CN106789239A - Towards the information application system failure trend prediction method and device of power business - Google Patents
Towards the information application system failure trend prediction method and device of power business Download PDFInfo
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- CN106789239A CN106789239A CN201611185498.9A CN201611185498A CN106789239A CN 106789239 A CN106789239 A CN 106789239A CN 201611185498 A CN201611185498 A CN 201611185498A CN 106789239 A CN106789239 A CN 106789239A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/06—Management of faults, events, alarms or notifications
- H04L41/0631—Management of faults, events, alarms or notifications using root cause analysis; using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/14—Network analysis or design
- H04L41/147—Network analysis or design for predicting network behaviour
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
Abstract
The present invention relates to a kind of computer realm, more particularly to a kind of information application system failure trend prediction method and device towards power business.Method includes being monitored at least one equipment included in information application system, and obtains Monitoring Data；Using default failure trend prediction rule, the Monitoring Data to getting carries out data processing, obtains corresponding fault trend information；The fault trend information is carried out into visual presentation in given display device.Device includes：Monitoring modular, for being monitored at least one equipment included in information application system, and obtains Monitoring Data；Processing module, for using default failure trend prediction rule, the Monitoring Data to getting to carry out data processing, obtains corresponding fault trend information；Display module, for the fault trend information to be carried out into visual presentation in given display device.
Description
Technical field
The present invention relates to a kind of computer realm, more particularly to a kind of information application system failure towards power business
Trend forecasting method and device.
Background technology
With the continuous propulsion that state's net company informationization is built, the type and quantity of information system are continuously increased, information system
System safe and reliable operation requirement is improved constantly, and IMS has been built in the unification of Guo Wang companies, and (IP Multimedia Subsystem, IP is more
Media subsystem) system enhancement is to the Centralized Monitoring ability of information system ruuning situation.Especially night only have dispatcher on duty
In the case of, when information application system happens suddenly significant trouble, operation maintenance personnel needs the regular hour to get to live exclusion
Failure.In order to further lift the reliability service and operation management level of Information application, information system security reliability service is improved
Supportability, it is necessary to the actual conditions of system are allocated and transported with reference to company information, actively research and application message technology are to existing letter
The operation monitoring analysis and emergency handling mechanism for ceasing application carry out innovation improvement.
Domestic and international research level summary：
1) foreign study level：
Data center is a whole set of complicated facility, and it not only includes information system and other matched services
The equipment such as device, communication, storage, data communication connection, environmental control equipment, monitoring device and various safety also comprising redundancy
Device.For common monitoring demand, by basic monitoring method, optimal monitoring effect can not be reached.
Information system O＆M monitored object mainly includes main frame and network, and host monitor can be divided into application layer monitoring, clothes
The monitoring of business layer, server layer monitoring and network interface layer monitoring.Information systems internetting is exactly in fact the set of distinct device, route
Device, interchanger, fire wall etc. can be considered as special " server ", and the contact between them constitutes network.Therefore, network
The equipment that monitored object is namely based on network environment in fact.
At present, external main flow commercialization IT monitoring tools product includes IBM Tivoli, HP Open View, Microsoft
SCCM, BMC Patrol, CA Unicenter etc., commercial product price costly, typically in hundreds of thousands to millions of, and work(
Customized extension can be difficult.The IT monitoring technologies increased income including Cacti, Nagios, Zenoss, Zabbix, Hyperic HQ etc., with
Free form is provided, the Host Status of energy effective monitoring Windows, Linux and Unix, and the network such as interchanger, router sets
It is standby etc., the agreements such as WMI, PerfMon, SNMP, JMX, HTTP, Telnet, SSH, Syslog, ICMP, FTP, SMTP can be supported,
But general lack of friendly user interface.
2) studies in China level
In recent years, the country be have developed rapidly in IT monitoring theories and technical field of research, and skill is monitored based on the above-mentioned IT for increasing income
Art, domestic commercial IT monitoring tools product and solution are rapidly developed, the product of comparative maturity include Bei Ta, east China,
The IT O＆M monitoring management systems of the companies such as Divine Land Tai Yue, mocha, Tai Hao.
Even if existing information application system can realize fault detect, phase also can only can be just detected upon a fault
Failure is answered, reliable failure trend prediction cannot be realized, it is impossible to " alarming in advance " function is realized.
The content of the invention
In view of the above problems, it is proposed that the present invention overcomes above mentioned problem or solve at least in part in order to provide one kind
The information application system failure trend prediction method and device towards power business of above mentioned problem.
Towards the information application system failure trend prediction method of power business, it is characterised in that including：
At least one equipment to being included in information application system is monitored, and obtains Monitoring Data；
Using default failure trend prediction rule, the Monitoring Data to getting carries out data processing, obtains right
The fault trend information answered；
The fault trend information is carried out into visual presentation in given display device.
At least one equipment includes：Server, storage device, interchanger and the route specified in information application system
It is any one or more in device node；
The Monitoring Data includes network interface layer data, server layer data, service layer data and application layer data；Its
In,
The network interface layer data include IP address, MAC Address, routing table, port existing state, up-downgoing flow；
The server layer data include cpu load, memory usage, process status, magnetic disc i/o；
Service layer's data include middleware, the status data of database platform software；
The application layer data includes the performance state data of information application system.
