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https://github.com/TeamRossi/ccnSim-0.4-Parallel
This is the parallel, blazing fast, version of ccnSim-0.4!
https://github.com/TeamRossi/ccnSim-0.4-Parallel
Last synced: about 1 month ago
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This is the parallel, blazing fast, version of ccnSim-0.4!
- Host: GitHub
- URL: https://github.com/TeamRossi/ccnSim-0.4-Parallel
- Owner: TeamRossi
- Created: 2017-08-01T08:56:29.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2018-03-27T07:43:09.000Z (over 6 years ago)
- Last Synced: 2024-08-02T05:12:01.983Z (4 months ago)
- Language: C++
- Homepage: http://perso.telecom-paristech.fr/~drossi/index.php?n=Software.ccnSim
- Size: 3.04 MB
- Stars: 1
- Watchers: 4
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-blazingly-fast - ccnSim-0.4-Parallel - This is the parallel, blazing fast, version of ccnSim-0.4! (C++)
README
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# Welcome
Thank you for joining the ccnSim community!
This is ccnSim-0.4-Parallel, the new ccnSim version which implements in addition to:
* the classical Event Driven (ED) engine [1]
* the hybrid stochastic/Monte-Carlo simulation engine known as ModelGraft (MG) [2], that allow 100x gains with respect to ED
* a new parallel engine, known as CS-POST-MT [3] that allows gains of 100x with respect to MG, and thus 10000x with respect to ED!
## Where to start
Note that https://github.com/TeamRossi/ccnSim-0.4-Parallel only specifically deals with the parallel version of ccnSim, and assume users are already familiar with ccnSim (and hopefully with both ED and MG engines). It also assumes users to have at least quickly gone through the technical report describing the new parallel CS-POST-MT engine [3].
Readers interested in the single-threaded stable version of ccnSim-0.4 (ED or MG engines), should instead check https://github.com/TeamRossi/ccnSim-0.4 if need access to the source code, or directly use the docker container version https://hub.docker.com/r/nonsns/ccnsim-0.4/
For information about installation and sample scenarios, please follow the detailed instructions provided in this README.md (as well as in the the ccnSim-Parallel "User Manual", available in the Manual/ folder of this Git https://github.com/TeamRossi/ccnSim-0.4-Parallel/blob/master/Manual/Parallel_ModelGraft_Manual.pdf ) Please also read the documentation inside the provided "runsim_script_Parallel_ModelGraft.sh" script in order to have a clear understanding of the simulation process.
Finally, please note that simulations with ccnSim-0.4-Parallel require a patched version of the Akaroa2 software [4, 5]. While the patch is freely distributed in this Git, users should obtain a valid license in order to download Akaroa-2.7.13 (i.e.,
the version used for the development of ccnSim-0.4-Parallel) to which the patch can be applied. For info related to the various types of license please visit the Akaroa Project Website at [4].
Specifically, the files we had to modify to suit our purpose are the following
* src/engine/ak_observation.C
* src/include/observation.H
* src/engine/observation_handler.H
* src/engine/observation_analyzer.C
* src/engine/observation_analyzer.H
* src/engine/parameter_analyzer.C
* src/engine/parameter_analyzer.H
* src/engine/spectral/sa_variance_estimator.C
* src/engine/spectral/sa_variance_estimator.H
* src/include/checkpoint.H
* src/include/checkpoint.C
* src/ipc/connection.H
* src/akmaster/engine.H
* src/akmaster/engine_connection.C
* src/akmaster/engine.C
* src/akmaster/simulation.C
* src/akmaster/simulation.H
## References
A few references to the ED [1], ModelGraft [2] and Parallel (CS-POST-MT) [3] engines:
[1] Chiocchetti, Raffaele, Rossi, Dario and Rossini, Giuseppe,
"ccnSim: an Highly Scalable CCN Simulator"
In IEEE International Conference on Communications (ICC), June 2013.
[2] M. Tortelli, D. Rossi, E. Leonardi,
"A Hybrid Methodology for the Performance Evaluation of Internet-scale Cache Networks",
Elsevier Computer Networks, 2017, DOI: 10.1016/j.comnet.2017.04.006.
[3] Tortelli, Michele, Rossi, Dario and Leonardi, Emilio,
"Parallel Simulation of Very Large-Scale General Cache Networks"
http://www.enst.fr/~drossi/paper/rossi17parallel-cache.pdf, November 2017.
[4] Akaroa Project Website, https://akaroa.canterbury.ac.nz/akaroa/.
[5] G. Ewing, K. Pawlikowski, and D. McNickle. Akaroa-2: Exploiting network computing by distributingstochastic simulation. SCSI Press, 1999.
# Instruction to install ccnSim-Parallel
In this section we will cover all the steps needed for the installation of ccnSim-Parallel. We suggest the reader to check and execute them by following the presentation order.
