ccnSim: An highly scalable CCN simulator

Abstract

Abstract-Research interest about Information Centric Networking (ICN) has grown at a very fast pace over the last few years, especially after the 2009 seminal paper of Van Jacobson et al. describing a Content Centric Network (CCN) architecture. While significant research effort has been produced in terms of architectures, algorithms, and models, the scientific community currently lacks common tools and scenarios to allow a fair crosscomparison among the different proposals.The situation is particularly complex as the commonly used general-purpose simulators cannot cope with the expected system scale: thus, many proposals are currently evaluated over small and unrealistic scale, especially in terms of dominant factors like catalog and cache sizes. As such, there is need of a scalable tool under 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 for the analysis of caching performance of CCN network. In this paper, we briefly describe the tool, and present an extensive benchmark of its performance. To give an idea of ccnSim scalability, a common off-the-shelf PC equipped with 8GB of RAM memory is able to simulate 2-hours of a 50-nodes CCN network, where each nodes is equipped with 10 GB caches, serving a 1 PB catalog in about 20 min CPU time.

Trace-Driven Analysis of ICN Caching Algorithms on Video-on-Demand Workloads

“…ICN evaluation: There are many ICN evaluation platforms such as ndnSIM [10], ccnSim [20], DEC [5], and Mini-CCNx [15]. Unfortunately, our experiences showed that these cannot handle the scale of the workload and the topology we study in this paper.…”

“…There are several ICN simulation platforms currently in use including CCNx [1], ccnSim [20], DCE [5], mini-CCNx [15], and ndnSIM [10]. ndnSIM is generally considered to be the most scalable ICN platform; e.g., as reported by Afsanyev [10] et al, CCNx, ccnSim, DCE, and mini-CCNx can only support ICN simulations with a few hundred routers, and cannot be used for our large-scale evaluation with 80,000+ routers.…”

A novel architecture of CCN for better security and applicability

“…CCN/NDN has many simulators designed which could run a simulation environment for the basic CCN architecture. CCnx [32] , ndnSIM [33] , ccnSim [34] and OMNet++ [35] are the most common examples of CCN simulators. Most of these simulators are open source and is written in C++.…”

“…The FIB consists of the forwarding entries for the interfaces connected to the node and based on these FIB entries the interest is send to the next node. The forwarding strategies are based on the many forwarding architectures like multipath forwarding or shortest path forwarding or the random forwarding [34] . So, the interest moves on towards the producer until it finds the content either in the CS of the nodes or in the content producer.…”

A Markov chain-based Approximation of CCN caching Systems

“…In order to evaluate the accuracy of our proposal, we compared the analytical model presented in the previous section with the results of simulations under ccnSim [12], which is a discrete-event and a chunk-level simulator for CCN networks. The accuracy of MACS, compared to the simulation results, can be affected by many parameters.…”