When the distributed monitoring approach using intelligent agent, intelligent monitoring is installed on every monitored equipment and acts on behalf of SMA
When, at least one equipment to being included in information application system is monitored, and obtains Monitoring Data, including：
Intelligent monitoring acts on behalf of SMA and at least one equipment included in described information application system is monitored, and is supervised
Survey data；
Monitoring service end obtains the intelligent monitoring and acts on behalf of the Monitoring Data that SMA is monitored, the monitoring service end
SMA is acted on behalf of according to intelligent monitoring described in the regular taking turn in setting time interval, acts on behalf of what SMA was monitored to obtain the intelligent monitoring
The Monitoring Data；
Wherein, the monitoring service end obtains between SMA is acted on behalf of in the intelligent monitoring and transmits the monitoring by XML format
Data.
At least one equipment to being included in information application system is monitored, and obtains Monitoring Data, also includes：
The intelligent monitoring acts on behalf of SMA and sets up heartbeat with the monitoring service end and is connected；The monitoring service end monitors the intelligence
During monitoring agent SMA heartbeats connection time-out, show that the corresponding device fails of SMA are acted on behalf of in the intelligent monitoring, and generate phase
The failure message answered；Wherein, the failure message is included in the Monitoring Data；
When the network monitoring mode using snmp protocol, at least one equipment to being included in information application system
It is monitored, and obtains Monitoring Data, including：The network performance of at least one equipment to being included in described information application system
And network errors are monitored, and obtain Monitoring Data；
When the hostdown using intelligent agent diagnoses monitor mode, be installed intelligent monitoring generation on every monitored equipment
During reason SMA, at least one equipment to being included in information application system is monitored, and obtains Monitoring Data, including：Institute
State intelligent monitoring and act on behalf of SMA according to the monitoring policy specified, at least one equipment to being included in described information application system is entered
Row monitoring；Monitoring master server receives the intelligent monitoring and acts on behalf of the announcement that SMA sends when the equipment operation exception is monitored
Alert or failure message；Wherein, the alarm or failure message are included in the Monitoring Data；
At least one equipment to being included in information application system is monitored, and obtains Monitoring Data, also includes：
The intelligent monitoring acts on behalf of SMA and sets up heartbeat and be connected with the monitoring master server；The monitoring master server monitors described
When SMA heartbeats connection time-out is acted on behalf of in intelligent monitoring, show that the corresponding device fails of SMA are acted on behalf of in the intelligent monitoring, and it is raw
Into corresponding failure message；Wherein, the failure message is included in the Monitoring Data；
Described regular using default failure trend prediction, the Monitoring Data to getting carries out data processing, obtains
To corresponding fault trend information, including：
Using default linear regression algorithm and Exponential Backoff Algorithm, the Monitoring Data to getting is carried out at data
Reason, obtains corresponding failure future trend information；
Using default trigonometric function regression algorithm, the Monitoring Data to getting carries out data processing, obtains right
The troublesome periodic tendency information answered；
Wherein, the fault trend information includes failure future trend information and troublesome periodic tendency information.
Described to use default trigonometric function regression algorithm, the Monitoring Data to getting carries out data processing, obtains
To corresponding troublesome periodic tendency information, including：
Take out finally the state factor parameter value of collection and its before m-1 shape in Monitoring Data state factor argument sequence
State factor parameter value carries out periodicity analysis, according to state factor ginseng in the state factor parameter value calculation this period for collecting
The cyclic parameter of numerical value change, obtains periodic regression analytic function, then draws state factor parameter value according to the function
The cyclic curve of change；
The periodicity analysis algorithm is specific as follows：The state factor argument sequence for being gathered is { y1, y2 ... ..., yn },
Acquisition time sequence be { t1, t2 ... ..., tn }, the trigonometric function regression function for using for：
Wherein k is default partial wave number, and the precision for controlling trigonometric function periodic regression, m is state factor parameter
The size of sequence, ej(j=0,1 ..., k) and fj(j=1,2 ..., k) for trigonometric function periodic regression function parameter, its
Middle calculation method of parameters is as follows：
After analysis is finished every time, the state factor parameter value for continuing to gather next cycle is put into state factor argument sequence
End, while by the state factor parameter value of collection is deleted earliest in original state factor parameter sequence, hold mode factor parameter
Sequence size is m.
A kind of information application system failure trend prediction device, including：
Monitoring modular, for being monitored at least one equipment included in information application system, and obtains monitoring number
According to；
Processing module, for using default failure trend prediction rule, the Monitoring Data to getting to enter line number
According to treatment, corresponding fault trend information is obtained；
Display module, for the fault trend information to be carried out into visual presentation in given display device.
When the distributed monitoring approach using intelligent agent, intelligent monitoring is installed on every monitored equipment and acts on behalf of SMA
When, the monitoring modular, including：
SMA is acted on behalf of in intelligent monitoring, for being monitored at least one equipment included in described information application system, is obtained
To Monitoring Data；
Monitoring service end, the Monitoring Data that SMA is monitored is acted on behalf of for obtaining the intelligent monitoring；
Wherein, the monitoring service end obtains between SMA is acted on behalf of in the intelligent monitoring and transmits the monitoring by XML format
Data.
