022.9
70,5,20,10,10,2,66465.3,500,30,0.538128,3.29,SENDINTERVAL,5,32442.4,34022.9
10,5,15,10,10,2,58355.1,2685,25,3.35424,3.29,SENSORSPOS,1,24332.1,34023
10,5,5,10,10,2,42133.5,895,15,3.34757,3.29,SENSORSPOS,3,8110.6,34022.9
10,5,10,10,10,2,50244.2,1790,20,3.35204,3.29,NBSENSORS,5,16221.3,34022.9
10,5,15,10,10,2,58355.1,2685,25,3.35431,3.29,SENSORSPOS,3,24332.1,34023
10,5,10,10,10,2,50244.2,1790,20,3.35208,3.29,SENSORSPOS,7,16221.3,34022.9
10,5,20,10,10,2,66466,3580,30,3.36334,3.29,SENSORSPOS,5,32443,34023
10,5,5,10,10,2,42133.5,895,15,3.34757,3.29,SENSORSPOS,4,8110.6,34022.9
30,5,5,10,10,2,42133.5,295,15,1.14056,3.29,SENDINTERVAL,5,8110.55,34022.9
10,5,20,10,10,2,66466,3580,30,3.36334,3.29,SENDINTERVAL,5,32443,34023
10,5,5,10,10,2,42133.5,895,15,3.34757,3.29,NBSENSORS,5,8110.6,34022.9
90,5,5,10,10,2,42133.5,95,15,0.399939,3.29,SENDINTERVAL,5,8110.55,34022.9
10,5,20,10,10,2,66466,3580,30,3.36258,3.29,SENSORSPOS,1,32443,34023
10,5,20,10,10,2,66466,3580,30,3.3623,3.29,SENSORSPOS,10,32443,34023
50,5,20,10,10,2,66465.3,700,30,0.714712,3.29,SENDINTERVAL,5,32442.4,34022.9
30,5,20,10,10,2,66465.3,1180,30,1.15317,3.29,SENDINTERVAL,5,32442.4,34022.9
10,5,5,10,10,2,42133.5,895,15,3.34757,3.29,SENSORSPOS,8,8110.6,34022.9
10,5,7,10,10,2,45377.8,1253,17,3.34712,3.29,NBSENSORS,5,11354.8,34022.9
10,5,20,10,10,2,66466,3580,30,3.36257,3.29,SENSORSPOS,8,32443,34023
10,5,6,10,10,2,43755.7,1074,16,3.34474,3.29,NBSENSORS,5,9732.72,34022.9
10,5,15,10,10,2,58355.1,2685,25,3.35444,3.29,SENSORSPOS,6,24332.1,34023
100,5,20,10,10,2,66465.1,340,30,0.366182,3.29,SENDINTERVAL,5,32442.2,34022.9
10,5,5,10,10,2,42133.5,895,15,3.34757,3.29,SENSORSPOS,10,8110.6,34022.9
10,5,10,10,10,2,50244.2,1790,20,3.35204,3.29,SENDINTERVAL,5,16221.3,34022.9
10,5,15,10,10,2,58355.1,2685,25,3.35431,3.29,SENSORSPOS,9,24332.1,34023
40,5,15,10,10,2,58354.7,660,25,0.867591,3.29,SENDINTERVAL,5,24331.8,34022.9
90,5,10,10,10,2,50244,190,20,0.401651,3.29,SENDINTERVAL,5,16221.1,34022.9
20,5,10,10,10,2,50244.1,890,20,1.70086,3.29,SENDINTERVAL,5,16221.2,34022.9
10,5,10,10,10,2,50244.2,1790,20,3.35204,3.29,SENSORSPOS,9,16221.3,34022.9
30,5,15,10,10,2,58354.7,885,25,1.14605,3.29,SENDINTERVAL,5,24331.8,34022.9
50,5,15,10,10,2,58354.7,525,25,0.707443,3.29,SENDINTERVAL,5,24331.8,34022.9
10,5,5,10,10,2,42133.5,895,15,3.34757,3.29,SENSORSPOS,2,8110.6,34022.9
10,5,20,10,10,2,66466,3580,30,3.3632,3.29,SENSORSPOS,4,32443,34023
90,5,15,10,10,2,58354.6,285,25,0.402918,3.29,SENDINTERVAL,5,24331.7,34022.9
10,5,10,10,10,2,50244.2,1790,20,3.35244,3.29,SENSORSPOS,6,16221.3,34022.9
20,5,20,10,10,2,66465.6,1780,30,1.70899,3.29,SENDINTERVAL,5,32442.6,34023
80,5,10,10,10,2,50244,220,20,0.461559,3.29,SENDINTERVAL,5,16221.1,34022.9
10,5,15,10,10,2,58355.1,2685,25,3.35449,3.29,SENSORSPOS,2,24332.1,34023
10,5,20,10,10,2,66466,3580,30,3.36186,3.29,SENSORSPOS,7,32443,34023
60,5,5,10,10,2,42133.5,145,15,0.582833,3.29,SENDINTERVAL,5,8110.55,34022.9
90,5,20,10,10,2,66465.1,380,30,0.408763,3.29,SENDINTERVAL,5,32442.2,34022.9
10,5,20,10,10,2,66466,3580,30,3.36311,3.29,SENSORSPOS,9,32443,34023
10,5,5,10,10,2,42133.5,895,15,3.34757,3.29,SENSORSPOS,5,8110.6,34022.9
20,5,5,10,10,2,42133.5,445,15,1.6963,3.29,SENDINTERVAL,5,8110.55,34022.9
40,5,20,10,10,2,66465.3,880,30,0.872766,3.29,SENDINTERVAL,5,32442.4,34022.9
10,5,20,10,10,2,66466,3580,30,3.36267,3.29,SENSORSPOS,3,32443,34023
10,5,3,10,10,2,38889.2,537,13,3.35175,3.29,NBSENSORS,5,4866.33,34022.9
50,5,10,10,10,2,50244,350,20,0.706067,3.29,SENDINTERVAL,5,16221.1,34022.9
10,5,9,10,10,2,48622.1,1611,19,3.35182,3.29,NBSENSORS,5,14599.2,34022.9
10,5,10,10,10,2,50244.2,1790,20,3.35204,3.29,SENSORSPOS,5,16221.3,34022.9
10,5,2,10,10,2,37267.1,358,12,3.34176,3.29,NBSENSORS,5,3244.22,34022.9
10,5,10,10,10,2,50244.2,1790,20,3.35251,3.29,SENSORSPOS,2,16221.3,34022.9
1,192,15,10,10000,11,58361.4,26985,25,178.32,3.29,SENSORSPOS,10,24337.5,34023.9
70,192,9,10,10000,11,48621.9,225,19,2.54726,3.29,SENDINTERVAL,5,14599,34022.9
40,192,11,10,10000,11,51866.1,484,21,4.41612,3.29,SENDINTERVAL,5,17843.2,34022.9
40,192,15,10,10000,11,58354.7,660,25,4.42019,3.29,SENDINTERVAL,5,24331.8,34022.9
60,192,9,10,10000,11,48621.9,261,19,2.926,3.29,SENDINTERVAL,5,14599,34022.9
20,192,7,10,10000,11,45377.8,623,17,8.88267,3.29,SENDINTERVAL,5,11354.8,34022.9
60,192,5,10,10000,11,42133.5,145,15,2.92529,3.29,SENDINTERVAL,5,8110.55,34022.9
90,192,13,10,10000,11,55110.4,247,23,1.93879,3.29,SENDINTERVAL,5,21087.4,34022.9
1,192,11,10,10000,11,51870.1,19789,21,178.315,3.29,SENSORSPOS,8,17846.4,34023.7
70,192,5,10,10000,11,42133.5,125,15,2.54461,3.29,SENDINTERVAL,5,8110.55,34022.9
50,192,9,10,10000,11,48621.9,315,19,3.53335,3.29,SENDINTERVAL,5,14599,34022.9
1,192,11,10,10000,11,51870.1,19789,21,178.314,3.29,SENSORSPOS,2,17846.4,34023.7
20,192,5,10,10000,11,42133.5,445,15,8.8852,3.29,SENDINTERVAL,5,8110.55,34022.9
1,192,11,10,10000,11,51870.1,19789,21,178.315,3.29,SENSORSPOS,5,17846.4,34023.7
1,192,11,10,10000,11,51870.1,19789,21,178.314,3.29,SENSORSPOS,3,17846.4,34023.7
90,192,15,10,10000,11,58354.6,285,25,1.93848,3.29,SENDINTERVAL,5,24331.7,34022.9
1,192,4,10,10000,11,40512.2,7196,14,178.311,3.29,NBSENSORS,5,6488.92,34023.2
1,192,5,10,10000,11,42134.5,8995,15,178.312,3.29,SENSORSPOS,8,8111.25,34023.3
1,192,14,10,10000,11,56738.4,25186,24,178.322,3.29,NBSENSORS,5,22714.6,34023.8
1,192,5,10,10000,11,42134.5,8995,15,178.312,3.29,SENSORSPOS,9,8111.25,34023.3
30,192,7,10,10000,11,45377.7,413,17,5.90362,3.29,SENDINTERVAL,5,11354.8,34022.9
1,192,11,10,10000,11,51870.1,19789,21,178.315,3.29,NBSENSORS,5,17846.4,34023.7
1,192,15,10,10000,11,58361.4,26985,25,178.319,3.29,SENSORSPOS,9,24337.5,34023.9
20,192,13,10,10000,11,55110.6,1157,23,8.88931,3.29,SENDINTERVAL,5,21087.7,34022.9
1,192,11,10,10000,11,51870.1,19789,21,178.315,3.29,SENSORSPOS,6,17846.4,34023.7
10,192,11,10,10000,11,51866.5,1969,21,17.8076,3.29,SENDINTERVAL,5,17843.5,34023
60,192,13,10,10000,11,55110.4,377,23,2.92925,3.29,SENDINTERVAL,5,21087.4,34022.9
1,192,9,10,10000,11,48624.7,16191,19,178.316,3.29,NBSENSORS,5,14601.2,34023.5
60,192,7,10,10000,11,45377.7,203,17,2.9205,3.29,SENDINTERVAL,5,11354.8,34022.9
60,192,15,10,10000,11,58354.7,435,25,2.92858,3.29,SENDINTERVAL,5,24331.7,34022.9
80,192,7,10,10000,11,45377.7,154,17,2.23268,3.29,SENDINTERVAL,5,11354.8,34022.9
10,192,9,10,10000,11,48622.1,1611,19,17.8109,3.29,SENDINTERVAL,5,14599.2,34022.9
1,192,13,10,10000,11,55115.6,23387,23,178.317,3.29,SENSORSPOS,5,21091.9,34023.7
100,192,11,10,10000,11,51866.1,187,21,1.72967,3.29,SENDINTERVAL,5,17843.2,34022.9
