Ioam data release optimization method and system for SRV6 cloud network

Abstract

The present invention provides an SRv6 cloud network-oriented IOAM data distribution optimization method and system, wherein the method includes: switching between the silent state and the measurement state according to the set timing parameters, so as to make the SRv6 controllable edge in the measurement state The node inserts the measurement instruction to the flow data packet, and in the silent state SRv6 controllable edge node abandons the insertion measurement instruction; the non-edge node uses the measurement instruction to measure the flow data packet to obtain the measurement data packet; according to the compression parameter, the measurement data packet Compressing and encapsulating the measurement data of the same type of traffic data packets cached in the non-edge nodes to obtain a new measurement data packet, and uploading and publishing the new measurement data packet to the destination node. Through the above solution, it can be compatible with the loose control architecture of the SRv6 cloud network, and reduce the amount of measurement data.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to an SRv6 cloud network-oriented IOAM data distribution optimization method and system. Background technique [0002] In recent years, the awareness of enterprises to use the cloud has been continuously enhanced, and enterprise use of the cloud has become a trend; at the same time, in order to ensure the normal operation of cloud services, the needs of enterprises for the network environment are also constantly changing. A single high bandwidth or low latency has become It cannot meet the requirements of enterprises to migrate to the cloud in parallel in multiple scenarios and cross-collaborate with multiple services. Therefore, under the double drive of technological innovation and business requirements, cloud computing technology and network architecture have undergone profound changes. The two are highly coordinated and no longer develop independently. The concept of cloud-net...

AI Technical Summary

Problems solved by technology

Therefore, under the loosely controlled cloud network control architecture, due to the loose network control method and the uncertainty of the measured data volume, it is difficult for managers to quantitatively limit the uploaded data volume, and there is a risk of excessive uploaded data volume.

[0012] 2) The measurement data density leads to a large scale of measurement data

The low load of Postcard data packets will amplify the actual bandwidth usage of uploaded data, which also brings the risk of excessive network bandwidth resources

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