CN208001290U - A kind of multidimensional power telecom network volume forecasting system - Google Patents
A kind of multidimensional power telecom network volume forecasting system Download PDFInfo
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- CN208001290U CN208001290U CN201820179995.6U CN201820179995U CN208001290U CN 208001290 U CN208001290 U CN 208001290U CN 201820179995 U CN201820179995 U CN 201820179995U CN 208001290 U CN208001290 U CN 208001290U
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Abstract
The utility model discloses a kind of multidimensional power telecom network volume forecasting system, the system comprises:Application layer equipment and interface module, SDN controllers, SDN coordinators, SDN equipment, OTN equipment, EOPN equipment.The excellent effect of the utility model is:The technology of cloud service is introduced in the data measuring method of use.SDN technologies are introduced in part of data acquisition.The transverse dimensions data of acquisition are trained using BP neural network algorithm.The longitudinal dimension data of acquisition uses the algorithm that FARIMA and Elman algorithms are combined.Improve the precision of prediction algorithm;Using the weights of single exponent smoothing algorithm update multidimensional prediction algorithm output, the fluctuation dimension of error is reduced.
Description
Technical field
The utility model is related to a kind of multidimensional power telecom network volume forecasting systems, and it is pre- to belong to power telecom network network flow
Survey management domain.
Background technology
Communication network as electric system second open covering universe range network, be carrying power grid it is stable, protection, control,
The unique passage of the significant data of information, the stability of transmission, reliability, safety directly affect grid power transmission circuit
Reliability service.If because network performance problems cause power grid catastrophe failure occur, national people's livelihood property and safety will be caused
Loss.
With the deep propulsion of intelligent grid and national grid, power telecom network network size continuous enlargement, SDH
The increase of (Synchronous Digital Hierarchy, synchronous digital system) number of devices, transmission capacity are constantly expanded
Hold, meanwhile, network bearer type is also continuously increased, and network-flow characteristic becomes increasingly complicated.Power grid is carried out energetically at present
Build intelligent distribution network and informatization platform, end Network intelligent construction access different bandwidth, flow power distribution automation, regard
Frequency monitoring, robot inspection, distributed generation resource, informationization business, cause the mutability of edge network and non-intellectual, further
Also impact and challenge are brought to backbone communications capacity.Therefore, network service demand is on the increase, the diversification of business and
The difference of IT application in management business and power grid production scheduling business, network capacity and optimization to communication network bring new choose
War.Currently, the variation tendency due to being unable to look-ahead powerline network data traffic, causes not conforming to for limited network resources
Reason distribution, causes network congestion, affects the service quality of business, and provides the data of mistake for the dilatation construction of network in turn
Support.Therefore, it is necessary to monitor data transfer throughput in communication network in real time using a kind of technological means, and the stream of acquisition can be passed through
Amount data characteristics finds changing rule and establishes differentiated service flux prediction model to assess network flow development trend, be
Distribute rationally and the expansion planning of electric power communication network Internet resources provide basic data support.
The Chinese patent application of Publication No. CN107564281A discloses a kind of macroscopical wagon flow stream based on WIFI signal
Prediction algorithm is measured, prediction device systems are set along traffic route, the prediction device systems include multiple sub-networks, each subnet
Network includes host and several extension sets, the extension set by wireless passive perceptual model, acquisition by mobile terminal device with
The machine broadcast data packet that environment is sent around, and screen the wherein data packet with mobile terminal device id information and examined
Rope is uploaded to host after stamping extension set label, and the data being collected into are carried out unified storage and stamp time tag by host, and on
It reaches in data server and stores, and assessment prediction is carried out to macroscopical wagon flow flow by data analysis.
The Chinese patent application of Publication No. CN107547154A discloses a kind of side establishing video traffic prediction model
Method and device, including:It obtains in preset duration for the historical video streams amount data set generated on default geographic area and extremely
A kind of few characteristic data set;Every historical video streams amount data for including by the historical video streams amount data set acquired point
The characteristic that do not concentrated with each characteristic is associated, and obtains the data set for establishing video traffic prediction model;
Characteristic parameter screening is carried out to the data set for establishing video traffic prediction model using the combination of preset feature selecting algorithm,
It determines and the relevant at least one characteristic parameter of video flow;It is used using the data set for establishing video traffic prediction model
Preset model training algorithm carries out model training, obtain with the relevant at least one characteristic parameter of video flow and video flow it
Between mapping relations.