1,192,9,10,10000,11,48624.7,16191,19,178.316,3.29,SENSORSPOS,5,14601.2,34023.5
1,192,7,10,10000,11,45379.5,12593,17,178.309,3.29,SENSORSPOS,1,11356.1,34023.4
1,192,5,10,10000,11,42134.5,8995,15,178.312,3.29,SENSORSPOS,3,8111.25,34023.3
1,192,5,10,10000,11,42134.5,8995,15,178.312,3.29,SENSORSPOS,7,8111.25,34023.3
1,192,11,10,10000,11,51870.1,19789,21,178.316,3.29,SENSORSPOS,9,17846.4,34023.7
1,192,9,10,10000,11,48624.7,16191,19,178.316,3.29,SENSORSPOS,7,14601.2,34023.5
1,192,9,10,10000,11,48624.7,16191,19,178.315,3.29,SENSORSPOS,3,14601.2,34023.5
50,192,15,10,10000,11,58354.7,525,25,3.53509,3.29,SENDINTERVAL,5,24331.8,34022.9
1,192,13,10,10000,11,55115.6,23387,23,178.318,3.29,SENSORSPOS,3,21091.9,34023.7
1,192,15,10,10000,11,58361.4,26985,25,178.319,3.29,SENSORSPOS,8,24337.5,34023.9
1,192,13,10,10000,11,55115.6,23387,23,178.317,3.29,SENSORSPOS,1,21091.9,34023.7
1,192,5,10,10000,11,42134.5,8995,15,178.312,3.29,SENSORSPOS,5,8111.25,34023.3
80,192,13,10,10000,11,55110.4,286,23,2.24123,3.29,SENDINTERVAL,5,21087.4,34022.9
1,192,5,10,10000,11,42134.5,8995,15,178.312,3.29,SENSORSPOS,10,8111.25,34023.3
100,192,15,10,10000,11,58354.6,255,25,1.73512,3.29,SENDINTERVAL,5,24331.7,34022.9
1,192,15,10,10000,11,58361.4,26985,25,178.32,3.29,NBSENSORS,5,24337.5,34023.9
1,192,11,10,10000,11,51870.1,19789,21,178.314,3.29,SENSORSPOS,4,17846.4,34023.7
30,192,13,10,10000,11,55110.5,767,23,5.91148,3.29,SENDINTERVAL,5,21087.6,34022.9
30,192,11,10,10000,11,51866.2,649,21,5.90819,3.29,SENDINTERVAL,5,17843.3,34022.9
20,192,11,10,10000,11,51866.3,979,21,8.88459,3.29,SENDINTERVAL,5,17843.3,34022.9
1,192,9,10,10000,11,48624.7,16191,19,178.315,3.29,SENSORSPOS,9,14601.2,34023.5
1,192,7,10,10000,11,45379.5,12593,17,178.309,3.29,SENSORSPOS,5,11356.1,34023.4
80,192,9,10,10000,11,48621.9,198,19,2.23715,3.29,SENDINTERVAL,5,14599,34022.9
1,192,15,10,10000,11,58361.4,26985,25,178.319,3.29,SENSORSPOS,3,24337.5,34023.9
70,192,7,10,10000,11,45377.7,175,17,2.54203,3.29,SENDINTERVAL,5,11354.8,34022.9
1,192,3,10,10000,11,38889.7,5397,13,178.316,3.29,NBSENSORS,5,4866.6,34023.1
1,192,2,10,10000,11,37267.4,3598,12,178.306,3.29,NBSENSORS,5,3244.36,34023.1
40,192,5,10,10000,11,42133.5,220,15,4.41517,3.29,SENDINTERVAL,5,8110.55,34022.9
1,192,6,10,10000,11,43757,10794,16,178.31,3.29,NBSENSORS,5,9733.68,34023.3
1,192,13,10,10000,11,55115.6,23387,23,178.317,3.29,SENSORSPOS,2,21091.9,34023.7
100,192,9,10,10000,11,48621.9,153,19,1.73113,3.29,SENDINTERVAL,5,14599,34022.9
1,192,11,10,10000,11,51870.1,19789,21,178.314,3.29,SENSORSPOS,10,17846.4,34023.7
1,192,8,10,10000,11,47002.1,14392,18,178.324,3.29,NBSENSORS,5,12978.6,34023.5
1,192,5,10,10000,11,42134.5,8995,15,178.312,3.29,SENSORSPOS,4,8111.25,34023.3
1,192,7,10,10000,11,45379.5,12593,17,178.309,3.29,SENSORSPOS,7,11356.1,34023.4
100,192,5,10,10000,11,42133.5,85,15,1.72994,3.29,SENDINTERVAL,5,8110.55,34022.9
1,192,5,10,10000,11,42134.5,8995,15,178.312,3.29,SENSORSPOS,6,8111.25,34023.3
80,192,11,10,10000,11,51866.1,242,21,2.23691,3.29,SENDINTERVAL,5,17843.2,34022.9
1,192,7,10,10000,11,45379.5,12593,17,178.309,3.29,SENSORSPOS,4,11356.1,34023.4
1,192,11,10,10000,11,51870.1,19789,21,178.315,3.29,SENSORSPOS,7,17846.4,34023.7
30,192,9,10,10000,11,48622,531,19,5.91042,3.29,SENDINTERVAL,5,14599.1,34022.9
50,192,13,10,10000,11,55110.5,455,23,3.53395,3.29,SENDINTERVAL,5,21087.6,34022.9
30,192,5,10,10000,11,42133.5,295,15,5.90658,3.29,SENDINTERVAL,5,8110.55,34022.9
50,192,5,10,10000,11,42133.5,175,15,3.52862,3.29,SENDINTERVAL,5,8110.55,34022.9
1,192,9,10,10000,11,48624.7,16191,19,178.315,3.29,SENSORSPOS,2,14601.2,34023.5
1,192,13,10,10000,11,55115.6,23387,23,178.318,3.29,SENSORSPOS,4,21091.9,34023.7
1,192,13,10,10000,11,55115.6,23387,23,178.318,3.29,SENSORSPOS,6,21091.9,34023.7
20,192,15,10,10000,11,58354.9,1335,25,8.89027,3.29,SENDINTERVAL,5,24332,34022.9
70,192,11,10,10000,11,51866.1,275,21,2.54459,3.29,SENDINTERVAL,5,17843.2,34022.9
80,192,5,10,10000,11,42133.5,110,15,2.2354,3.29,SENDINTERVAL,5,8110.55,34022.9
1,192,15,10,10000,11,58361.4,26985,25,178.319,3.29,SENSORSPOS,4,24337.5,34023.9
1,192,7,10,10000,11,45379.5,12593,17,178.309,3.29,SENSORSPOS,9,11356.1,34023.4
100,192,7,10,10000,11,45377.7,119,17,1.72775,3.29,SENDINTERVAL,5,11354.8,34022.9
40,192,9,10,10000,11,48621.9,396,19,4.41683,3.29,SENDINTERVAL,5,14599,34022.9
80,192,15,10,10000,11,58354.6,330,25,2.24177,3.29,SENDINTERVAL,5,24331.7,34022.9
1,192,5,10,10000,11,42134.5,8995,15,178.312,3.29,SENSORSPOS,1,8111.25,34023.3
10,192,13,10,10000,11,55110.8,2327,23,17.8115,3.29,SENDINTERVAL,5,21087.8,34023
50,192,11,10,10000,11,51866.1,385,21,3.53003,3.29,SENDINTERVAL,5,17843.2,34022.9
1,192,7,10,10000,11,45379.5,12593,17,178.309,3.29,SENSORSPOS,8,11356.1,34023.4
1,192,15,10,10000,11,58361.4,26985,25,178.32,3.29,SENSORSPOS,5,24337.5,34023.9
1,192,9,10,10000,11,48624.7,16191,19,178.315,3.29,SENSORSPOS,4,14601.2,34023.5
1,192,9,10,10000,11,48624.7,16191,19,178.315,3.29,SENSORSPOS,10,14601.2,34023.5
1,192,1,10,10000,11,35645.1,1799,11,178.302,3.29,NBSENSORS,5,1622.16,34022.9
1,192,7,10,10000,11,45379.5,12593,17,178.309,3.29,NBSENSORS,5,11356.1,34023.4
1,192,13,10,10000,11,55115.6,23387,23,178.318,3.29,SENSORSPOS,8,21091.9,34023.7
90,192,11,10,10000,11,51866.1,209,21,1.93316,3.29,SENDINTERVAL,5,17843.2,34022.9
1,192,15,10,10000,11,58361.4,26985,25,178.319,3.29,SENSORSPOS,2,24337.5,34023.9
1,192,12,10,10000,11,53492.7,21588,22,178.323,3.29,NBSENSORS,5,19469,34023.7
100,192,13,10,10000,11,55110.4,221,23,1.73604,3.29,SENDINTERVAL,5,21087.4,34022.9
1,192,15,10,10000,11,58361.4,26985,25,178.319,3.29,SENSORSPOS,6,24337.5,34023.9
70,192,13,10,10000,11,55110.4,325,23,2.54803,3.29,SENDINTERVAL,5,21087.4,34022.9
90,192,7,10,10000,11,45377.7,133,17,1.92972,3.29,SENDINTERVAL,5,11354.8,34022.9
1,192,13,10,10000,11,55115.6,23387,23,178.317,3.29,SENSORSPOS,9,21091.9,34023.7
10,192,15,10,10000,11,58355.3,2685,25,17.8136,3.29,SENDINTERVAL,5,24332.3,34023.1
1,192,13,10,10000,11,55115.6,23387,23,178.317,3.29,NBSENSORS,5,21091.9,34023.7
90,192,9,10,10000,11,48621.9,171,19,1.9345,3.29,SENDINTERVAL,5,14599,34022.9
1,192,5,10,10000,11,42134.5,8995,15,178.312,3.29,NBSENSORS,5,8111.25,34023.3
1,192,7,10,10000,11,45379.5,12593,17,178.309,3.29,SENSORSPOS,6,11356.1,34023.4
70,192,15,10,10000,11,58354.7,375,25,2.55086,3.29,SENDINTERVAL,5,24331.8,34022.9
40,192,7,10,10000,11,45377.7,308,17,4.41222,3.29,SENDINTERVAL,5,11354.8,34022.9
50,192,7,10,10000,11,45377.7,245,17,3.52585,3.29,SENDINTERVAL,5,11354.8,34022.9
