CN112559263A - Real-time intelligent hard disk monitoring and early warning system and method - Google Patents
Real-time intelligent hard disk monitoring and early warning system and method Download PDFInfo
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- G06F11/22—Detection or location of defective computer hardware by testing during standby operation or during idle time, e.g. start-up testing
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Abstract
The invention discloses a real-time hard disk intelligent monitoring and early warning system and a method, wherein a hard disk of a computer is connected with a user side, the system comprises a hot data layer and a cold data layer, data uploaded by the hard disk of the computer is transmitted to the hot data layer first, and when the available storage space of the hot data layer reaches a certain threshold value, the hot data layer can transfer the data which are accessed least recently to the cold data layer, or the data uploaded by the hard disk of the computer are directly stored to the cold data layer. The invention can provide the risk condition for the client in advance, prevent the data loss problem of the client, and in order to ensure the data safety problem of the client at the server operation stage, the monitoring and alarming function aiming at the hard disk operation state is realized by researching the parameters of the hard disk, when the hard disk has certain quality hidden trouble, the system can find the fault as soon as possible and inform the client to carry out data backup and hard disk replacement in advance by an alarming mode, thereby greatly reducing the risk of data loss.
Description
Technical Field
The invention relates to the field of hard disk monitoring control, in particular to a real-time hard disk intelligent monitoring and early warning system and method.
Background
With the increase of the physical machine service, hardware faults occur in a large number of servers with overlong service time, and other hardware fault problems can be solved for users through replacement of some accessories, so that the data level influence on the service of a client cannot be caused, but with the occurrence of the hard disk problem, the risks of data damage and data loss of the client are often accompanied. The computer normally runs, the hard disk file can be read normally, too many data response problems cannot exist, however, when the hard disk has problems, data on the server can be read slowly or cannot be read, data loss is caused, when the hard disk has problems, people cannot sense the data timely and effectively, and the data can be found only when a large fault occurs.
Disclosure of Invention
The invention aims to solve the problem that hard disk faults cannot be found in real time manually in the running process of a computer, and provides a real-time intelligent hard disk monitoring and early warning system and method.
In order to achieve the purpose, the invention adopts the following technical scheme:
on one hand, a real-time intelligent monitoring and early warning system for a hard disk is provided, the hard disk and a user side of a computer are connected, the system comprises a hot data layer and a cold data layer, data uploaded by the hard disk of the computer first reaches the hot data layer, and when the available storage space of the hot data layer reaches a certain threshold value, the hot data layer can transfer the data which are accessed least recently to the cold data layer, or the data uploaded by the hard disk of the computer are directly stored to the cold data layer;
the data redundancy strategy adopted by the thermal data layer is a copy replication mode, the storage server adopts a general server, the storage hard disks adopt common mechanical hard disks, and the common mechanical hard disks form an RAID0 disk array to improve the data read-write performance;
the data redundancy strategy adopted by the cold data layer is an erasure code mode, the storage server adopts a customized 1U16 storage server which is low in cost and power consumption and can manage the power supply of a single hard disk in a fine-grained manner, the storage hard disk adopts a common mechanical hard disk, and the power on and off of the storage hard disk can be controlled through an I2C interface.
Preferably, the cold data layer mainly comprises a control node, a transmission node, a storage node, a log node and a database cluster, and provides service for cold data storage.
Preferably, the control node runs on a general server and serves as a control and decision center of a cold data layer, the control node sends control messages to the transmission node, the storage node and the log node, collects heartbeat of the transmission node, the storage node and the log node and node up-down state information, and monitors the overall running condition of the cold data layer; the control node is used for selecting a certain transmission node according to the load condition of the transmission node to perform data interaction with the client so as to perform load balancing, planning data to be stored in the detailed position of the storage node, and writing the metadata into the database cluster.
Preferably, the transmission node runs on a general server and serves as a data calculation and data transmission center of a cold data layer; when data are uploaded, the transmission nodes receive the data through HTTP requests, check data are calculated according to an erasure code algorithm, and the original data and the check code data are transmitted to different storage nodes through SOCKET channels to be stored; when downloading data, the transmission node pulls the data from the storage node and receives the data through the SOCKET channel, original data are reconstructed, and the original data are sent to the client through the HTTP request.
Preferably, the storage node generally operates on a customized 1U16 storage server and serves as a data storage center of a cold data layer, and the storage node is responsible for data interaction with the transmission node through a SOCKET channel and stores data at a position determined by the control node; the storage node reports the state information of the hard disk to the control node, receives the operation management of the control node on the power-on and power-off of the hard disk, regularly checks the health state of the hard disk, regularly scans the data of the hard disk and reports the position of the data block with the error check to the control node task.