SMA is acted on behalf of in the intelligent monitoring, is additionally operable to set up heartbeat with the monitoring service end and is connected；The monitoring service
End, is additionally operable to, when monitoring that SMA heartbeats connection time-out is acted on behalf of in the intelligent monitoring, show that the intelligent monitoring acts on behalf of SMA pairs
The device fails answered, and generate corresponding failure message；Wherein, the failure message is included in the Monitoring Data；
When the network monitoring mode using snmp protocol, the monitoring modular, specifically for：To described information application system
The network performance and network errors of at least one equipment included in system are monitored, and obtain Monitoring Data；
When the hostdown using intelligent agent diagnoses monitor mode, be installed intelligent monitoring generation on every monitored equipment
During reason SMA, the monitoring modular, including：SMA is acted on behalf of in the intelligent monitoring, for according to the monitoring policy specified, to the letter
At least one equipment included in breath application system is monitored；Monitoring master server, for receiving the intelligent monitoring agency
Alarm or failure message that SMA sends when the equipment operation exception is monitored；Wherein, the alarm or failure message are included
In the Monitoring Data；
SMA is acted on behalf of in the intelligent monitoring, is additionally operable to set up heartbeat and be connected with the monitoring master server；The main clothes of monitoring
Business device, when being additionally operable to monitor that SMA heartbeats connection time-out is acted on behalf of in the intelligent monitoring, show that the intelligent monitoring acts on behalf of SMA pairs
The device fails answered, and generate corresponding failure message；Wherein, the failure message is included in the Monitoring Data；
The processing module, including：
First processing units, for using default linear regression algorithm and Exponential Backoff Algorithm, described in getting
Monitoring Data carries out data processing, obtains corresponding failure future trend information；
Second processing unit, for using default trigonometric function regression algorithm, the Monitoring Data to getting is entered
Row data processing, obtains corresponding troublesome periodic tendency information；
Wherein, the fault trend information includes failure future trend information and troublesome periodic tendency information.
The second processing unit, specifically for：
Take out finally the state factor parameter value of collection and its before m-1 shape in Monitoring Data state factor argument sequence
State factor parameter value carries out periodicity analysis, according to state factor ginseng in the state factor parameter value calculation this period for collecting
The cyclic parameter of numerical value change, obtains periodic regression analytic function, then draws state factor parameter value according to the function
The cyclic curve of change；
The periodicity analysis algorithm is specific as follows：The state factor argument sequence for being gathered is { y1, y2 ... ..., yn },
Acquisition time sequence be { t1, t2 ... ..., tn }, the trigonometric function regression function for using for：
Wherein k is default partial wave number, and the precision for controlling trigonometric function periodic regression, m is state factor parameter
The size of sequence, ej(j=0,1 ..., k) and fj(j=1,2 ..., k) for trigonometric function periodic regression function parameter, its
Middle calculation method of parameters is as follows：
After analysis is finished every time, the state factor parameter value for continuing to gather next cycle is put into state factor argument sequence
End, while by the state factor parameter value of collection is deleted earliest in original state factor parameter sequence, hold mode factor parameter
Sequence size is m.
By above-mentioned technical proposal, technical scheme provided in an embodiment of the present invention at least has following advantages：
Technical scheme provided in an embodiment of the present invention is monitored by the equipment included in information application system, and adopts
Regular with default failure trend prediction, the Monitoring Data to getting carries out data processing, obtains corresponding failure and become
Gesture information, realizes the Accurate Prediction of fault trend, i.e., " alarm in advance ", and then is favorably improved information system security reliably fortune
Row supportability.
Described above is only the general introduction of technical solution of the present invention, in order to better understand technological means of the invention,
And can be practiced according to the content of specification, below with presently preferred embodiments of the present invention and coordinate accompanying drawing describe in detail as after.
Brief description of the drawings
By reading the detailed description of hereafter preferred embodiment, various other advantages and benefit is common for this area
Technical staff will be clear understanding.Accompanying drawing is only used for showing the purpose of preferred embodiment, and is not considered as to the present invention
Limitation.And in whole accompanying drawing, identical part is denoted by the same reference numerals.In the accompanying drawings：
Fig. 1 shows the schematic flow sheet of information application system failure trend prediction method of the present invention；
Fig. 2 shows the structural representation of information application system failure trend prediction device of the present invention.
Specific embodiment
To make the purpose, technical scheme and advantage of the embodiment of the present invention clearer, below in conjunction with the embodiment of the present invention
In accompanying drawing, the technical scheme in the embodiment of the present invention is clearly and completely described, it is clear that described embodiment is
A part of embodiment of the present invention, rather than whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art
The every other embodiment obtained under the premise of creative work is not made, belongs to the scope of protection of the invention.
Before the technical scheme that the present invention is provided is described in detail, basic conception of the invention is introduced first.This hair
The principle framework of the technical scheme that bright embodiment is provided, is respectively from bottom to top acquisition layer, data Layer, presentation layer.Acquisition layer is born
Each stratiform that duty passes through the nodes such as given server, managed interchanger, router in the agreement real-time collecting networks such as SNMP, WMI
State data.Data Layer is responsible for carrying out the Monitoring Data that acquisition layer is collected storage and further treatment, such as according to formula or model
Early warning, alarm is carried out to calculate.Presentation layer is responsible for providing data Layer Monitoring Data and the result to data is visualized
Displaying.
