Multi-modal network-oriented hybrid FIB storage structure and data processing method thereof

Abstract

The invention discloses a data processing method for a multi-modal network mixed type FIB storage structure, and the method comprises the following steps: performing parallel retrieval operation on name prefixes or IP addresses with different lengths in a memory according to an LPM index mechanism, and judging whether the name prefix or the IP address prefix of a data packet exists in an FIB of a mixed router or not, so as to obtain the forwarding information of the next-hop route or output a retrieval result of Not Matched. The hybrid router can process different modal data packets in a multi-modal network, and differentiated processing is performed on the data by judging whether the packet header of the data packet is name data or IP address data, so that forwarding information is finally indexed. In the invention, the hybrid index model for realizing the above functions forms a tower structure through a BP neural network, and then forms the hybrid index model. Rapid retrieval of forwarding information is realized through the hybrid index model in the on-chip memory and the off-chip memory.

Description

technical field [0001] The invention belongs to the field of multimodal data indexing and storage structure design in multimodal networks, and is particularly aimed at the FIB storage structure and data retrieval algorithm in multimodal networks. Background technique [0002] With the continuous emergence of various innovative network applications such as holographic communication, Internet of Vehicles, and AR / VR, the current network architecture can no longer meet users' needs for Internet content, personalization, ubiquitous mobility, security and privacy, etc. In recent years, all walks of life have actively explored the future network architecture. Multi-modal network architectures such as fully-dimensional and definable multi-modal networks, smart logo symbiosis networks, NewIP networks for Network 5.0, and hICN networks have been continuously proposed. With the innovative development of multi-modal network construction technology and related enabling technologies, the...

AI Technical Summary

Problems solved by technology

Among them, the hash table operation speed is fast, but it needs to consume more storage space to reduce conflicts; the Bloom filter cannot locate the address of the element; the search speed of the search tree and the jump table are both slow

In addition, the current research mainly focuses on the data index of a certain modality, and there is relatively little research on the mixed index of multi-modal data in the future.

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