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

• 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

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

Networkx, scipy, numpy, pylru[2]

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

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.

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.

Written by César Bernardini mesarpe@gmail.com
Copyright (C) 2014 César Bernardini. You can contact us by email (mesarpe@gmail.com).

[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.