White board data management system and method based on touch all-in-one machine
By implementing real-time monitoring and early warning mechanisms, the problem of content loss caused by database anomalies was resolved, ensuring the stability and reliability of the whiteboard data management system and preventing the impact on important tasks.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SHENZHEN HEIJIN IND MFG CO LTD
- Filing Date
- 2023-10-12
- Publication Date
- 2026-04-21
AI Technical Summary
In existing whiteboard data management systems based on touch screen all-in-one machines, if abnormal database operation is not detected in time, it may lead to the permanent loss of user-created content, increase maintenance difficulty, and have a serious impact on education, enterprise collaboration, and meetings.
The data acquisition module monitors the performance of the database's storage devices and resource utilization indicators in real time, generates a risk index, and compares it with preset thresholds through a comparison and analysis module to issue early warnings, reminding users to perform timely maintenance and management to prevent data loss.
It effectively prevents the permanent loss of user-created content, reduces the risk of escalating database anomalies, ensures stable system operation, and reduces the difficulty of later maintenance.
Smart Images
Figure CN121901045A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of whiteboard data management technology, specifically to a whiteboard data management system and method based on a touch screen all-in-one machine. Background Technology
[0002] Whiteboard data management based on touch screen all-in-one machines combines digital whiteboard content with hardware devices to enable users in education, business, and other fields to better create, save, share, and manage whiteboard content. It allows users to use touch screen whiteboards for digital creation, presentation, and collaboration, while providing data management and sharing functions.
[0003] In a whiteboard data management system based on a touchscreen all-in-one machine, the database plays a crucial role with multiple important functions. The database is used to store user-created content, such as presentations, charts, drawings, text, and multimedia files. This data needs to be stored long-term so that users can access and edit it at any time. The database management system allows data to be organized, classified, and retrieved. Users can easily find and access the content they have created without having to manually manage files or content. The database allows multiple users to access and share the same content, which is very useful in educational and collaborative environments. Multiple users can collaborate to edit the same document or whiteboard simultaneously.
[0004] The existing technology has the following shortcomings: In the existing technology, most whiteboard data management systems based on touch screen all-in-one machines adopt a regular maintenance approach to manage their databases. However, when the database is in an abnormal operating state but is not detected in time, the content created by users may be permanently lost, including presentations, charts, drawings, text, or other media. This may have a serious impact on important work in fields such as education, enterprise collaboration, and meetings. Secondly, if the abnormal operating state of the database is not detected in time, the abnormality will become more serious, increasing the difficulty of later maintenance.
[0005] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention
[0006] The purpose of this invention is to provide a whiteboard data management system and method based on a touch screen all-in-one machine. By monitoring the operating status of the database in the whiteboard data management system in real time, when there is a risk of permanent loss when the database stores user-created content, the system reminds the user to perform relevant maintenance and management work on the database in advance and take measures to save the created content separately in a timely manner. This effectively prevents the permanent loss of user-created content and avoids serious impact on important work in fields such as education, enterprise collaboration, and meetings. Secondly, performing relevant maintenance and management work on the abnormally operating database in advance can also effectively prevent the database abnormality from becoming more serious, thereby reducing the difficulty of later maintenance and solving the problems in the background art mentioned above.
[0007] To achieve the above objectives, the present invention provides the following technical solution: a whiteboard data management system based on a touch screen all-in-one machine, comprising a data acquisition module, a central processing unit, a comparison and analysis module, and a prompting module;
[0008] The data acquisition module collects multiple data information during the database operation of the whiteboard data management system based on the touch screen all-in-one machine, including storage device performance indicators and resource utilization indicators. After collection, the storage device performance indicators and resource utilization indicators of the database operation are processed and uploaded to the central processing unit.
[0009] The central processing unit comprehensively analyzes the storage device performance indicators and resource utilization indicators after the database has been processed during runtime, generates a risk index, and transmits the risk index to the comparison and analysis module.
[0010] The comparison and analysis module compares the risk index generated by the database during runtime with the pre-set risk index reference threshold, generates a high-risk signal or a low-risk signal, and transmits the signal to the alert module, which then issues a warning alert for the high-risk signal.
[0011] Preferably, the storage device performance indicators during database operation include disk temperature anomaly deviation coefficient and disk write rate anomaly concealment coefficient, and the resource utilization indicators during database operation include IO wait time anomaly concealment coefficient. After collection, the disk temperature anomaly deviation coefficient and disk write rate anomaly concealment coefficient are respectively calibrated as ωω by the data acquisition module. τ and θθ τ The anomaly concealment coefficient of IO wait time is calibrated as ββ. π .
[0012] Preferably, the logic for obtaining the disk temperature abnormal deviation coefficient is as follows:
[0013] S101. Obtain the optimal operating temperature of the database disk in the whiteboard data management system during normal operation, and calibrate the optimal operating temperature as ωω. 最佳 ;
[0014] S102. Obtain the actual temperature values of the database disk in the whiteboard data management system at different times during time T, and calibrate the actual temperature values as ωω. x x represents the number of the actual temperature value at different times within time T in the whiteboard data management system database disk during runtime, x = 1, 2, 3, 4, ..., m, where m is a positive integer;
[0015] S103. Compare the actual temperature value obtained by the database disk in the whiteboard data management system during time T with the optimal operating temperature of the database disk during normal operation, and recalibrate the actual temperature value that is greater than the optimal operating temperature as ωω. x′ x′ represents the number of the actual temperature value that is greater than the optimal operating temperature obtained by the database disk in the whiteboard data management system during time T. x′ = 1, 2, 3, 4, ..., m′, where m′ is a positive integer.