1,192,7,10,10000,11,45379.5,12593,17,178.309,3.29,SENSORSPOS,3,11356.1,34023.4
1,192,13,10,10000,11,55115.6,23387,23,178.318,3.29,SENSORSPOS,10,21091.9,34023.7
1,192,11,10,10000,11,51870.1,19789,21,178.315,3.29,SENSORSPOS,1,17846.4,34023.7
1,192,9,10,10000,11,48624.7,16191,19,178.316,3.29,SENSORSPOS,6,14601.2,34023.5
1,192,15,10,10000,11,58361.4,26985,25,178.319,3.29,SENSORSPOS,1,24337.5,34023.9
20,192,9,10,10000,11,48622,801,19,8.88829,3.29,SENDINTERVAL,5,14599.1,34022.9
10,192,5,10,10000,11,42133.5,895,15,17.8062,3.29,SENDINTERVAL,5,8110.6,34022.9
1,192,9,10,10000,11,48624.7,16191,19,178.315,3.29,SENSORSPOS,1,14601.2,34023.5
40,192,13,10,10000,11,55110.5,572,23,4.42054,3.29,SENDINTERVAL,5,21087.6,34022.9
1,192,7,10,10000,11,45379.5,12593,17,178.309,3.29,SENSORSPOS,10,11356.1,34023.4
1,192,7,10,10000,11,45379.5,12593,17,178.309,3.29,SENSORSPOS,2,11356.1,34023.4
1,192,5,10,10000,11,42134.5,8995,15,178.312,3.29,SENSORSPOS,2,8111.25,34023.3
10,192,7,10,10000,11,45377.8,1253,17,17.8058,3.29,SENDINTERVAL,5,11354.9,34022.9
90,192,5,10,10000,11,42133.5,95,15,1.93453,3.29,SENDINTERVAL,5,8110.55,34022.9
1,192,13,10,10000,11,55115.6,23387,23,178.318,3.29,SENSORSPOS,7,21091.9,34023.7
1,192,15,10,10000,11,58361.4,26985,25,178.319,3.29,SENSORSPOS,7,24337.5,34023.9
30,192,15,10,10000,11,58354.7,885,25,5.91265,3.29,SENDINTERVAL,5,24331.8,34022.9
1,192,9,10,10000,11,48624.7,16191,19,178.315,3.29,SENSORSPOS,8,14601.2,34023.5
1,192,10,10,10000,11,50247.3,17990,20,178.319,3.29,NBSENSORS,5,16223.7,34023.6
60,192,11,10,10000,11,51866.1,319,21,2.92373,3.29,SENDINTERVAL,5,17843.2,34022.9
10,5,5,4,10,2,684.039,30,9,0.0441026,3.29,NBHOP
10,5,1,10,10,4,1188.08,6,11,0.218504,3.29,LATENCY
10,5,12,8,10,2,1541.81,72,20,0.0990603,3.29,NBHOP
10,5,10,5,10,2,1074.44,60,15,0.0610499,3.29,NBHOP
10,5,3,10,10,1,1296.13,18,13,0.0643722,3.29,LATENCY
10,5,10,10,50,2,1674.32,60,20,0.121688,3.29,BW
10,5,10,10,10,8,1674.32,60,20,0.446898,3.29,LATENCY
10,5,15,10,10,2,1944.47,90,25,0.126884,3.29,NBHOP
10,5,4,2,10,2,390.03,24,6,0.0210262,3.29,NBHOP
10,5,6,10,10,5,1458.21,36,16,0.281644,3.29,LATENCY
10,5,14,4,10,2,1170.08,84,18,0.0516451,3.29,NBHOP
10,5,4,10,10,5,1350.16,24,14,0.280468,3.29,LATENCY
10,5,8,10,10,7,1566.27,48,18,0.389686,3.29,LATENCY
10,5,12,6,10,2,1301.92,72,18,0.0753212,3.29,NBHOP
10,5,12,3,10,2,942.445,72,15,0.0369372,3.29,NBHOP
10,5,14,6,10,2,1409.91,84,20,0.0770229,3.29,NBHOP
10,5,3,8,10,2,1055.95,18,11,0.0919907,3.29,NBHOP
10,5,14,10,10,1,1890.44,84,24,0.0720317,3.29,LATENCY
10,5,11,10,10,1,1728.35,66,21,0.0686554,3.29,LATENCY
10,5,11,10,10,9,1728.35,66,21,0.500655,3.29,LATENCY
10,5,1,10,10,1,1188.08,6,11,0.0565039,3.29,LATENCY
10,5,13,10,10,5,1836.41,78,23,0.285283,3.29,LATENCY
10,5,3,1,10,2,215.981,0,4,0,3.29,NBHOP
10,5,4,9,10,2,1230.05,24,13,0.105932,3.29,NBHOP
10,5,6,10,10,7,1458.21,36,16,0.389644,3.29,LATENCY
10,5,6,10,30,2,1458.21,36,16,0.118636,3.29,BW
10,5,11,10,10,5,1728.35,66,21,0.284655,3.29,LATENCY
10,5,8,1,10,2,485.927,0,9,0,3.29,NBHOP
10,5,8,10,10,2,1566.27,48,18,0.119686,3.29,LATENCY
10,5,2,10,10,10,1242.1,12,12,0.549517,3.29,LATENCY
10,5,10,10,30,2,1674.32,60,20,0.12189,3.29,BW
10,5,9,10,50,2,1620.29,54,19,0.119964,3.29,BW
10,5,9,5,10,2,1020.4,54,14,0.0605286,3.29,NBHOP
10,5,3,6,10,2,815.987,18,9,0.0695587,3.29,NBHOP
10,5,6,10,50,2,1458.21,36,16,0.118434,3.29,BW
10,5,10,10,10,7,1674.32,60,20,0.392898,3.29,LATENCY
10,5,4,10,10,2,1350.16,24,14,0.118468,3.29,BW
10,5,1,10,10,2,1188.08,6,11,0.110504,3.29,NBSENSORS
10,5,14,3,10,2,1050.52,84,17,0.0408313,3.29,NBHOP
10,5,5,10,10,2,1404.18,30,15,0.120484,3.29,NBHOP
10,5,8,10,50,2,1566.27,48,18,0.118476,3.29,BW
10,5,4,10,10,3,1350.16,24,14,0.172468,3.29,LATENCY
10,5,10,1,10,2,593.906,0,11,0,3.29,NBHOP
10,5,15,2,10,2,984.068,90,17,0.030147,3.29,NBHOP
10,5,4,10,10,2,1350.16,24,14,0.118468,3.29,LATENCY
10,5,6,10,10,4,1458.21,36,16,0.227644,3.29,LATENCY
10,5,8,10,10,8,1566.27,48,18,0.443686,3.29,LATENCY
10,5,13,10,10,9,1836.41,78,23,0.501283,3.29,LATENCY
10,5,15,6,10,2,1463.9,90,21,0.0789799,3.29,NBHOP
10,5,1,10,10,8,1188.08,6,11,0.434504,3.29,LATENCY
10,5,4,5,10,2,750.211,24,9,0.0577648,3.29,NBHOP
10,5,2,10,10,5,1242.1,12,12,0.279517,3.29,LATENCY
10,5,15,10,10,8,1944.47,90,25,0.450884,3.29,LATENCY
10,5,3,10,50,2,1296.13,18,13,0.117162,3.29,BW
10,5,12,10,10,5,1782.38,72,22,0.284763,3.29,LATENCY
10,5,12,9,10,2,1662.12,72,21,0.111567,3.29,NBHOP
10,5,11,1,10,2,647.896,0,12,0,3.29,NBHOP
10,5,3,3,10,2,456.149,18,6,0.0317123,3.29,NBHOP
10,5,2,8,10,2,1001.97,12,10,0.0915105,3.29,NBHOP
10,5,9,10,10,5,1620.29,54,19,0.283174,3.29,LATENCY
10,5,5,10,10,7,1404.18,30,15,0.390484,3.29,LATENCY
10,5,5,10,10,3,1404.18,30,15,0.174484,3.29,LATENCY
10,5,3,10,10,10,1296.13,18,13,0.550372,3.29,LATENCY
10,5,2,10,10,2,1242.1,12,12,0.117517,3.29,LATENCY
10,5,1,1,10,2,108.004,0,2,0,3.29,NBHOP
10,5,8,10,10,6,1566.27,48,18,0.335686,3.29,LATENCY
10,5,6,10,10,9,1458.21,36,16,0.497644,3.29,LATENCY
10,5,8,4,10,2,846.051,48,12,0.0468565,3.29,NBHOP
10,5,6,6,10,2,977.962,36,12,0.0692437,3.29,NBHOP
10,5,1,3,10,2,348.087,6,4,0.026229,3.29,NBHOP
10,5,6,10,70,2,1458.21,36,16,0.118348,3.29,BW
10,5,3,10,10,8,1296.13,18,13,0.442372,3.29,LATENCY
10,5,9,10,10,7,1620.29,54,19,0.391174,3.29,LATENCY
10,5,3,10,10,6,1296.13,18,13,0.334372,3.29,LATENCY
10,5,6,10,10,3,1458.21,36,16,0.173644,3.29,LATENCY
10,5,5,1,10,2,323.959,0,6,0,3.29,NBHOP
10,5,6,8,10,2,1217.9,36,14,0.093869,3.29,NBHOP
10,5,4,10,10,8,1350.16,24,14,0.442468,3.29,LATENCY
10,5,10,10,10,2,1674.32,60,20,0.122898,3.29,NBHOP
10,5,2,10,10,9,1242.1,12,12,0.495517,3.29,LATENCY
10,5,14,10,10,5,1890.44,84,24,0.288032,3.29,LATENCY
10,5,4,7,10,2,990.372,24,11,0.0806572,3.29,NBHOP
10,5,14,5,10,2,1290.6,84,19,0.0646285,3.29,NBHOP
10,5,13,10,70,2,1836.41,78,23,0.121987,3.29,BW
10,5,14,10,10,9,1890.44,84,24,0.504032,3.29,LATENCY
10,5,10,10,10,4,1674.32,60,20,0.230898,3.29,LATENCY
10,5,14,10,10,10,1890.44,84,24,0.558032,3.29,LATENCY
10,5,13,10,10,10,1836.41,78,23,0.555283,3.29,LATENCY
10,5,2,10,10,7,1242.1,12,12,0.387517,3.29,LATENCY
10,5,11,10,10,2,1728.35,66,21,0.122655,3.29,NBHOP
10,5,2,10,30,2,1242.1,12,12,0.11651,3.29,BW
10,5,1,10,10,2,1188.08,6,11,0.110504,3.29,LATENCY
10,5,13,3,10,2,996.481,78,16,0.0386852,3.29,NBHOP
10,5,10,4,10,2,954.061,60,14,0.0477382,3.29,NBHOP
10,5,7,10,70,2,1512.24,42,17,0.118248,3.29,BW
10,5,5,3,10,2,564.212,30,8,0.0334324,3.29,NBHOP
10,5,3,7,10,2,936.302,18,10,0.0814983,3.29,NBHOP
10,5,1,10,10,5,1188.08,6,11,0.272504,3.29,LATENCY
10,5,10,10,10,1,1674.32,60,20,0.0688975,3.29,LATENCY
10,5,13,10,50,2,1836.41,78,23,0.122073,3.29,BW
