# STA 247, Assignment 3 - program.


# Constants describing the disk.

n.tracks <- 20		# Number of tracks on the disk

read.time <- 5		# Time to read a track once the head is there (ms)
seek.time <- 2		# Time to move the head by one track (ms)


# Simulate the elevator or the closest-track scheme.  The arguments are as
# follows:
#
#    scheme       Either "elevator" or "closest"
#    n.accesses   Number of accesses to simulate (default 2000)
#    n.proc       Number of processes simulated (default 5)
#
# The value returned is a list with the following elements:
#
#    time         Total time taken for n.accesses accesses
#    track        Number of each track accessed
#    satisfied    Vector with the number of requests satisfied for each process
#    wait         Vector with the wait time for each satisfied request

simulate <- function (scheme, n.accesses=2000, n.proc=5)
{
  if (scheme!="elevator" && scheme!="closest")
  { stop("Scheme must be either \"elevator\" or \"closest\"")
  }

  # Initialize the variables that record what happens.
  
  time <- 0
  satisfied <- rep(0,n.proc)
  wait <- c()
  track <- rep(NA,n.accesses+1)

  # Set the probabilities of each process sticking to the current track.

  p.same <- (1:n.proc) / (n.proc+1)

  # Initialize the vector of tracks each process wants to access, and
  # a vector holding the time that each current request was first made.

  track.wanted <- sample (1:n.tracks, n.proc, replace=TRUE)
  request.time <- rep(0,n.proc)

  # Set up the initial state of the disk.

  track[1] <- sample(1:n.tracks,1)	# Head is positioned randomly to start
  if (scheme=="elevator")
  { dir <- sample(c(-1,+1),1)		# Set direction randomly
  }

  # Do the requested number of disk accesses.

  for (i in 1:(n.accesses-1))
  { 
    # The elevator scheme.

    if (scheme=="elevator")
    {
      # Move one more track in the same direction as before.

      track[i+1] <- track[i] + dir

      # Reverse direction if there's nothing to do in this direction.

      if (dir>0 && all(track.wanted<track[i+1]) 
       || dir<0 && all(track.wanted>track[i+1]))
      { dir <- -dir
      }

      # Find the closest track where data is wanted in the current direction.

      if (dir>0)
      { track[i+1] <- min(track.wanted[track.wanted>=track[i+1]])
      }
      else
      { track[i+1] <- max(track.wanted[track.wanted<=track[i+1]])
      }
    }

    # The closest track scheme.

    if (scheme=="closest")
    { 
      # Look for requests at increasing distances from the current track.

      for (j in 0:n.tracks)
      { if (j==n.tracks) stop("Something wrong!")
        if (any(abs(track.wanted-track[i])==j)) 
        { break;
        }
      }

      # If more than one track is the same distance away, choose randomly.

      if (sum(abs(track.wanted-track[i])==j)==1)
      { track[i+1] <- track.wanted[abs(track.wanted-track[i])==j]
      }
      else
      { track[i+1] <- sample(track.wanted[abs(track.wanted-track[i])==j],1)
      }
    }

    # Update time by the amount of time to seek and then read the track.

    time <- time + read.time + seek.time*abs(track[i+1]-track[i])

    # See which processes have had their request satisfied, and pick new
    # requests for them.

    for (j in 1:n.proc)
    { 
      if (track.wanted[j]==track[i+1])
      { 
        satisfied[j] <- satisfied[j]+1
        wait <- c (wait, time-request.time[j])
        request.time[j] <- time

        if (runif(1)>=p.same[j])
        { track.wanted[j] <- sample(1:n.tracks,1)
        }
      }
    }  
  }

  list (time=time, track=track, satisfied=satisfied, wait=wait)
}


# Do the stuff needed for the assignment.  The argument is the random 
# number seed to use.

do.stuff <- function (seed=1)
{
  set.seed(seed)
  cl.sim <<- simulate("closest")

  set.seed(seed)
  el.sim <<- simulate("elevator")
  
  postscript("ass3-plots.ps",paper="letter",horizontal=TRUE)

  plot(cl.sim$track[1:200],xlab="closest track scheme",ylab="track number")
  plot(el.sim$track[1:200],xlab="elevator scheme",ylab="track number")

  hist(cl.sim$wait,xlab="Wait times for closest track scheme",main="")
  hist(el.sim$wait,xlab="Wait times for elevator scheme",main="")

  cat("Rates of requests being satisfied:  elevator =",
      round(sum(el.sim$satisfied)/el.sim$time,3),
      ", closest track =",round(sum(cl.sim$satisfied)/cl.sim$time,3),"\n")
  cat("Average wait times:  elevator =",round(mean(el.sim$wait),3),
      ", closest track =",round(mean(cl.sim$wait),3),"\n")

  dev.off()
}