[0016] S104. Calculate the disk temperature abnormal deviation coefficient. The expression for the calculation is:
[0017] Preferably, the logic for obtaining the disk write rate anomaly concealment coefficient is as follows:
[0018] S201. Obtain the optimal write speed range for the database disk in the whiteboard data management system during operation, and define the optimal write speed range as...
[0019] S202. Obtain the actual average write rate of the database disk in the whiteboard data management system during different time periods within time T, and calibrate the actual average write rate as... y represents the number of the actual average write rate of the database disk in the whiteboard data management system during different time periods within time T, y = 1, 2, 3, 4, ..., n, where n is a positive integer;
[0020] S203. Compare the actual average write rate and the optimal write rate range obtained by the database disk in the whiteboard data management system during time T, and recalibrate the actual average write rate that is not within the optimal write rate range. y′ represents the number of the actual average write rate that is not within the optimal write rate range obtained by the database disk in the whiteboard data management system during time T. y′=1, 2, 3, 4, …, n′, where n′ is a positive integer.
[0021] S204. Calculate the disk write rate anomaly concealment coefficient. The expression for the calculation is: n represents the total number of actual average write rates obtained by the database disk during time T in the whiteboard data management system.
[0022] Preferably, the logic for obtaining the anomaly concealment coefficient of IO wait time is as follows:
[0023] S301. Obtain several actual I / O wait times generated by the database in the whiteboard data management system during runtime within time T, and label the actual I / O wait times as... k represents the number of the actual I / O wait time generated during the database runtime in the whiteboard data management system within time T, k = 1, 2, 3, 4, ..., p, where p is a positive integer;
[0024] S302. Compare several actual I / O wait times obtained by the database in the whiteboard data management system during time T with a pre-set I / O wait time reference threshold, and recalibrate the actual I / O wait times that exceed the I / O wait time reference threshold. k′ represents the number of the actual IO wait time greater than the IO wait time reference threshold obtained by the database during time T in the whiteboard data management system. k′ = 1, 2, 3, 4, ..., p′, where p′ is a positive integer.
[0025] S303. Calculate the anomaly concealment coefficient of IO wait time. The expression for the calculation is: p represents the total number of actual I / O wait times acquired during database runtime in the whiteboard data management system within time T.
[0026] Preferably, the central processing unit obtains the disk temperature anomaly deviation coefficient ωω after processing during database operation. τ Disk write speed anomaly concealment coefficient θ τ And the anomaly concealment coefficient β for IO wait time π After that, ωω τ , θθ τ and ββ π Establish a data analysis model for ωω τ , θθ τ and ββ π Perform formulaic analysis to generate a risk index. The formula used is: In the formula, e1, e2, and e3 are the disk temperature abnormality deviation coefficients ωω τ Disk write speed anomaly concealment coefficient θτ And the anomaly concealment coefficient β for IO wait time π The preset proportional coefficients, and e1, e2, and e3 are all greater than 0.
[0027] Preferably, the comparison and analysis module compares the risk index generated by the database at runtime with a pre-set risk index reference threshold. The results of the comparison and analysis are as follows:
[0028] If the risk index is greater than or equal to the risk index reference threshold, a high-risk signal is generated through the comparison and analysis module and transmitted to the alert module, which then issues a warning alert for the high-risk signal.
[0029] If the risk index is less than the risk index reference threshold, a low-risk signal is generated through the comparison and analysis module and transmitted to the alert module. The high-risk signal is not alerted through the alert module.
[0030] Preferably, it also includes a maintenance management module;
[0031] The maintenance management module performs comprehensive analysis on a data set established by several risk indices output in real time by the central processor during database maintenance. It generates maintenance management signals and transmits these signals to mobile terminals to provide prompts to maintenance management personnel.
[0032] Preferably, the maintenance management module establishes a data set based on several risk indices output in real time by the central processing unit during database maintenance, and labels the data set as U, then: U = {μμ} j}, j = 1, 2, 3, 4, ..., s, where s is a positive integer;
[0033] The average and standard deviation of the risk indices are calculated from several risk indices within the dataset, and E is denoted as E. ε1 and E ε2 ,but: but:
[0034] The average risk index E ε1 and the standard deviation of the risk index E ε2 Each is compared with a pre-set risk index reference threshold F ε1 and the pre-set standard deviation reference threshold F ε2 The comparison yielded the following results:
[0035] If E ε1 Greater than or equal to F ε1If the failure occurs, the maintenance management module will generate a maintenance management failure signal and transmit the signal to the mobile terminal. The mobile terminal will then notify the maintenance management personnel that the database maintenance management has failed and that maintenance management needs to continue.