10,5,11,10,10,10,1728.35,66,21,0.554655,3.29,LATENCY
10,5,8,10,10,9,1566.27,48,18,0.497686,3.29,LATENCY
10,5,15,10,10,3,1944.47,90,25,0.180884,3.29,LATENCY
10,5,2,3,10,2,402.118,12,5,0.0315625,3.29,NBHOP
10,5,4,1,10,2,269.97,0,5,0,3.29,NBHOP
10,5,7,10,10,8,1512.24,42,17,0.443544,3.29,LATENCY
10,5,7,10,10,2,1512.24,42,17,0.119544,3.29,NBHOP
10,5,15,10,10,1,1944.47,90,25,0.0728842,3.29,LATENCY
10,5,10,9,10,2,1554.1,60,19,0.111113,3.29,NBHOP
10,5,1,10,70,2,1188.08,6,11,0.109208,3.29,BW
10,5,1,10,10,10,1188.08,6,11,0.542504,3.29,LATENCY
10,5,11,10,10,2,1728.35,66,21,0.122655,3.29,LATENCY
10,5,2,10,10,4,1242.1,12,12,0.225517,3.29,LATENCY
10,5,15,9,10,2,1824.14,90,24,0.11431,3.29,NBHOP
10,5,11,4,10,2,1008.07,66,15,0.0502385,3.29,NBHOP
10,5,11,10,10,2,1728.35,66,21,0.122655,3.29,BW
10,5,5,10,10,8,1404.18,30,15,0.444484,3.29,LATENCY
10,5,8,3,10,2,726.31,48,11,0.0361296,3.29,NBHOP
10,5,10,3,10,2,834.377,60,13,0.0359287,3.29,NBHOP
10,5,11,10,10,4,1728.35,66,21,0.230655,3.29,LATENCY
10,5,4,10,10,7,1350.16,24,14,0.388468,3.29,LATENCY
10,5,12,5,10,2,1182.52,72,17,0.0615217,3.29,NBHOP
10,5,9,9,10,2,1500.09,54,18,0.109942,3.29,NBHOP
10,5,1,10,30,2,1188.08,6,11,0.109496,3.29,BW
10,5,7,10,10,1,1512.24,42,17,0.065544,3.29,LATENCY
10,5,11,10,10,6,1728.35,66,21,0.338655,3.29,LATENCY
10,5,2,10,10,2,1242.1,12,12,0.117517,3.29,BW
10,5,11,8,10,2,1487.82,66,19,0.0984001,3.29,NBHOP
10,5,14,10,10,2,1890.44,84,24,0.126032,3.29,BW
10,5,6,10,90,2,1458.21,36,16,0.1183,3.29,BW
10,5,5,10,10,1,1404.18,30,15,0.0664843,3.29,LATENCY
10,5,12,10,10,7,1782.38,72,22,0.392763,3.29,LATENCY
10,5,15,10,50,2,1944.47,90,25,0.125674,3.29,BW
10,5,2,10,90,2,1242.1,12,12,0.116173,3.29,BW
10,5,2,10,10,2,1242.1,12,12,0.117517,3.29,NBSENSORS
10,5,9,6,10,2,1139.94,54,15,0.0732161,3.29,NBHOP
10,5,1,10,50,2,1188.08,6,11,0.109294,3.29,BW
10,5,9,10,70,2,1620.29,54,19,0.119878,3.29,BW
10,5,6,1,10,2,377.948,0,7,0,3.29,NBHOP
10,5,12,10,10,1,1782.38,72,22,0.0687625,3.29,LATENCY
10,5,13,1,10,2,755.876,0,14,0,3.29,NBHOP
10,5,14,10,50,2,1890.44,84,24,0.124822,3.29,BW
10,5,13,10,10,2,1836.41,78,23,0.123283,3.29,NBHOP
10,5,13,10,10,7,1836.41,78,23,0.393283,3.29,LATENCY
10,5,6,10,10,8,1458.21,36,16,0.443644,3.29,LATENCY
10,5,13,10,10,8,1836.41,78,23,0.447283,3.29,LATENCY
10,5,5,6,10,2,923.97,30,11,0.068991,3.29,NBHOP
10,5,4,6,10,2,869.978,24,10,0.0702622,3.29,NBHOP
10,5,11,7,10,2,1368.87,66,18,0.0867735,3.29,NBHOP
10,5,1,10,10,2,1188.08,6,11,0.110504,3.29,BW
10,5,11,10,10,8,1728.35,66,21,0.446655,3.29,LATENCY
10,5,12,10,10,6,1782.38,72,22,0.338763,3.29,LATENCY
10,5,15,10,10,5,1944.47,90,25,0.288884,3.29,LATENCY
10,5,9,4,10,2,900.056,54,13,0.0477678,3.29,NBHOP
10,5,7,1,10,2,431.937,0,8,0,3.29,NBHOP
10,5,6,7,10,2,1098.51,36,13,0.0812177,3.29,NBHOP
10,5,2,10,10,2,1242.1,12,12,0.117517,3.29,NBHOP
10,5,7,4,10,2,792.047,42,11,0.0471126,3.29,NBHOP
10,5,11,3,10,2,888.412,66,14,0.0379922,3.29,NBHOP
10,5,4,10,10,10,1350.16,24,14,0.550468,3.29,LATENCY
10,5,10,10,10,9,1674.32,60,20,0.500898,3.29,LATENCY
10,5,5,7,10,2,1044.44,30,12,0.0806844,3.29,NBHOP
10,5,12,10,30,2,1782.38,72,22,0.121755,3.29,BW
10,5,5,5,10,2,804.249,30,10,0.056026,3.29,NBHOP
10,5,3,10,90,2,1296.13,18,13,0.117028,3.29,BW
10,5,8,10,10,10,1566.27,48,18,0.551686,3.29,LATENCY
10,5,6,10,10,10,1458.21,36,16,0.551644,3.29,LATENCY
10,5,14,8,10,2,1649.78,84,22,0.101877,3.29,NBHOP
10,5,14,10,90,2,1890.44,84,24,0.124688,3.29,BW
10,5,7,10,10,9,1512.24,42,17,0.497544,3.29,LATENCY
10,5,14,10,10,2,1890.44,84,24,0.126032,3.29,NBHOP
10,5,4,10,10,6,1350.16,24,14,0.334468,3.29,LATENCY
10,5,12,10,10,2,1782.38,72,22,0.122763,3.29,LATENCY
10,5,9,10,10,4,1620.29,54,19,0.229174,3.29,LATENCY
10,5,11,9,10,2,1608.11,66,20,0.110984,3.29,NBHOP
10,5,11,10,50,2,1728.35,66,21,0.121445,3.29,BW
10,5,13,10,10,1,1836.41,78,23,0.0692831,3.29,LATENCY
10,5,1,4,10,2,468.029,6,5,0.04246,3.29,NBHOP
10,5,10,10,70,2,1674.32,60,20,0.121602,3.29,BW
10,5,12,10,70,2,1782.38,72,22,0.121467,3.29,BW
10,5,7,10,10,7,1512.24,42,17,0.389544,3.29,LATENCY
10,5,13,10,10,4,1836.41,78,23,0.231283,3.29,LATENCY
10,5,13,10,10,2,1836.41,78,23,0.123283,3.29,BW
10,5,12,10,90,2,1782.38,72,22,0.121419,3.29,BW
10,5,8,10,10,5,1566.27,48,18,0.281686,3.29,LATENCY
10,5,7,10,10,6,1512.24,42,17,0.335544,3.29,LATENCY
10,5,11,6,10,2,1247.93,66,17,0.0749006,3.29,NBHOP
10,5,12,10,50,2,1782.38,72,22,0.121553,3.29,BW
10,5,9,1,10,2,539.916,0,10,0,3.29,NBHOP
10,5,13,10,10,2,1836.41,78,23,0.123283,3.29,LATENCY
10,5,15,7,10,2,1585.16,90,22,0.0899177,3.29,NBHOP
10,5,3,10,10,2,1296.13,18,13,0.118372,3.29,NBSENSORS
10,5,15,10,10,10,1944.47,90,25,0.558884,3.29,LATENCY
10,5,4,3,10,2,510.181,24,7,0.03217,3.29,NBHOP
10,5,13,10,30,2,1836.41,78,23,0.122275,3.29,BW
10,5,6,10,10,6,1458.21,36,16,0.335644,3.29,LATENCY
10,5,7,10,10,4,1512.24,42,17,0.227544,3.29,LATENCY
10,5,15,10,10,6,1944.47,90,25,0.342884,3.29,LATENCY
10,5,13,10,90,2,1836.41,78,23,0.121939,3.29,BW
10,5,12,10,10,2,1782.38,72,22,0.122763,3.29,NBHOP
10,5,7,7,10,2,1152.58,42,14,0.0835217,3.29,NBHOP
10,5,12,10,10,4,1782.38,72,22,0.230763,3.29,LATENCY
10,5,14,7,10,2,1531.09,84,21,0.090289,3.29,NBHOP
10,5,14,10,70,2,1890.44,84,24,0.124736,3.29,BW
10,5,3,10,10,2,1296.13,18,13,0.118372,3.29,BW
10,5,8,10,10,3,1566.27,48,18,0.173686,3.29,LATENCY
10,5,15,10,30,2,1944.47,90,25,0.125876,3.29,BW
10,5,14,2,10,2,930.063,84,16,0.0284299,3.29,NBHOP
10,5,7,10,30,2,1512.24,42,17,0.118536,3.29,BW
10,5,10,10,10,3,1674.32,60,20,0.176898,3.29,LATENCY
10,5,2,2,10,2,282.028,12,4,0.019416,3.29,NBHOP
10,5,3,10,10,9,1296.13,18,13,0.496372,3.29,LATENCY
10,5,8,10,10,1,1566.27,48,18,0.0656858,3.29,LATENCY
10,5,2,9,10,2,1122.04,12,11,0.104295,3.29,NBHOP
10,5,2,4,10,2,522.032,12,6,0.045181,3.29,NBHOP
10,5,4,10,30,2,1350.16,24,14,0.11746,3.29,BW
10,5,4,10,10,2,1350.16,24,14,0.118468,3.29,NBSENSORS
10,5,12,7,10,2,1422.94,72,19,0.0862663,3.29,NBHOP
10,5,2,7,10,2,882.233,12,9,0.0803245,3.29,NBHOP
10,5,14,10,10,6,1890.44,84,24,0.342032,3.29,LATENCY
10,5,14,10,10,3,1890.44,84,24,0.180032,3.29,LATENCY
10,5,6,10,10,1,1458.21,36,16,0.0656441,3.29,LATENCY
10,5,12,4,10,2,1062.07,72,16,0.0491456,3.29,NBHOP
10,5,13,4,10,2,1116.08,78,17,0.0508868,3.29,NBHOP
10,5,9,10,10,10,1620.29,54,19,0.553174,3.29,LATENCY
10,5,15,1,10,2,863.855,0,16,0,3.29,NBHOP
10,5,1,10,10,6,1188.08,6,11,0.326504,3.29,LATENCY
10,5,4,10,70,2,1350.16,24,14,0.117172,3.29,BW
10,5,12,1,10,2,701.886,0,13,0,3.29,NBHOP
10,5,12,10,10,3,1782.38,72,22,0.176763,3.29,LATENCY
10,5,6,3,10,2,618.245,36,9,0.0334377,3.29,NBHOP
10,5,10,10,10,6,1674.32,60,20,0.338898,3.29,LATENCY