## Portability
ccnSim-Parallel has been tested on the following platforms, and with the following softwares:
* Ubuntu Linux 14.04 (64-bit)
* Ubuntu Linux 16.04 Server (64-bit)
* Omnetpp-4.6
* Omnetpp-5.0
* Akaroa-2.7.13
## Prerequisites
* Boost libraries ≥ 1.54
They can be installed either by using the standard packet manager of your system (e.g., apt-get install, yum install, port install, etc.), or by downloading them from http://www.boost.org/users/download/, and following instructions therein.
* gcc > 4.8.1
On Ubuntu platforms, gcc can be updated by adding the ubuntu-toolchain-r/test PPA. Sample commands for the latest 5.x version are:
sudo add-apt-repository ppa:ubuntu-toolchain-r/test
sudo apt update
sudo apt install gcc-5 g++-5
sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-5 60 --slave /usr/bin/g++ g++ /usr/bin/g++-5
• parallel-ssh
In order to ease the simulation workflow, a passwordless SSH login needs to be present on all the available servers. parallel-ssh can than be used in order to send commands to slaves from the master node.
sudo apt-get install pssh
## Akaroa2
As mentioned above, Akaroa2 requires a specific license in order to be used. For instructions about software download and licenses, please visit the website https://akaroa.canterbury. ac.nz/akaroa/. ccnSim-Parallel has been developed starting from Akaroa-2.7.13. The whole set of modifications that have been made in order to implement the parallel ModelGraft strategy are grouped inside the Akaroa_2.7.13_for_PMG.patch.
Once obtained the original licensed Akaroa-2.7.13, place it in the same directory with the aforementioned patch, and type:
patch -s -p0 < Akaroa_2.7.13_for_PMG.patch
Notice that the original Akaroa directory will keep the same name even after the application of the patch.
Once the patch is applied, type the following commands from the root directory of the patched Akaroa in order to install it:
./configure
make
sudo make install
Akaroa binaries, libraries, and include files will be installed in /usr/local/akaroa/bin, /usr/local/akaroa/lib, and /usr/local/akaroa/include, respectively. If you do not have sudo privileges, and you need to install Akaroa into another location, e.g., , please add this location to your PATH variable, and use the following commands:
./configure --prefix=
make
make install
Furthermore, always in the case of lacking sudo privileges, users might need to modify LIB and PYTHON paths in the several “Makefile.config_*” files and inside the “pyconfig.py” file, according to the customized locations of related libraries, before compiling and installing Akaroa.
## Omnet++
ccnSim-Parallel has been tested with both Omnetpp-4.6 and Omnetpp-5.0, which are available at https://omnetpp.org/. Before the installation, Omnetpp-x requires prerequisite packages to be installed. For the complete list, please read the official installation manual. Furthermore, since Omnetpp-x bin/ directory needs to be added to the PATH variable, the following line should be put at the end of the /.bashrc file:
export PATH=$PATH:$HOME/omnetpp-x/bin
After having closed and saved the file, please close and re-open the terminal.
Regardless of the Omnetpp version, a couple of patch files need to be applied to it before compilation and installation. These patch files are provided with ccnSim-Parallel, which we suppose being located in $CCNSIM_DIR. Provided that Omnetpp is located in $OMNET_DIR, specific instructions to patch, compile, and install it without the graphical interface (not needed for parallel ModelGraft simulations) are provided in the following, according to the selected version:
* Omnetpp-4.6
pint:$ cd $CCNSIM_DIR
pint:CCNSIM_DIR$ cp ./patch/omnet4x/ctopology.h $OMNET_DIR/include/
pint:CCNSIM_DIR$ cp ./patch/omnet4x/ctopology.cc $OMNET_DIR/src/sim/
pint:CCNSIM_DIR$ cd $OMNET_DIR/
pint:OMNET_DIR$ NO_TCL=1 ./configure
pint:OMNET_DIR$ make

* Omnetpp-5.0
pint:$ cd $CCNSIM_DIR
pint:CCNSIM_DIR$ cp ./patch/omnet5x/ctopology.h $OMNET_DIR/include/omnetpp
pint:CCNSIM_DIR$ cp ./patch/omnet5x/ctopology.cc $OMNET_DIR/src/sim
pint:CCNSIM_DIR$ cd $OMNET_DIR/
pint:OMNET_DIR$ ./configure WITH_TKENV=no
pint:OMNET_DIR$ make
Compilation flags can also be set through the file configure.user (e.g., to disable Qtenv).
## ccnSim-Parallel
Installation requires the following commands from the $CCNSIM_DIR:
./scripts/makemake.sh
make
If all the steps described in the previous sections have been successfully executed, simulations of general cache networks using the parallel ModelGraft technique can now be launched.
# Using ccnSim-Parallel
We have provided plenty of scripts and example of usage. Please refer to the PDF Manual for details about the execution of sample scenarios! The PDF manual allow you to repeat experiments of the technical report [3] listed above
https://github.com/TeamRossi/ccnSim-0.4-Parallel/blob/master/ccnSim-0.4-Parallel-Manual.pdf