CN101887387A - Method for remotely intelligently monitoring and analyzing RAID faults - Google Patents
Method for remotely intelligently monitoring and analyzing RAID faults Download PDFInfo
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- CN101887387A CN101887387A CN2010101405187A CN201010140518A CN101887387A CN 101887387 A CN101887387 A CN 101887387A CN 2010101405187 A CN2010101405187 A CN 2010101405187A CN 201010140518 A CN201010140518 A CN 201010140518A CN 101887387 A CN101887387 A CN 101887387A
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Abstract
The invention provides a method for remotely intelligently monitoring and analyzing RAID faults. A distributed data processing mode is adopted, and the working state of the RAID is monitored and predicted locally in real time; and when exception is discovered, a local computer sends RAID related parameters and the working state of the RAID to a Web servicer, and a server program determines the alarm level and a corresponding solution and timely informs a user of alarm information and a fault solution automatically generated by the system. The method has the advantages that: when the RAID has a fault or exception, the user is timely informed and the loss caused by data loss is avoided; the remotely intelligent fault diagnosis and problem solution provided for the user helps the user quickly position the fault and quickly and effectively solve the problem.
Description
Technical field
The present invention relates to Computer Storage, field of artificial intelligence, the method for specifically a kind of remotely intelligently monitoring and analyzing RAID faults.
Background technology
The user uses RAID, and both direction is arranged, and RAID0 improves the disk response speed; RAID1/RAID5/RAID10 realizes data redundancy, ensures data security.
For RAID1/RAID5/RAID1, if fall a hard disk, data can also effectively be recovered, if but after falling dish, the client is ignorant, and follow-up other hard disks that occur once more fall dish, and irremediable losing will appear in data.
Traditional method after generation RAID falls dish, provide the warning of aspects such as buzzing, backboard lamp, but these warnings all only limits to this locality.
Current, often trustship is to telecommunications room for client's computing machine, if fall dish, though local the triggering reported to the police, the client often and do not know.By the remote cross-network section can only the RAID method for supervising, can notify the client to change hard disk timely and effectively, thus standard the risk of loss of data.
For the problem that solves because of the RAID fault or the operation irregularity user is ignorant, the need intelligent trouble is judged and scheme is supported, the method for a kind of remotely intelligently monitoring RAID is proposed.
Summary of the invention
The method that the purpose of this invention is to provide a kind of remotely intelligently monitoring and analyzing RAID faults.
The objective of the invention is to realize in the following manner, adopt the distributed data processing pattern, local real time monitoring and the duty of predicting RAID, when sending now when unusual, local computer will be relevant with RAID parameter and the duty of RAID be sent to the Web service end, determine the rank and the corresponding processing scheme of alarm by serve end program, and the fault solution that warning information and system produce automatically in time informed the user, the architecture of this method comprises: local information is collected and pretreatment unit (1), communication unit (2) and long-distance intelligent decision-making and decision-making performance element (3), wherein:
Local information is collected and pretreatment unit (1), be responsible for collecting the information of this locality RAID card, physical disks and virtual disk relevant with RAID, comprise RAID model, type, temperature, the demarcation access speed of physical disks and actual speed, temperature, power up time, read-write situation, the size of virtual disk, RAID grade, duty, local program at first will influence the parameter valuesization of RAID work, utilize local default value that each running parameter is tentatively judged, be not inconsistent with local preset value, then data sent to service end;
Communication unit (2) is responsible for Data transmission between local client and the service end;
Long-distance intelligent decision-making and decision-making performance element (3), be responsible for receiving the data of sending by client, utilize the BP neural network that RAID information is judged, determine the grade and the type of warning according to judged result, from the solution storehouse, extract corresponding solution by type of alarm, and inform the user by mail, short message mode.
Local information is collected with pretreatment unit (1) can obtain the parameters that influence RAID work, and with parameter valuesization, with the working range or the normal condition comparison of local parameter preset, sends abnormal information to service end when the value of non-expectation occurring; Serve end program utilizes three layers of BP neural network of forward direction type that fault type is judged, and extracts corresponding solution according to fault type in scheme base, informs the user by short message mode at last, how to be carried out by user's decision.
The long-distance intelligent decision-making is carried out initialized sample data with the weights of performance element (3) to the BP neural network of making a strategic decision, and derives from experimental data and the experience that RAID is diagnosed; The training function of neural network is the product behind the centering adjustment point of normal distyribution function and window function; The fault scheme base is the result to the solution long-term accumulation of the various faults of RAID.
The invention has the beneficial effects as follows: RAID breaks down or in time informs the user when unusual, avoids factor according to losing the loss that brings.For the user provides long-range intelligentized fault diagnosis and issue-resolution, help the quick fault location of user, and effectively deal with problems rapidly.