Preferably, the log nodes are divided into log service and log collection programs, the log service program and the control node are generally operated on the same general server and serve as a log service center, and log query search service is provided for operation and maintenance personnel to analyze.
Preferably, the database cluster generally runs on a general-purpose server, and can run on the same server as the control node to serve as a storage center for the metadata.
The invention also provides a real-time intelligent hard disk monitoring and early warning method, which comprises the following steps:
s1: installing a hard disk detection service on the server and acquiring health parameters of the hard disk in real time;
s2: synchronizing the acquired data to a monitoring system in real time, and counting and comparing the data by the monitoring system;
s3: when the acquired data is fault data, triggering threshold setting of a monitoring system;
s4: the monitoring system searches the contact information of the corresponding responsible person and sends out warning information to the responsible person through the information.
Preferably, in the second step, the statistics and comparison of the data further include:
s21, constructing a data set and preprocessing the data, namely dividing historical data of the hard disk into a training data set and a testing data set, preprocessing the data in the data set, converting the data into data which can be used by a fault prediction model construction algorithm, and preprocessing the data, wherein the preprocessing method comprises processing abnormal values in the data, selecting data characteristics and normalizing the data;
s22, constructing a hard disk fault prediction model according to different model training algorithms by using the training data set obtained in S21;
s23, testing and evaluating a hard disk fault prediction model, wherein the hard disk fault prediction model is usually constructed by multiple times of training and optimization results and is not a one-time training process, parameters in the model are selected for multiple times of different values in the training process, and model prediction performance tests under different parameter values are carried out to ensure that the model trained by the algorithm is close to the optimum to the maximum extent, a test data set is used for evaluating the performance of the prediction model constructed on the training data set in the testing process, a cross validation method is usually used in the testing process, and evaluation indexes comprise accuracy, accuracy and recall rate.
Preferably, in step S22, the hard disk failure prediction model construction algorithm includes a bayesian network algorithm, a naive bayes algorithm, a neural network algorithm, a decision tree algorithm, and a support vector machine algorithm.
The invention has the advantages that the risk condition can be provided for the client in advance, the data loss problem of the client is prevented, in order to ensure the data safety problem of the client at the server operation stage, the monitoring and alarming function aiming at the hard disk operation state is realized by researching the parameters of the hard disk, when the hard disk has certain quality hidden trouble, the system can find the fault as soon as possible and inform the client to carry out data backup and hard disk replacement in advance by an alarming mode, and the risk of data loss is greatly reduced.
Drawings
FIG. 1 is a schematic diagram of an application of the real-time intelligent monitoring and early warning system for a hard disk according to the present invention;
FIG. 2 is a block diagram of a real-time intelligent monitoring and early warning system for a hard disk according to the present invention;
fig. 3 is a block diagram of a structure of a cold data layer.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
Referring to fig. 1-2, this embodiment provides a real-time intelligent hard disk monitoring and early warning system, which connects a hard disk of a computer and a user side, where the system includes a hot data layer and a cold data layer, data uploaded by the hard disk of the computer first arrives at the hot data layer, and when an available storage space of the hot data layer reaches a certain threshold, the hot data layer may transfer data that is least recently accessed to the cold data layer, or data uploaded by the hard disk of the computer is directly stored in the cold data layer;
the data redundancy strategy adopted by the thermal data layer is a copy replication mode, the storage server adopts a general server, the storage hard disks adopt common mechanical hard disks, and the common mechanical hard disks form an RAID0 disk array to improve the data read-write performance;
the data redundancy strategy adopted by the cold data layer is an erasure code mode, the storage server adopts a customized 1U16 storage server which is low in cost and power consumption and can manage the power supply of a single hard disk in a fine-grained manner, the storage hard disk adopts a common mechanical hard disk, and the power on and off of the storage hard disk can be controlled through an I2C interface.
As shown in fig. 3, the cold data layer is mainly composed of a control node, a transmission node, a storage node, a log node, and a database cluster, and provides services for cold data storage.
The control node runs on a general server and serves as a control and decision center of a cold data layer, sends control messages to the transmission node, the storage node and the log node, collects heartbeat information and node up-down line state information of the transmission node, the storage node and the log node, and monitors the whole running condition of the cold data layer; the control node is used for selecting a certain transmission node according to the load condition of the transmission node to perform data interaction with the client so as to perform load balancing, planning data to be stored in the detailed position of the storage node, and writing the metadata into the database cluster.