Information application system monitoring data can be divided into network interface layer, server layer, service layer, four level classes of application layer
Not.Network interface layer mainly includes mainframe network state data, such as IP address, MAC Address, port survival, up-downgoing flow, speed
Rate, routing table, network interface card transmission/bag/rascal flow etc..Server layer mainly includes host B IOS and operating system state data,
Including operating system/temperature/fan/voltage/server state, CPU/ load/internal memories/disk/IO service conditions, install it is hard
Part and software information etc..Service layer mainly includes middleware, the status data of database platform software, including serve port/
Service processes, IIS/Apache/Webloglc, Mssql/Mysql/Oracle/DB2, other application service.The main pin of application layer
The status datas such as availability, performance to business application system, including the performance accessed based on user, such as WEB page are accessed and rung
Between seasonable etc..
As shown in figure 1, the schematic flow sheet of information application system failure trend prediction method of the present invention.
S1：Acquisition layer by the server specified in communications protocol real-time collecting network, storage device, managed interchanger,
Each layer state Monitoring Data of router node；
S2：Data Layer is stored to the Monitoring Data that acquisition layer is collected, fault detection analysis and failure trend prediction divide
Analysis；
S3：Presentation layer provides data Layer Monitoring Data and the result to data and carries out visual presentation.
The executive agent of the methods described that the present embodiment is provided can realize that the present embodiment provides the hard of methods described
Part equipment, and/or be the application on the hardware device.Specifically, the methods described that the present embodiment is provided, including：
Step 101, at least one equipment to being included in information application system are monitored, and obtain Monitoring Data.
Wherein, at least one equipment can include：Server, storage device, the friendship specified in information application system
Change planes with it is any one or more in router node.When i.e. equipment under test is one, during the equipment can be above-mentioned
Any one, equipment under test for it is multiple when, the equipment can be it is above-mentioned in it is any number of.
Described Monitoring Data includes network interface layer data, server layer data, service layer data and application layer data,
Network interface layer data include mainframe network state data, including IP address, MAC Address, routing table, port existing state, on
Downlink traffic；Server layer data include host B IOS and operating system state data, including cpu load, memory usage, enter
Journey state, magnetic disc i/o；Service layer's data include middleware, the status data of database platform software；Application layer data includes letter
Cease availability, the performance state data of application system.
Specifically, the present embodiment can be realized according to different monitor modes using different methods：
(1) using the distributed monitoring approach of intelligent agent
I.e. when be provided with the distributed monitoring approach using intelligent agent, every monitored equipment intelligent monitoring agency
During SMA, at least one equipment to being included in information application system is monitored, and obtains Monitoring Data, including：
Step S11, intelligent monitoring act on behalf of SMA and at least one equipment included in described information application system are supervised
Survey, obtain Monitoring Data.
Step S12, monitoring service end obtain the intelligent monitoring and act on behalf of the Monitoring Data that SMA is monitored.
Wherein, the monitoring service end obtains between SMA is acted on behalf of in the intelligent monitoring and transmits the monitoring by XML format
Data.
Based on distributed monitoring structure, SMA is acted on behalf of in installation intelligent monitoring on every cluster computer.Intelligent monitoring is acted on behalf of
SMA collects the work state information of computer, the installation and operation monitoring service end on monitoring host computer；Intelligent monitoring act on behalf of SMA with
Monitoring data is transmitted by XML format between monitoring service end, the regular taking turn intelligent monitoring in monitoring service end acts on behalf of SMA and obtains prison
Control information, monitoring host computer detects the running status of any computer in cluster using heartbeat detection.
It is i.e. further, above-mentioned steps：Monitoring service end obtains the intelligent monitoring and acts on behalf of the monitoring that SMA is monitored
Data, can be specially：SMA is acted on behalf of in the monitoring service end according to intelligent monitoring described in the regular taking turn in setting time interval, to obtain
Take the intelligent monitoring and act on behalf of the Monitoring Data that SMA is monitored.
Further, step：At least one equipment to being included in information application system is monitored, and obtains prison
Data are surveyed, be may also include：
Step S13, the intelligent monitoring act on behalf of SMA and set up heartbeat with the monitoring service end and be connected.
When step S14, the monitoring service end monitor that SMA heartbeats connection time-out is acted on behalf of in the intelligent monitoring, institute is drawn
State intelligent monitoring and act on behalf of the corresponding device fails of SMA, and generate corresponding failure message.
Wherein, the failure message is included in the Monitoring Data.
(2) using the network monitoring mode of snmp protocol
When the network monitoring mode using snmp protocol, at least one equipment to being included in information application system
It is monitored, and obtains Monitoring Data, including：
The network performance of at least one equipment and network errors to being included in described information application system are monitored,
And obtain Monitoring Data.
In the specific implementation, the network monitoring function based on Simple Network Management Protocol SNMP include monitoring network performance,
Detection and analysis network errors and Configuration network equipment, in network normal work, SNMP realizes statistics, configuration and test function；
In network failure, realize various mistake monitorings and recover function.
(3) using the hostdown diagnosis monitor mode of intelligent agent
When the hostdown using intelligent agent diagnoses monitor mode, be installed intelligent monitoring generation on every monitored equipment
During reason SMA, at least one equipment to being included in information application system is monitored, and obtains Monitoring Data, including：
Step S21, the intelligent monitoring act on behalf of SMA according to the monitoring policy specified, to being wrapped in described information application system
At least one equipment for containing is monitored.
Step S22, the monitoring master server reception intelligent monitoring act on behalf of SMA when the equipment operation exception is monitored
The alarm of transmission or failure message.
Wherein, the alarm or failure message are included in the Monitoring Data.
