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tor_multipath_voip
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Better logs + other stuff

This commit is contained in:
Quentin 2020-01-23 10:48:36 +01:00
parent 451fb9cdd6
commit 7f9e044b6c
9 changed files with 250 additions and 112 deletions
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4
Dockerfile
View File

@ -20,13 +20,13 @@ WORKDIR /home/donar-build
RUN chown -R 1000 /home/donar-build
USER 1000
RUN git clone --single-branch --branch patch/relay_2 https://gitlab.inria.fr/qdufour/wide-tor.git tor2 && \
RUN git clone --single-branch --branch patch/relay_2 https://gitlab.inria.fr/qdufour/wide-tor.git tor2 && \
cd ./tor2 && \
./autogen.sh && \
./configure --disable-asciidoc || cat config.log && \
make -j`nproc`
RUN git clone --single-branch --branch master https://gitlab.inria.fr/qdufour/wide-tor.git tor3 && \
RUN git clone --single-branch --branch master https://gitlab.inria.fr/qdufour/wide-tor.git tor3 && \
cd ./tor3 && \
./autogen.sh && \
./configure --disable-asciidoc && \

326
r/config_light.R
View File

@ -4,33 +4,45 @@ library(plyr)
library(dplyr)
library(cowplot)
scale_fill_bw_qdu_6 <- scale_fill_manual(values = c("#000000", "#333333", "#666666", "#999999", "#cccccc", "#ffffff"))
scale_fill_bw_qdu_4 <- scale_fill_manual(values = c("#000000", "#555555", "#aaaaaa", "#ffffff"))
d <- read.csv("../../donar-res/tmp_light/window3.csv")
d <- d %>% mutate (window = window / 1000)
d$strat <- as.factor(d$strat)
d$window <- as.factor(d$window)
#d$decile <- factor(d$decile, levels = c("MIN", "D0.1", "D1", "D25", "D50", "D75", "D99", "D99.9"))
d$percentile <-factor(d$percentile,levels=c("MAX", "P99.9", "P99", "P75", "P50", "P25", "P1", "P0.1", "MIN"))
d$strat <- revalue(d$strat, c("1"="T", "0"="D"))
d$strat <- revalue(d$strat, c("1"="TickTock", "0"="Duplicate"))
d <- d %>% mutate (lat = latency / 1000)
gd <- ggplot(sqldf("select * from d where percentile != 'MAX' and percentile != 'P1' and percentile != 'P0.1'") %>% arrange(percentile), aes(x=strat:window,y=lat,group=percentile,fill=percentile)) +
geom_bar(stat='identity', position='identity') +
dwin <- sqldf("select * from d where percentile != 'MAX' and percentile != 'P1' and percentile != 'P0.1'") %>% arrange(percentile)
gd <- ggplot(dwin, aes(x=window,y=lat,group=percentile,fill=percentile)) +
geom_bar(stat='identity', position='identity', color="black", width=1) +
scale_fill_grey() +
ylab("Latency (ms)") +
xlab("Strategy:Window (sec)") +
xlab("Window (sec)") +
labs(fill="Percentile") +
scale_x_discrete(expand = c(0, 0)) +
scale_y_continuous(expand = c(0, 0)) +
coord_cartesian(ylim=c(0,600)) +
geom_hline(yintercept = 200) +
geom_hline(yintercept = 400) +
theme_classic()
geom_hline(yintercept = 160, linetype="dashed", color="white") +
annotate("text", x=4, y=160, label = "QoS: OWD best", vjust = -1, color="white") +
geom_hline(yintercept = 360) +
annotate("text", x=4, y=360, label = "QoS: OWD limit", vjust = -1,color="black") +
theme_classic() +
theme(legend.position="none") +
facet_grid( . ~ strat)
e <- read.csv("../../donar-res/tmp_light/links3.csv")
e$strat <- as.factor(e$strat)
e$links <- as.factor(e$links)
e$strat <- revalue(e$strat, c("1"="T", "0"="D"))
e$strat <- revalue(e$strat, c("1"="TickTock", "0"="Duplicate"))
