tor_multipath_voip/r/config_light.R

library(ggplot2)
library(sqldf)
library(plyr)
library(dplyr)
library(cowplot)

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 <- 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') +
  scale_fill_grey() +
  ylab("Latency (ms)") +
  xlab("Strategy:Window (sec)") +
  labs(fill="Percentile") +
  coord_cartesian(ylim=c(0,600)) +
  geom_hline(yintercept = 200) +
  geom_hline(yintercept = 400) +
  theme_classic()

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$percentile <-factor(e$percentile,levels=c("MAX", "P99.9", "P99", "P75", "P50", "P25", "P1", "P0.1", "MIN"))
e <- e %>% mutate (lat = latency / 1000)
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') +
  scale_fill_grey() +
  ylab("Latency (ms)") +
  xlab("Strategy:Links") +
  labs(fill="Percentile") +
  geom_hline(yintercept = 200) +
  geom_hline(yintercept = 400) +
  coord_cartesian(ylim=c(0,600)) +
  theme_classic()

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$fast_count <- as.factor(f$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 != 'D1' and percentile != 'D0.1'") %>% arrange(percentile), aes(x=strat:fast_count,y=lat,group=percentile,fill=percentile)) +
  geom_bar(stat='identity', position='identity') +
  scale_fill_grey() +
  geom_hline(yintercept = 200) +
  geom_hline(yintercept = 400) +
  coord_cartesian(ylim=c(0,600)) +
  ylab("Latency (ms)") +
  xlab("Strategy:Fast Links") +
  labs(fill="Percentile") +
  theme_classic()

plot_grid(gd, ge, gf, ncol=1) + ggsave("light_config.png", dpi=300, dev='png', height=17, width=15, 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$guard <- as.factor(g$guard)
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 <- 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) +
  coord_cartesian(ylim=c(0,600)) +
  ylab("Latency (ms)") +
  xlab("Strategy:Guards") +
  theme_classic()

gg + ggsave("light_guards.png", dpi=300, dev='png', height=7, width=15, units="cm")