Hash Bloom Filter and Data Forwarding Method for Name Lookup in NDN

Abstract

The invention discloses a Hash Bloom filter and a data forwarding method for name search in NDN. The Hash Bloom filter consists of g counter Bloom filters and g counters located in the on-chip memory It consists of g hash tables located in the off-chip memory; each of the hash tables is associated with 1 counter Bloom filter and 1 counter; the hash Bloom filter is selected by the secondary hash method The complete information of the FIB / CS / PIT entries in the NDN router is uniformly distributed and stored in g counter Bloom filters and g hash tables. The HBF of the present invention utilizes the positioning and filtering functions of the CBF in the on-chip memory to greatly reduce the access overhead of the off-chip memory, thereby reducing the overall access cost of the HBF, increasing the forwarding rate of data packets, and effectively avoiding flood attacks at the same time.

Description

technical field [0001] The invention relates to the field of big data processing in the fields of distributed systems, networks, etc., in particular to a hashbloom filter and a data forwarding method for name lookup in NDN. Background technique [0002] With the transformation of the Internet application mode, the Internet based on the TCP / IP system structure has also exposed several problems. At the beginning of the Internet design, it was to solve the interconnection problem of network devices to realize the sharing of hardware resources. However, with the development of Internet of Things, mobile Internet, cloud computing and other technologies, the main body of network applications has changed to text information, images and videos, and content services have become Become the main body of network services. The TCP / IP architecture designed according to the end-to-end principle has increasingly prominent problems in routing scalability, dynamics, manageability, security, ...

AI Technical Summary

Problems solved by technology

However, because BF can only remember whether an element belongs to a certain set, it cannot remember the detailed information of the element, such as the PIT timestamp and other information, so it cannot effectively process the expired entries in the PIT

Images