Further, at least one equipment to being included in information application system is monitored, and obtains monitoring number
According to may also include：
Step S23, the intelligent monitoring act on behalf of SMA and set up heartbeat and be connected with the monitoring master server.
When step S24, the monitoring master server monitor that SMA heartbeats connection time-out is acted on behalf of in the intelligent monitoring, draw
The corresponding device fails of SMA are acted on behalf of in the intelligent monitoring, and generate corresponding failure message.
Wherein, the failure message is included in the Monitoring Data.
Step 102, using default failure trend prediction rule, the Monitoring Data to getting carried out at data
Reason, obtains corresponding fault trend information.
In the specific implementation, this step 102 can be adopted and realized with the following method：
First, using default linear regression algorithm and Exponential Backoff Algorithm, the Monitoring Data to getting is carried out
Data processing, obtains corresponding failure future trend information.
Then, using default trigonometric function regression algorithm, the Monitoring Data to getting carries out data processing, obtains
To corresponding troublesome periodic tendency information.
Wherein, the fault trend information includes failure future trend information and troublesome periodic tendency information.
More specifically, it is above-mentioned to use default linear regression algorithm and Exponential Backoff Algorithm, the monitoring to getting
Data carry out data processing, obtain corresponding failure future trend information, it may include：
(1) linear regression algorithm
1. using Monitoring Data related to failure in described information application system as the sample data of linear regression algorithm
Collect, collect the historical data that described information application system occurs various failures, wherein, the historical data includes various events
The specific time of barrier, the number of times that the failure occurs in a period of time, and there is corresponding state factor number during the failure every time
According to；
Linear regression algorithm model is as follows：Y=a+b1x1+b2x2+b3x3+ ...；
Wherein y is dependent variable, is also prediction object outages future trend；X1, x2, x3 are independent variable, are also Information application
The Monitoring Data related to failure in system, i.e. the malfunction factor, are the correlative factors of y；A is linear regression coeffficient, b1,
B2, b3 are linear partial regression coefficient.
2. partial Correlation Analysis are carried out, that is, determines that described information application system setting future period is expected the main event for occurring
Barrier, wherein, major failure is that any two partial correlation coefficient is more than or equal to -1 and the failure less than or equal to 1；
3. use method of gradual regression, to step 2. in each described major failure determined set up respectively failure and state because
The mapping relations equation of subdata, and F inspections are carried out, if level of signifiance P can not meet P ＜ given thresholds, rejecting should
Major failure, otherwise retains the mapping relations equation of the failure and state factor data set up by the major failure；
4. the Monitoring Data state factor parameter value of future period is set described in prediction described information application system, and will be pre-
The state factor parameter value measured substitutes into the failure of the reservation and the mapping relations equation of state factor data
In, draw the probable value and failure future trend information of corresponding failure；
(2) Exponential Backoff Algorithm
Calculated using the default Exponential Backoff Algorithm according to the Monitoring Data state factor argument sequence value for collecting
Monitoring Data predicted value in the described information application system following multiple cycle：
The state factor argument sequence for being gathered is { y1, y2... ..., yn, acquisition time sequence is { t1, t2... ...,
tn, the index return function for using for：Y=cedt；
Wherein c and d is the parameter of index return function, and calculation method of parameters is：
Wherein,
Using equation below, the state factor parameter prediction of following a cycle is calculated according to above-mentioned parameter result of calculation
Value：
Above-mentioned to use default trigonometric function regression algorithm, the Monitoring Data to getting carries out data processing, obtains
To corresponding troublesome periodic tendency information, it may include：
Take out finally the state factor parameter value of collection and its before m-1 shape in Monitoring Data state factor argument sequence
State factor parameter value carries out periodicity analysis, according to state factor ginseng in the state factor parameter value calculation this period for collecting
The cyclic parameter of numerical value change, obtains periodic regression analytic function, then draws state factor parameter value according to the function
The cyclic curve of change；
The periodicity analysis algorithm is specific as follows：The state factor argument sequence for being gathered is { y1, y2 ... ..., yn },
Acquisition time sequence be { t1, t2 ... ..., tn }, the trigonometric function regression function for using for：
Wherein k is default partial wave number, and the precision for controlling trigonometric function periodic regression, m is state factor parameter
The size of sequence, ej(j=0,1 ..., k) and fj(j=1,2 ..., k) for trigonometric function periodic regression function parameter, its
Middle calculation method of parameters is as follows：
After analysis is finished every time, the state factor parameter value for continuing to gather next cycle is put into state factor argument sequence
End, while by the state factor parameter value of collection is deleted earliest in original state factor parameter sequence, hold mode factor parameter
Sequence size is m.
Step 103, in given display device the fault trend information is carried out into visual presentation.
The technical scheme that the present embodiment is provided is monitored by the equipment included in information application system, and using pre-
If failure trend prediction rule, the Monitoring Data to getting carries out data processing, obtains corresponding fault trend letter
Breath, realizes the Accurate Prediction of fault trend, i.e., " alarm in advance ", and then is favorably improved information system security reliability service guarantor
Barrier ability.
It should be noted that：For foregoing each method embodiment, in order to be briefly described, therefore it is all expressed as a series of
Combination of actions, but those skilled in the art should know, the present invention not by described by sequence of movement limited because
According to the present invention, some steps can sequentially or simultaneously be carried out using other.Secondly, those skilled in the art should also know
Know, embodiment described in this description belongs to preferred embodiment, involved action and module is not necessarily of the invention
It is necessary.
