Prerequisites

Download, configure, compile, and install NS-3 and ndnSIM. For more information refer to http://ndnsim.net

Example steps to install NS-3 and ndnSIM in optimized mode (without logging, but with all compiler optimizations):

# switch to some folder outside this repository. For example, to ~/Downloads
cd ~/Downloads/

mkdir ndnSIM
cd ndnSIM
git clone git://github.com/cawka/ns-3-dev-ndnSIM.git ns-3
(cd ns-3; git checkout -b ndnSIM-0.4.3 origin/ndnSIM-0.4.3)
git clone git://github.com/cawka/pybindgen.git pybindgen
git clone git://github.com/NDN-Routing/ndnSIM.git ns-3/src/ndnSIM
(cd ns-3/src/ndnSIM; git checkout -b v0.4.3 v0.4.3)

cd ns-3
./waf configure -d optimized
./waf

# install to /usr/local
sudo ./waf install

For more information how to install NS-3 and ndnSIM, please refer to http://ndnsim.net website.

Compiling

(switch back to this repository)

./waf configure

or (configure in debug mode with logging enabled)

./waf configure --debug

If you have installed NS-3 in a non-standard location, you may need to set up PKG_CONFIG_PATH variable. For example, if NS-3 is installed in /usr/local/, then the following command should be used to configure scenario

PKG_CONFIG_PATH=/usr/local/lib/pkgconfig ./waf configure

or

PKG_CONFIG_PATH=/usr/local/lib/pkgconfig ./waf configure --debug

Running

Normally, you can run scenarios either directly

./build/<scenario_name>

or using waf

./waf --run <scenario_name>

If NS-3 is installed in a non-standard location, on some platforms (e.g., Linux) you need to specify LD_LIBRARY_PATH variable:

LD_LIBRARY_PATH=/usr/local/lib ./build/<scenario_name>

or

LD_LIBRARY_PATH=/usr/local/lib ./waf --run <scenario_name>

When running using ./waf, it is possible to run scenario with visualizer:

./waf --run <scenario_name> --vis

Available simulations

For more detail refer to L. Wang, A. Afanasyev, R. Kuntz, R. Vuyyuru, R. Wakikawa, and L. Zhang, "Rapid Traffic Information Dissemination Using Named Data," in Proceedings of the 1st ACM workshop on Emerging Name-Oriented Mobile Networking Design - Architecture, Algorithms, and Applications (NoM 12), Hilton Head Island, South Carolina, June 2012, pp. 7–12. (http://dx.doi.org/10.1145/2248361.2248365, http://lasr.cs.ucla.edu/afanasyev/data/files/Wang/nom.pdf)

Data propagation over time (Figure 3)

Simulation scenario:

scenarios/car-relay.cc

To automatically run 10 runs of simulations with different parameters for the figure and build a graph for the simulation:

./waf
./run.py -s figure-3-data-propagation-vs-time

To rebuild the graph without rerunning the simulation:

./run.py figure-3-data-propagation-vs-time

User ./run.py -h for other options.

Note that provided scripts rely on R (http://www.r-project.org/) with proto, ggplot2, and doBy modules to be installed. For example, after you install R, run the following to install necessary modules:

sudo R
install.packages ('proto')
install.packages ('ggplot2')
install.packages ('doBy')

Data propagation speed vs distance between cars (Figure 4)

Simulation scenario:

scenarios/car-relay.cc

To automatically run 10 runs of simulations with different parameters for the figure:

./waf
./run.py -s figure-4-data-propagation-vs-distance

To rebuild the graph without rerunning the simulation:

./run.py figure-4-data-propagation-vs-distance

Count of data transmissions (Figure 5)

Simulation scenario:

scenarios/car-relay.cc

To automatically run 10 runs of simulations with different parameters for the figure:

./waf
./run.py -s figure-5-retx-count

To rebuild the graph without rerunning the simulation:

./run.py figure-5-retx-count