Network flow classifying, state tracking and message processing device and method

Abstract

The invention relates to a classifying, status tracking and message processing device and method for network, implementing finely granular flow control by dynamic flow classification method based on IP quinary group or other specific tags, implementing high speed parallel flow processing by plural parallel devices and inside-device multiple process / thread mechanisms, avoiding large number of exclusive and synchronous operations caused by parallel processing by the measures of slitting network flow table, setting unique writer of flow recording list, strictly stipulating write instruction sequence in list insert and delete operating processes to keep list integrity, etc, and thus further raising processing efficiency. And it is applied to various parallel processing environments, such as network processor, ASIC, FPGA, multikernel processor, symmetrical multiprocessor (SMP), and software process / thread, having good inter-platform compatibility, extendibility and practicality.

Description

technical field [0001] The invention belongs to the technical field of computer network and data communication, and specifically relates to a device and method for classifying, state tracking and message processing of network flows, which can be used for routers, security gateways, traffic monitoring and auditing, network billing, load Among network devices and software such as balancer, it realizes fine-grained control of traffic and improves the efficiency of packet processing. Background technique [0002] With the increasing demand for emerging applications such as VoIP (Voice over IP), mobile data services, and P2P (Peer-to-Peer), network applications are showing a rapid development trend. At the same time, network bandwidth is also increasing rapidly. QoS (Quality of Service), attack / intrusion detection and defense, traffic monitoring and auditing, network billing, load balancing and other key business functions of network facilities are facing new and greater challeng...

AI Technical Summary

Problems solved by technology

The static flow classification method does not record the context status information of the flow, and needs to be searched for each packet, so it is often complicated and has a large load

A service flow usually includes traffic in two directions, and the static flow classification method cannot establish the correlation between the traffic in these two directions, and cannot meet the needs of some applications (such as intrusion detection)

In addition, the static flow classification method also has scalability issues such as the limitation of the number of rules (usually up to tens of thousands), incremental update of rules, etc., which has certain limitations

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