As shown in Fig. 2 the structural representation of information application system failure trend prediction device of the present invention.The present embodiment is provided
Described device can realize above-described embodiment one provide methods described.Specifically, the described device that the present embodiment is provided includes：
Monitoring modular 1, for being monitored at least one equipment included in information application system, and obtains monitoring number
According to；
Processing module 2, for using default failure trend prediction rule, the Monitoring Data to getting to enter line number
According to treatment, corresponding fault trend information is obtained；
Display module 3, for the fault trend information to be carried out into visual presentation in given display device.
The technical scheme that the present embodiment is provided is monitored by the equipment included in information application system, and using pre-
If failure trend prediction rule, the Monitoring Data to getting carries out data processing, obtains corresponding fault trend letter
Breath, realizes the Accurate Prediction of fault trend, i.e., " alarm in advance ", and then is favorably improved information system security reliability service guarantor
Barrier ability.
Further, when the distributed monitoring approach using intelligent agent, intelligent prison is installed on every monitored equipment
When SMA is acted on behalf of in control, described monitoring modular, including：
SMA is acted on behalf of in intelligent monitoring, for being monitored at least one equipment included in described information application system, is obtained
To Monitoring Data；
Monitoring service end, the Monitoring Data that SMA is monitored is acted on behalf of for obtaining the intelligent monitoring；
Wherein, the monitoring service end obtains between SMA is acted on behalf of in the intelligent monitoring and transmits the monitoring by XML format
Data.
Further, the monitoring service end, specifically for：
SMA is acted on behalf of according to intelligent monitoring described in the regular taking turn in setting time interval, SMA is acted on behalf of to obtain the intelligent monitoring
The Monitoring Data for monitoring.
Further, SMA is acted on behalf of in the intelligent monitoring, is additionally operable to set up heartbeat with the monitoring service end and is connected；
The monitoring service end, is additionally operable to, when monitoring that SMA heartbeats connection time-out is acted on behalf of in the intelligent monitoring, draw institute
State intelligent monitoring and act on behalf of the corresponding device fails of SMA, and generate corresponding failure message；
Wherein, the failure message is included in the Monitoring Data.
Further, when the network monitoring mode using snmp protocol, the monitoring modular, specifically for：
The network performance of at least one equipment and network errors to being included in described information application system are monitored,
And obtain Monitoring Data.
Further, when the hostdown using intelligent agent diagnoses monitor mode, it is provided with every monitored equipment
When SMA is acted on behalf of in intelligent monitoring, the monitoring modular, including：
SMA is acted on behalf of in the intelligent monitoring, for according to the monitoring policy specified, to what is included in described information application system
At least one equipment is monitored；
Monitoring master server, acts on behalf of SMA for receiving the intelligent monitoring and is sent out when the equipment operation exception is monitored
The alarm sent or failure message；
Wherein, the alarm or failure message are included in the Monitoring Data.
Further, SMA is acted on behalf of in the intelligent monitoring, is additionally operable to set up heartbeat and be connected with the monitoring master server；
The monitoring master server, when being additionally operable to monitor that SMA heartbeats connection time-out is acted on behalf of in the intelligent monitoring, draws institute
State intelligent monitoring and act on behalf of the corresponding device fails of SMA, and generate corresponding failure message；
Wherein, the failure message is included in the Monitoring Data.
Further, the processing module, including：
First processing units, for using default linear regression algorithm and Exponential Backoff Algorithm, described in getting
Monitoring Data carries out data processing, obtains corresponding failure future trend information；
Second processing unit, for using default trigonometric function regression algorithm, the Monitoring Data to getting is entered
Row data processing, obtains corresponding troublesome periodic tendency information；
Wherein, the fault trend information includes failure future trend information and troublesome periodic tendency information.
Further, the first processing units, specifically for：
(1) linear regression algorithm
Using in described information application system the Monitoring Data related to failure as linear regression algorithm sample data set,
The historical data that described information application system occurs various failures is collected, wherein, the historical data includes various failures
The specific time, there is the number of times of the failure in a period of time, and there are corresponding state factor data during the failure every time；
Partial Correlation Analysis are carried out, that is, determine that described information application system setting future period is expected the major failure for occurring,
Wherein, major failure is that any two partial correlation coefficient is more than or equal to -1 and the failure less than or equal to 1；
Using method of gradual regression, each described major failure to determining sets up reflecting for failure and state factor data respectively
Governing equation is penetrated, and carries out F inspections, if level of signifiance P can not meet P ＜ given thresholds, reject the major failure, it is no
Then retain the mapping relations equation of the failure and state factor data set up by the major failure；
The Monitoring Data state factor parameter value of setting future period described in prediction described information application system, and will prediction
The state factor parameter value haveing is substituted into the failure of the reservation and the mapping relations equation of state factor data,
Draw the probable value and failure future trend information of corresponding failure；
(2) Exponential Backoff Algorithm
Calculated using the default Exponential Backoff Algorithm according to the Monitoring Data state factor argument sequence value for collecting
Monitoring Data predicted value in the described information application system following multiple cycle：
The state factor argument sequence for being gathered is { y1, y2... ..., yn, acquisition time sequence is { t1, t2... ...,
tn, the index return function for using for：Y=cedt；
Wherein c and d is the parameter of index return function, and calculation method of parameters is：
Wherein,
Using equation below, the state factor parameter prediction of following a cycle is calculated according to above-mentioned parameter result of calculation
Value：
Further, the second processing unit, specifically for：
Take out finally the state factor parameter value of collection and its before m-1 shape in Monitoring Data state factor argument sequence
State factor parameter value carries out periodicity analysis, according to state factor ginseng in the state factor parameter value calculation this period for collecting
The cyclic parameter of numerical value change, obtains periodic regression analytic function, then draws state factor parameter value according to the function
The cyclic curve of change；
The periodicity analysis algorithm is specific as follows：The state factor argument sequence for being gathered is { y1, y2 ... ..., yn },
Acquisition time sequence be { t1, t2 ... ..., tn }, the trigonometric function regression function for using for：
Wherein k is default partial wave number, and the precision for controlling trigonometric function periodic regression, m is state factor parameter
The size of sequence, ej(j=0,1 ..., k) and fj(j=1,2 ..., k) for trigonometric function periodic regression function parameter, its
Middle calculation method of parameters is as follows：
After analysis is finished every time, the state factor parameter value for continuing to gather next cycle is put into state factor argument sequence
End, while by the state factor parameter value of collection is deleted earliest in original state factor parameter sequence, hold mode factor parameter
Sequence size is m.
