Most Information Centric Networking designs propose the usage of widely distributed in-network storage. However, the huge amount of content exchanged in the Internet, and the volatility of content replicas cached across the network pose significant challenges to the definition of a scalable routing protocol able to address all available copies. In addition, the number of available copies of a given content item and their distribution among caches is clearly impacted by the request forwarding policy.In this paper we gather initial design considerations for an ICN request forwarding strategy by spanning over two extremes: a deterministic exploitation of forwarding information towards a "known" copy and a random network exploration towards an "unknown" copy, via request flooding. By means of packet-level simulations, we investigate the performance trade-offs of exploitation/exploration approaches, and introduce an hybrid solution. Our forwarding scheme shows a good potential, whether carefully tuned, in terms of delivery performance, implicit cache coordination and possible reduction of forwarding table size.

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.

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