e$percentile <-factor(e$percentile,levels=c("MAX", "P99.9", "P99", "P75", "P50", "P25", "P1", "P0.1", "MIN"))
e <- e %>% mutate (lat = latency / 1000)
elinks <- sqldf("select * from e where percentile != 'MAX' and percentile != 'P1' and percentile != 'P0.1' and links != 6 and links != 4") %>% arrange(percentile)
ge <- ggplot(sqldf("select * from e where percentile != 'MAX' and percentile != 'P1' and percentile != 'P0.1' and links != 6 and links != 4") %>% arrange(percentile), aes(x=strat:links,y=lat,group=percentile,fill=percentile)) +
geom_bar(stat='identity', position='identity') +
geom_bar(stat='identity', position='identity', width=1, color="black") +
scale_fill_grey() +
ylab("Latency (ms)") +
xlab("Strategy:Links") +
@ -42,11 +54,12 @@ ge <- ggplot(sqldf("select * from e where percentile != 'MAX' and percentile !=
f <- read.csv("../../donar-res/tmp_light/fast3.csv")
f$strat <- as.factor(f$strat)
f$strat <- revalue(f$strat, c("1"="T", "0"="D"))
f$strat <- revalue(f$strat, c("1"="TickTock", "0"="Duplicate"))
f$fast_count <- as.factor(f$fast_count)
f$percentile <-factor(f$percentile,levels=c("MAX", "P99.9", "P99", "P75", "P50", "P25", "P1", "P0.1", "MIN"))
f <- f %>% mutate (lat = latency / 1000)
gf <- ggplot(sqldf("select * from f where percentile != 'MAX' and percentile != 'P1' and percentile != 'P0.1'") %>% arrange(percentile), aes(x=strat:fast_count,y=lat,group=percentile,fill=percentile)) +
ffast <- sqldf("select * from f where percentile != 'MAX' and percentile != 'P1' and percentile != 'P0.1'") %>% arrange(percentile)
gf <- ggplot(ffast, aes(x=strat:fast_count,y=lat,group=percentile,fill=percentile)) +
geom_bar(stat='identity', position='identity') +
scale_fill_grey() +
geom_hline(yintercept = 200) +
@ -57,84 +70,166 @@ gf <- ggplot(sqldf("select * from f where percentile != 'MAX' and percentile !=
labs(fill="Percentile") +
theme_classic()
plot_grid(gd, ge, gf, ncol=1) + ggsave("light_config.pdf", dpi=300, dev='pdf', height=17, width=15, units="cm")
plot_grid(gd, gdbis, ge, ge, gf, gf, ncol=3) +
ggsave("light_config.pdf", dpi=300, dev='pdf', height=17, width=15, units="cm")
mega <- sqldf("
select window as variable, lat, strat, percentile, 'Window (sec)' as variable_name from dwin
union
select links as variable, lat, strat, percentile, '# of total links' as variable_name from elinks
union
select fast_count as variable, lat, strat, percentile, '# of fast links' as variable_name from ffast
") %>% arrange(percentile)
mega$percentile <- revalue(mega$percentile, c("P99.9" = "99.9%", "P99" = "99%", "P75"="75%", "P50" = "50%", "P25" = "25%", "MIN" = "Min"))
mega$variable <- factor(mega$variable, levels =c("0.2", "1", "2", "3", "4", "5", "6", "8", "10", "12", "13", "14", "16", "20", "34"))
QoS <- data.frame(x = c(1.2, 1.5), name = c("bar", "foo"))
ggplot(mega, aes(x=variable,y=lat,group=percentile,fill=percentile)) +
geom_bar(stat='identity', position='identity', color="black", width=1) +
scale_fill_bw_qdu_6 +
ylab("Latency (ms)") +
xlab("Protocol Parameter Value") +
labs(fill="Distribution") +
scale_x_discrete(expand = c(0, 0)) +
scale_y_continuous(expand = c(0, 0)) +
coord_cartesian(ylim=c(0,600)) +
geom_hline(aes(yintercept = 110, linetype="Target One Way Delay"), color="grey") +
