Scalable name identifier lookup for Industrial Internet

Abstract

Name identifiers are considered more effective than IP addresses in routing and forwarding billions of heterogeneous resource-restrained Industrial Internet objects. Although the design of name-based longest prefix matching lookup has been developed for nearly a decade, it is still attractive to design an efficient name lookup scheme for the Industrial Internet due to hierarchical variable-length names, large-scale forwarding tables, and frequent updates. In this paper, we present a memory-optimized binary search (MOBS) algorithm in the counting Bloom filter (CBF), which decreases memory consumption by reducing the storage of prefix marker entries while maintaining the fast lookup efficiency of binary search. Furthermore, we propose CBF-HT, an efficient and scalable name lookup method that combines counting Bloom filter and hash table to facilitate content forwarding. CBF-HT consists of two stages. Firstly, the longest prefix matching results are obtained through binary search in the counting Bloom filter with MOBS, and then the final lookup results are acquired by linear backtracking in the hash table. CBF-HT can achieve high-speed lookups and fast updates, and significantly reduces memory consumption caused by marker entries through MOBS. We have implemented and evaluated CBF-HT with 10 billion name identifiers. Experimental results show that, compared with the existing binary search on hash table algorithm (BS-HT), CBF-HT increases the forwarding throughput by 45%, eliminates 73% and 90% of memory consumption, and improves the update performance by 48.1%, at the cost of a 7.8% increase in the average number of memory accesses.