[0036] If E ε1 Less than F ε1 And E ε2 Greater than or equal to F ε2 If the maintenance management module generates an unstable maintenance management signal, it will transmit the signal to the mobile terminal, prompting the maintenance management personnel that the database maintenance management is unstable and that maintenance management needs to continue.
[0037] If E ε1 Less than F ε1 And E ε2 Less than F ε2 If the maintenance management module generates a maintenance management success signal, it will be transmitted to the mobile terminal, which will then notify the maintenance management personnel that the database maintenance management has been successful.
[0038] A whiteboard data management method based on a touch screen all-in-one machine includes the following steps:
[0039] Collect multiple data points from the database runtime in the whiteboard data management system based on a touch screen all-in-one machine, including storage device performance indicators and resource utilization indicators. After collection, process the storage device performance indicators and resource utilization indicators from the database runtime.
[0040] A risk index is generated by comprehensively analyzing the storage device performance indicators and resource utilization indicators after the database is run.
[0041] The risk index generated during database runtime is compared and analyzed with a pre-set risk index reference threshold to generate a high-risk signal or a low-risk signal, and a warning is issued for the high-risk signal.
[0042] During database maintenance, a data set is established based on several risk indices output in real time by the central processing unit. This data set is then analyzed to generate maintenance management signals, which are then transmitted to mobile terminals to provide prompts to maintenance management personnel.
[0043] The technical effects and advantages provided by the present invention in the above technical solution are as follows:
[0044] This invention monitors the operational status of the database in the whiteboard data management system in real time. When there is a risk of permanent loss when the database stores user-created content, it reminds users to perform relevant maintenance and management work on the database in advance and take measures to save the created content in a timely manner. This effectively prevents the permanent loss of user-created content and avoids serious impact on important work in fields such as education, enterprise collaboration, and meetings. Secondly, performing relevant maintenance and management work on the abnormally operating database in advance can also effectively prevent the database abnormality from becoming more serious, thereby reducing the difficulty of later maintenance.
[0045] This invention comprehensively analyzes a dataset of several risk indices output in real time by the central processing unit during database maintenance to determine the status of database maintenance and management. This effectively prevents maintenance and management failures or instability after maintenance, ensuring the stable and efficient operation of the database after maintenance and effectively preventing the permanent loss of user-created content when storing it in the database. Attached Figure Description
[0046] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.
[0047] Figure 1 This is a schematic diagram of a whiteboard data management system and method based on a touch screen all-in-one machine according to the present invention.
[0048] Figure 2 This is a flowchart of a whiteboard data management system and method based on a touch screen all-in-one machine according to the present invention. Detailed Implementation
[0049] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that the description of this disclosure will be more complete and fully convey the concept of the exemplary embodiments to those skilled in the art.
[0050] This invention provides, for example Figure 1 The whiteboard data management system based on a touch screen all-in-one machine shown includes a data acquisition module, a central processing unit, a comparison and analysis module, and a prompting module;
[0051] The data acquisition module collects multiple data information during the database operation of the whiteboard data management system based on the touch screen all-in-one machine, including storage device performance indicators and resource utilization indicators. After collection, the storage device performance indicators and resource utilization indicators of the database operation are processed and uploaded to the central processing unit.
[0052] The storage device performance metrics during database operation include disk temperature anomaly deviation coefficient and disk write rate anomaly concealment coefficient. After collection, the disk temperature anomaly deviation coefficient and disk write rate anomaly concealment coefficient are calibrated as ωω by the data acquisition module. τ and θθ τ ;
[0053] High temperatures during database disk operation can increase the risk of permanent loss of user-created content. This is because high temperatures can negatively impact disk reliability and data integrity. The following is a detailed explanation:
[0054] Impact on disk lifespan: High temperatures accelerate the aging process of disks. Disks contain mechanical components, such as rotating platters and read / write heads. High temperatures can damage these components, shortening the disk's lifespan. When a disk fails, the data stored on it may be permanently lost. Therefore, high temperatures increase the risk of disk failure, which may lead to data loss.
[0055] Possibility of data corruption: High temperatures can also increase the likelihood of data corruption on the disk. Data on the disk is stored in magnetic media, and high temperatures may cause the magnetic media to become unstable, thus causing data corruption. This data corruption may affect the content created by the user, making it unreadable or unusable.
[0056] Performance issues: High temperatures can cause disk performance to degrade, including slower or unstable read and write speeds. If the database system cannot read and write data normally, the content created by users may not be saved or retrieved correctly, which may eventually lead to data loss.
[0057] Caching issues: Disks typically have an internal cache to store temporary read and write data. High temperatures can cause the cached data to become unstable, meaning that data may be lost or corrupted before it is written to the disk.
[0058] Therefore, monitoring the temperature of the database disk in a whiteboard data management system based on a touch all-in-one machine can promptly detect the risk that a high operating temperature of the database disk may lead to the permanent loss of user-created content.
[0059] The logic for obtaining the disk temperature abnormal deviation coefficient is as follows:
[0060] S101. Obtain the optimal operating temperature of the database disk in the whiteboard data management system during normal operation, and calibrate the optimal operating temperature as ωω. 最佳 ;
[0061] It should be noted that by consulting the technical specifications and user manuals provided by the disk manufacturer, the manufacturer will usually provide the disk's operating temperature range, which is the temperature range required for the disk to operate normally. This information can usually be found on the disk manufacturer's official website.