Description of drawings
The RAID diagnostic method that accompanying drawing 1 is traditional;
The RAID diagnostic method of accompanying drawing 2 remote intelligents;
Embodiment
The implementation of this method is (with reference to the accompanying drawings 2):
1) information of RAID card, physical disks and the virtual disk that collection this locality is relevant with RAID, as RAID model, type, temperature, the demarcation access speed of physical disks and actual speed, temperature, power up time, read-write situation, the size of virtual disk, RAID grade, duty etc.;
2) local program at first will influence the parameter valuesization of RAID work, utilize local default value that each running parameter is tentatively judged;
3) if be not inconsistent, then adopt the RPC agreement to send to service end with the XML formatted data with local preset value;
4) receive the data of sending by client, utilize the BP neural network that RAID information is judged;
5) according to definite grade and the type of reporting to the police of judged result;
6) from solution storehouse (depositing), extract corresponding solution by type of alarm, and write journal file with text mode;
7) warning message and solution are informed the user by modes such as mail, notes.
Embodiment
Adopt the distributed data processing pattern, the duty of local real time monitoring and prediction RAID, when sending (may break down) when now unusual, parameter that local computer will be relevant with RAID and the duty of RAID are sent to the Web service end.Determine the rank and corresponding processing scheme of alarm by serve end program, and the automatic fault solution that produces of warning information and system is informed the user by modes such as mail, notes.The architecture of this method comprises: local information is collected and pretreatment unit (1), communication unit (2), long-distance intelligent decision-making and decision-making performance element (3).Wherein:
Local information is collected and pretreatment unit (1), collect the information of this locality RAID card, physical disks and virtual disk relevant with RAID, as RAID model, type, temperature, the demarcation access speed of physical disks and actual speed, temperature, power up time, read-write situation, the size of virtual disk, RAID grade, duty etc.Local program at first will influence the parameter valuesization of RAID work, utilize local default value that each running parameter is tentatively judged, if be not inconsistent with local preset value, then data be sent to service end;
Communication unit (2), mainly responsible local client is communicated by letter with service, adopts the RPC agreement to transmit information with the XML form;
Long-distance intelligent decision-making and decision-making performance element (3), the data that reception is sent by client, utilize the BP neural network that RAID information is judged, determine the grade and the type of warning according to judged result, from solution storehouse (depositing), extract corresponding solution by type of alarm, and inform the user by modes such as mail, notes with text mode.
Claims (3)
1. the method for remotely intelligently monitoring and analyzing RAID faults, it is characterized in that, adopt the distributed data processing pattern, local real time monitoring and the duty of predicting RAID, when sending now when unusual, local computer will be relevant with RAID parameter and the duty of RAID be sent to the Web service end, determine the rank and the corresponding processing scheme of alarm by serve end program, and the fault solution that warning information and system produce automatically in time informed the user, the architecture of this method comprises: local information is collected and pretreatment unit (1), communication unit (2) and long-distance intelligent decision-making and decision-making performance element (3), wherein:
Local information is collected and pretreatment unit (1), be responsible for collecting the information of this locality RAID card, physical disks and virtual disk relevant with RAID, comprise RAID model, type, temperature, the demarcation access speed of physical disks and actual speed, temperature, power up time, read-write situation, the size of virtual disk, RAID grade, duty, local program at first will influence the parameter valuesization of RAID work, utilize local default value that each running parameter is tentatively judged, be not inconsistent with local preset value, then data sent to service end;
Communication unit (2) is responsible for Data transmission between local client and the service end;
Long-distance intelligent decision-making and decision-making performance element (3), be responsible for receiving the data of sending by client, utilize the BP neural network that RAID information is judged, determine the grade and the type of warning according to judged result, from the solution storehouse, extract corresponding solution by type of alarm, and inform the user by mail, short message mode.
2. method according to claim 1, it is characterized in that: local information is collected with pretreatment unit (1) can obtain the parameters that influences RAID work, and with parameter valuesization, with the working range of local parameter preset or normal condition relatively, send abnormal information to service end when the value of non-expectation occurring; Serve end program utilizes three layers of BP neural network of forward direction type that fault type is judged, and extracts corresponding solution according to fault type in scheme base, informs the user by short message mode at last, how to be carried out by user's decision.
3. method according to claim 1 is characterized in that: the long-distance intelligent decision-making is carried out initialized sample data with the weights of performance element (3) to the BP neural network of making a strategic decision, and derives from experimental data and the experience that RAID is diagnosed; The training function of neural network is the product behind the centering adjustment point of normal distyribution function and window function; The fault scheme base is the result to the solution long-term accumulation of the various faults of RAID.