#annotate("text", x=4, y=160, label = "OWD best", vjust = 1.5, color="white") +
geom_hline(aes(yintercept = 360, linetype="Max One Way Delay"), color="grey") +
#annotate("text", x=4, y=360, label = "OWD limit", vjust = -1, color="black") +
theme_classic() +
theme(legend.position="top",
legend.direction = "horizontal",
legend.box = "vertical",
panel.spacing.y = unit(4, "mm"),
strip.placement = "outside",
legend.margin=margin(t = -0.1, unit='cm')) +
guides(fill = guide_legend(nrow = 1)) +
facet_grid(strat ~ variable_name, scales = "free", switch = "x") +
scale_linetype_manual(name = "QoS", values = c(1, 2), guide = guide_legend(override.aes = list(linetype = c("solid", "dashed")))) +
ggsave("light_config.pdf", dpi=300, dev='pdf', height=12.5, width=12.5, units="cm")
g <- read.csv("../../donar-res/tmp_light/guards.csv")
g$strat <- as.factor(g$strat)
g$strat <- revalue(g$strat, c("1"="T", "0"="D"))
g$strat <- revalue(g$strat, c("1"="TickTock", "0"="Duplicate"))
g$guard <- as.factor(g$guard)
g$percentile <- revalue(g$percentile, c("MAX" = "100%", "P99.9"="99.9%", "P99"="99%", "P75" = "75%", "P50"="50%","P25"="25%","P1"="1%","P0.1"="0.1%","MIN"="Min"))
g$guard <- revalue(g$guard, c("guard_1"="1", "guard_3"="3", "guard_5"="5", "guard_7"="7", "guard_9"="9", "guard_11"="11", "simple"="inf"))
g$guard <- factor(g$guard, levels=c("1", "3", "5", "7", "9", "11", "inf"))
g$percentile <-factor(g$percentile,levels=c("MAX", "P99.9", "P99", "P75", "P50", "P25", "P1", "P0.1", "MIN"))
g$percentile <-factor(g$percentile,levels=c("100%", "99.9%", "99%", "75%", "50%", "25%", "1%", "0.1%", "Min"))
g <- g %>% mutate (lat = latency / 1000)
gg <- ggplot(sqldf("select * from g where percentile != 'MAX' and percentile != 'P1' and percentile != 'P0.1' ") %>% arrange(percentile), aes(x=strat:guard,y=lat,group=percentile,fill=percentile)) +
geom_bar(stat='identity', position='identity') +
scale_fill_grey() +
geom_hline(yintercept = 200) +
geom_hline(yintercept = 400) +
gg <- ggplot(sqldf("select * from g where percentile != '100%' and percentile != '1%' and percentile != '0.1%' ") %>% arrange(percentile), aes(x=guard,y=lat,group=percentile,fill=percentile)) +
geom_bar(stat='identity', position='identity', width=1, color="black") +
scale_fill_bw_qdu_6 +
scale_x_discrete(expand = c(0, 0)) +
scale_y_continuous(expand = c(0, 0)) +
coord_cartesian(ylim=c(0,600)) +
ylab("Latency (ms)") +
xlab("Strategy:Guards") +
labs(fill="Percentile") +
theme_classic()
xlab("# of guards") +
labs(fill="Distribution") +
scale_linetype_manual(name = "QoS", values = c(1, 2), guide = guide_legend(override.aes = list(linetype = c("solid", "dashed")))) +
geom_hline(aes(yintercept = 110, linetype="Target One Way Delay"), color="grey") +
geom_hline(aes(yintercept = 360, linetype="Max One Way Delay"), color="grey") +
facet_grid(. ~ strat, scales = "free", switch = "x") +
theme_classic() +
guides(fill = guide_legend(nrow = 1)) +
theme(strip.placement = "outside",
legend.position="top",
legend.direction = "horizontal",
legend.box = "vertical",
legend.margin=margin(t = -0.2, l=-0.8, unit='cm'))
gg + ggsave("light_guards.png", dpi=300, dev='png', height=7, width=15, units="cm")
gg + ggsave("light_guards.pdf", dpi=300, dev='pdf', height=7.5, width=12.5, units="cm")
h <- read.csv("../../donar-res/tmp_light/complem.csv")