In the above-described embodiments, the description to each embodiment all emphasizes particularly on different fields, and does not have the portion described in detail in certain embodiment
Point, may refer to the associated description of other embodiment.
Claims (9)
1. towards the information application system failure trend prediction method of power business, it is characterised in that including：
At least one equipment to being included in information application system is monitored, and obtains Monitoring Data；
Using default failure trend prediction rule, the Monitoring Data to getting carries out data processing, obtains corresponding
Fault trend information；
The fault trend information is carried out into visual presentation in given display device.
2. method according to claim 1, it is characterised in that at least one equipment includes：In information application system
It is any one or more in server, storage device, interchanger and the router node specified；
The Monitoring Data includes network interface layer data, server layer data, service layer data and application layer data；Wherein,
The network interface layer data include IP address, MAC Address, routing table, port existing state, up-downgoing flow；
The server layer data include cpu load, memory usage, process status, magnetic disc i/o；
Service layer's data include middleware, the status data of database platform software；
The application layer data includes the performance state data of information application system.
3. method according to claim 1, it is characterised in that
When the distributed monitoring approach using intelligent agent, when intelligent monitoring being installed on every monitored equipment acting on behalf of SMA, institute
State at least one equipment to being included in information application system to be monitored, and obtain Monitoring Data, including：
Intelligent monitoring acts on behalf of SMA and at least one equipment included in described information application system is monitored, and obtains monitoring number
According to；
Monitoring service end obtains the intelligent monitoring and acts on behalf of the Monitoring Data that SMA is monitored, the monitoring service end according to
Setting time be spaced regular taking turn described in intelligent monitoring act on behalf of SMA, acted on behalf of described in SMA monitors with obtaining the intelligent monitoring
Monitoring Data；
Wherein, the monitoring service end obtains between SMA is acted on behalf of in the intelligent monitoring and transmits the monitoring number by XML format
According to.
At least one equipment to being included in information application system is monitored, and obtains Monitoring Data, also includes：It is described
Intelligent monitoring acts on behalf of SMA and sets up heartbeat with the monitoring service end and is connected；The monitoring service end monitors the intelligent monitoring
When acting on behalf of SMA heartbeats connection time-out, show that the corresponding device fails of SMA are acted on behalf of in the intelligent monitoring, and generate corresponding
Failure message；Wherein, the failure message is included in the Monitoring Data；
When the network monitoring mode using snmp protocol, at least one equipment to being included in information application system is carried out
Monitoring, and Monitoring Data is obtained, including：To the network performance of at least one equipment that is included in described information application system and
Network errors are monitored, and obtain Monitoring Data；
When the hostdown using intelligent agent diagnoses monitor mode, intelligent monitoring agency is installed on every monitored equipment
During SMA, at least one equipment to being included in information application system is monitored, and obtains Monitoring Data, including：It is described
Intelligent monitoring acts on behalf of SMA according to the monitoring policy specified, and at least one equipment to being included in described information application system is carried out
Monitoring；Monitoring master server receives the intelligent monitoring and acts on behalf of the alarm that SMA sends when the equipment operation exception is monitored
Or failure message；Wherein, the alarm or failure message are included in the Monitoring Data；
At least one equipment to being included in information application system is monitored, and obtains Monitoring Data, also includes：It is described
Intelligent monitoring acts on behalf of SMA and sets up heartbeat and be connected with the monitoring master server；The monitoring master server monitors the intelligence
During monitoring agent SMA heartbeats connection time-out, show that the corresponding device fails of SMA are acted on behalf of in the intelligent monitoring, and generate phase
The failure message answered；Wherein, the failure message is included in the Monitoring Data.
4. method according to claim 3, it is characterised in that described using default failure trend prediction rule, to obtaining
The Monitoring Data got carries out data processing, obtains corresponding fault trend information, including：
Using default linear regression algorithm and Exponential Backoff Algorithm, the Monitoring Data to getting carries out data processing,
Obtain corresponding failure future trend information；
Using default trigonometric function regression algorithm, the Monitoring Data to getting carries out data processing, obtains corresponding
Troublesome periodic tendency information；
Wherein, the fault trend information includes failure future trend information and troublesome periodic tendency information.