It is dynamic that the Chinese patent application of Publication No. CN107483265A discloses a kind of network flow based on wavelet analysis
State prediction technique is normalized the primary data of end to end network data on flows to be analyzed in network topology structure
Processing, obtains the time-domain signal of network flow to be analyzed;Based on Wavelet Analysis Theory, it converts the time-domain signal to net to be analyzed
The time-frequency domain signal of network flow;It is low frequency component, intermediate frequency component and high fdrequency component by the time-frequency domain signal decomposition, and according to small echo
Inverse transformation, obtain corresponding low frequency signal, intermediate-freuqncy signal and high-frequency signal respectively;Low frequency signal, intermediate-freuqncy signal are built respectively
With the flux prediction model of high-frequency signal, and the prediction result of low frequency signal, intermediate-freuqncy signal and high-frequency signal is respectively obtained;To low
The prediction result of frequency signal, intermediate-freuqncy signal and high-frequency signal is synthesized, and the prediction result of network flow to be analyzed is obtained.
In conclusion existing transmission device network management system does not have the volume forecasting mechanism of network, to having network flow
The analysis of amount is also estimated simply by the mode for manually calculating traffic peak flow, and then the bandwidth of planned network,
And provide foundation to the network capacity extension.This mode reliability is low, effective poor, reflects the variation of network not in time, with new
The quick appearance of business, network flow are fast-developing, and with certain sudden, the optimization and configuration means to network by
To limitation.
Utility model content
The utility model is to solve flow present in power telecom network current situation it is difficult to predict, network capacity extension management to lack
The problem of weary technical basis, proposes a kind of multidimensional power telecom network volume forecasting system.
System described in the utility model includes:Application layer equipment and interface module, SDN controllers, SDN coordinators, SDN are set
Standby, OTN equipment, EOPN equipment.Application layer equipment and interface module are connect with SDN controllers, SDN controllers and SDN coordinators
Connection;SDN equipment is connect with SDN controllers, and SDN equipment, OTN equipment, EOPN equipment are sequentially connected.
The framework of system described in the utility model is divided into three layers, is divided into physical layer, virtual controlling layer from bottom-up and answers
With layer.Wherein physical layer with IaaS (Infrastructure as a Service, as application foundation facility) to virtual controlling
Layer provide service encapsulation, physical layer, virtual controlling layer with PaaS (Platform as a Service, as application platform) to
Application layer provides service encapsulation.
System described in the utility model realizes the virtualization of underlying device gatherer process, resource pool, is controlled using SDN
The data information of device scheduling acquisition simultaneously carries out estimation prediction to the congestion and future traffic of network appearance.Sampling instrument is embedded into net
On network transmission device, SDH (Synchronous Digital Hierarchy, synchronous digital system) equipment, OTN are acquired in real time
(optical transfer network, OpticalTransportNetwork) equipment and EPON (Ethernet Passive Optical
Network, Ethernet passive optical network) equipment outlet data transmit flow.
The Netflow functions that system described in the utility model is carried using router carry out Network Traffic Monitoring and in SG-
It is for statistical analysis to data on flows in TMS (national grid communications management system) power communication network management system.
Physical layer is made of transmission device, the network equipment, and transmission device includes SDH equipment, OTN equipment, EPON equipment, net
Network equipment includes router, interchanger.Storage server is cluster distributed to be positioned over each network node, and storage server cluster is made
With the work for being completion network measure and data storage.
SDN controllers can load is arranged SDN controllers and SDN coordinators on the optical communication network upper layer of OTN, SDH.
SDN controllers can regulate and control balanced device, and SDN controllers support the work(that exchange, routing, secure accessing, flow equalization and flow are isolated
Energy.SDN coordinators are connected with virtual level coordinator to obtain the resource number and data mode of virtual level.SDN controllers pass through
Open northbound interface is connected with upper application layer, and the demand that resource pool energy information and user are obtained by southbound interface is believed
The demand information and status information for ceasing and collecting user's transmission, configuration information is issued by southbound interface.
Application layer equipment and interface module are built on the server of control centre, for realizing application layer and control layer
Interaction, completes the calling to physical layer resources, and application layer obtains traffic statistics using SG-TMS network management systems, adopted with scene
Collect module intercommunication, flow collection measurement service is completed with interacting for bottom by interface layer.
The excellent effect of the utility model is:
The technology of cloud service is introduced, and the data traffic information for bottom transmission device being acquired in the form of cloud service is to upper layer
It using transmission, stores and calculates convenient for data, be a kind of simple service, enhancing by the device measuring procedural abstraction of bottom complexity
Sharing and collaborative between data, lifting system data-handling efficiency.Realize underlying device gatherer process virtualization,
Resource pool, SDN controllers freely dispatch the data information of acquisition, realize control, monitoring, coordinate, virtual function, embody
Intelligence, self-healing property and the controllability of system entirety.
Description of the drawings
Fig. 1 is the structural schematic diagram of system described in the utility model.
Specific implementation mode
Specific embodiment of the present utility model is described in further detail below in conjunction with the accompanying drawings.
The structure chart of system described in the utility model is as shown in Figure 1:System described in the utility model includes:Application layer equipment
And interface module, SDN controllers, SDN coordinators, SDN equipment, OTN equipment, EOPN equipment.Application layer equipment and interface module
It is connect with SDN controllers, SDN controllers are connect with SDN coordinators;SDN equipment is connect with SDN controllers, and SDN equipment, OTN are set
Standby, EOPN equipment is sequentially connected.
