Add datasize scalability results

.Rhistory

@@ -0,0 +1,2 @@
+q()
+n

.gitignore

@@ -1,6 +1,6 @@
 simulator
-libs/simgrid
+libs/simgrid*
-libs/rapidjson
+libs/rapidjson*
 compile_commands.json
 platform.xml
 ./scenarios

Makefile

@@ -7,7 +7,7 @@ CC := g++ $(addprefix -L , $(LIBS)) $(addprefix -I , $(INCLUDES))
 all: $(EXEC) $(basename $(notdir $(SCENARIOS)))
 
 $(EXEC): $(filter-out $(SCENARIOS), $(wildcard src/*))
-	$(CC) -lsimgrid $^ -o $@
+	$(CC) $^ -lsimgrid -o $@
 
 $(basename $(notdir $(SCENARIOS))): $(SCENARIOS)
 	$(CC) $^ -o $@
@@ -16,4 +16,4 @@ run: $(EXEC)
 	export LD_LIBRARY_PATH=$(addprefix :, $(LIBS)) && ./$(EXEC) 10 --cfg=network/bandwidth-factor:1.05 --cfg=network/model:CM02 -–cfg=network/crosstraffic:0
 
 clean:
-	-rm $(EXEC) $(basename $(notdir $(SCENARIOS)))
+	-rm $(EXEC) $(basename $(notdir $(SCENARIOS)))

libs/setup.sh

@@ -2,8 +2,8 @@
 
 set -e
 
-[ ! -e "simgrid" ] && git clone https://framagit.org/simgrid/simgrid
+[ ! -e "simgrid" ] && wget https://data.loicguegan.com/Apps/SimGrid/simgrid-v3.27.tar.gz && tar -xvf simgrid-v3.27.tar.gz && ln -s simgrid-v3.27 simgrid # We use the SimGrid Ragnar Release
-[ ! -e "rapidjson"] && git clone https://github.com/Tencent/rapidjson
+[ ! -e "rapidjson" ] && wget https://data.loicguegan.com/Apps/RapidJSON/rapidjson-commit_ab1842a-Aprl9.tar.gz && tar -xvf rapidjson-commit_ab1842a-Aprl9.tar.gz && ln -s rapidjson-commit_ab1842a-Aprl9 rapidjson
 