10,5,9,10,10,3,1620.29,54,19,0.175174,3.29,LATENCY
10,5,2,5,10,2,642.136,12,7,0.055376,3.29,NBHOP
10,5,10,10,10,2,1674.32,60,20,0.122898,3.29,BW
10,5,4,10,10,1,1350.16,24,14,0.0644679,3.29,LATENCY
10,5,2,10,70,2,1242.1,12,12,0.116222,3.29,BW
10,5,8,5,10,2,966.364,48,13,0.0590559,3.29,NBHOP
10,5,12,10,10,8,1782.38,72,22,0.446763,3.29,LATENCY
10,5,1,10,10,3,1188.08,6,11,0.164504,3.29,LATENCY
10,5,4,8,10,2,1109.94,24,12,0.094549,3.29,NBHOP
10,5,15,8,10,2,1703.76,90,23,0.100124,3.29,NBHOP
10,5,11,10,30,2,1728.35,66,21,0.121647,3.29,BW
10,5,5,10,10,2,1404.18,30,15,0.120484,3.29,NBSENSORS
10,5,2,10,10,8,1242.1,12,12,0.441518,3.29,LATENCY
10,5,13,8,10,2,1595.79,78,21,0.0999088,3.29,NBHOP
10,5,2,10,50,2,1242.1,12,12,0.116307,3.29,BW
10,5,1,7,10,2,828.163,6,8,0.082982,3.29,NBHOP
10,5,13,6,10,2,1355.91,78,19,0.0751484,3.29,NBHOP
10,5,8,6,10,2,1085.95,48,14,0.071326,3.29,NBHOP
10,5,7,10,50,2,1512.24,42,17,0.118334,3.29,BW
10,5,3,4,10,2,576.034,18,7,0.043352,3.29,NBHOP
10,5,2,10,10,1,1242.1,12,12,0.0635174,3.29,LATENCY
10,5,3,10,30,2,1296.13,18,13,0.117364,3.29,BW
10,5,8,10,10,2,1566.27,48,18,0.119686,3.29,NBHOP
10,5,5,10,70,2,1404.18,30,15,0.119188,3.29,BW
10,5,2,10,10,6,1242.1,12,12,0.333518,3.29,LATENCY
10,5,3,10,10,2,1296.13,18,13,0.118372,3.29,LATENCY
10,5,6,10,10,2,1458.21,36,16,0.119644,3.29,BW
10,5,11,10,10,7,1728.35,66,21,0.392655,3.29,LATENCY
10,5,7,2,10,2,552.036,42,9,0.0218391,3.29,NBHOP
10,5,7,10,10,2,1512.24,42,17,0.119544,3.29,LATENCY
10,5,8,10,70,2,1566.27,48,18,0.11839,3.29,BW
10,5,7,10,10,5,1512.24,42,17,0.281544,3.29,LATENCY
10,5,4,10,10,9,1350.16,24,14,0.496468,3.29,LATENCY
10,5,15,4,10,2,1224.09,90,19,0.0531475,3.29,NBHOP
10,5,15,10,90,2,1944.47,90,25,0.12554,3.29,BW
10,5,15,10,10,9,1944.47,90,25,0.504884,3.29,LATENCY
10,5,2,1,10,2,161.992,0,3,0,3.29,NBHOP
10,5,11,10,90,2,1728.35,66,21,0.121311,3.29,BW
10,5,10,8,10,2,1433.84,60,18,0.097937,3.29,NBHOP
10,5,6,2,10,2,498.033,36,8,0.0211543,3.29,NBHOP
10,5,8,2,10,2,606.039,48,10,0.0233409,3.29,NBHOP
10,5,11,2,10,2,768.049,66,13,0.0253035,3.29,NBHOP
10,5,3,10,10,5,1296.13,18,13,0.280372,3.29,LATENCY
10,5,3,2,10,2,336.029,18,5,0.0229953,3.29,NBHOP
10,5,5,9,10,2,1284.06,30,14,0.107476,3.29,NBHOP
10,5,2,10,10,3,1242.1,12,12,0.171517,3.29,LATENCY
10,5,1,2,10,2,228.027,6,3,0.017115,3.29,NBHOP
10,5,12,10,10,10,1782.38,72,22,0.554763,3.29,LATENCY
10,5,13,2,10,2,876.058,78,15,0.0264602,3.29,NBHOP
10,5,2,6,10,2,761.997,12,8,0.068391,3.29,NBHOP
10,5,10,7,10,2,1314.8,60,17,0.0847696,3.29,NBHOP
10,5,15,10,70,2,1944.47,90,25,0.125588,3.29,BW
10,5,13,9,10,2,1716.12,78,22,0.110708,3.29,NBHOP
10,5,13,5,10,2,1236.56,78,18,0.0634254,3.29,NBHOP
10,5,8,10,10,2,1566.27,48,18,0.119686,3.29,BW
10,5,12,10,10,2,1782.38,72,22,0.122763,3.29,BW
10,5,15,5,10,2,1344.65,90,20,0.0657167,3.29,NBHOP
10,5,12,10,10,9,1782.38,72,22,0.500763,3.29,LATENCY
10,5,7,10,10,2,1512.24,42,17,0.119544,3.29,BW
10,5,9,10,10,1,1620.29,54,19,0.0671741,3.29,LATENCY
10,5,5,8,10,2,1163.92,30,13,0.0942834,3.29,NBHOP
10,5,9,10,90,2,1620.29,54,19,0.11983,3.29,BW
10,5,14,10,10,2,1890.44,84,24,0.126032,3.29,LATENCY
10,5,14,9,10,2,1770.13,84,23,0.114168,3.29,NBHOP
10,5,1,6,10,2,708.007,6,7,0.070751,3.29,NBHOP
10,5,1,9,10,2,1068.04,6,10,0.102327,3.29,NBHOP
10,5,4,10,10,4,1350.16,24,14,0.226468,3.29,LATENCY
10,5,9,3,10,2,780.344,54,12,0.034807,3.29,NBHOP
10,5,14,10,10,4,1890.44,84,24,0.234032,3.29,LATENCY
10,5,4,4,10,2,630.037,24,8,0.04541,3.29,NBHOP
10,5,15,10,10,4,1944.47,90,25,0.234884,3.29,LATENCY
10,5,5,10,30,2,1404.18,30,15,0.119476,3.29,BW
10,5,3,10,10,2,1296.13,18,13,0.118372,3.29,NBHOP
10,5,15,10,10,2,1944.47,90,25,0.126884,3.29,LATENCY
10,5,13,10,10,6,1836.41,78,23,0.339283,3.29,LATENCY
10,5,11,5,10,2,1128.48,66,16,0.0627003,3.29,NBHOP
10,5,1,10,90,2,1188.08,6,11,0.10916,3.29,BW
10,5,5,10,10,6,1404.18,30,15,0.336484,3.29,LATENCY
10,5,1,10,10,2,1188.08,6,11,0.110504,3.29,NBHOP
10,5,15,10,10,7,1944.47,90,25,0.396884,3.29,LATENCY
10,5,6,5,10,2,858.287,36,11,0.056738,3.29,NBHOP
10,5,5,10,10,10,1404.18,30,15,0.552484,3.29,LATENCY
10,5,6,9,10,2,1338.07,36,15,0.106302,3.29,NBHOP
10,5,9,10,10,2,1620.29,54,19,0.121174,3.29,BW
10,5,3,9,10,2,1176.05,18,12,0.104621,3.29,NBHOP
10,5,9,10,10,6,1620.29,54,19,0.337174,3.29,LATENCY
10,5,3,10,10,4,1296.13,18,13,0.226372,3.29,LATENCY
10,5,3,10,10,7,1296.13,18,13,0.388372,3.29,LATENCY
10,5,5,10,10,5,1404.18,30,15,0.282484,3.29,LATENCY
10,5,5,10,10,2,1404.18,30,15,0.120484,3.29,BW
10,5,12,2,10,2,822.053,72,14,0.0254289,3.29,NBHOP
10,5,5,10,10,4,1404.18,30,15,0.228484,3.29,LATENCY
10,5,14,1,10,2,809.865,0,15,0,3.29,NBHOP
10,5,10,2,10,2,714.045,60,12,0.0236707,3.29,NBHOP
10,5,1,10,10,7,1188.08,6,11,0.380504,3.29,LATENCY
10,5,6,10,10,2,1458.21,36,16,0.119644,3.29,LATENCY
10,5,9,10,10,2,1620.29,54,19,0.121174,3.29,LATENCY
10,5,1,10,10,9,1188.08,6,11,0.488504,3.29,LATENCY
10,5,10,10,90,2,1674.32,60,20,0.121554,3.29,BW
10,5,9,2,10,2,660.041,54,11,0.0225149,3.29,NBHOP
10,5,3,10,70,2,1296.13,18,13,0.117076,3.29,BW
10,5,9,10,30,2,1620.29,54,19,0.120166,3.29,BW
10,5,10,10,10,10,1674.32,60,20,0.554898,3.29,LATENCY
10,5,14,10,30,2,1890.44,84,24,0.125024,3.29,BW
10,5,9,10,10,8,1620.29,54,19,0.445174,3.29,LATENCY
10,5,8,10,10,4,1566.27,48,18,0.227686,3.29,LATENCY
10,5,15,3,10,2,1104.55,90,18,0.0404363,3.29,NBHOP
10,5,10,6,10,2,1193.93,60,16,0.0726894,3.29,NBHOP
10,5,4,10,50,2,1350.16,24,14,0.117258,3.29,BW
10,5,9,7,10,2,1260.73,54,16,0.0857653,3.29,NBHOP
10,5,8,10,90,2,1566.27,48,18,0.118342,3.29,BW
10,5,10,10,10,2,1674.32,60,20,0.122898,3.29,LATENCY
10,5,9,10,10,2,1620.29,54,19,0.121174,3.29,NBHOP
10,5,6,10,10,2,1458.21,36,16,0.119644,3.29,NBHOP
10,5,15,10,10,2,1944.47,90,25,0.126884,3.29,BW
10,5,7,10,10,10,1512.24,42,17,0.551544,3.29,LATENCY
10,5,8,7,10,2,1206.65,48,15,0.0822275,3.29,NBHOP
10,5,7,8,10,2,1271.89,42,15,0.0957549,3.29,NBHOP
10,5,5,10,50,2,1404.18,30,15,0.119274,3.29,BW
10,5,9,8,10,2,1379.85,54,17,0.0962989,3.29,NBHOP
10,5,5,10,90,2,1404.18,30,15,0.11914,3.29,BW
10,5,4,10,10,2,1350.16,24,14,0.118468,3.29,NBHOP
10,5,8,8,10,2,1325.87,48,16,0.0955481,3.29,NBHOP
10,5,5,10,10,2,1404.18,30,15,0.120484,3.29,LATENCY
10,5,5,10,10,9,1404.18,30,15,0.498484,3.29,LATENCY
10,5,13,10,10,3,1836.41,78,23,0.177283,3.29,LATENCY
10,5,8,10,30,2,1566.27,48,18,0.118678,3.29,BW
10,5,4,10,90,2,1350.16,24,14,0.117124,3.29,BW
10,5,7,9,10,2,1392.07,42,16,0.108944,3.29,NBHOP
10,5,3,10,10,3,1296.13,18,13,0.172372,3.29,LATENCY
10,5,7,5,10,2,912.325,42,12,0.0595301,3.29,NBHOP
10,5,7,3,10,2,672.278,42,10,0.0346726,3.29,NBHOP
10,5,10,10,10,5,1674.32,60,20,0.284898,3.29,LATENCY
