A New Bloom Filter Architecture for FIB Lookup in Named Data Networking

Abstract

Network traffic has increased rapidly in recent years, mainly associated with the massive growth of various applications on mobile devices. Named data networking (NDN) technology has been proposed as a future Internet architecture for effectively handling this ever-increasing network traffic. In order to realize the NDN, high-speed lookup algorithms for a forwarding information base (FIB) are crucial. This paper proposes a level-priority trie (LPT) and a 2-phase Bloom filter architecture implementing the LPT. The proposed Bloom filters are sufficiently small to be implemented with on-chip memories (less than 3 MB) for FIB tables with up to 100,000 name prefixes. Hence, the proposed structure enables high-speed FIB lookup. The performance evaluation result shows that FIB lookups for more than 99.99% of inputs are achieved without needing to access the database stored in an off-chip memory.

Addition of a Secondary Functional Bloom Filter

“…Let S F represent the event of a search failure for an FBF [4]. Let I and F P be indeterminable and false positive events, respectively.…”

“…Among querying set U , one third is the same as programming set A, and the remaining two thirds are included in set A c . A 64-bit CRC generator is used for obtaining Bloom filter indexes for programming and querying [4]. The total memory is set as 8nL (i.e., m = 8n), where n is the number of elements and L is the size of a cell.…”

“…The total memory is set as 8nL (i.e., m = 8n), where n is the number of elements and L is the size of a cell. In other words, the memory factor is set to 8, which is the most used case in many applications [4]. If the memory factor is too large such as 16, using the s-FBF has no effect because of almost no indeterminable from the p-FBF.…”

“…K ey-value data structures have been used in various applications, such as Facebook, Twitter, Google's BigTable, and Amazon's Dynamo [1]- [4]. As the most representative key-value data structure, a hash table stores both keys and their return values.…”

Vectored-Bloom Filter for IP Address Lookup: Algorithm and Hardware Architectures

“…A Bloom filter [17] is a multi-bit probabilistic data structure used for membership querying to determine whether an input is the element included in a given set. Bloom filters have been applied to many network applications due to their space-efficient attributes [18][19][20][21] and hardware-friendly features [22][23][24][25][26].…”