Network flow estimating method

Abstract

The invention discloses a network flow estimating method which concretely comprises the steps of initializing, obtaining a sigma point set, predicting the state, estimating the state and updating the process. In the method, the flow matrix estimating problem is modeled into a nonlinear system which more meets the OD (Origin-Destination) flow real characteristic; the sigma point set obtained by UT (Unscented Transformation) is subjected to nonlinear transformation; the coefficient of the system sate equation needed by nonlinear transformation is obtained concretely by Chebyshev polynomial fitting instead of approximately obtaining the system state equation by the traditional local linearization; accordingly, the state equation of the system does not need to meet the available linear function approximating condition; a symmetrical sampling policy is adopted for the UT; the particle point set approaches the probability density function distribution of a nonlinear function to obtain the higher-order approximation of state estimation, the result of OD flow estimation has higher precision, and the calculating complexity of the system is reduced.

Description

Technical field [0001] The invention belongs to the technical field of computer network communication, and particularly relates to a network flow estimation method therein. Background technique [0002] With the rapid development of the Internet, the network is developing in the direction of large-scale, high-speed, multi-service, and large-capacity. It becomes more difficult to control and manage the network. The network status parameters do not matter to network managers, network service providers, or network service providers. Network researchers are a very important physical quantity. [0003] The network traffic matrix (Traffic Matrix, TM) is an important indicator of network performance parameters. It represents the traffic between any OD (Origin-Destination) pair (or flow, or node) in the network, and describes the network traffic between each OD pair Distribution. The acquisition of the flow matrix can be divided into active measurement and passive measurement according t...

AI Technical Summary

Problems solved by technology

[0005] (1) In order to obtain the OD traffic information of the whole network, Netflow software must be installed on all core routers, which is a big expense;

[0006] (2) The direct measurement process needs to consume a lot of router resources, which affects the performance of the router;

[0007] (3) It is very difficult to process and analyze the data collected by the large-scale network and the measurement data

When the system has strong nonlinearity, a large linearization error will be introduced, which will affect the accuracy of OD flow estimation; at the same time, it is necessary to calculate the partial derivative matrix, which increases the computational complexity of the system

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