10,5,14,10,10,8,1890.44,84,24,0.450032,3.29,LATENCY
10,5,1,8,10,2,947.989,6,9,0.088168,3.29,NBHOP
10,5,11,10,10,3,1728.35,66,21,0.176655,3.29,LATENCY
10,5,1,5,10,2,588.099,6,6,0.049619,3.29,NBHOP
10,5,13,7,10,2,1477.01,78,20,0.0873509,3.29,NBHOP
10,5,7,10,10,3,1512.24,42,17,0.173544,3.29,LATENCY
10,5,6,4,10,2,738.044,36,10,0.0461945,3.29,NBHOP
10,5,7,6,10,2,1031.95,42,13,0.0716466,3.29,NBHOP
10,5,5,2,10,2,444.032,30,7,0.0212024,3.29,NBHOP
10,5,3,5,10,2,696.174,18,8,0.0551053,3.29,NBHOP
10,5,14,10,10,7,1890.44,84,24,0.396032,3.29,LATENCY
10,5,7,10,90,2,1512.24,42,17,0.1182,3.29,BW
10,5,9,10,10,9,1620.29,54,19,0.499174,3.29,LATENCY
10,5,8,9,10,2,1446.08,48,17,0.108599,3.29,NBHOP
10,5,11,10,70,2,1728.35,66,21,0.121359,3.29,BW
10,5,5,4,10,2,684.039,30,9,0.0441026,3.29,NBHOP
10,5,1,10,10,4,1188.08,6,11,0.218504,3.29,LATENCY
10,5,12,8,10,2,1541.81,72,20,0.0990603,3.29,NBHOP
10,5,10,5,10,2,1074.44,60,15,0.0610499,3.29,NBHOP
10,5,3,10,10,1,1296.13,18,13,0.0643722,3.29,LATENCY
10,5,10,10,50,2,1674.32,60,20,0.121688,3.29,BW
10,5,10,10,10,8,1674.32,60,20,0.446898,3.29,LATENCY
10,5,15,10,10,2,1944.47,90,25,0.126884,3.29,NBHOP
10,5,4,2,10,2,390.03,24,6,0.0210262,3.29,NBHOP
10,5,6,10,10,5,1458.21,36,16,0.281644,3.29,LATENCY
10,5,14,4,10,2,1170.08,84,18,0.0516451,3.29,NBHOP
10,5,4,10,10,5,1350.16,24,14,0.280468,3.29,LATENCY
10,5,8,10,10,7,1566.27,48,18,0.389686,3.29,LATENCY
10,5,12,6,10,2,1301.92,72,18,0.0753212,3.29,NBHOP
10,5,12,3,10,2,942.445,72,15,0.0369372,3.29,NBHOP
10,5,14,6,10,2,1409.91,84,20,0.0770229,3.29,NBHOP
10,5,3,8,10,2,1055.95,18,11,0.0919907,3.29,NBHOP
10,5,14,10,10,1,1890.44,84,24,0.0720317,3.29,LATENCY
10,5,11,10,10,1,1728.35,66,21,0.0686554,3.29,LATENCY
10,5,11,10,10,9,1728.35,66,21,0.500655,3.29,LATENCY
10,5,1,10,10,1,1188.08,6,11,0.0565039,3.29,LATENCY
10,5,13,10,10,5,1836.41,78,23,0.285283,3.29,LATENCY
10,5,3,1,10,2,215.981,0,4,0,3.29,NBHOP
10,5,4,9,10,2,1230.05,24,13,0.105932,3.29,NBHOP
10,5,6,10,10,7,1458.21,36,16,0.389644,3.29,LATENCY
10,5,6,10,30,2,1458.21,36,16,0.118636,3.29,BW
10,5,11,10,10,5,1728.35,66,21,0.284655,3.29,LATENCY
10,5,8,1,10,2,485.927,0,9,0,3.29,NBHOP
10,5,8,10,10,2,1566.27,48,18,0.119686,3.29,LATENCY
10,5,2,10,10,10,1242.1,12,12,0.549517,3.29,LATENCY
10,5,10,10,30,2,1674.32,60,20,0.12189,3.29,BW
10,5,9,10,50,2,1620.29,54,19,0.119964,3.29,BW
10,5,9,5,10,2,1020.4,54,14,0.0605286,3.29,NBHOP
10,5,3,6,10,2,815.987,18,9,0.0695587,3.29,NBHOP
10,5,6,10,50,2,1458.21,36,16,0.118434,3.29,BW
10,5,10,10,10,7,1674.32,60,20,0.392898,3.29,LATENCY
10,5,4,10,10,2,1350.16,24,14,0.118468,3.29,BW
10,5,1,10,10,2,1188.08,6,11,0.110504,3.29,NBSENSORS
10,5,14,3,10,2,1050.52,84,17,0.0408313,3.29,NBHOP
10,5,5,10,10,2,1404.18,30,15,0.120484,3.29,NBHOP
10,5,8,10,50,2,1566.27,48,18,0.118476,3.29,BW
10,5,4,10,10,3,1350.16,24,14,0.172468,3.29,LATENCY
10,5,10,1,10,2,593.906,0,11,0,3.29,NBHOP
10,5,15,2,10,2,984.068,90,17,0.030147,3.29,NBHOP
10,5,4,10,10,2,1350.16,24,14,0.118468,3.29,LATENCY
10,5,6,10,10,4,1458.21,36,16,0.227644,3.29,LATENCY
10,5,8,10,10,8,1566.27,48,18,0.443686,3.29,LATENCY
10,5,13,10,10,9,1836.41,78,23,0.501283,3.29,LATENCY
10,5,15,6,10,2,1463.9,90,21,0.0789799,3.29,NBHOP
10,5,1,10,10,8,1188.08,6,11,0.434504,3.29,LATENCY
10,5,4,5,10,2,750.211,24,9,0.0577648,3.29,NBHOP
10,5,2,10,10,5,1242.1,12,12,0.279517,3.29,LATENCY
10,5,15,10,10,8,1944.47,90,25,0.450884,3.29,LATENCY
10,5,3,10,50,2,1296.13,18,13,0.117162,3.29,BW
10,5,12,10,10,5,1782.38,72,22,0.284763,3.29,LATENCY
10,5,12,9,10,2,1662.12,72,21,0.111567,3.29,NBHOP
10,5,11,1,10,2,647.896,0,12,0,3.29,NBHOP
10,5,3,3,10,2,456.149,18,6,0.0317123,3.29,NBHOP
10,5,2,8,10,2,1001.97,12,10,0.0915105,3.29,NBHOP
10,5,9,10,10,5,1620.29,54,19,0.283174,3.29,LATENCY
10,5,5,10,10,7,1404.18,30,15,0.390484,3.29,LATENCY
10,5,5,10,10,3,1404.18,30,15,0.174484,3.29,LATENCY
10,5,3,10,10,10,1296.13,18,13,0.550372,3.29,LATENCY
10,5,2,10,10,2,1242.1,12,12,0.117517,3.29,LATENCY
10,5,1,1,10,2,108.004,0,2,0,3.29,NBHOP
10,5,8,10,10,6,1566.27,48,18,0.335686,3.29,LATENCY
10,5,6,10,10,9,1458.21,36,16,0.497644,3.29,LATENCY
10,5,8,4,10,2,846.051,48,12,0.0468565,3.29,NBHOP
10,5,6,6,10,2,977.962,36,12,0.0692437,3.29,NBHOP
10,5,1,3,10,2,348.087,6,4,0.026229,3.29,NBHOP
10,5,6,10,70,2,1458.21,36,16,0.118348,3.29,BW
10,5,3,10,10,8,1296.13,18,13,0.442372,3.29,LATENCY
10,5,9,10,10,7,1620.29,54,19,0.391174,3.29,LATENCY
10,5,3,10,10,6,1296.13,18,13,0.334372,3.29,LATENCY
10,5,6,10,10,3,1458.21,36,16,0.173644,3.29,LATENCY
10,5,5,1,10,2,323.959,0,6,0,3.29,NBHOP
10,5,6,8,10,2,1217.9,36,14,0.093869,3.29,NBHOP
10,5,4,10,10,8,1350.16,24,14,0.442468,3.29,LATENCY
10,5,10,10,10,2,1674.32,60,20,0.122898,3.29,NBHOP
10,5,2,10,10,9,1242.1,12,12,0.495517,3.29,LATENCY
10,5,14,10,10,5,1890.44,84,24,0.288032,3.29,LATENCY
10,5,4,7,10,2,990.372,24,11,0.0806572,3.29,NBHOP
10,5,14,5,10,2,1290.6,84,19,0.0646285,3.29,NBHOP
10,5,13,10,70,2,1836.41,78,23,0.121987,3.29,BW
10,5,14,10,10,9,1890.44,84,24,0.504032,3.29,LATENCY
10,5,10,10,10,4,1674.32,60,20,0.230898,3.29,LATENCY
10,5,14,10,10,10,1890.44,84,24,0.558032,3.29,LATENCY
10,5,13,10,10,10,1836.41,78,23,0.555283,3.29,LATENCY
10,5,2,10,10,7,1242.1,12,12,0.387517,3.29,LATENCY
10,5,11,10,10,2,1728.35,66,21,0.122655,3.29,NBHOP
10,5,2,10,30,2,1242.1,12,12,0.11651,3.29,BW
10,5,1,10,10,2,1188.08,6,11,0.110504,3.29,LATENCY
10,5,13,3,10,2,996.481,78,16,0.0386852,3.29,NBHOP
10,5,10,4,10,2,954.061,60,14,0.0477382,3.29,NBHOP
10,5,7,10,70,2,1512.24,42,17,0.118248,3.29,BW
10,5,5,3,10,2,564.212,30,8,0.0334324,3.29,NBHOP
10,5,3,7,10,2,936.302,18,10,0.0814983,3.29,NBHOP
10,5,1,10,10,5,1188.08,6,11,0.272504,3.29,LATENCY
10,5,10,10,10,1,1674.32,60,20,0.0688975,3.29,LATENCY
10,5,13,10,50,2,1836.41,78,23,0.122073,3.29,BW
10,5,11,10,10,10,1728.35,66,21,0.554655,3.29,LATENCY
10,5,8,10,10,9,1566.27,48,18,0.497686,3.29,LATENCY
10,5,15,10,10,3,1944.47,90,25,0.180884,3.29,LATENCY
10,5,2,3,10,2,402.118,12,5,0.0315625,3.29,NBHOP
10,5,4,1,10,2,269.97,0,5,0,3.29,NBHOP
10,5,7,10,10,8,1512.24,42,17,0.443544,3.29,LATENCY
10,5,7,10,10,2,1512.24,42,17,0.119544,3.29,NBHOP
10,5,15,10,10,1,1944.47,90,25,0.0728842,3.29,LATENCY
10,5,10,9,10,2,1554.1,60,19,0.111113,3.29,NBHOP
10,5,1,10,70,2,1188.08,6,11,0.109208,3.29,BW
10,5,1,10,10,10,1188.08,6,11,0.542504,3.29,LATENCY
10,5,11,10,10,2,1728.35,66,21,0.122655,3.29,LATENCY
10,5,2,10,10,4,1242.1,12,12,0.225517,3.29,LATENCY
10,5,15,9,10,2,1824.14,90,24,0.11431,3.29,NBHOP
10,5,11,4,10,2,1008.07,66,15,0.0502385,3.29,NBHOP
10,5,11,10,10,2,1728.35,66,21,0.122655,3.29,BW