The transmission node runs on a general server and is used as a data calculation and data transmission center of a cold data layer; when data are uploaded, the transmission nodes receive the data through HTTP requests, check data are calculated according to an erasure code algorithm, and the original data and the check code data are transmitted to different storage nodes through SOCKET channels to be stored; when downloading data, the transmission node pulls the data from the storage node and receives the data through the SOCKET channel, original data are reconstructed, and the original data are sent to the client through the HTTP request.
The storage nodes generally run on a customized 1U16 storage server and serve as a data storage center of a cold data layer, and the storage nodes are responsible for data interaction with the transmission nodes through SOCKET channels and store data at positions determined by the control nodes; the storage node reports the state information of the hard disk to the control node, receives the operation management of the control node on the power-on and power-off of the hard disk, regularly checks the health state of the hard disk, regularly scans the data of the hard disk and reports the position of the data block with the error check to the control node task.
The log nodes are divided into log service and log collection programs, the log service program and the control node are generally operated on the same general server and used as a log service center to provide log query and search service for operation and maintenance personnel to analyze.
The database cluster generally runs on a general server and can run on the same server as the control node to serve as a storage center of the metadata.
The embodiment also provides a real-time intelligent hard disk monitoring and early warning method, which comprises the following steps:
s1: installing a hard disk detection service on the server and acquiring health parameters of the hard disk in real time;
s2: synchronizing the acquired data to a monitoring system in real time, and counting and comparing the data by the monitoring system;
s3: when the acquired data is fault data, triggering threshold setting of a monitoring system;
s4: the monitoring system searches the contact information of the corresponding responsible person and sends out warning information to the responsible person through the information.
In S2, the statistics and comparison of data further include:
s21, constructing a data set and preprocessing the data, namely dividing historical data of the hard disk into a training data set and a testing data set, preprocessing the data in the data set, converting the data into data which can be used by a fault prediction model construction algorithm, and preprocessing the data, wherein the preprocessing method comprises processing abnormal values in the data, selecting data characteristics and normalizing the data;
s22, constructing a hard disk fault prediction model according to different model training algorithms by using the training data set obtained in S21, wherein the hard disk fault prediction model construction algorithms comprise a Bayes network algorithm, a naive Bayes algorithm, a neural network algorithm, a decision tree algorithm and a support vector machine algorithm;
s23, testing and evaluating a hard disk fault prediction model, wherein the hard disk fault prediction model is usually constructed by multiple times of training and optimization results and is not a one-time training process, parameters in the model are selected for multiple times of different values in the training process, and model prediction performance tests under different parameter values are carried out to ensure that the model trained by the algorithm is close to the optimum to the maximum extent, a test data set is used for evaluating the performance of the prediction model constructed on the training data set in the testing process, a cross validation method is usually used in the testing process, and evaluation indexes comprise accuracy, accuracy and recall rate.
Preferably, in step S22,
in the description of the present invention, it should be further noted that, unless otherwise specifically stated or limited, the terms "disposed," "mounted," "connected," and "connected" are to be construed broadly and may be, for example, fixedly connected, detachably connected, integrally connected, mechanically connected, electrically connected, directly connected, connected through an intermediate medium, or connected through the insides of two elements. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (10)
1. A real-time hard disk intelligent monitoring and early warning system is connected with a hard disk of a computer and a user side and is characterized in that the system comprises a hot data layer and a cold data layer, data uploaded by the hard disk of the computer first reaches the hot data layer, and when the available storage space of the hot data layer reaches a certain threshold value, the hot data layer can transfer the data which are accessed least recently to the cold data layer, or the data uploaded by the hard disk of the computer are directly stored to the cold data layer;
the data redundancy strategy adopted by the thermal data layer is a copy replication mode, the storage server adopts a general server, the storage hard disks adopt common mechanical hard disks, and the common mechanical hard disks form an RAID0 disk array to improve the data read-write performance;
the data redundancy strategy adopted by the cold data layer is an erasure code mode, the storage server adopts a customized 1U16 storage server which is low in cost and power consumption and can manage the power supply of a single hard disk in a fine-grained manner, the storage hard disk adopts a common mechanical hard disk, and the power on and off of the storage hard disk can be controlled through an I2C interface.
2. The system of claim 1, wherein the cold data layer is mainly composed of a control node, a transmission node, a storage node, a log node and a database cluster, and provides services for cold data storage.
3. The real-time intelligent hard disk monitoring and early warning system according to claim 2, wherein the control node runs on a general server and serves as a control and decision center of a cold data layer, the control node sends control messages to the transmission node, the storage node and the log node, collects heartbeat information of the transmission node, the storage node and the log node and upper and lower line state information of the nodes, and monitors the overall running condition of the cold data layer; the control node is used for selecting a certain transmission node according to the load condition of the transmission node to perform data interaction with the client so as to perform load balancing, planning data to be stored in the detailed position of the storage node, and writing the metadata into the database cluster.