h$strat <- revalue(h$strat, c("ticktock"="T", "duplicate"="D"))
h$percentile <-factor(h$percentile,levels=c("MAX", "P99.9", "P99", "P75", "P50", "P25", "P1", "P0.1", "MIN"))
h$strat <- revalue(h$strat, c("ticktock"="TickTock", "duplicate"="Duplicate"))
h$percentile <- revalue(h$percentile, c("MAX" = "100%", "P99.9"="99.9%", "P99"="99%", "P75" = "75%", "P50"="50%","P25"="25%","P1"="1%","P0.1"="0.1%","MIN"="Min"))
h$percentile <-factor(h$percentile,levels=c("100%", "99.9%", "99%", "75%", "50%", "25%", "1%", "0.1%", "Min"))
h$mode <- factor(h$mode, levels=c("no_redundancy", "no_scheduler", "donar"))
h$mode <- revalue(h$mode, c("no_redundancy" = "scheduler", "no_scheduler" = "padding", "donar"="both"))
h <- h %>% mutate (lat = latency / 1000)
gh <- ggplot(sqldf("select * from h where percentile != 'MAX' and percentile != 'P1' and percentile != 'P0.1' ") %>% arrange(percentile), aes(x=strat:mode,y=lat,group=percentile,fill=percentile)) +
geom_bar(stat='identity', position='identity') +
scale_fill_grey() +
geom_hline(yintercept = 200) +
geom_hline(yintercept = 400) +
gh <- ggplot(sqldf("select * from h where percentile != '100%' and percentile != '1%' and percentile != '0.1%' ") %>% arrange(percentile), aes(x=mode,y=lat,group=percentile,fill=percentile)) +
geom_bar(stat='identity', position='identity', width=1, color="black") +
scale_fill_bw_qdu_6 +
scale_x_discrete(expand = c(0, 0)) +
scale_y_continuous(expand = c(0, 0)) +
scale_linetype_manual(name = "QoS", values = c(1, 2), guide = guide_legend(override.aes = list(linetype = c("solid", "dashed")))) +
geom_hline(aes(yintercept = 110, linetype="Target One Way Delay"), color="grey") +
geom_hline(aes(yintercept = 360, linetype="Max One Way Delay"), color="grey") +
coord_cartesian(ylim=c(0,500)) +
ylab("Latency (ms)") +
xlab("Strategy:Feature") +
labs(fill="Percentile") +
theme_classic()
gh + ggsave("light_complementary.png", dpi=300, dev='png', height=7, width=15, units="cm")
xlab("Feature") +
labs(fill="Distribution") +
facet_grid(. ~ strat, scales = "free", switch = "x") +
theme_classic() +
guides(fill = guide_legend(nrow = 1)) +
theme(strip.placement = "outside",
legend.position="top",
legend.direction = "horizontal",
legend.box = "vertical",
legend.margin=margin(t = -0.2, l=-0.8, unit='cm'))
gh + ggsave("light_complementary.pdf", dpi=300, dev='pdf', height=7.5, width=12.5, units="cm")
i <- read.csv("../../donar-res/tmp_light/battle.csv")
i$percentile <- revalue(i$percentile, c("MAX" = "100%", "P99.9"="99.9%", "P99"="99%", "P75" = "75%", "P50"="50%","P25"="25%","P1"="1%","P0.1"="0.1%","MIN"="0%"))
i$percentile <-factor(i$percentile,levels=c("100%", "99.9%", "99%", "75%", "50%", "25%", "1%", "0.1%", "0%"))
i$percentile <- revalue(i$percentile, c("MAX" = "100%", "P99.9"="99.9%", "P99"="99%", "P75" = "75%", "P50"="50%","P25"="25%","P1"="1%","P0.1"="0.1%","MIN"="Min"))
i$percentile <-factor(i$percentile,levels=c("100%", "99.9%", "99%", "75%", "50%", "25%", "1%", "0.1%", "Min"))
i <- i %>% mutate (lat = latency / 1000)
i$secmode <- factor(i$secmode, levels=c("hardened", "default", "light"))
i$algo <- factor(i$algo, levels=c("simple", "dup2", "lightning-ticktock", "lightning-dup"))
i$algo <- revalue(i$algo, c("dup2"="torfone", "simple"="simple", "lightning-ticktock"="donar-ticktock", "lightning-dup"="donar-dup"))
