This is the simulator that was used to benchmark the performance of footprint scheduling, Pfitzmann's algorithm, and the Herbivore implementation of Chaum's map-reservation algorithm.
Run make to compile the simulator. This requires Java 7 (or newer).
After that, run ./simulation.sh to start the interactive simulator.
The folder scripts contains various benchmark scripts that run simulations automatically.
In order to execute a script (e.g. the script scripts/benchmarks/activity), enter
run scripts/benchmarks/activity
in the interactive simulator or execute
./simulation.sh scripts/benchmarks/activity
from the shell.
In order to save the results of a simulation, enter write in the interactive simulator once the
simulation is finished.
The results will be written to a .csv file in the folder benchmark-data. If this file is
already present, the new results will be appended to the existing data.
The plots in the paper can be reproduced with the provided R script process.R. This requires
the ggplot2 library. By default, all plots are commented out.
Browsing the predefined scripts gives a good overview of the available options for each simulation. Below is a quick guideline for running custom simulations:
For footprint scheduling:
footprint S B P A C
where
S is the number of slots that can be reserved
B is the number of bits per footprint
P is a list containing the number of participants in the simulated networks
A is the activity rate of all participants as a floating point value between 0 and 1
C is a boolean that determines whether the discussion should stop once the schedule converged.
Note that this is only possible in a simulation, not in a real-life scenario where
footprints are kept secret in general.
So, a simulation of footprint scheduling could look like this:
`footprint 16 8 [100 200 500 1000 2000 5000 10000] 0.01 false`
For Pfitzmann's algorithm:
pfitzmann i P A
where
i is the number of available slots per participant (as discussed in Appendix A)
P is a list containing the number of participants in the simulated networks
A is the activity rate of all participants as a floating point value between 0 and 1
So, a simulation of Pfitzmann's algorithm could look like this:
`pfitzmann 32 [100 200 500 1000 2000 5000 10000] 0.01`
For the Chaum's map reservations:
chaum P A
where
P is a list containing the number of participants in the simulated networks
A is the activity rate of all participants as a floating point value between 0 and 1
So, this is how a simulation of Chaum's reservation map could look like:
`chaum [100 200 500 1000 2000 5000 10000] 0.01`