SocialCCNSim

Description

SocialCCNSim is a discrete-event trace executor of a CCN network.

Features

Simulator of a network of caches
Support SONETOR[0] traces
Supported Caching Strategies:
- ProbCache [8]
- Cache 'Less For More' [7]
- Leave Copy Everywhere [6]
- Leave Copy Down
- MAGIC[5]
- Rand Copy One
- Most Popular Caching (MPC) [3]
- Leave Copy on the Edge
Supported replacement policies:
- Last Recently Used (LRU)
- First-In First-Out (FIFO)
Supported Social Network topologies:
- Facebook
- LastFM
- Every networkx graph can be used as topology, by placing it on the graphs folder.
Supported Network Topologies:
- Abilene
- GEANT
- DTELECOM
- Tiger
- Tree
- Diamond
- Every networkx graph can be used as topology, by placing it on the graphs folder.
Implementation of Cache Hit, Stretch, Diversity and Cache Evictions metrics[1]
Supports mobility of the users
Plugins for new caching strategies
Plugins for every new replacement policy

Installation

Typical Ubuntu installation:

> apt-get install python-networkx python-scipy python-numpy python-pyparsing
> git clone git://github.com/panisson/pymobility.git
> cd pymobility
> python setup.py install (run as admin/root)
> cd ..

Using virtualenv:

> virtualenv .
> source bin/activate
> easy_install networkx
> easy_install numpy
> easy_install scipy
> easy_install pyparsing
> easy_install pymobility
> git clone https://github.com/mesarpe/socialccnsim.git
> cd socialccnsim

Dependencies

Networkx, scipy, numpy, pylru[2]

Examples

Execute the trace test_trace in a CCN network with abilene as topology and Leave Copy Everywhere (LCE) as caching strategy. LRU is used as replacement policy, Links acquaintances among simulated users is represented with a graph of a Facebook social network.

> python -O socialccnsim.py -c 2 -s lce -u facebook -t abilene -p lru -f exampletrace/verysmall

Frequently Asked Questions

Q. How do I change the cache size per node?

A. Set the first parameter (i.e. 2 in the example) to the desired cache size per node.

Q. How do I change the popularity properties of the trace?

A. Socialccnsim executes synthetic traces. If you want to create traces with special properties (special parameters), you are encouraged to give it a visit to SONETOR [https://github.com/mesarpe/sonetor]. SONETOR is a synthetic traces generator. With SONETOR, traces can be generated and then executed into Socialccnsim.

Contributing

If you have a Github account please fork the repository, create a topic branch, and commit your changes. Then submit a pull request from that branch.

License

References

[0] Cesar Bernardini, Thomas Silverston, Olivier Festor. SONETOR: a Social Network Traffic Generator. IEEE ICC 2014.

[1] Cesar Bernardini, Thomas Silverston, Olivier Festor.

[2] https://github.com/jlhutch/pylru

[3] Cesar Bernardini, Thomas Silverston, Olivier Festor. MPC: Popularity-based Caching Strategy for Content Centric Networks. IEEE ICC 2013

[4] Cesar Bernardini, Thomas Silverston, Olivier Festor. Socially-Aware Caching Strategy for Content Centric Networking. IFIP NETWORKING 2014

[5] Ren, Jing, et al. MAGIC: A distributed MAx-Gain In-network Caching strategy in information-centric networks. IEEE INFOCOM NOM WORKSHOP 2014.

[6] Zhang, B., Alexander Afanasyev, Jeffrey Burke, Van Jacobson, Patrick Crowley, Christos Papadopoulos, Lan Wang, and Beichuan Zhang. Named Data Networking. (2010).

[7] Chai, Wei Koong, et al. "Cache “less for more” in information-centric networks." NETWORKING 2012. Springer Berlin Heidelberg, 2012. 27-40.

[8] Psaras, Ioannis, Wei Koong Chai, and George Pavlou. "Probabilistic in-network caching for information-centric networks." Proceedings of the second edition of the ICN workshop on Information-centric networking. ACM, 2012.

mesarpe / socialccnsim

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