gi <- ggplot(sqldf("select * from i where percentile != '100%' and percentile != '1%' and percentile != '0.1%' and secmode = 'default' ") %>% arrange(percentile), aes(x=algo,y=lat,group=percentile,fill=percentile)) +
geom_bar(stat='identity', position='identity',width=1) +
#scale_fill_grey() +
gi <- ggplot(sqldf("select * from i where percentile != '100%' and percentile != '1%' and percentile != '0.1%' ") %>% arrange(percentile), aes(x=algo,y=lat,group=percentile,fill=percentile)) +
geom_bar(stat='identity', position='identity',width=1,color="black") +
scale_fill_bw_qdu_6 +
scale_y_continuous(expand = c(0, 0)) +
scale_x_discrete(expand = c(0, 0)) +
scale_fill_viridis_d() +
geom_hline(yintercept = 200) +
geom_hline(yintercept = 400) +
#scale_fill_viridis_d() +
geom_hline(aes(yintercept = 110, linetype="Target One Way Delay"), color="grey") +
geom_hline(aes(yintercept = 360, linetype="Max One Way Delay"), color="grey") +
coord_cartesian(ylim=c(0,600)) +
ylab("Latency (ms)") +
xlab("Algorithm") +
labs(fill="Distribution") +#, title="linear scale, zoomed") +
labs(fill="Distribution", title="linear scale, cropped") +
theme_classic() +
theme(axis.text.x = element_text(angle = 10, hjust=1), plot.margin = unit(c(0.3,0.2,0.2,1), "cm"))
gibis <- ggplot(sqldf("select * from i where percentile != 'MAX' and percentile != 'P1' and percentile != 'P0.1' ") %>% arrange(percentile), aes(x=algo:secmode,y=lat,group=percentile,fill=percentile)) +
geom_bar(stat='identity', position='identity') +
scale_fill_grey() +
scale_y_log10() +
#geom_hline(yintercept = 200) +
#geom_hline(yintercept = 400) +
coord_cartesian(ylim=c(100,250000)) +
ylab("Latency (ms)") +
xlab("Algorithm:Security Profile") +
labs(fill="Percentile", title="log scale, full") +
theme_classic() +
theme(axis.text.x = element_text(angle = 20, hjust=1), plot.margin = unit(c(0.2,0.2,0.2,1), "cm"))
plot_grid(gibis, gi, ncol=1) + ggsave("light_battle.png", dpi=300, dev='png', height=12, width=15, units="cm")
scale_linetype_manual(name = "QoS", values = c(1, 2), guide = guide_legend(override.aes = list(linetype = c("solid", "dashed")))) +
guides(fill = guide_legend(nrow = 1)) +
facet_grid(. ~ secmode, scales = "free", switch = "x") +
theme(axis.text.x = element_text(angle = 20, hjust=1),
plot.margin = unit(c(0.3,0.2,0.2,1), "cm"),
strip.placement = "outside",
legend.position="none",
legend.direction = "horizontal",
legend.box = "vertical",
legend.margin=margin(t = -0.1, unit='cm'))
gi + ggsave("battle_color.pdf", dpi=300, dev='pdf', height=7, width=12, units='cm')
gibis <- ggplot(sqldf("select * from i where percentile != '100%' and percentile != '1%' and percentile != '0.1%' ") %>% arrange(percentile), aes(x=algo,y=lat,group=percentile,fill=percentile)) +
geom_bar(stat='identity', position='identity', color="black", width=1) +
scale_fill_bw_qdu_6 +
scale_y_log10() +
#geom_hline(aes(yintercept = 160, linetype="Target One Way Delay"), color="grey") +
#geom_hline(aes(yintercept = 360, linetype="Max One Way Delay"), color="grey") +
scale_x_discrete(expand = c(0, 0)) +
coord_cartesian(ylim=c(30,250000)) +
ylab("Latency (ms)") +
xlab("Algorithm") +
labs(fill="Distribution", title="log scale, full") +
facet_grid(. ~ secmode, scales = "free", switch = "x") +
