Reliably scalable name prefix lookup

Abstract

Name prefix lookup is a core building block of information-centric networking (ICN). In ICN hierarchical naming schemes, each packet has a name that consists of multiple variable-length name components, and packets are forwarded based on longest name prefix matching (LNPM). LNPM is challenging because names are longer than IP addresses and the namespace is unbounded. Recently proposed solutions have shown encouraging performance, however, most are optimized for or evaluated with a limited number of URL datasets that may not fully characterize the forwarding information base (FIB).What's more, the worst-case scenarios of several schemes require O(k) string lookups, where k is the number of components in each prefix. Thus, the sustained performance of existing solutions is not guaranteed. In this paper, we present a LNPM design based on the binary search of hash tables, which was originally proposed for IP lookup. With this design, the worst-case number of string lookups is O(log(k)) for prefixes with up to k components, regardless of the characteristics of the FIB. We implemented the design in software and demonstrated 10 Gbps throughput with one billion synthetic longest name prefix matching rules, each containing up to seven components. We also propose level pulling to optimize the average LNPM performance based on the observation that some prefixes have large numbers of next-level suffixes in the available URL datasets.