[0062] S102. Obtain the actual temperature values of the database disk in the whiteboard data management system at different times during time T, and calibrate the actual temperature values as ωω. x x represents the number of the actual temperature value at different times within time T in the whiteboard data management system database disk during runtime, x = 1, 2, 3, 4, ..., m, where m is a positive integer;
[0063] It should be noted that many modern servers and computing devices are equipped with temperature sensors that can monitor disk temperature in real time. Typically, these sensors feed temperature data back to the motherboard or controller, and then hardware monitoring tools (such as IPMI, DRAC, iLO, etc.) can be used to view this data. These tools usually provide real-time readings of disk temperature as well as historical data records.
[0064] S103. Compare the actual temperature value obtained by the database disk in the whiteboard data management system during time T with the optimal operating temperature of the database disk during normal operation, and recalibrate the actual temperature value that is greater than the optimal operating temperature as ωω. x′ x′ represents the number of the actual temperature value that is greater than the optimal operating temperature obtained by the database disk in the whiteboard data management system during time T. x′ = 1, 2, 3, 4, ..., m′, where m′ is a positive integer.
[0065] S104. Calculate the disk temperature abnormal deviation coefficient. The expression for the calculation is:
[0066] The calculation formula of the disk temperature abnormal deviation coefficient shows that the larger the value of the disk temperature abnormal deviation coefficient generated by the database during the T-time in the whiteboard data management system, the greater the risk of permanent loss of the user-created content when the database stores the user-created content; conversely, the smaller the value, the smaller the risk of permanent loss of the user-created content when the database stores the user-created content.
[0067] In a whiteboard data management system based on a touch screen all-in-one machine, the disk write rate of the database represents the speed at which the disk can write data to the storage medium. It is usually measured in terms of data transfer speed per second, with units of MB / s or GB / s. A higher write rate means that the disk can accept and save new data faster. In the whiteboard data management system, the speed of the write rate will affect how quickly users can add new data to the database.
[0068] In a whiteboard data management system, both high and low write rates on the database disk can increase the risk of permanent loss of user-created content. Although write rate itself is not a direct cause of data loss, the following is a detailed explanation:
[0069] Risks of high write speeds:
[0070] Data integrity issues: High write rates may cause data to be written too quickly, and the database management system may not be able to process all write requests in time. This may result in incomplete or inconsistent data writing because some data may fail to be written to the disk correctly. If this happens, the content created by users may be corrupted or incomplete, which may result in the permanent loss of some data.
[0071] Premature disk wear: High write rates may lead to frequent write operations on the disk, which may accelerate disk wear and aging. If the disk fails prematurely as a result, the data stored on it may be permanently lost.
[0072] Risks of low write speeds:
[0073] Performance issues: Low write rates may cause the database management system to be unable to write data in a timely manner, resulting in performance degradation. If the write rate is too low, users may experience delays and data write failures, which may lead to the loss of user-created content.
[0074] Data inconsistency: Low write rates may cause data to be stored in memory or cache before being written to disk, instead of being written to disk immediately. If the system crashes or loses power, the data in the cache may be lost, resulting in data inconsistency in the database, which may affect the content created by users.
[0075] Therefore, monitoring the write rate of the database disk in a whiteboard data management system based on a touch all-in-one machine can promptly detect the risk that a high or low write rate of the database disk may lead to the permanent loss of user-created content.
[0076] The logic for obtaining the anomaly concealment coefficient of disk write rate is as follows:
[0077] S201. Obtain the optimal write speed range for the database disk in the whiteboard data management system during operation, and define the optimal write speed range as...
[0078] It should be noted that performance testing tools are used to simulate actual database workloads and measure disk write performance. These tests can include random writes, sequential writes, and concurrent writes. By conducting performance tests under different workload conditions, the maximum acceptable write rate of the disk is determined to avoid performance degradation and data loss. Secondly, the write operations of the database in actual operation are monitored to observe the types and frequencies of database write operations. Then, based on actual needs, the optimal write rate range for the database disk in the whiteboard data management system is comprehensively determined. The optimal write rate range for the database disk in the whiteboard data management system is not specifically limited here and can be adjusted according to the actual use case and needs.
[0079] S202. Obtain the actual average write rate of the database disk in the whiteboard data management system during different time periods within time T (write rate represents the total amount of data written by the disk within a certain time period; the duration of each time period can be all equal, all unequal, or a combination of both; the duration of each time period is not specifically limited here), and calibrate the actual average write rate as... y represents the number of the actual average write rate of the database disk in the whiteboard data management system during different time periods within time T, y = 1, 2, 3, 4, ..., n, where n is a positive integer;
[0080] It should be noted that performance monitoring tools or software, such as Windows Performance Monitor or Linux's sar command, can be used. These tools provide real-time performance metrics and historical performance data recording functions. These tools can be configured to monitor disk write speed and set data collection intervals to obtain the actual average write speed of the database disk in the whiteboard data management system at different times within time T.
