End-to-end network flow reconstruction method based on compression sensing in dynamic network

Abstract

The invention discloses an end-to-end network flow reconstruction method based on compression sensing in a dynamic network. In a large-scale IP backbone network, the OD flow is selected by a random walk method; the flow value of partial OD flow acquired by a router subset is described by constructing a sparse flow matrix; a compressing sensing reconstruction module is established by adopting a main information analysis method; a relationship between the OD flow generated by the router sublet and all the end-to-end OD flow in the IP backbone network is descried by using the module, and further all the end-to-end OD flow of the whole IP backbone network is determined. The method can more accurately acquire end-to-end network flow detail characteristic, cannot consume mass hardware resources, can track the dynamic changes of the OD flow in a real time manner, and the reconstruction error is less.

Description

technical field [0001] The invention belongs to the field of traffic measurement and analysis under a dynamic network, and in particular relates to an end-to-end network traffic reconstruction method based on compressed sensing under a dynamic network. Background technique [0002] In recent years, with the rapid development of the Internet, an increasing number of network applications have provided users with convenient services. But it also makes the network increasingly complex. For network operators, network management and control are becoming more and more difficult. The traffic matrix is ​​the most important input parameter in network traffic engineering, which represents all end-to-end traffic in the network, and completely describes the distribution of traffic, and provides the network manager with the current network status, but it is difficult to obtain it accurately in practical applications traffic matrix. [0003] Even though the traffic matrix is ​​very impo...

AI Technical Summary

Problems solved by technology

But using NetFlow to measure every OD flow is unrealistic, even impossible

This is because the port of the router will consume a lot of hardware resources when running the NetFlow program, and direct measurement will cause additional communication overhead

This reduces the store-and-forward efficiency of routers, thus increasing network delay and easily causing network congestion

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