SocialCCNSim: A Simulator for Caching Strategies in Information-Centric Networking

After 2009, research interest about Information-Centric Networking (ICN), which is a new network model, has grown at a very rapid speed. Various architectures have been proposed for implementing this network model. A common feature to all architectures is the in-network caching, which has received enormous consideration by the research community. ICN is a popular network model that supports caching: the most viable feature of the Future Internet. Although considerable research effort has been produced in terms of models and architectures for the Future Internet, the scientific community currently lacks common tools to allow a fair cross-comparison among the different proposals, especially for the effective evaluation of the performance of caching systems. In fact, all available simulators are either designed for a particular architecture or unable to execute simulations within a reasonable time-frame and at the required criterion. To address these issues, in this paper we study the performance of SocialCCNSim, which is a Python-based simulator for ICN caching. This simulator provides support for evaluating caching strategies in Content-Centric Networking (CCN) architecture of ICN.