10,5,5,10,10,8,1404.18,30,15,0.444484,3.29,LATENCY
10,5,8,3,10,2,726.31,48,11,0.0361296,3.29,NBHOP
10,5,10,3,10,2,834.377,60,13,0.0359287,3.29,NBHOP
10,5,11,10,10,4,1728.35,66,21,0.230655,3.29,LATENCY
10,5,4,10,10,7,1350.16,24,14,0.388468,3.29,LATENCY
10,5,12,5,10,2,1182.52,72,17,0.0615217,3.29,NBHOP
10,5,9,9,10,2,1500.09,54,18,0.109942,3.29,NBHOP
10,5,1,10,30,2,1188.08,6,11,0.109496,3.29,BW
10,5,7,10,10,1,1512.24,42,17,0.065544,3.29,LATENCY
10,5,11,10,10,6,1728.35,66,21,0.338655,3.29,LATENCY
10,5,2,10,10,2,1242.1,12,12,0.117517,3.29,BW
10,5,11,8,10,2,1487.82,66,19,0.0984001,3.29,NBHOP
10,5,14,10,10,2,1890.44,84,24,0.126032,3.29,BW
10,5,6,10,90,2,1458.21,36,16,0.1183,3.29,BW
10,5,5,10,10,1,1404.18,30,15,0.0664843,3.29,LATENCY
10,5,12,10,10,7,1782.38,72,22,0.392763,3.29,LATENCY
10,5,15,10,50,2,1944.47,90,25,0.125674,3.29,BW
10,5,2,10,90,2,1242.1,12,12,0.116173,3.29,BW
10,5,2,10,10,2,1242.1,12,12,0.117517,3.29,NBSENSORS
10,5,9,6,10,2,1139.94,54,15,0.0732161,3.29,NBHOP
10,5,1,10,50,2,1188.08,6,11,0.109294,3.29,BW
10,5,9,10,70,2,1620.29,54,19,0.119878,3.29,BW
10,5,6,1,10,2,377.948,0,7,0,3.29,NBHOP
10,5,12,10,10,1,1782.38,72,22,0.0687625,3.29,LATENCY
10,5,13,1,10,2,755.876,0,14,0,3.29,NBHOP
10,5,14,10,50,2,1890.44,84,24,0.124822,3.29,BW
10,5,13,10,10,2,1836.41,78,23,0.123283,3.29,NBHOP
10,5,13,10,10,7,1836.41,78,23,0.393283,3.29,LATENCY
10,5,6,10,10,8,1458.21,36,16,0.443644,3.29,LATENCY
10,5,13,10,10,8,1836.41,78,23,0.447283,3.29,LATENCY
10,5,5,6,10,2,923.97,30,11,0.068991,3.29,NBHOP
10,5,4,6,10,2,869.978,24,10,0.0702622,3.29,NBHOP
10,5,11,7,10,2,1368.87,66,18,0.0867735,3.29,NBHOP
10,5,1,10,10,2,1188.08,6,11,0.110504,3.29,BW
10,5,11,10,10,8,1728.35,66,21,0.446655,3.29,LATENCY
10,5,12,10,10,6,1782.38,72,22,0.338763,3.29,LATENCY
10,5,15,10,10,5,1944.47,90,25,0.288884,3.29,LATENCY
10,5,9,4,10,2,900.056,54,13,0.0477678,3.29,NBHOP
10,5,7,1,10,2,431.937,0,8,0,3.29,NBHOP
10,5,6,7,10,2,1098.51,36,13,0.0812177,3.29,NBHOP
10,5,2,10,10,2,1242.1,12,12,0.117517,3.29,NBHOP
10,5,7,4,10,2,792.047,42,11,0.0471126,3.29,NBHOP
10,5,11,3,10,2,888.412,66,14,0.0379922,3.29,NBHOP
10,5,4,10,10,10,1350.16,24,14,0.550468,3.29,LATENCY
10,5,10,10,10,9,1674.32,60,20,0.500898,3.29,LATENCY
10,5,5,7,10,2,1044.44,30,12,0.0806844,3.29,NBHOP
10,5,12,10,30,2,1782.38,72,22,0.121755,3.29,BW
10,5,5,5,10,2,804.249,30,10,0.056026,3.29,NBHOP
10,5,3,10,90,2,1296.13,18,13,0.117028,3.29,BW
10,5,8,10,10,10,1566.27,48,18,0.551686,3.29,LATENCY
10,5,6,10,10,10,1458.21,36,16,0.551644,3.29,LATENCY
10,5,14,8,10,2,1649.78,84,22,0.101877,3.29,NBHOP
10,5,14,10,90,2,1890.44,84,24,0.124688,3.29,BW
10,5,7,10,10,9,1512.24,42,17,0.497544,3.29,LATENCY
10,5,14,10,10,2,1890.44,84,24,0.126032,3.29,NBHOP
10,5,4,10,10,6,1350.16,24,14,0.334468,3.29,LATENCY
10,5,12,10,10,2,1782.38,72,22,0.122763,3.29,LATENCY
10,5,9,10,10,4,1620.29,54,19,0.229174,3.29,LATENCY
10,5,11,9,10,2,1608.11,66,20,0.110984,3.29,NBHOP
10,5,11,10,50,2,1728.35,66,21,0.121445,3.29,BW
10,5,13,10,10,1,1836.41,78,23,0.0692831,3.29,LATENCY
10,5,1,4,10,2,468.029,6,5,0.04246,3.29,NBHOP
10,5,10,10,70,2,1674.32,60,20,0.121602,3.29,BW
10,5,12,10,70,2,1782.38,72,22,0.121467,3.29,BW
10,5,7,10,10,7,1512.24,42,17,0.389544,3.29,LATENCY
10,5,13,10,10,4,1836.41,78,23,0.231283,3.29,LATENCY
10,5,13,10,10,2,1836.41,78,23,0.123283,3.29,BW
10,5,12,10,90,2,1782.38,72,22,0.121419,3.29,BW
10,5,8,10,10,5,1566.27,48,18,0.281686,3.29,LATENCY
10,5,7,10,10,6,1512.24,42,17,0.335544,3.29,LATENCY
10,5,11,6,10,2,1247.93,66,17,0.0749006,3.29,NBHOP
10,5,12,10,50,2,1782.38,72,22,0.121553,3.29,BW
10,5,9,1,10,2,539.916,0,10,0,3.29,NBHOP
10,5,13,10,10,2,1836.41,78,23,0.123283,3.29,LATENCY
10,5,15,7,10,2,1585.16,90,22,0.0899177,3.29,NBHOP
10,5,3,10,10,2,1296.13,18,13,0.118372,3.29,NBSENSORS
10,5,15,10,10,10,1944.47,90,25,0.558884,3.29,LATENCY
10,5,4,3,10,2,510.181,24,7,0.03217,3.29,NBHOP
10,5,13,10,30,2,1836.41,78,23,0.122275,3.29,BW
10,5,6,10,10,6,1458.21,36,16,0.335644,3.29,LATENCY
10,5,7,10,10,4,1512.24,42,17,0.227544,3.29,LATENCY
10,5,15,10,10,6,1944.47,90,25,0.342884,3.29,LATENCY
10,5,13,10,90,2,1836.41,78,23,0.121939,3.29,BW
10,5,12,10,10,2,1782.38,72,22,0.122763,3.29,NBHOP
10,5,7,7,10,2,1152.58,42,14,0.0835217,3.29,NBHOP
10,5,12,10,10,4,1782.38,72,22,0.230763,3.29,LATENCY
10,5,14,7,10,2,1531.09,84,21,0.090289,3.29,NBHOP
10,5,14,10,70,2,1890.44,84,24,0.124736,3.29,BW
10,5,3,10,10,2,1296.13,18,13,0.118372,3.29,BW
10,5,8,10,10,3,1566.27,48,18,0.173686,3.29,LATENCY
10,5,15,10,30,2,1944.47,90,25,0.125876,3.29,BW
10,5,14,2,10,2,930.063,84,16,0.0284299,3.29,NBHOP
10,5,7,10,30,2,1512.24,42,17,0.118536,3.29,BW
10,5,10,10,10,3,1674.32,60,20,0.176898,3.29,LATENCY
10,5,2,2,10,2,282.028,12,4,0.019416,3.29,NBHOP
10,5,3,10,10,9,1296.13,18,13,0.496372,3.29,LATENCY
10,5,8,10,10,1,1566.27,48,18,0.0656858,3.29,LATENCY
10,5,2,9,10,2,1122.04,12,11,0.104295,3.29,NBHOP
10,5,2,4,10,2,522.032,12,6,0.045181,3.29,NBHOP
10,5,4,10,30,2,1350.16,24,14,0.11746,3.29,BW
10,5,4,10,10,2,1350.16,24,14,0.118468,3.29,NBSENSORS
10,5,12,7,10,2,1422.94,72,19,0.0862663,3.29,NBHOP
10,5,2,7,10,2,882.233,12,9,0.0803245,3.29,NBHOP
10,5,14,10,10,6,1890.44,84,24,0.342032,3.29,LATENCY
10,5,14,10,10,3,1890.44,84,24,0.180032,3.29,LATENCY
10,5,6,10,10,1,1458.21,36,16,0.0656441,3.29,LATENCY
10,5,12,4,10,2,1062.07,72,16,0.0491456,3.29,NBHOP
10,5,13,4,10,2,1116.08,78,17,0.0508868,3.29,NBHOP
10,5,9,10,10,10,1620.29,54,19,0.553174,3.29,LATENCY
10,5,15,1,10,2,863.855,0,16,0,3.29,NBHOP
10,5,1,10,10,6,1188.08,6,11,0.326504,3.29,LATENCY
10,5,4,10,70,2,1350.16,24,14,0.117172,3.29,BW
10,5,12,1,10,2,701.886,0,13,0,3.29,NBHOP
10,5,12,10,10,3,1782.38,72,22,0.176763,3.29,LATENCY
10,5,6,3,10,2,618.245,36,9,0.0334377,3.29,NBHOP
10,5,10,10,10,6,1674.32,60,20,0.338898,3.29,LATENCY
10,5,9,10,10,3,1620.29,54,19,0.175174,3.29,LATENCY
10,5,2,5,10,2,642.136,12,7,0.055376,3.29,NBHOP
10,5,10,10,10,2,1674.32,60,20,0.122898,3.29,BW
10,5,4,10,10,1,1350.16,24,14,0.0644679,3.29,LATENCY
10,5,2,10,70,2,1242.1,12,12,0.116222,3.29,BW
10,5,8,5,10,2,966.364,48,13,0.0590559,3.29,NBHOP
10,5,12,10,10,8,1782.38,72,22,0.446763,3.29,LATENCY
10,5,1,10,10,3,1188.08,6,11,0.164504,3.29,LATENCY
10,5,4,8,10,2,1109.94,24,12,0.094549,3.29,NBHOP
10,5,15,8,10,2,1703.76,90,23,0.100124,3.29,NBHOP
10,5,11,10,30,2,1728.35,66,21,0.121647,3.29,BW
10,5,5,10,10,2,1404.18,30,15,0.120484,3.29,NBSENSORS
10,5,2,10,10,8,1242.1,12,12,0.441518,3.29,LATENCY
10,5,13,8,10,2,1595.79,78,21,0.0999088,3.29,NBHOP
10,5,2,10,50,2,1242.1,12,12,0.116307,3.29,BW
10,5,1,7,10,2,828.163,6,8,0.082982,3.29,NBHOP
10,5,13,6,10,2,1355.91,78,19,0.0751484,3.29,NBHOP