4. The system of claim 2, wherein the transmission node operates on a general-purpose server and serves as a data computation and data transmission center of a cold data layer; when data are uploaded, the transmission nodes receive the data through HTTP requests, check data are calculated according to an erasure code algorithm, and the original data and the check code data are transmitted to different storage nodes through SOCKET channels to be stored; when downloading data, the transmission node pulls the data from the storage node and receives the data through the SOCKET channel, original data are reconstructed, and the original data are sent to the client through the HTTP request.
5. The real-time intelligent hard disk monitoring and early warning system as claimed in claim 2, wherein the storage node generally operates on a customized 1U16 storage server as a data storage center of a cold data layer, and the storage node is responsible for data interaction with the transmission node through SOCKET channels, and stores data at a position determined by the control node; the storage node reports the state information of the hard disk to the control node, receives the operation management of the control node on the power-on and power-off of the hard disk, regularly checks the health state of the hard disk, regularly scans the data of the hard disk and reports the position of the data block with the error check to the control node task.
6. The real-time intelligent hard disk monitoring and early warning system as claimed in claim 2, wherein the log nodes are divided into log service and log collection programs, the log service program and the control node are generally operated on the same general server as a log service center, and the log service center provides log query search service for analysis of operation and maintenance personnel.
7. A real-time intelligent hard disk monitoring and early warning system as claimed in claim 2, wherein the database cluster is generally operated on a general-purpose server, and can be operated on the same server as the control node to serve as a storage center of the metadata.
8. A real-time intelligent hard disk monitoring and early warning method is characterized by comprising the following steps:
s1: installing a hard disk detection service on the server and acquiring health parameters of the hard disk in real time;
s2: synchronizing the acquired data to a monitoring system in real time, and counting and comparing the data by the monitoring system;
s3: when the acquired data is fault data, triggering threshold setting of a monitoring system;
s4: the monitoring system searches the contact information of the corresponding responsible person and sends out warning information to the responsible person through the information.
9. The real-time intelligent monitoring and early warning method for the hard disk according to claim 8, wherein in the second step, the statistics and comparison of the data further comprises:
s21, constructing a data set and preprocessing the data, namely dividing historical data of the hard disk into a training data set and a testing data set, preprocessing the data in the data set, converting the data into data which can be used by a fault prediction model construction algorithm, and preprocessing the data, wherein the preprocessing method comprises processing abnormal values in the data, selecting data characteristics and normalizing the data;
s22, constructing a hard disk fault prediction model according to different model training algorithms by using the training data set obtained in S21;
s23, testing and evaluating a hard disk fault prediction model, wherein the hard disk fault prediction model is usually constructed by multiple times of training and optimization results and is not a one-time training process, parameters in the model are selected for multiple times of different values in the training process, and model prediction performance tests under different parameter values are carried out to ensure that the model trained by the algorithm is close to the optimum to the maximum extent, a test data set is used for evaluating the performance of the prediction model constructed on the training data set in the testing process, a cross validation method is usually used in the testing process, and evaluation indexes comprise accuracy, accuracy and recall rate.
10. The real-time intelligent monitoring and early warning method for the hard disk as claimed in claim 9, wherein in step S22, the hard disk failure prediction model construction algorithm comprises a bayesian network algorithm, a naive bayes algorithm, a neural network algorithm, a decision tree algorithm and a support vector machine algorithm.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116680114A (en) * | 2023-08-04 | 2023-09-01 | 浙江鹏信信息科技股份有限公司 | LVM fault data quick recovery method, system and computer readable storage medium |
| CN116701150A (en) * | 2023-06-19 | 2023-09-05 | 深圳市银闪科技有限公司 | Storage data safety supervision system and method based on Internet of things |
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- 2020-12-03 CN CN202011411836.2A patent/CN112559263A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116701150A (en) * | 2023-06-19 | 2023-09-05 | 深圳市银闪科技有限公司 | Storage data safety supervision system and method based on Internet of things |
| CN116701150B (en) * | 2023-06-19 | 2024-01-16 | 深圳市银闪科技有限公司 | Storage data safety supervision system and method based on Internet of things |
| CN116680114A (en) * | 2023-08-04 | 2023-09-01 | 浙江鹏信信息科技股份有限公司 | LVM fault data quick recovery method, system and computer readable storage medium |
| CN116680114B (en) * | 2023-08-04 | 2023-10-31 | 浙江鹏信信息科技股份有限公司 | LVM fault data quick recovery method, system and computer readable storage medium |
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Application publication date: 20210326 |