theme_classic() +
theme(legend.position="none",
axis.text.x = element_text(angle = 20, hjust=1),
plot.margin = unit(c(0.2,0.2,0.2,1), "cm"),
strip.placement = "outside")
gilegend <- get_legend(gi + theme(legend.position = "top"))
plot_grid(gilegend, plot_grid(gibis, gi, align="v", ncol=1), ncol=1, rel_heights = c(1,6)) +
ggsave("light_battle.pdf", dpi=300, dev='pdf', height=15, width=12.5, units="cm")
#gi + ggsave("battle_color.pdf", dpi=300, dev='pdf', height=7, width=12, units='cm')
fastprobe = read.csv(text=
"
@ -159,78 +254,119 @@ gj <- ggplot(fastprobe, aes(x=group:pad, y=count, fill=strat)) +
theme(axis.text.x = element_text(angle = 20, hjust=1))
gj + ggsave("light_fastprobe.png", dpi=300, dev='png', height=7, width=15, units="cm")
fastprobe2 = read.csv(text="
strat,schedule_state,packet_position,ratio
Ticktock,tick,original on 1st class,0.946975638
Ticktock,tick,piggybacked on 2nd class,0.053025421
Ticktock,tock,original on 2nd class,0.474113253
Ticktock,tock,piggybacked on 1st class,0.525885688
Duplicate,all,original on 1st class,0.7349205324574037
Duplicate,all,piggybacked on 1st class,0.13431755481879454
Duplicate,all,original on 2nd class,0.1154165656941915
Duplicate,all,piggybacked on 2nd class,0.015345347029610245
")
fastprobe2$schedule_state <-factor(fastprobe2$schedule_state,levels=c("all", "tock", "tick"))
ggplot(fastprobe2, aes(x=schedule_state, y=ratio, fill=packet_position)) +
geom_bar(stat='identity', position='stack', width=1, color="black") +
facet_grid(strat ~ ., scales = "free", switch = "x") +
scale_y_continuous(expand = c(0, 0), labels = scales::percent) +
scale_x_discrete(expand = c(0, 0)) +
scale_fill_bw_qdu_4 +
xlab("Schedule State") +
ylab("Fastest Delivery") +
labs(fill="Scheduling Decision") +
coord_flip() +
theme_classic() +
ggsave("light_fastprobe.pdf", dpi=300, dev='pdf', height=5, width=12.5, units="cm")
fastlinks = read.csv(text=
"
link_count,occ_count,strat
5,0,ticktock
9,0.20634920634920634,ticktock
8,0.25396825396825395,ticktock
7,0.1111111111111111,ticktock
6,0.1746031746031746,ticktock
10,0.1746031746031746,ticktock
11,0.07936507936507936,ticktock
12,0,ticktock
9,0.19047619047619047,duplicate
8,0.14285714285714285,duplicate
10,0.20634920634920634,duplicate
7,0.09523809523809523,duplicate
6,0.09523809523809523,duplicate
11,0.14285714285714285,duplicate
5,0.015873015873015872,duplicate
12,0.1111111111111111,duplicate
5,0,Ticktock
9,0.20634920634920634,Ticktock
8,0.25396825396825395,Ticktock
7,0.1111111111111111,Ticktock
6,0.1746031746031746,Ticktock
10,0.1746031746031746,Ticktock
11,0.07936507936507936,Ticktock
12,0,Ticktock
9,0.19047619047619047,Duplicate
8,0.14285714285714285,Duplicate
10,0.20634920634920634,Duplicate
7,0.09523809523809523,Duplicate
6,0.09523809523809523,Duplicate
11,0.14285714285714285,Duplicate
5,0.015873015873015872,Duplicate
12,0.1111111111111111,Duplicate
")
gk <- ggplot(fastlinks, aes(x=link_count, y=occ_count, fill=strat)) +
geom_bar(stat='identity', position='dodge') +
geom_bar(stat='identity', position='dodge', color="black") +
scale_fill_grey() +
ylab("Runs") +
ylab("Calls") +
xlab("Links fast at least once") +
labs(fill="Strategy") +
scale_y_continuous(labels = scales::percent) +
scale_y_continuous(expand = c(0, 0), labels = scales::percent) +