 cd simgrid
 mkdir -p build

results/.Rhistory

@@ -0,0 +1,4 @@
+q()
+n
+q()
+n

results/analysis_datasize.R

@@ -0,0 +1,68 @@
+library("tidyverse")
+library("gridExtra")
+library("patchwork")
+library("knitr")
+library(RColorBrewer)
+library(latex2exp)
+
+r_=function(x){round(x,digits=2)}
+color=function(){scale_fill_brewer(palette = "Accent")}
+color2=function(){scale_fill_brewer(palette = "Set2")}
+nolegend=function(){theme(legend.position="none")}
+simkeys=unique(read_csv("results.csv")$simkey)
+nsimkeys=length(simkeys)
+s_=function(x){if(x<0){return("")}else{return("+")}}
+simkey_rename=function(key){
+    if(key=="hint")
+        return("Hints")
+    if(key=="baseline")
+        return("Baseline")
+    if(key=="extended")
+        return("Extended")
+    if(key=="hintandextended")
+        return("Hints+\nExtended")
+    return(key)
+}
+dformat=function(data){
+    data%>%rowwise()%>%mutate(simkey=simkey_rename(simkey))%>%
+        mutate(wireless=ifelse(wireless=="lora","LoRa","Nb-IoT"))%>%mutate(facet=paste0("With ",wakeupfor,"s uptime using ",wireless))
+}
+
+
+
+data=read_csv("results_datasize.csv")
+
+data=data%>%filter(isSender!=0)%>%group_by(wakeupfor,simkey,datasize,wireless)%>%summarize(success_mean=mean(nSend),success_sd=sd(nSend))
+data=data%>%mutate(datasize=ifelse(datasize==1000,"1KB",as.character(datasize)))
+data=data%>%mutate(datasize=ifelse(datasize==10000,"10KB",as.character(datasize)))
+data=data%>%mutate(datasize=ifelse(datasize==100000,"100KB",as.character(datasize)))
+data=data%>%mutate(datasize=ifelse(datasize==500000,"500KB",as.character(datasize)))
+data=data%>%mutate(datasize=ifelse(datasize==1000000,"1MB",as.character(datasize)))
+data=data%>%mutate(datasize=ifelse(datasize==2000000,"2MB",as.character(datasize)))
+data=data%>%mutate(datasize=ifelse(datasize==10000000,"10MB",as.character(datasize)))
+data=data%>%mutate(datasize=ifelse(datasize==50000000,"50MB",as.character(datasize)))
+data=data%>%mutate(datasize=ifelse(datasize==100000000,"100MB",as.character(datasize)))
+data=data%>%mutate(datasize=ifelse(datasize==500000000,"500MB",as.character(datasize)))
+data=data%>%mutate(datasize=ifelse(datasize==1000000000,"1GB",as.character(datasize)))
+data$datasize=factor(data$datasize,levels=c("1KB","10KB","100KB","500KB","1MB","2MB","10MB","50MB","100MB","500MB","1GB"))
+data=data%>%dformat()
+data$facet=factor(data$facet,levels=c("With 60s uptime using LoRa","With 60s uptime using Nb-IoT","With 180s uptime using LoRa","With 180s uptime using Nb-IoT"))
+                                        #ggplot(data,aes(x=datasize,y=success, color=simkey))+geom_point()
+
+ggplot(data,aes(x=datasize,y=success_mean,color=simkey,group=simkey))+
+    geom_point()+geom_line()+facet_wrap(~facet)+
+    xlab("Data size")+ylab(TeX(r'(#Succ$_p$)'))+scale_fill_brewer(palette = "Set1")+scale_color_brewer(palette = "Set1")+
+    labs(color="Policy:")+labs(fill="Standard deviation:")+
+    geom_ribbon(aes(ymin=success_mean-success_sd, ymax=success_mean+success_sd,fill=simkey),linetype=0,alpha=0.2)+
+    guides(color=guide_legend(override.aes=list(fill=NA)))+theme_bw()+ theme(legend.position="top")
+ggsave("datasize.pdf",width=12,height=6)
+
+ggplot(data%>%filter(wakeupfor==180,wireless=="LoRa"),aes(x=datasize,y=success_mean,color=simkey,group=simkey))+
+    geom_point()+geom_line()+facet_wrap(~facet)+
+    xlab("Data size")+ylab(TeX(r'(#Succ$_p$)'))+scale_fill_brewer(palette = "Set1")+scale_color_brewer(palette = "Set1")+
+    labs(color="Policy:")+labs(fill="Standard deviation:")+
+    geom_ribbon(aes(ymin=success_mean-success_sd, ymax=success_mean+success_sd,fill=simkey),linetype=0,alpha=0.2)+
+    guides(color=guide_legend(override.aes=list(fill=NA)))+theme_bw()+ theme(legend.position="top")
+ggsave("datasize_lora180.pdf",width=9.5,height=4)
+
+

