The invention discloses a measurement method for time-varying non-stationary network flow and belongs to the technical field of networks. A singular value decomposes historical flow to obtain an orthogonal basis matrix to replace a sparse base. A mode that a novel network tomography model is constructed through a gauss stochastic matrix is adopted to describe the flow from a source router to an objective router and a relation between a route choice and a link circuit load. The highly ill-conditioned problem of end-to-end flow reconfiguration can be converted to a convex optimization problem which can be solved by compressed sensing, and the application of a compressed sensing reconfiguration algorithm can accurately reconstruct the end-to-end flow. According to the measurement method for the time-varying non-stationary network flow, the end-to-end flow is reconstructed to conduct network operation such as network planning, route planning, novel routing protocol performance evaluation and network fault analysis.

Measurement method for time-varying non-stationary network flow

The invention relates to a fast distributed monitoring method for electric-power communication network services The method includes the following steps: generating a Bernoulli matrix and selecting OD streams which need to be measured directly through the matrix and constructing a traffic matrix; obtaining a measurement matrix; constructing an optimization greedy adaptive dictionary; and reconstructing the traffic matrix through compression sensing In the fast distributed monitoring method for the electric-power communication-network services, part of OD streams, which need to be measured directly, are selected through a random matrix according power-law distribution of electric-power communication-network traffic and a traffic acquisition function is operated in part of routers as needed so as to obtain traffic information of the OD streams An end-to-end network traffic reconstruction model is constructed through the traffic information and the model is solved through use of a compression-sensing reconstruction algorithm so as to obtain monitoring values of the traffic The method is capable of obtaining the monitoring values of the traffic accurately in a real-time manner and at the same time reducing network traffic acquisition loss effectively

Fast distributed monitoring method for electric-power communication network services

The invention discloses a data collection method combining compressive sensing and random walk. The method comprises the following steps of (1) during an initialization stage, carrying out sensor nodedeployment, constructing an annular network topology structure, and respectively generating a previous layer of neighbor node set for each node in a network; (2) during each measurement process, randomly and uniformly selecting a certain number of nodes from the network as starting points of random walk paths, and enabling each sensor node to cooperatively complete compressive sensing measurementbased on the random walk according to the respective previous layer of neighbor node set; and (3) enabling an SINK node to carry out data recovery by utilizing a compressive sensing measurement result collected from each random walk path and adopting an existing compressive sensing data recovery technology. Compared with an existing scheme, the method has the advantages that the communication cost is smaller, and the data recovery precision is higher.

Data collection method combining compressive sensing and random walk

The invention discloses a full network flow monitoring method which comprises the following steps: (1) selecting routers and collectors for monitoring the flow in a full network; (2) acquiring m OD flows, extracting path information of the OD flows to construct an OD flow matrix P, and encoding the OD flows to form an OD pair identity mapping table; (3) computing sampling lists in different ranges by use of the OD flow matrix, the path information of the OD flows, and the resource constraint of the routers; (4) distributing the sampling lists to the routers, and distributing the OD pair identity mapping table while entering the router; (5) enabling the routers and the collectors thereof to monitor a data packet according to the OD pair identity mapping table and the sampling lists so as to update flow data in the collector flow table; and (6) enabling the collectors to collect and upload the flow data to form a monitoring report. Through the adoption of the monitoring method disclosed by the invention, a large number of redundancy cannot be produced between the routers, the communication between the collectors is unnecessary, and the monitoring method has the advantages of being small in network burden, large in full network coverage rate and high in processing efficiency.

Full network flow monitoring method

The present invention provides a method and system for estimating dynamic traffic in a data communication network. The method comprises: acquiring a link load, an OD flow and a network topology structure in a data communication network; dividing a traffic matrix into a trend part and a fluctuation part; separately conducting S transform on a link load matrix, the traffic matrix, an OD flow change matrix and a link load change matrix; calculating an estimation value of the S transform result of the trend part of the traffic matrix and an estimation value of the S transform result of the OD flow change matrix, and conducting inverse S transform, to obtain an estimation value of the trend part of the traffic matrix and an estimation value of the fluctuation part of the traffic matrix X; obtaining an estimation value of the traffic matrix, and then estimating dynamic traffic in the current data communication network. By means of the method, a traffic matrix is estimated from a time domain and a frequency domain comprehensively, thereby avoiding inaccurate estimation caused by analyzing and estimating the traffic matrix in the time domain. By the accurate estimation of the traffic matrix, all states of network traffic can be monitored, thereby knowing the characteristics and flow directions of the network traffic.

Method and system for estimating dynamic traffic in data communication network

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.

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

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