[0081] S203. Compare the actual average write rate and the optimal write rate range obtained by the database disk in the whiteboard data management system during time T, and recalibrate the actual average write rate that is not within the optimal write rate range. y′ represents the number of the actual average write rate that is not within the optimal write rate range obtained by the database disk in the whiteboard data management system during time T. y′=1, 2, 3, 4, …, n′, where n′ is a positive integer.
[0082] S204. Calculate the disk write rate anomaly concealment coefficient. The expression for the calculation is: n represents the total number of actual average write rates obtained by the database disk during time T in the whiteboard data management system.
[0083] According to the calculation expression of the disk write rate anomaly concealment coefficient, the larger the performance value of the disk write rate anomaly concealment coefficient generated by the database during the T time period in the whiteboard data management system, the greater the risk of permanent loss of the user-created content when the database stores the user-created content; conversely, the smaller the value, the smaller the risk of permanent loss of the user-created content when the database stores the user-created content.
[0084] Resource utilization metrics during database runtime include an anomaly concealment coefficient for IO wait time. After collection, the IO wait time anomaly concealment coefficient is calibrated as β by the data acquisition module. π ;
[0085] In a whiteboard data management system based on a touch screen all-in-one machine, the database IO wait time refers to the total time that I / O operations (input / output operations) occur in the database system and wait to complete. This includes the time to wait for disk read or write operations to complete and other operations involving input / output, such as network transmission.
[0086] Specifically, IO wait time represents the cumulative time for the following situations:
[0087] When a database needs to read data from disk, it must wait for the read operation to complete. The I / O wait time includes the total time spent waiting for all read operations. When a database needs to write data to disk, it must also wait for the write operation to complete. The I / O wait time includes the total time spent waiting for all write operations. If the database needs to transmit data over a network, such as receiving data from a client or sending data to other computers, it will also wait for the network transmission to complete. These waiting times are also included in the I / O wait time.
[0088] Increased database I / O wait times can increase the risk of permanent loss of user-created content, especially under certain circumstances, as explained in detail below:
[0089] Delayed data writes: When the database IO wait time increases, write operations may be affected. Databases typically use caching and logs to manage write operations and then write data to disk asynchronously to improve performance. If the IO wait time increases, write operations may take longer to complete. This means that write operations will remain in memory or cache while waiting for disk completion and will not be persisted to disk immediately. If a system crash, power outage, or disk failure occurs during this period, the data in memory or cache may be permanently lost.
[0090] Data integrity issues: Long I / O wait times may lead to incomplete or inconsistent data writes in the database. If part of a write operation has been committed while another part is still waiting to be written to disk, the database state may be inconsistent during this time window. If the system encounters problems in this situation, it may result in partial data loss or the database becoming unusable.
[0091] Transactional operations: In many databases, write operations are typically performed as transactions, which either all succeed or all fail. If the IO wait time becomes too long and the write operation cannot be completed, the database may need to roll back the transaction, which may result in the undoing of the completed part of the operation, thus losing the data created by the user.
[0092] System crashes and failures: Long I / O wait times increase the risk of system crashes and disk failures. If the database system crashes or fails while waiting to write to disk, the data that has not been written to disk may be permanently lost.
[0093] Therefore, monitoring the IO wait time of the database in the whiteboard data management system based on touch all-in-one machine can promptly detect the risk that long database IO wait time may lead to the permanent loss of user-created content;
[0094] The logic for obtaining the anomaly concealment coefficient of IO wait time is as follows:
[0095] S301. Obtain several actual I / O wait times generated by the database in the whiteboard data management system during runtime within time T, and label the actual I / O wait times as... k represents the number of the actual I / O wait time generated during the database runtime in the whiteboard data management system within time T, k = 1, 2, 3, 4, ..., p, where p is a positive integer;
[0096] It should be noted that specialized performance monitoring tools, such as Prometheus, Grafana, and Nagios, can be used. These tools can be configured to monitor various performance metrics of the database, including IO wait times.
[0097] S302. Compare several actual I / O wait times obtained by the database in the whiteboard data management system during time T with a pre-set I / O wait time reference threshold, and recalibrate the actual I / O wait times that exceed the I / O wait time reference threshold. k′ represents the number of the actual IO wait time greater than the IO wait time reference threshold obtained by the database during time T in the whiteboard data management system. k′ = 1, 2, 3, 4, ..., p′, where p′ is a positive integer.
[0098] It should be noted that the setting of the IO wait time reference threshold should take into account business needs and the performance level expected by users. If the business has high requirements for real-time performance, the IO wait time threshold can be set lower to detect potential problems earlier. A reasonable IO wait time threshold should take into account a variety of factors. For example, if historical data shows that the average IO wait time under normal circumstances is 1 millisecond, and the business requires a response within 5 milliseconds, the threshold can be set to 5 milliseconds to trigger an alarm when this time is exceeded. Therefore, the setting of the IO wait time reference threshold is not specifically limited here and can be adjusted according to the specific situation.
[0099] S303. Calculate the anomaly concealment coefficient of IO wait time. The expression for the calculation is: p represents the total number of actual I / O wait times acquired during database runtime in the whiteboard data management system within time T.