results/analysis_datasize2.R

@@ -0,0 +1,135 @@
+library("tidyverse")
+library("ggthemes")
+library("gridExtra")
+library("patchwork")
+library(RColorBrewer)
+
+data=read_csv("results_datasize.csv")    
+r_=function(x){round(x,digits=1)}
+color=function(){scale_fill_brewer(palette = "Accent")}
+color2=function(){scale_fill_brewer(palette = "Set2")}
+nolegend=function(){theme(legend.position="none")}
+simkeys=unique(data$simkey)
+nsimkeys=length(simkeys)
+s_=function(x){if(x<0){return("")}else{return("+")}}
+simkey_rename=function(key){
+    if(key=="hint")
+        return("Hints")
+    if(key=="baseline")
+        return("Baseline")
+    if(key=="extended")
+        return("Extended")
+    if(key=="hintandextended")
+        return("Hints+Extended")
+    return(key)
+}
+dformat=function(data){
+    data%>%rowwise()%>%mutate(simkey=simkey_rename(simkey))%>%mutate(wireless=ifelse(wireless=="lora","LoRa","Nb-IoT"))
+}
+
+dsformat=function(data){
+    data=data%>%mutate(datasize=ifelse(datasize==1000,"1KB",as.character(datasize)))
+    data=data%>%mutate(datasize=ifelse(datasize==10000,"10KB",as.character(datasize)))
+    data=data%>%mutate(datasize=ifelse(datasize==100000,"100KB",as.character(datasize)))
+    data=data%>%mutate(datasize=ifelse(datasize==500000,"500KB",as.character(datasize)))
+    data=data%>%mutate(datasize=ifelse(datasize==1000000,"1MB",as.character(datasize)))
+    data=data%>%mutate(datasize=ifelse(datasize==2000000,"2MB",as.character(datasize)))
+    data=data%>%mutate(datasize=ifelse(datasize==10000000,"10MB",as.character(datasize)))
+    data=data%>%mutate(datasize=ifelse(datasize==50000000,"50MB",as.character(datasize)))
+    data=data%>%mutate(datasize=ifelse(datasize==100000000,"100MB",as.character(datasize)))
+    data=data%>%mutate(datasize=ifelse(datasize==500000000,"500MB",as.character(datasize)))
+    data=data%>%mutate(datasize=ifelse(datasize==1000000000,"1GB",as.character(datasize)))
+    data$datasize=factor(data$datasize,levels=c("1KB","10KB","100KB","500KB","1MB","2MB","10MB","50MB","100MB","500MB","1GB"))
+    return(data)
+}
+
+g_legend <- function(a.gplot){ 
+    tmp <- ggplot_gtable(ggplot_build(a.gplot)) 
+    leg <- which(sapply(tmp$grobs, function(x) x$name) == "guide-box") 
+    legend <- tmp$grobs[[leg]] 
+    legend
+}
+
+custom_theme=function(){theme_clean()+ theme(plot.background=element_blank())}
+
+data=data%>%dformat()
+
+# Compute delivery success
+statsSuccess=data%>%filter(isSender!=0)%>%group_by(wireless,wakeupfor,datasize,seed,simkey)%>%summarize(success=mean(nSend))%>%ungroup()
+data=data%>%left_join(statsSuccess,by=c("wireless","wakeupfor","datasize","seed","simkey"))
+
+# Computer stats senders
+statsSender=data%>%filter(isSender!=0)%>%group_by(wireless,wakeupfor,datasize,seed,simkey)%>%summarize(success=mean(success),energy=mean(energy))%>%ungroup()
+statsSender=statsSender%>%group_by(wireless,wakeupfor,datasize,simkey)%>%summarize(success_sd=sd(success),success=mean(success),energy_sd=sd(energy),energy=mean(energy))%>%ungroup()
+
+# Computer stats receiver
+statsReceiver=data%>%filter(isSender==0)%>%group_by(wireless,wakeupfor,datasize,seed,simkey)%>%summarize(success=mean(success),energy=mean(energy))%>%ungroup()
+statsReceiver=statsReceiver%>%group_by(wireless,wakeupfor,datasize,simkey)%>%summarize(success_sd=sd(success),success=mean(success),energy_sd=sd(energy),energy=mean(energy))%>%ungroup()
+
+
+# Energy 
+sender60sPlotEnergy=ggplot(statsSender%>%filter(wakeupfor==60)%>%dsformat(),aes(datasize,energy,color=simkey,group=simkey))+
+    geom_ribbon(aes(ymin=energy-energy_sd, ymax=energy+energy_sd,fill=simkey),linetype=1,alpha=0.4)+
+    geom_point()+geom_line()+
+    facet_wrap(~wireless)+xlab("Data size")+ylab("Energy consumption (J)")+labs(colour="Policy")+custom_theme()+theme(legend.position="top")+ggtitle("Sender")+
+    guides(colour=FALSE,fill=guide_legend(title="Policy"))
+
+sender180sPlotEnergy=ggplot(statsSender%>%filter(wakeupfor==180)%>%dsformat(),aes(datasize,energy,color=simkey,group=simkey))+
+    geom_ribbon(aes(ymin=energy-energy_sd, ymax=energy+energy_sd,fill=simkey),linetype=1,alpha=0.4)+
+    geom_point()+geom_line()+
