ccnSim: an Highly Scalable CCN Simulator

Research interest about Information Centric Networking (ICN) has grown at a very fast pace over the last fewyears, especially after the 2009 seminal paper of Van Jacobsonet al. describing a Content Centric Network (CCN) architecture.While significant research effort has been produced in terms ofarchitectures, algorithms, and models, the scientific communitycurrently lacks common tools and scenarios to allow a fair cross-comparison among the different proposals.The situation is particularly complex as the commonly usedgeneral-purpose simulators cannot cope with the expected systemscale: thus, many proposals are currently evaluated over smalland unrealistic scale, especially in terms of dominant factors likecatalog and cache sizes. As such, there is need of a scalable toolunder which different algorithms can be tested and compared.Over the last years, we have developed and optimized ccnSim,an highly scalable chunk-level simulator especially suitable forthe analysis of caching performance of CCN network. In thispaper, we briefly describe the tool, and present an extensivebenchmark of its performance. To give an idea of ccnSimscalability, a common off-the-shelf PC equipped with 8GB ofRAM memory is able to simulate 2-hours of a 50-nodes CCNnetwork, where each nodes is equipped with 10 GB caches,serving a 1 PB catalog in about 20 min CPU tim