[0100] The expression for calculating the IO wait time anomaly concealment coefficient shows that the larger the IO wait time anomaly concealment coefficient generated by the database disk during the T-time in the whiteboard data management system, the greater the risk of permanent loss of user-created content when the database stores it; conversely, the smaller the value, the lower the risk of permanent loss of user-created content when the database stores it.
[0101] The central processing unit comprehensively analyzes the storage device performance indicators and resource utilization indicators after the database has been processed during runtime, generates a risk index, and transmits the risk index to the comparison and analysis module.
[0102] The central processing unit obtains the disk temperature anomaly deviation coefficient ωω after processing during database runtime. τ Disk write speed anomaly concealment coefficient θ τ And the anomaly concealment coefficient β for IO wait time π After that, ωω τ , θθ τ and ββ π Establish a data analysis model for ωω τ , θθ τ and ββ π Perform formulaic analysis to generate a risk index. The formula used is: In the formula, e1, e2, and e3 are the disk temperature abnormality deviation coefficients ωω τ Disk write speed anomaly concealment coefficient θ τ And the anomaly concealment coefficient β for IO wait time πThe preset proportional coefficients, and e1, e2, and e3 are all greater than 0;
[0103] As shown by the calculation formula, the larger the disk temperature anomaly deviation coefficient, the larger the disk write rate anomaly concealment coefficient, and the larger the IO wait time anomaly concealment coefficient generated by the database during the runtime of the whiteboard data management system within time T, the greater the risk index generated by the database during the runtime of the whiteboard data management system within time T. The higher the value, the greater the risk of permanent loss of user-created content when the database stores it; conversely, the lower the value, the smaller the risk of permanent loss of user-created content when the database stores it.
[0104] It should be noted that the above-mentioned time T is a relatively short time period. The time within this period is not specifically limited and can be set according to the actual situation. The purpose is to monitor the status of the database disk in the whiteboard data management system during the time T, so as to monitor the running status of the database disk in the whiteboard data management system in real time during different time periods (within the time T).
[0105] The comparison and analysis module compares the risk index generated by the database at runtime with the pre-set risk index reference threshold, generates a high-risk signal or a low-risk signal, and transmits the signal to the prompting module, which issues a warning prompt for the high-risk signal.
[0106] The comparison and analysis module compares the risk index generated during database runtime with a pre-set risk index reference threshold. The results of the comparison and analysis are as follows:
[0107] If the risk index is greater than or equal to the risk index reference threshold, a high-risk signal is generated by the comparison and analysis module and transmitted to the alert module. The alert module issues an early warning for the high-risk signal, reminding the user that there is a high risk of permanent loss of the created content when storing it in the database. The user is reminded to carry out relevant maintenance and management work on the database in advance and take measures to save the created content separately in a timely manner.
[0108] If the risk index is less than the risk index reference threshold, a low-risk signal is generated through the comparison and analysis module and transmitted to the prompting module. The high-risk signal is not issued a warning through the prompting module.
[0109] It also includes a maintenance and management module;
[0110] The maintenance management module performs comprehensive analysis on a set of data based on several risk indices output in real time by the central processor during database maintenance. It generates maintenance management signals and transmits these signals to mobile terminals to provide prompts to maintenance management personnel.
[0111] The maintenance management module establishes a dataset based on several risk indices output in real time by the central processing unit during database maintenance, and labels the dataset as U. Then: U = {μμ} j}, j = 1, 2, 3, 4, ..., s, where s is a positive integer;
[0112] The average and standard deviation of the risk indices are calculated from several risk indices within the dataset, and E is denoted as E. ε1 and E ε2 ,but: but:
[0113] The average risk index E ε1 and the standard deviation of the risk index E ε2 Each is compared with a pre-set risk index reference threshold F ε1 and the pre-set standard deviation reference threshold F ε2 The comparison yielded the following results:
[0114] If E ε1 Greater than or equal to F ε1 If the failure occurs, the maintenance management module will generate a maintenance management failure signal and transmit the signal to the mobile terminal. The mobile terminal will then notify the maintenance management personnel that the database maintenance management has failed and that maintenance management needs to continue.
[0115] If E ε1 Less than F ε1 And E ε2 Greater than or equal to F ε2 If the maintenance management module generates an unstable maintenance management signal, it will transmit the signal to the mobile terminal, prompting the maintenance management personnel that the database maintenance management is unstable and that maintenance management needs to continue.
[0116] If E ε1 Less than F ε1 And E ε2 Less than F ε2 If the maintenance management module generates a maintenance management success signal, it will transmit the signal to the mobile terminal, which will then notify the maintenance management personnel that the database maintenance management has been successful.
[0117] This invention monitors the operational status of the database in the whiteboard data management system in real time. When there is a risk of permanent loss when the database stores user-created content, it reminds users to perform relevant maintenance and management work on the database in advance and take measures to save the created content in a timely manner. This effectively prevents the permanent loss of user-created content and avoids serious impact on important work in fields such as education, enterprise collaboration, and meetings. Secondly, performing relevant maintenance and management work on the abnormally operating database in advance can also effectively prevent the database abnormality from becoming more serious, thereby reducing the difficulty of later maintenance.
[0118] This invention comprehensively analyzes a dataset of several risk indices output in real time by the central processing unit during database maintenance to determine the status of database maintenance and management. This effectively prevents maintenance and management failures or instability after maintenance, ensuring the stable and efficient operation of the database after maintenance and effectively preventing the permanent loss of user-created content when storing it in the database.