5. method according to claim 4, it is characterised in that described to use default trigonometric function regression algorithm, to obtaining
The Monitoring Data got carries out data processing, obtains corresponding troublesome periodic tendency information, including：
Take out last collection in Monitoring Data state factor argument sequence state factor parameter value and its before m-1 state because
Sub-parameter value carries out periodicity analysis, according to state factor parameter value in the state factor parameter value calculation this period for collecting
The cyclic parameter of change, obtains periodic regression analytic function, then draws state factor parameter value variation according to the function
Cyclic curve；
The periodicity analysis algorithm is specific as follows：The state factor argument sequence for being gathered is { y1, y2 ... ..., yn }, collection
Time series be { t1, t2 ... ..., tn }, the trigonometric function regression function for using for：
Wherein k is default partial wave number, and the precision for controlling trigonometric function periodic regression, m is state factor argument sequence
Size, ej(j=0,1 ..., k) and fj(j=1,2 ..., k) for trigonometric function periodic regression function parameter, wherein joining
Number calculating method is as follows：
After analysis is finished every time, the state factor parameter value for continuing to gather next cycle is put into state factor argument sequence end
Tail, while by the state factor parameter value of collection is deleted earliest in original state factor parameter sequence, hold mode factor parameter sequence
Row size is m.
6. a kind of information application system failure trend prediction device, it is characterised in that including：
Monitoring modular, for being monitored at least one equipment included in information application system, and obtains Monitoring Data；
Processing module, for using default failure trend prediction rule, the Monitoring Data to getting to be carried out at data
Reason, obtains corresponding fault trend information；
Display module, for the fault trend information to be carried out into visual presentation in given display device.
7. device according to claim 6, it is characterised in that
When the distributed monitoring approach using intelligent agent, when intelligent monitoring being installed on every monitored equipment acting on behalf of SMA, institute
Monitoring modular is stated, including：
SMA is acted on behalf of in intelligent monitoring, for being monitored at least one equipment included in described information application system, is supervised
Survey data；
Monitoring service end, the Monitoring Data that SMA is monitored is acted on behalf of for obtaining the intelligent monitoring；
Wherein, the monitoring service end obtains between SMA is acted on behalf of in the intelligent monitoring and transmits the monitoring number by XML format
According to.
SMA is acted on behalf of in the intelligent monitoring, is additionally operable to set up heartbeat with the monitoring service end and is connected；The monitoring service end, also
For when monitoring that SMA heartbeats connection time-out is acted on behalf of in the intelligent monitoring, showing that the intelligent monitoring acts on behalf of that SMA is corresponding to be set
It is standby to break down, and generate corresponding failure message；Wherein, the failure message is included in the Monitoring Data；
When the network monitoring mode using snmp protocol, the monitoring modular, specifically for：To in described information application system
Comprising at least one equipment network performance and network errors be monitored, and obtain Monitoring Data；
When the hostdown using intelligent agent diagnoses monitor mode, intelligent monitoring agency is installed on every monitored equipment
During SMA, the monitoring modular, including：SMA is acted on behalf of in the intelligent monitoring, for according to the monitoring policy specified, to described information
At least one equipment included in application system is monitored；Monitoring master server, SMA is acted on behalf of for receiving the intelligent monitoring
The alarm sent when the equipment operation exception is monitored or failure message；Wherein, the alarm or failure message are included in
The Monitoring Data；
SMA is acted on behalf of in the intelligent monitoring, is additionally operable to set up heartbeat and be connected with the monitoring master server；The main service of monitoring
Device, when being additionally operable to monitor that SMA heartbeats connection time-out is acted on behalf of in the intelligent monitoring, show that SMA correspondences are acted on behalf of in the intelligent monitoring
Device fails, and generate corresponding failure message；Wherein, the failure message is included in the Monitoring Data.
8. device according to claim 7, it is characterised in that the processing module, including：
First processing units, for using default linear regression algorithm and Exponential Backoff Algorithm, the monitoring to getting
Data carry out data processing, obtain corresponding failure future trend information；
Second processing unit, for using default trigonometric function regression algorithm, the Monitoring Data to getting enters line number
According to treatment, corresponding troublesome periodic tendency information is obtained；
Wherein, the fault trend information includes failure future trend information and troublesome periodic tendency information.
9. device according to claim 8, it is characterised in that the second processing unit, specifically for：
Take out last collection in Monitoring Data state factor argument sequence state factor parameter value and its before m-1 state because
Sub-parameter value carries out periodicity analysis, according to state factor parameter value in the state factor parameter value calculation this period for collecting
The cyclic parameter of change, obtains periodic regression analytic function, then draws state factor parameter value variation according to the function
Cyclic curve；
The periodicity analysis algorithm is specific as follows：The state factor argument sequence for being gathered is { y1, y2 ... ..., yn }, collection
Time series be { t1, t2 ... ..., tn }, the trigonometric function regression function for using for：
Wherein k is default partial wave number, and the precision for controlling trigonometric function periodic regression, m is state factor argument sequence
Size, ej(j=0,1 ..., k) and fj(j=1,2 ..., k) for trigonometric function periodic regression function parameter, wherein joining
Number calculating method is as follows：
After analysis is finished every time, the state factor parameter value for continuing to gather next cycle is put into state factor argument sequence end
Tail, while by the state factor parameter value of collection is deleted earliest in original state factor parameter sequence, hold mode factor parameter sequence
Row size is m.
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