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Cited By (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102819480A (en) * | 2011-06-08 | 2012-12-12 | 联想(北京)有限公司 | Computer and method for monitoring memory thereof |
| CN102866933A (en) * | 2012-09-03 | 2013-01-09 | 厦门市美亚柏科信息股份有限公司 | Method for judging type of redundant array of independent disks (RAID) |
| CN102968113A (en) * | 2012-11-16 | 2013-03-13 | 国电南瑞科技股份有限公司 | Failure analysis and exhibition method of power generator excitation system |
| CN103150233A (en) * | 2013-03-18 | 2013-06-12 | 厦门市美亚柏科信息股份有限公司 | Data recovery method of RAID-5 |
| CN103207820A (en) * | 2013-02-05 | 2013-07-17 | 北京百度网讯科技有限公司 | Method and device for fault positioning of hard disk on basis of raid card log |
| GB2504956A (en) * | 2012-08-14 | 2014-02-19 | Ibm | Management of RAID error recovery procedures and configuration |
| CN104486426A (en) * | 2014-12-17 | 2015-04-01 | 天脉聚源（北京）教育科技有限公司 | Early warning method and early warning device for intelligent teaching system |
| CN106301823A (en) * | 2015-05-19 | 2017-01-04 | 中兴通讯股份有限公司 | The fault alarming method of a kind of key component, device and big data management system |
| CN106980562A (en) * | 2016-01-18 | 2017-07-25 | 中兴通讯股份有限公司 | A kind of hard disk monitoring method and device |
| CN107133669A (en) * | 2017-07-13 | 2017-09-05 | 天津凯发电气股份有限公司 | Track traffic synthetic monitoring intelligent short message alarm method |
| CN107220009A (en) * | 2017-06-29 | 2017-09-29 | 济南浪潮高新科技投资发展有限公司 | The unified acquisition methods and device of a kind of different manufacturers RAID card status information |
| CN107623610A (en) * | 2017-09-22 | 2018-01-23 | 郑州云海信息技术有限公司 | A kind of monitoring method of application apparatus, device and computer-readable storage medium |
| CN110311802A (en) * | 2019-05-17 | 2019-10-08 | 网宿科技股份有限公司 | Network operation method, device, electronic equipment and storage medium |
| CN112527639A (en) * | 2020-12-02 | 2021-03-19 | 平安医疗健康管理股份有限公司 | Remote debugging method and device in production environment, computer equipment and storage medium |
| CN113221937A (en) * | 2021-02-24 | 2021-08-06 | 山东万博科技股份有限公司 | Emergency processing system and method based on artificial intelligence judgment |
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Cited By (20)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102819480A (en) * | 2011-06-08 | 2012-12-12 | 联想(北京)有限公司 | Computer and method for monitoring memory thereof |
| US9940211B2 (en) | 2012-08-14 | 2018-04-10 | International Business Machines Corporation | Resource system management |
| GB2504956A (en) * | 2012-08-14 | 2014-02-19 | Ibm | Management of RAID error recovery procedures and configuration |
| CN102866933A (en) * | 2012-09-03 | 2013-01-09 | 厦门市美亚柏科信息股份有限公司 | Method for judging type of redundant array of independent disks (RAID) |
| CN102968113A (en) * | 2012-11-16 | 2013-03-13 | 国电南瑞科技股份有限公司 | Failure analysis and exhibition method of power generator excitation system |
| CN103207820A (en) * | 2013-02-05 | 2013-07-17 | 北京百度网讯科技有限公司 | Method and device for fault positioning of hard disk on basis of raid card log |
| CN103207820B (en) * | 2013-02-05 | 2016-06-29 | 北京百度网讯科技有限公司 | The Fault Locating Method of hard disk and device based on raid card log |
| CN103150233A (en) * | 2013-03-18 | 2013-06-12 | 厦门市美亚柏科信息股份有限公司 | Data recovery method of RAID-5 |
| CN103150233B (en) * | 2013-03-18 | 2016-06-08 | 厦门市美亚柏科信息股份有限公司 | A kind of data reconstruction method of RAID-5 |
| CN104486426A (en) * | 2014-12-17 | 2015-04-01 | 天脉聚源（北京）教育科技有限公司 | Early warning method and early warning device for intelligent teaching system |
| CN106301823A (en) * | 2015-05-19 | 2017-01-04 | 中兴通讯股份有限公司 | The fault alarming method of a kind of key component, device and big data management system |
| CN106301823B (en) * | 2015-05-19 | 2020-12-18 | 中兴通讯股份有限公司 | Fault warning method and device for key component and big data management system |
| CN106980562A (en) * | 2016-01-18 | 2017-07-25 | 中兴通讯股份有限公司 | A kind of hard disk monitoring method and device |
| CN107220009A (en) * | 2017-06-29 | 2017-09-29 | 济南浪潮高新科技投资发展有限公司 | The unified acquisition methods and device of a kind of different manufacturers RAID card status information |
| CN107220009B (en) * | 2017-06-29 | 2020-02-14 | 浪潮集团有限公司 | Method and device for uniformly acquiring state information of RAID cards of different manufacturers |
| CN107133669A (en) * | 2017-07-13 | 2017-09-05 | 天津凯发电气股份有限公司 | Track traffic synthetic monitoring intelligent short message alarm method |
| CN107623610A (en) * | 2017-09-22 | 2018-01-23 | 郑州云海信息技术有限公司 | A kind of monitoring method of application apparatus, device and computer-readable storage medium |
| CN110311802A (en) * | 2019-05-17 | 2019-10-08 | 网宿科技股份有限公司 | Network operation method, device, electronic equipment and storage medium |
| CN112527639A (en) * | 2020-12-02 | 2021-03-19 | 平安医疗健康管理股份有限公司 | Remote debugging method and device in production environment, computer equipment and storage medium |
| CN113221937A (en) * | 2021-02-24 | 2021-08-06 | 山东万博科技股份有限公司 | Emergency processing system and method based on artificial intelligence judgment |
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