[0119] This invention provides, for example Figure 2 The whiteboard data management method based on a touch screen all-in-one machine, as shown, includes the following steps:
[0120] Collect multiple data points from the database runtime in the whiteboard data management system based on a touch screen all-in-one machine, including storage device performance indicators and resource utilization indicators. After collection, process the storage device performance indicators and resource utilization indicators from the database runtime.
[0121] A risk index is generated by comprehensively analyzing the storage device performance indicators and resource utilization indicators after the database is run.
[0122] The risk index generated during database runtime is compared and analyzed with a pre-set risk index reference threshold to generate a high-risk signal or a low-risk signal, and a warning is issued for the high-risk signal.
[0123] During database maintenance, a data set is established based on several risk indices output in real time by the central processing unit. This data set is then analyzed to generate maintenance management signals, which are then transmitted to mobile terminals to provide prompts to maintenance management personnel.
[0124] This invention provides a whiteboard data management method based on a touch screen all-in-one machine, which is implemented through the aforementioned whiteboard data management system based on a touch screen all-in-one machine. For details of the specific method and process of the whiteboard data management method based on a touch screen all-in-one machine, please refer to the aforementioned embodiment of the whiteboard data management system based on a touch screen all-in-one machine, which will not be repeated here.
[0125] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.
[0126] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, magnetic disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state disk.
[0127] It should be understood that, in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.
[0128] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.
[0129] In the several embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.
[0130] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.
[0131] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.
[0132] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.
[0133] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.
[0134] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.
Claims
1. A whiteboard data management system based on a touch screen all-in-one machine, characterized in that, It includes a data acquisition module, a central processing unit, a comparison and analysis module, and a prompting module; The data acquisition module collects multiple data information during the database operation of the whiteboard data management system based on the touch screen all-in-one machine, including storage device performance indicators and resource utilization indicators. After collection, the storage device performance indicators and resource utilization indicators of the database operation are processed and uploaded to the central processing unit. The central processing unit comprehensively analyzes the storage device performance indicators and resource utilization indicators after the database has been processed during runtime, generates a risk index, and transmits the risk index to the comparison and analysis module. The comparison and analysis module compares the risk index generated by the database during runtime with the pre-set risk index reference threshold, generates a high-risk signal or a low-risk signal, and transmits the signal to the alert module, which then issues a warning alert for the high-risk signal.
2. The whiteboard data management system based on a touch screen all-in-one machine according to claim 1, characterized in that, The storage device performance metrics during database operation include disk temperature anomaly deviation coefficient and disk write rate anomaly concealment coefficient. Resource utilization metrics during database operation include IO wait time anomaly concealment coefficient. After collection, the disk temperature anomaly deviation coefficient and disk write rate anomaly concealment coefficient are denoted as ωω by the data acquisition module. τ and θθ τ The anomaly concealment coefficient of IO wait time is calibrated as ββ. π .
3. A whiteboard data management system based on a touch screen all-in-one machine according to claim 2, characterized in that, The logic for obtaining the disk temperature abnormal deviation coefficient is as follows: S101. Obtain the optimal operating temperature of the database disk in the whiteboard data management system during normal operation, and calibrate the optimal operating temperature as ωω. 最佳 ; S102. Obtain the actual temperature values of the database disk in the whiteboard data management system at different times during time T, and calibrate the actual temperature values as ωω. x x represents the number of the actual temperature value at different times within time T in the whiteboard data management system database disk during runtime, x = 1, 2, 3, 4, ..., m, where m is a positive integer; S103. Compare the actual temperature value obtained by the database disk in the whiteboard data management system during time T with the optimal operating temperature of the database disk during normal operation, and recalibrate the actual temperature value that is greater than the optimal operating temperature as ωω. x′ x′ represents the number of the actual temperature value that is greater than the optimal operating temperature obtained by the database disk in the whiteboard data management system during time T. x′ = 1, 2, 3, 4, ..., m′, where m′ is a positive integer. S104. Calculate the disk temperature abnormal deviation coefficient. The expression for the calculation is:
4. A whiteboard data management system based on a touch screen all-in-one machine according to claim 3, characterized in that, The logic for obtaining the anomaly concealment coefficient of disk write rate is as follows: S201. Obtain the optimal write speed range for the database disk in the whiteboard data management system during operation, and define the optimal write speed range as... S202. Obtain the actual average write rate of the database disk in the whiteboard data management system during different time periods within time T, and calibrate the actual average write rate as... y represents the number of the actual average write rate of the database disk in the whiteboard data management system during different time periods within time T, y = 1, 2, 3, 4, ..., n, where n is a positive integer; S203. Compare the actual average write rate and the optimal write rate range obtained by the database disk in the whiteboard data management system during time T, and recalibrate the actual average write rate that is not within the optimal write rate range. y′ represents the number of the actual average write rate that is not within the optimal write rate range obtained by the database disk in the whiteboard data management system during time T. y′=1, 2, 3, 4, …, n′, where n′ is a positive integer; S204. Calculate the disk write rate anomaly concealment coefficient. The expression for the calculation is: n represents the total number of actual average write rates obtained by the database disk during time T in the whiteboard data management system.