+    facet_wrap(~wireless)+xlab("Data size")+ylab("Energy consumption (J)")+labs(colour="Policy")+custom_theme()+theme(legend.position="top")+ggtitle("Sender")+
+    guides(colour=FALSE,fill=guide_legend(title="Policy"))
+
+
+receiver60sPlotEnergy=ggplot(statsReceiver%>%filter(wakeupfor==60)%>%dsformat(),aes(datasize,energy,color=simkey,group=simkey))+
+    geom_ribbon(aes(ymin=energy-energy_sd, ymax=energy+energy_sd,,fill=simkey),linetype=1,alpha=0.4)+
+    geom_point()+geom_line()+
+    facet_wrap(~wireless)+xlab("Data size")+ylab("Energy consumption (J)")+labs(colour="Policy") +  custom_theme()+theme(legend.position="top")+ggtitle("Receiver")+
+    guides(colour=FALSE,fill=guide_legend(title="Policy"))
+
+receiver180sPlotEnergy=ggplot(statsReceiver%>%filter(wakeupfor==180)%>%dsformat(),aes(datasize,energy,color=simkey,group=simkey))+
+    geom_ribbon(aes(ymin=energy-energy_sd, ymax=energy+energy_sd,fill=simkey),linetype=1,alpha=0.4)+
+    geom_point()+geom_line()+
+    facet_wrap(~wireless)+xlab("Data size")+ylab("Energy consumption (J)")+labs(colour="Policy")+custom_theme()+theme(legend.position="top")+ggtitle("Receiver")+
+    guides(colour=FALSE,fill=guide_legend(title="Policy"))
+
+# Success
+sender60sPlotSuccess=ggplot(statsSender%>%filter(wakeupfor==60)%>%dsformat(),aes(datasize,success,color=simkey,group=simkey))+
+    geom_ribbon(aes(ymin=success-success_sd, ymax=success+success_sd,fill=simkey),linetype=1,alpha=0.4)+
+    geom_point()+geom_line()+
+    facet_wrap(~wireless)+xlab("Data size")+ylab("Number of delivery success")+labs(colour="Policy")+custom_theme()+theme(legend.position="top")+
+    theme(panel.background = element_rect(fill = '#EFEFEF', color=NA))+guides(colour=FALSE,fill=guide_legend(title="Policy"))
+
+sender180sPlotSuccess=ggplot(statsSender%>%filter(wakeupfor==180)%>%dsformat(),aes(datasize,success,color=simkey,group=simkey))+
+    geom_ribbon(aes(ymin=success-success_sd, ymax=success+success_sd,fill=simkey),linetype=1,alpha=0.4)+
+    geom_point()+geom_line()+
+    facet_wrap(~wireless)+xlab("Data size")+ylab("Number of delivery success")+labs(colour="Policy")+custom_theme()+theme(legend.position="top")+
+    theme(panel.background = element_rect(fill = '#EFEFEF', color=NA))+guides(colour=FALSE,fill=guide_legend(title="Policy"))
+
+
+receiver60sPlotSuccess=ggplot(statsReceiver%>%filter(wakeupfor==60)%>%dsformat(),aes(datasize,success,color=simkey,group=simkey))+
+    geom_ribbon(aes(ymin=success-success_sd, ymax=success+success_sd,fill=simkey),linetype=1,alpha=0.4)+
+    geom_point()+geom_line()+
+    facet_wrap(~wireless)+xlab("Data size")+ylab("Number of delivery success")+labs(colour="Policy") +  custom_theme()+theme(legend.position="top")+
+    theme(panel.background = element_rect(fill = '#EFEFEF', color=NA))+guides(colour=FALSE,fill=guide_legend(title="Policy"))
+
+receiver180sPlotSuccess=ggplot(statsReceiver%>%filter(wakeupfor==180)%>%dsformat(),aes(datasize,success,color=simkey,group=simkey))+
+    geom_ribbon(aes(ymin=success-success_sd, ymax=success+success_sd,fill=simkey),linetype=1,alpha=0.4)+
+    geom_point()+geom_line()+
+    facet_wrap(~wireless)+xlab("Data size")+ylab("Number of delivery success")+labs(colour="Policy")+custom_theme()+theme(legend.position="top")+
+    theme(panel.background = element_rect(fill = '#EFEFEF', color=NA))+guides(colour=FALSE,fill=guide_legend(title="Policy"))
+
+
+
+w1=10
+h1=4
+w2=15
+h2=4
+ggsave("scalability_datasize_60s_sender_energy.pdf",plot=sender60sPlotEnergy+guides(fill = FALSE, color = FALSE),width=w1,height=h1)
+ggsave("scalability_datasize_60s_receiver_energy.pdf",plot=receiver60sPlotEnergy+guides(fill = FALSE, color = FALSE),width=w1,height=h1)
+ggsave("scalability_datasize_60s_success.pdf",plot=sender60sPlotSuccess,width=w2,height=h2)
+
+ggsave("scalability_datasize_180s_sender_energy.pdf",plot=sender180sPlotEnergy+guides(fill = FALSE, color = FALSE),width=w1,height=h1)
+ggsave("scalability_datasize_180s_receiver_energy.pdf",plot=receiver180sPlotEnergy+guides(fill = FALSE, color = FALSE),width=w1,height=h1)
+ggsave("scalability_datasize_180s_success.pdf",plot=sender180sPlotSuccess,width=w2,height=h2)
+

