1 files changed, 0 insertions, 93 deletions
diff --git a/doc/design-paper/node-selection/vary-network-load.R b/doc/design-paper/node-selection/vary-network-load.R
deleted file mode 100644
index e2b96dd01f..0000000000
--- a/doc/design-paper/node-selection/vary-network-load.R
+++ /dev/null
@@ -1,93 +0,0 @@
-## The waiting time for a node (assuming no overloaded nodes)
-## x: 1/bandwidth
-## q: selection probability
-## L: network load
-wait <- function(x,q,L) {
-  a <- q*L*x*x
-  b <- 2*(1-q*x*L)
-  return (x + a/b)
-}
-
-## The weighted wait time
-wwait <- function(x,q,L) {
-  return (q*wait(x,q,L))
-}
-
-## Average latency, returning NA for infinite
-netLatency <- function(x, q, L) {
-  if (any(x*q*L <0 | x*q*L >1)) {
-    return (NA)
-  } else {
-    return (sum(wwait(x, q, L)))
-  }
-}
-
-## Load in data files
-t1 <- read.table("opt_1e-6.pickle.dat", header=TRUE)
-t2 <- read.table("opt_1e-3.pickle.dat", header=TRUE)
-t3 <- read.table("opt_1e-1.pickle.dat", header=TRUE)
-t4 <- read.table("opt_0.75.pickle.dat", header=TRUE)
-t5 <- read.table("opt_0.5.pickle.dat", header=TRUE)
-t6 <- read.table("opt_0.25.pickle.dat", header=TRUE)
-t7 <- read.table("opt_0.1.pickle.dat", header=TRUE)
-tt <- read.table("opt_tor.pickle.dat", header=TRUE)
-
-## Node bandwidth and reciprocal
-bw <- t1$bw
-x <- 1/bw
-
-## Calculate network capcity
-capacity <- sum(bw)
-
-## Calculate selection probabilties that Tor uses
-torProb <- bw/sum(bw)
-
-## Load values to try
-varyLoad <- seq(0.01,0.93,0.01)
-latencyTor <- c()
-latency3 <- c()
-latency4 <- c()
-latency5 <- c()
-for (L in varyLoad) {
-  latencyTor <- append(latencyTor,
-                       netLatency(x, torProb, capacity*L))
-  latency3   <- append(latency3,
-                       netLatency(x, t3$prob, capacity*L))
-  latency4   <- append(latency4,
-                       netLatency(x, t4$prob, capacity*L))
-  latency5   <- append(latency5,
-                       netLatency(x, t5$prob, capacity*L))
-}
-
-## Output graph
-pdf("vary-network-load.pdf")
-
-## Set up axes
-yFac <- 1000
-xFac <- 100
-
-ylim <- range(na.omit(c(latencyTor, latency3, latency4, latency5)))
-ylim <- c(0,0.015) * yFac
-xlim <- c(0,1) * xFac
-plot(NA, NA,
-     xlim=xlim, ylim=ylim,
-     frame.plot=FALSE,
-     xlab = "Network load (%)",
-     ylab = "Average queuing delay (ms)",
-     main = "Latency for varying network loads")
-
-## Plot data
-col <- rainbow(8)
-lines(varyLoad*xFac, latency3*yFac, col=col[3])
-lines(varyLoad*xFac, latency4*yFac, col=col[4])
-lines(varyLoad*xFac, latency5*yFac, col=col[5])
-lines(varyLoad*xFac, latencyTor*yFac)
-
-## Plot points at which selection probabilities are optimal
-par(xpd=TRUE)
-points(c(0.9, 0.75, 0.5, 1)*xFac, rep(par("usr")[3], 4),
-       col=c(col[3:5], "black"), pch=20,
-       cex=2)
-
-## Close output device
-dev.off()