Data name searching method and system and storage medium

Abstract

The invention discloses a data name searching method and system and a storage medium, an additional step is added on the basis of an existing data name searching algorithm, when data name prefixes arestored in a hash table according to the number of components, the first n bits of each component in the data name prefixes are taken out to serve as feature prefixes of the data name prefixes, and the feature prefixes of the data name prefixes are stored in the hash table. And the feature prefixes of the same component sequence are counted together, and the feature prefixes are stored by using aBloom filter. When the target data name needs to be searched, the feature data name of the target data name is obtained according to the corresponding method, then the feature data name is put into the feature prefix Bloom filter of the corresponding component number to be matched, and if matching fails, the feature data name does not need to enter the hash table of the corresponding component number to be searched. According to the invention, data name search is completed quickly, and network delay is reduced.

Description

technical field [0001] The invention relates to the field of computer network transmission, in particular to a data name search method, system and storage medium. Background technique [0002] Different from the address-centric traditional IP network, NDN, as a new network architecture, shifts the focus of the network from data location to data content. That is to say, in the traditional IP network, users need to find the IP address of the content they want and find the server location where the content is located before they can get the content; while NDN only pays attention to the content that the user needs, and does not care where it comes from, which is more in line with the user's search habits. Therefore, the transmission of NDN is different from that of traditional IP networks. In IP search, only the 32-bit (IPv4) or 128-bit (IPv6) IP address "01" string needs to be searched, while the data name in NDN must be composed of It is much more complicated: firstly, each d...

AI Technical Summary

Problems solved by technology

However, this method does not take advantage of the characteristics of the prefix itself, but only stores the data name prefix according to the number of components, which does not have the effect of filtering the data name prefix at all, making the query efficiency not high

Especially in the scenario where there are many times of data name matching failures, the search efficiency of this method is low, because each search will go to the hash table with a component number of 1 and the search fails. The number of searches is large, resulting in an increase in the number of memory accesses and a large network delay

[0008] All in all, the existing method will generate a large number of hash search processes in each data name search process, which makes the number of memory accesses in the data name search process more and the search efficiency is low; there are a large number of hashes in the existing data name search method. Hash search process, and the time occupied by the hash search process accounts for a large proportion of the entire search process, making the delay in the network transmission process relatively high

Images