results/paper_datasize.sh

@@ -0,0 +1,140 @@
+#!/usr/bin/env bash
+
+set -e
+
+wai=$(dirname $(readlink -f "$0"))
+scenarios="${wai}/../scenarios"
+inputs="${wai}/../inputs.json"
+simulator="make -C ${wai}/../ run"
+sched="${wai}/scheduler/analysis.sh"
+parser="${wai}/../parser.awk"
+results="${wai}/results_datasize.csv"
+aheaders="simkey,wireless,wakeupfor,n_nodes,datasize"
+avalues="none,none,none,none"
+log_file="${wai}/logs/$(date +%s).org" && mkdir -p "${wai}/logs/"
+gen_log=0 # Should we generate logs ?
+
+run-simulation () {
+    # Generate inputs
+    $scenarios $seed $simtime $wakeupevery $wakeupfor $n_nodes $extended $hint $poff $pon $prx $ptx $datasize $bitrate $hintsize $latency $shutdown_on_rcv $unschedule_on_rcv $farhint $hintdist > "$inputs"
+
+    # Init logs
+    [ $gen_log -eq 1 ] && echo -e "* seed=$seed simtime=$simtime wakeupevery=$wakeupevery wakeupfor=$wakeupfor n_nodes=$n_nodes extended=$extended hint=$hint poff=$poff pon=$pon prx=$prx ptx=$ptx datasize=$datasize bitrate=$bitrate \n" >> "${log_file}"
+
+    # Run simulations
+    tmp=$(mktemp)
+    $simulator &> $tmp
+    [ $gen_log -eq 1 ] && cp $tmp "${log_file}"
+
+    # Gen csv
+    [ ! -e "$results" ] && { cat $tmp | $parser | sed "1 s/$/,${aheaders}/g" | sed "2,\$s/$/,${avalues}/" > "$results"; }
+    [ -e "$results"  ] && { cat $tmp | $parser | sed 1d | sed "s/$/,${avalues}/" >> "$results"; }
+
+    # Gen scheduler analysis
+    #[ $seed -eq 1 ] && $sched $tmp "logs/$(echo ${avalues}|tr ',' '_')_hint${hint}_extended${extended}.png"
+
+    # Clear tmp
+    rm $tmp
+}
+
+# Default Parameters
+seed=0
+simtime=86400 # One day
+wakeupevery=3600
+wakeupfor=60
+n_nodes=13 # First node will be the sender so n_receivers=n_nodes-1
+extended="false"
+hint="false"
+poff=0
+pon=0.4
+prx=0.16
+ptx=0.16
+datasize=1000000 # 1Mb
+hintsize=8 # Integer
+hintdist=10800 # Hint distance while using farhint
+latency=0 # in Seconds
+shutdown_on_rcv="false"
+unschedule_on_rcv="false"
+farhint="false"
+bitrate="100kbps"
+
+
+run-scenarios() {
+    # Configure number of seed per scenarios
+    nseed=200
+
+    # Baseline
+    avalues="baseline,$wireless,$wakeupfor,$n_nodes,$datasize"
+    for seed in $(seq 1 $nseed)
+    do
+        printf "\rBaseline...${seed}"
+        run-simulation
+    done
+    echo 
+
+    # Hint
+    hint="true"
+    avalues="hint,$wireless,$wakeupfor,$n_nodes,$datasize"
+    for seed in $(seq 1 $nseed)
+    do
+        printf "\rHint...${seed}"
+        run-simulation
+    done
+    hint="false"
+    echo 
+
+    # Extended
+    extended="true"
+    avalues="extended,$wireless,$wakeupfor,$n_nodes,$datasize"
+    for seed in $(seq 1 $nseed)
+    do
+        printf "\rExtended...${seed}"
+        run-simulation
+    done
+    extended="false"
+    echo 
+
+    # Hint+Extended
+    extended="true"
+    hint="true"
+    avalues="hintandextended,$wireless,$wakeupfor,$n_nodes,$datasize"
+    for seed in $(seq 1 $nseed)
+    do
+        printf "\rHint + Extended...${seed}"
+        run-simulation
+    done
+    extended="false"
+    hint="false"
+    echo
+}
+
+# Clean previous runs
+[ -e "${results}" ] && rm "${results}"
+
+for wakeupfor in 60 180
+do
+
+	# Datasize:     1KB  10KB  100KB  500KB  1MB     2MB     10MB     50MB     100MB     500MB     1GB
+    for datasize in 1000 10000 100000 500000 1000000 2000000 10000000 50000000 100000000 500000000 1000000000
+    do
+        # Lora
+        echo "----- Run Lora (wakeupfor=$wakeupfor datasize=$datasize) -----"
+        wireless="lora"
+        bitrate="50kbps"
+        pon=0.4
+        prx=0.16
+        ptx=0.16
+        latency=0
+        run-scenarios
+
+        # NbIot
+        echo "----- Run NbIoT (wakeupfor=$wakeupfor datasize=$datasize) -----"
+        wireless="nbiot"
+        bitrate="200kbps"
+        pon=0.4
+        prx=0.65
+        ptx=0.65
+        latency=0
+        run-scenarios
+    done
+done