10,5,8,6,10,2,1085.95,48,14,0.071326,3.29,NBHOP
10,5,7,10,50,2,1512.24,42,17,0.118334,3.29,BW
10,5,3,4,10,2,576.034,18,7,0.043352,3.29,NBHOP
10,5,2,10,10,1,1242.1,12,12,0.0635174,3.29,LATENCY
10,5,3,10,30,2,1296.13,18,13,0.117364,3.29,BW
10,5,8,10,10,2,1566.27,48,18,0.119686,3.29,NBHOP
10,5,5,10,70,2,1404.18,30,15,0.119188,3.29,BW
10,5,2,10,10,6,1242.1,12,12,0.333518,3.29,LATENCY
10,5,3,10,10,2,1296.13,18,13,0.118372,3.29,LATENCY
10,5,6,10,10,2,1458.21,36,16,0.119644,3.29,BW
10,5,11,10,10,7,1728.35,66,21,0.392655,3.29,LATENCY
10,5,7,2,10,2,552.036,42,9,0.0218391,3.29,NBHOP
10,5,7,10,10,2,1512.24,42,17,0.119544,3.29,LATENCY
10,5,8,10,70,2,1566.27,48,18,0.11839,3.29,BW
10,5,7,10,10,5,1512.24,42,17,0.281544,3.29,LATENCY
10,5,4,10,10,9,1350.16,24,14,0.496468,3.29,LATENCY
10,5,15,4,10,2,1224.09,90,19,0.0531475,3.29,NBHOP
10,5,15,10,90,2,1944.47,90,25,0.12554,3.29,BW
10,5,15,10,10,9,1944.47,90,25,0.504884,3.29,LATENCY
10,5,2,1,10,2,161.992,0,3,0,3.29,NBHOP
10,5,11,10,90,2,1728.35,66,21,0.121311,3.29,BW
10,5,10,8,10,2,1433.84,60,18,0.097937,3.29,NBHOP
10,5,6,2,10,2,498.033,36,8,0.0211543,3.29,NBHOP
10,5,8,2,10,2,606.039,48,10,0.0233409,3.29,NBHOP
10,5,11,2,10,2,768.049,66,13,0.0253035,3.29,NBHOP
10,5,3,10,10,5,1296.13,18,13,0.280372,3.29,LATENCY
10,5,3,2,10,2,336.029,18,5,0.0229953,3.29,NBHOP
10,5,5,9,10,2,1284.06,30,14,0.107476,3.29,NBHOP
10,5,2,10,10,3,1242.1,12,12,0.171517,3.29,LATENCY
10,5,1,2,10,2,228.027,6,3,0.017115,3.29,NBHOP
10,5,12,10,10,10,1782.38,72,22,0.554763,3.29,LATENCY
10,5,13,2,10,2,876.058,78,15,0.0264602,3.29,NBHOP
10,5,2,6,10,2,761.997,12,8,0.068391,3.29,NBHOP
10,5,10,7,10,2,1314.8,60,17,0.0847696,3.29,NBHOP
10,5,15,10,70,2,1944.47,90,25,0.125588,3.29,BW
10,5,13,9,10,2,1716.12,78,22,0.110708,3.29,NBHOP
10,5,13,5,10,2,1236.56,78,18,0.0634254,3.29,NBHOP
10,5,8,10,10,2,1566.27,48,18,0.119686,3.29,BW
10,5,12,10,10,2,1782.38,72,22,0.122763,3.29,BW
10,5,15,5,10,2,1344.65,90,20,0.0657167,3.29,NBHOP
10,5,12,10,10,9,1782.38,72,22,0.500763,3.29,LATENCY
10,5,7,10,10,2,1512.24,42,17,0.119544,3.29,BW
10,5,9,10,10,1,1620.29,54,19,0.0671741,3.29,LATENCY
10,5,5,8,10,2,1163.92,30,13,0.0942834,3.29,NBHOP
10,5,9,10,90,2,1620.29,54,19,0.11983,3.29,BW
10,5,14,10,10,2,1890.44,84,24,0.126032,3.29,LATENCY
10,5,14,9,10,2,1770.13,84,23,0.114168,3.29,NBHOP
10,5,1,6,10,2,708.007,6,7,0.070751,3.29,NBHOP
10,5,1,9,10,2,1068.04,6,10,0.102327,3.29,NBHOP
10,5,4,10,10,4,1350.16,24,14,0.226468,3.29,LATENCY
10,5,9,3,10,2,780.343,54,12,0.034807,3.29,NBHOP
10,5,14,10,10,4,1890.44,84,24,0.234032,3.29,LATENCY
10,5,4,4,10,2,630.037,24,8,0.04541,3.29,NBHOP
10,5,15,10,10,4,1944.47,90,25,0.234884,3.29,LATENCY
10,5,5,10,30,2,1404.18,30,15,0.119476,3.29,BW
10,5,3,10,10,2,1296.13,18,13,0.118372,3.29,NBHOP
10,5,15,10,10,2,1944.47,90,25,0.126884,3.29,LATENCY
10,5,13,10,10,6,1836.41,78,23,0.339283,3.29,LATENCY
10,5,11,5,10,2,1128.48,66,16,0.0627003,3.29,NBHOP
10,5,1,10,90,2,1188.08,6,11,0.10916,3.29,BW
10,5,5,10,10,6,1404.18,30,15,0.336484,3.29,LATENCY
10,5,1,10,10,2,1188.08,6,11,0.110504,3.29,NBHOP
10,5,15,10,10,7,1944.47,90,25,0.396884,3.29,LATENCY
10,5,6,5,10,2,858.287,36,11,0.056738,3.29,NBHOP
10,5,5,10,10,10,1404.18,30,15,0.552484,3.29,LATENCY
10,5,6,9,10,2,1338.07,36,15,0.106302,3.29,NBHOP
10,5,9,10,10,2,1620.29,54,19,0.121174,3.29,BW
10,5,3,9,10,2,1176.05,18,12,0.104621,3.29,NBHOP
10,5,9,10,10,6,1620.29,54,19,0.337174,3.29,LATENCY
10,5,3,10,10,4,1296.13,18,13,0.226372,3.29,LATENCY
10,5,3,10,10,7,1296.13,18,13,0.388372,3.29,LATENCY
10,5,5,10,10,5,1404.18,30,15,0.282484,3.29,LATENCY
10,5,5,10,10,2,1404.18,30,15,0.120484,3.29,BW
10,5,12,2,10,2,822.053,72,14,0.0254289,3.29,NBHOP
10,5,5,10,10,4,1404.18,30,15,0.228484,3.29,LATENCY
10,5,14,1,10,2,809.865,0,15,0,3.29,NBHOP
10,5,10,2,10,2,714.045,60,12,0.0236707,3.29,NBHOP
10,5,1,10,10,7,1188.08,6,11,0.380504,3.29,LATENCY
10,5,6,10,10,2,1458.21,36,16,0.119644,3.29,LATENCY
10,5,9,10,10,2,1620.29,54,19,0.121174,3.29,LATENCY
10,5,1,10,10,9,1188.08,6,11,0.488504,3.29,LATENCY
10,5,10,10,90,2,1674.32,60,20,0.121554,3.29,BW
10,5,9,2,10,2,660.041,54,11,0.0225149,3.29,NBHOP
10,5,3,10,70,2,1296.13,18,13,0.117076,3.29,BW
10,5,9,10,30,2,1620.29,54,19,0.120166,3.29,BW
10,5,10,10,10,10,1674.32,60,20,0.554898,3.29,LATENCY
10,5,14,10,30,2,1890.44,84,24,0.125024,3.29,BW
10,5,9,10,10,8,1620.29,54,19,0.445174,3.29,LATENCY
10,5,8,10,10,4,1566.27,48,18,0.227686,3.29,LATENCY
10,5,15,3,10,2,1104.55,90,18,0.0404363,3.29,NBHOP
10,5,10,6,10,2,1193.93,60,16,0.0726894,3.29,NBHOP
10,5,4,10,50,2,1350.16,24,14,0.117258,3.29,BW
10,5,9,7,10,2,1260.73,54,16,0.0857653,3.29,NBHOP
10,5,8,10,90,2,1566.27,48,18,0.118342,3.29,BW
10,5,10,10,10,2,1674.32,60,20,0.122898,3.29,LATENCY
10,5,9,10,10,2,1620.29,54,19,0.121174,3.29,NBHOP
10,5,6,10,10,2,1458.21,36,16,0.119644,3.29,NBHOP
10,5,15,10,10,2,1944.47,90,25,0.126884,3.29,BW
10,5,7,10,10,10,1512.24,42,17,0.551544,3.29,LATENCY
10,5,8,7,10,2,1206.65,48,15,0.0822275,3.29,NBHOP
10,5,7,8,10,2,1271.89,42,15,0.0957549,3.29,NBHOP
10,5,5,10,50,2,1404.18,30,15,0.119274,3.29,BW
10,5,9,8,10,2,1379.85,54,17,0.0962989,3.29,NBHOP
10,5,5,10,90,2,1404.18,30,15,0.11914,3.29,BW
10,5,4,10,10,2,1350.16,24,14,0.118468,3.29,NBHOP
10,5,8,8,10,2,1325.87,48,16,0.0955481,3.29,NBHOP
10,5,5,10,10,2,1404.18,30,15,0.120484,3.29,LATENCY
10,5,5,10,10,9,1404.18,30,15,0.498484,3.29,LATENCY
10,5,13,10,10,3,1836.41,78,23,0.177283,3.29,LATENCY
10,5,8,10,30,2,1566.27,48,18,0.118678,3.29,BW
10,5,4,10,90,2,1350.16,24,14,0.117124,3.29,BW
10,5,7,9,10,2,1392.07,42,16,0.108944,3.29,NBHOP
10,5,3,10,10,3,1296.13,18,13,0.172372,3.29,LATENCY
10,5,7,5,10,2,912.325,42,12,0.0595301,3.29,NBHOP
10,5,7,3,10,2,672.278,42,10,0.0346726,3.29,NBHOP
10,5,10,10,10,5,1674.32,60,20,0.284898,3.29,LATENCY
10,5,14,10,10,8,1890.44,84,24,0.450032,3.29,LATENCY
10,5,1,8,10,2,947.989,6,9,0.088168,3.29,NBHOP
10,5,11,10,10,3,1728.35,66,21,0.176655,3.29,LATENCY
10,5,1,5,10,2,588.099,6,6,0.049619,3.29,NBHOP
10,5,13,7,10,2,1477.01,78,20,0.0873509,3.29,NBHOP
10,5,7,10,10,3,1512.24,42,17,0.173544,3.29,LATENCY
10,5,6,4,10,2,738.044,36,10,0.0461945,3.29,NBHOP
10,5,7,6,10,2,1031.95,42,13,0.0716466,3.29,NBHOP
10,5,5,2,10,2,444.032,30,7,0.0212024,3.29,NBHOP
10,5,3,5,10,2,696.174,18,8,0.0551053,3.29,NBHOP
10,5,14,10,10,7,1890.44,84,24,0.396032,3.29,LATENCY
10,5,7,10,90,2,1512.24,42,17,0.1182,3.29,BW
10,5,9,10,10,9,1620.29,54,19,0.499174,3.29,LATENCY
10,5,8,9,10,2,1446.08,48,17,0.108599,3.29,NBHOP
10,5,11,10,70,2,1728.35,66,21,0.121359,3.29,BW
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