scale_x_continuous(expand = c(0, 0)) +
theme_classic()
#theme(axis.text.x = element_text(angle = 20, hjust=1))
gk + ggsave("light_fastlinks.png", dpi=300, dev='png', height=7, width=15, units="cm")
gk + ggsave("light_fastlinks.pdf", dpi=300, dev='pdf', height=6, width=12.5, units="cm")
l <- read.csv("../../donar-res/tmp_light/basic.csv")
l <- l %>% mutate (lat = latency / 1000)
gl <- ggplot(sqldf("select * from l where way='client'"), aes(x=packet_id,y=lat)) +
coord_cartesian(ylim=c(0,500)) +
geom_hline(yintercept = 200) +
geom_hline(yintercept = 400) +
scale_y_continuous(expand = c(0, 0)) +
scale_x_continuous(expand = c(0, 0)) +
xlab("Packet Identifier") +
ylab("Latency (ms)") +
labs(linetype="Way") +
geom_point() +
theme_classic()
gl + ggsave("light_single.png", dpi=300, dev='png', height=7, width=15, units="cm")
geom_point(size=0.1) +
geom_hline(aes(yintercept = 110, linetype="Target One Way Delay"), color="white") +
geom_hline(aes(yintercept = 360, linetype="Max One Way Delay"), color="grey") +
scale_linetype_manual(name = "QoS", values = c(1, 2), guide = guide_legend(override.aes = list(linetype = c("solid", "dashed")))) +
theme_classic() +
theme(legend.position="top",legend.margin=margin(t = -0.1, b = -0.1, unit='cm'))
#gl + ggsave("light_single.png", dpi=300, dev='png', height=7, width=15, units="cm")
m <- read.csv("../../donar-res/tmp_light/fp.csv")
m <- m %>% mutate (lat = latency / 1000)
m$group <- revalue(m$group, c("fast" = "1st class links", "probe" = "2nd class links"))
gm <- ggplot(sqldf("select * from m where `way`='client'"), aes(x=packet_id,y=lat,color=group)) +
scale_color_grey() +
coord_cartesian(ylim=c(0,500)) +
geom_hline(yintercept = 200) +
geom_hline(yintercept = 400) +
scale_y_continuous(expand = c(0, 0)) +
scale_x_continuous(expand = c(0, 0)) +
xlab("Packet Identifier") +
ylab("Latency (ms)") +
labs(color="Group") +
labs(color="Link Group") +
labs(linetype="Way") +
geom_point() +
theme_classic()
geom_point(size=0.1) +
geom_hline(yintercept = 110, linetype="dashed", color="white") +
geom_hline(yintercept = 360, linetype="solid", color="grey") +
guides(color = guide_legend(override.aes = list(size=2))) +
theme_classic() +
theme(legend.position="top", legend.margin=margin(t = -0.1, b = -0.1, unit='cm'))
n <- read.csv("../../donar-res/tmp_light/linkgroup.csv")
n$group <- revalue(n$group, c("fast" = "fast link", "probe" = "other link"))
n$group <- revalue(n$group, c("fast" = "1st class links", "probe" = "2nd class links"))
#n$link_id <- as.factor(n$link_id)
gn <- ggplot(n, aes(x=packet_id, y=link_id, color=group)) +
scale_color_grey() +
scale_fill_grey() +
geom_point(size=0.6) +
scale_y_continuous(expand = c(0.1, 0.1)) +
scale_x_continuous(expand = c(0, 0)) +
#scale_color_viridis_d() +
xlab("Packet Identifier") +
ylab("Link Identifier") +
labs(color="Group") +
geom_point() +
theme_classic()
labs(color="Link group") +
#geom_tile() +
theme_classic() +
theme(legend.position="none")
plot_grid(gl, gm, gn, ncol=1) + ggsave("light_single.png", dpi=300, dev='png', height=17, width=15, units="cm")
plot_grid(gl, gm, gn, ncol=1,align="v",rel_heights = c(1.3,1.3,1)) + ggsave("light_single.pdf", dpi=300, dev='pdf', height=12.5, width=12.5, units="cm")
gn+ggsave("links_group.pdf", dpi=300, dev='pdf', height=7, width=15, units="cm")

