DiPIT: A Distributed Bloom-Filter Based PIT Table for CCN Nodes

Content-Centric Network is a novel Internet design that investigates the shifting of the Internet usage from browsing to content dissemination. This new Internet architecture proposal can bring many benefits and it has attracted many research works. When we study on these research, we found that one of the important components, the Pending Interest Table (PIT), did not get much attention. Since that in CCN the networking behaviours are no longer based on endpoints location but rather on every piece of the content itself, and the PIT is involved in both the forwarding processes upstream and downstream, in case of large amount of requests, the table size is a big issue, that leads to a large required memory space for implementing such a CCN node. In this paper, we propose a distributed PIT table, named DiPIT, where a part of the PIT is on every interface. Our approach relies on Bloom Filters in order to reduce the necessary memory space for implementing the PIT, completed with a central Bloom Filter for limiting the false positives, generated by the individual Bloom Filters. The evaluations we have performed highlight that our DiPIT approach can significantly reduce the memory space (up to 63%) in the CCN node and support a higher incoming packet throughput, compared to the hash table technology, which is largely implemented in current routers.