The framework of system described in the utility model is divided into three layers, is divided into physical layer, virtual controlling layer from bottom-up and answers
With layer.Wherein physical layer with IaaS (Infrastructure as a Service, as application foundation facility) to virtual controlling
Layer provides service encapsulation, and physical layer, virtual controlling layer are with PaaS (Platformas a Service, as application platform) to answering
Service encapsulation is provided with layer.
System described in the utility model realizes the virtualization of underlying device gatherer process, resource pool, is controlled using SDN
The data information of device scheduling acquisition simultaneously carries out estimation prediction to the congestion and future traffic of network appearance.Sampling instrument is embedded into net
On network transmission device, SDH (Synchronous Digital Hierarchy, synchronous digital system) equipment, OTN are acquired in real time
(lightTransmission net, OpticalTransportNetwork) and equipment and EPON (Ethernet Passive Optical
Network, Ethernet passive optical network) equipment outlet data transmit flow.
The Netflow functions that system described in the utility model is carried using router carry out Network Traffic Monitoring and in SG-
It is for statistical analysis to data on flows in TMS (national grid communications management system) power communication network management system.
Physical layer is made of transmission device, the network equipment, and transmission device includes SDH equipment, OTN equipment, EPON equipment, net
Network equipment includes router, interchanger.Storage server is cluster distributed to be positioned over each network node, and storage server cluster is made
With the work for being completion network measure and data storage.
SDN controllers can load is arranged SDN controllers and SDN coordinators on the optical communication network upper layer of OTN, SDH.
SDN controllers can regulate and control balanced device, and SDN controllers support the work(that exchange, routing, secure accessing, flow equalization and flow are isolated
Energy.SDN coordinators are connected with virtual level coordinator to obtain the resource number and data mode of virtual level.SDN controllers pass through
Open northbound interface is connected with upper application layer, and the demand that resource pool energy information and user are obtained by southbound interface is believed
The demand information and status information for ceasing and collecting user's transmission, configuration information is issued by southbound interface.
Application layer equipment and interface module are built on the server of control centre, for realizing application layer and control layer
Interaction, completes the calling to physical layer resources, and application layer obtains traffic statistics using SG-TMS network management systems, adopted with scene
Collect module intercommunication, flow collection measurement service is completed with interacting for bottom by interface layer.
Above description is only a specific implementation of the present invention, but the scope of protection of the utility model is not limited to
In this, any one skilled in the art is in range disclosed by the utility model, the variation that can readily occur in
Or replace, it should all cover in the protection domain of the utility model claims.
Claims (3)
1. a kind of multidimensional power telecom network volume forecasting system, which is characterized in that including:Application layer equipment and interface module, SDN
Controller, SDN coordinators, SDN equipment, OTN equipment, EOPN equipment, application layer equipment and interface module connect with SDN controllers
It connects, SDN controllers are connect with SDN coordinators;SDN equipment is connect with SDN controllers, SDN equipment, OTN equipment, EOPN equipment according to
Secondary connection.
2. a kind of multidimensional power telecom network volume forecasting system according to claim 1, which is characterized in that the SDN controls
Device processed can load on the optical communication network upper layer of OTN, SDH and SDN controllers and SDN coordinators is arranged.
3. a kind of multidimensional power telecom network volume forecasting system according to claim 1, which is characterized in that the SDN controls
Device processed is connected by open northbound interface with upper application layer.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201820179995.6U CN208001290U (en) | 2018-02-01 | 2018-02-01 | A kind of multidimensional power telecom network volume forecasting system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201820179995.6U CN208001290U (en) | 2018-02-01 | 2018-02-01 | A kind of multidimensional power telecom network volume forecasting system |
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| CN208001290U true CN208001290U (en) | 2018-10-23 |
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| CN201820179995.6U Expired - Fee Related CN208001290U (en) | 2018-02-01 | 2018-02-01 | A kind of multidimensional power telecom network volume forecasting system |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113535386A (en) * | 2021-06-23 | 2021-10-22 | 河北中兴冀能电力发展有限公司 | Inter-board multi-operation chip resource monitoring system applied to power instrument equipment |
-
2018
- 2018-02-01 CN CN201820179995.6U patent/CN208001290U/en not_active Expired - Fee Related
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113535386A (en) * | 2021-06-23 | 2021-10-22 | 河北中兴冀能电力发展有限公司 | Inter-board multi-operation chip resource monitoring system applied to power instrument equipment |
| CN113535386B (en) * | 2021-06-23 | 2022-09-02 | 河北中兴冀能电力发展有限公司 | Inter-board multi-operation chip resource monitoring system applied to power instrument equipment |
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| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20181023 Termination date: 20190201 |