results/pareto.R

@@ -93,14 +93,26 @@ pareto = pareto %>% mutate(success = as.numeric(success))
 pareto = pareto %>% arrange(energy,success)
 pareto = pareto %>% dformat()
 
-ggplot(stats%>%dformat(),aes(energy,success,color=simkey,shape=strategy))+
+##### Policies
+ggplot(stats%>%dformat(),aes(energy,success,color=simkey,shape=simkey))+
     geom_line(data=pareto,aes(energy,success),linetype="dashed", size=1,inherit.aes=FALSE)+
-    geom_point(alpha=0.1,size=4)+
+    geom_point(size=4)+
     geom_point(data=pareto,size=4)+scale_y_reverse()+
-    labs(color="Policies:",shape="Strategies:")+scale_color_brewer(palette = "Spectral")+theme_minimal()+theme(text=element_text(size=20), legend.position=c(.8,.75),legend.box.background = element_rect(color="black", size=1, fill="white"))+
+    labs(color="Policies:",shape="Policies:")+scale_color_brewer(palette = "Set1")+theme_minimal()+theme(text=element_text(size=20), legend.position=c(.8,.75),legend.box.background = element_rect(color="black", size=1, fill="white"))+scale_shape_manual(values = c(17,18,20,3,4))+
     xlab("Sender energy consumption (J)")+ylab(TeX(r'(#Succ$_p$)'))
 #    +facet_wrap(~wakeupfor+wireless,scale="free")
-ggsave("pareto.pdf",width=10,height=9)
+ggsave("pareto_policies.pdf",width=10,height=9)
+
+##### Strategies
+ggplot(stats%>%dformat(),aes(energy,success,color=strategy,shape=strategy))+
+    geom_line(data=pareto,aes(energy,success),linetype="dashed", size=1,inherit.aes=FALSE)+
+    geom_point(size=4)+
+    geom_point(data=pareto,size=4)+scale_y_reverse()+
+    labs(color="Strategies:",shape="Strategies:")+scale_color_brewer(palette = "Dark2")+theme_minimal()+theme(text=element_text(size=20), legend.position=c(.8,.75),legend.box.background = element_rect(color="black", size=1, fill="white"))+scale_shape_manual(values = c(17,18,20,3,4))+
+    xlab("Sender energy consumption (J)")+ylab(TeX(r'(#Succ$_p$)'))
+#    +facet_wrap(~wakeupfor+wireless,scale="free")
+ggsave("pareto_strategies.pdf",width=10,height=9)
+
 
 message("Pareto infos:")
 print(pareto%>%group_by(simkey)%>%summarize(count=n()))