N-FIB: Scalable, memory efficient name-based forwarding

Abstract

Named Data Networking (NDN) is a promising future Internet which retrieves the content using their names. Content names composed of strings separated by ‘/’ are stored in the NDN Forwarding Information Base (FIB) to forward the incoming packets further. Though NDN has several benefits over traditional IP-based Internet, storing names instead of IP addresses has two major bottlenecks. While it consumes significantly large memory, it incurs higher search and update time. Another issue is the fast growth of routing table size through which FIB will not fit in existing routers’ line-card memory. Moreover, frequent updates to the FIB can degrade the packet delivery performance. In this paper, we propose a scalable and memory efficient Patricia trie based name forwarding scheme (called, N-FIB) for FIB. N-FIB supports FIB aggregation to significantly minimize the impact of large FIB size and high FIB update cost. Extensive experiment results show that the N-FIB scheme can reduce memory consumption by 68.18% compared to the BP scheme for 29 million named dataset. Moreover, N-FIB is reducing routers’ computation and memory overhead, while supporting strong forwarding correctness.