5. A whiteboard data management system based on a touch screen all-in-one machine according to claim 4, characterized in that, The logic for obtaining the anomaly concealment coefficient of IO wait time is as follows: S301. Obtain several actual I / O wait times generated by the database in the whiteboard data management system during runtime within time T, and label the actual I / O wait times as... k represents the number of the actual I / O wait time generated during the database runtime in the whiteboard data management system within time T, k = 1, 2, 3, 4, ..., p, where p is a positive integer; S302. Compare several actual I / O wait times obtained by the database in the whiteboard data management system during time T with a pre-set I / O wait time reference threshold, and recalibrate the actual I / O wait times that exceed the I / O wait time reference threshold. k′ represents the number of the actual IO wait time greater than the IO wait time reference threshold obtained by the database during time T in the whiteboard data management system. k′ = 1, 2, 3, 4, ..., p′, where p′ is a positive integer. S303. Calculate the anomaly concealment coefficient of IO wait time. The expression for the calculation is: p represents the total number of actual I / O wait times acquired during database runtime in the whiteboard data management system within time T.
6. A whiteboard data management system based on a touch screen all-in-one machine according to claim 5, characterized in that, The central processing unit obtains the disk temperature anomaly deviation coefficient ωω after processing during database runtime. τ Disk write speed anomaly concealment coefficient θ τ And the anomaly concealment coefficient β for IO wait time π After that, ωω τ , θθ τ and ββ π Establish a data analysis model for ωω τ , θθ τ and ββ π Perform formulaic analysis to generate a risk index. The formula used is: In the formula, e1, e2, and e3 are the disk temperature abnormality deviation coefficients ωω τ Disk write speed anomaly concealment coefficient θ τ And the anomaly concealment coefficient β for IO wait time π The preset proportional coefficients, and e1, e2, and e3 are all greater than 0.
7. A whiteboard data management system based on a touch screen all-in-one machine according to claim 6, characterized in that, The comparison and analysis module compares the risk index generated during database runtime with a pre-set risk index reference threshold. The results of the comparison and analysis are as follows: If the risk index is greater than or equal to the risk index reference threshold, a high-risk signal is generated through the comparison and analysis module and transmitted to the alert module, which then issues a warning alert for the high-risk signal. If the risk index is less than the risk index reference threshold, a low-risk signal is generated through the comparison and analysis module and transmitted to the alert module. The high-risk signal is not alerted through the alert module.
8. A whiteboard data management system based on a touch screen all-in-one machine according to claim 7, characterized in that, It also includes a maintenance and management module; The maintenance management module performs comprehensive analysis on a data set established by several risk indices output in real time by the central processor during database maintenance. It generates maintenance management signals and transmits these signals to mobile terminals to provide prompts to maintenance management personnel.
9. A whiteboard data management system based on a touch screen all-in-one machine according to claim 8, characterized in that, The maintenance management module establishes a dataset based on several risk indices output in real time by the central processing unit during database maintenance, and labels the dataset as U. Then: U = {μμ} j }, j = 1, 2, 3, 4, ..., s, where s is a positive integer; The average and standard deviation of the risk indices are calculated from several risk indices within the dataset, and E is denoted as E. ε1 and E ε2 ,but: but: The average risk index E ε1 and the standard deviation of the risk index E ε2 Each is compared with a pre-set risk index reference threshold F ε1 and the pre-set standard deviation reference threshold F ε2 The comparison yielded the following results: If E ε1 Greater than or equal to F ε1 If the failure occurs, the maintenance management module generates a maintenance management failure signal and transmits the signal to the mobile terminal. The mobile terminal then prompts the maintenance management personnel that the database maintenance management has failed and that maintenance management needs to continue. If E ε1 Less than F ε1 And E ε2 Greater than or equal to F ε2 If the maintenance management module generates an unstable maintenance management signal, it will transmit the signal to the mobile terminal, prompting the maintenance management personnel that the database maintenance management is unstable and that maintenance management needs to continue. If E ε1 Less than F ε1 And E ε2 Less than F ε2 If the maintenance management module generates a successful maintenance management signal, it will be transmitted to the mobile terminal, which will then notify the maintenance management personnel that the database maintenance management has been successful.
10. A whiteboard data management method based on a touch screen all-in-one machine, implemented by a whiteboard data management system based on a touch screen all-in-one machine as described in any one of claims 1-9, characterized in that, Includes the following steps: Collect multiple data points from the database runtime in the whiteboard data management system based on a touch screen all-in-one machine, including storage device performance indicators and resource utilization indicators. After collection, process the storage device performance indicators and resource utilization indicators from the database runtime. A risk index is generated by comprehensively analyzing the storage device performance indicators and resource utilization indicators after the database is run. The risk index generated during database runtime is compared and analyzed with a pre-set risk index reference threshold to generate high-risk or low-risk signals, and a warning is issued for high-risk signals. During database maintenance, a data set is established based on several risk indices output in real time by the central processing unit. This data set is then analyzed to generate maintenance management signals, which are then transmitted to mobile terminals to provide prompts to maintenance management personnel.