8
src/donar_client.c
View File

@ -71,7 +71,7 @@ void init_socks5_sinks(struct donar_client_ctx* app_ctx) {
int donar_client_stream_repair(struct evt_core_ctx* ctx, struct evt_core_fdinfo* fdinfo) {
// @FIXME: Ugly way to get donar_client_ctx. Shame on me :/
fprintf(stdout, "[donar-client] %s broke\n", fdinfo->url);
fprintf(stdout, "[%s][donar-client] %s broke\n", current_human_datetime (), fdinfo->url);
struct evt_core_cat* cat = evt_core_get_from_cat (ctx, "socks5-failed");
if (cat == NULL) {
fprintf(stderr, "Unable to reconnect stream as socks5-failed cat is not available...\n");
@ -99,14 +99,14 @@ int donar_client_stream_repair(struct evt_core_ctx* ctx, struct evt_core_fdinfo*
}
if (removed == 2) {
fprintf(stdout, "[donar-client] Retriggering socks5 for port %d\n", port);
fprintf(stdout, "[%s][donar-client] Retriggering socks5 for port %d\n", current_human_datetime (), port);
init_socks5_client (app_ctx, pos);
return 0;
} else if (removed == 0) {
fprintf(stdout, "[donar-client] Socks5 has already been retriggered for port %d\n", port);
fprintf(stdout, "[%s][donar-client] Socks5 has already been retriggered for port %d\n", current_human_datetime (), port);
return 0;
} else {
fprintf(stderr, "[donar-client] We only removed 1 link and not 2 for port %d, strange behaviour, exiting...\n", port);
fprintf(stderr, "[%s][donar-client] We only removed 1 link and not 2 for port %d, strange behaviour, exiting...\n", current_human_datetime (), port);
exit(EXIT_FAILURE);
}
}

2
src/donar_server.c
View File

@ -53,7 +53,7 @@ socket_create_err:
struct tor_ctl* ugly_global_tctl;
int donar_server_stream_repair(struct evt_core_ctx* ctx, struct evt_core_fdinfo* fd) {
fprintf(stderr, "I am a server, I do nothing with broken streams...\n");
fprintf(stderr, "[%s][donar-server] I am a server, I do nothing with broken streams...\n", current_human_datetime ());
tor_ctl_list_onions(ugly_global_tctl);
return 1;
}

5
src/measure.c
View File

@ -12,9 +12,6 @@ void measure_parse(int size, struct measure_conf* mc) {
perror("clock_gettime error");
exit(EXIT_FAILURE);
}
time_t now;
time(&now);
char* ctime_no_newline = strtok(ctime(&now), "\n");
micro_sec = elapsed_micros (&head->emit_time, &curr);
uint8_t is_slow = head->flag >> 7;
@ -22,7 +19,7 @@ void measure_parse(int size, struct measure_conf* mc) {
uint8_t link_id = head->flag & 0x3f;
printf(
"[%s] Packet %llu latency %luµs with flag %d sent on link %d with vanilla %d\n",
ctime_no_newline,
current_human_datetime(),
(unsigned long long)head->counter,
micro_sec,
is_slow,

7
src/utils.c
View File

@ -147,3 +147,10 @@ void timespec_set_unit(struct timespec *t, uint64_t value, enum time_units unit)
uint64_t timespec_get_unit(struct timespec *t, enum time_units unit) {
return t->tv_sec * (SEC / unit) + t->tv_nsec / unit;
}
char* current_human_datetime() {
time_t now;
time(&now);
char* ctime_no_newline = strtok(ctime(&now), "\n");
return ctime_no_newline;
}

2
src/utils.h
View File

@ -44,3 +44,5 @@ uint8_t timespec_lt(struct timespec *t1, struct timespec *t2);
void timespec_diff(struct timespec *end, struct timespec *begin, struct timespec *result);
void timespec_set_unit(struct timespec *t, uint64_t value, enum time_units unit);
uint64_t timespec_get_unit(struct timespec *t, enum time_units unit);
char* current_human_datetime();

2
torrc_guard_2
View File

@ -3,4 +3,4 @@ UseEntryGuards 1
NumEntryGuards 2
NumPrimaryGuards 2
SafeLogging 0
#Log INFO stdout
#Log DEBUG stdout

6
torrc_simple
View File

@ -1,9 +1,5 @@
ControlPort 9051
UseEntryGuards 0
SafeLogging 0
IsolateDestPort 1
#IsolateDestPort 1
#Log INFO stdout