A task assignment system for disaster recovery and methods of using the same

Abstract

The application discloses a task allocation system for disaster recovery and a use method thereof, a disaster recovery resource monitoring unit, different resource parameters and states are monitored, various resources include applications, databases, network equipment, middleware, load balancing, front-end machines, monitored data is classified and marked as SJ p ; a resource backup capacity calculation unit, the backup data capacity monitored by different resources on the same day is calculated to obtain the capacity value RL p of the corresponding resource, and the backup capacity value RL p均 of the corresponding resource on the same day is calculated according to historical data; and specifically relates to the field of disaster recovery, a set of comprehensive algorithms are designed to realize the priority ordering of resource data according to the importance of the resource data itself and the proportion of data loss, so that the most critical data can be recovered preferentially, different data recovery strategies and job tasks can be accurately formulated to the table level, and the key data can be recovered in time.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of disaster recovery, and more particularly to a task allocation system for disaster recovery and a method of using the same. BACKGROUND

[0002] Disaster recovery refers to the recovery means and the evaluation of the possible loss to the production system when any link or any time in the production operation fails and the entire system cannot work normally. The data recovery function can recover the lost data of the production business database through the backup program, thereby ensuring the availability of the data.

[0003] The application with the publication number CN112559151A discloses a task allocation system for disaster recovery and a method of using the same, which belongs to the technical field of task allocation systems. The task allocation system for disaster recovery and the method of using the same can collect the real-time parameters and the real-time state of the data center through each data center alarm module. When a disaster is perceived, the corresponding alarm is generated, and the tasks in the data center currently affected by the disaster are reasonably analyzed and disaster-ordered. Further, a more reasonable and optimized task allocation solution is given through the comprehensive analysis of the current situation of the backup data center. Compared with the traditional method, this method can deeply consider the influence of global environmental factors, effectively enhance the feasibility of the task allocation scheme, and optimize the task disaster performance.

[0004] The purpose of data backup is to prevent data loss in abnormal accidents. Once the running data has a problem, how to recover the most current data from the backup medium is the real concern. The occurrence of a disaster is often sudden and unpredictable, so a disaster recovery solution is needed to deal with various disaster situations for future use. The disaster recovery technology in the prior art generally directly restores the data of the corresponding resources, does not judge the importance of the corresponding resources to set priorities, causes some important data to be placed at the end for timely data recovery, and some resources with too much data loss cannot be recovered in time. When a data disaster occurs, it cannot be smoothly dealt with, resulting in serious data loss. SUMMARY

[0005] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present application provide a task allocation system for disaster recovery and a method of using the same. The technical problem to be solved by the present application is that the existing disaster recovery technology does not judge the importance of resources and set priorities, and cannot recover resources with a high data loss ratio in time, resulting in the problem of delayed recovery of key data and serious data loss when a disaster occurs.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a task allocation system for disaster recovery, comprising...

[0007] The disaster recovery resource monitoring unit monitors different resource parameters and statuses, including applications, databases, network devices, middleware, load balancers, and front-end servers. The monitored data is categorized and labeled as SJ. p ;

[0008] The resource backup capacity calculation unit calculates the backup data capacity monitored for different resources on the same day, and obtains the corresponding resource capacity value RL. p And calculate the daily backup capacity value RL for the corresponding resource based on historical data. p均 ;

[0009] The data priority recovery sorting unit prioritizes the lost data based on their importance, obtains the data priority sorting results, and prioritizes the recovery of important resource data.

[0010] The data recovery unit sorts data by priority and selects data to be recovered based on time points. Regardless of whether a full backup or an incremental backup was performed, the selected file recovery time point is automatically merged to restore the complete data at that time point.

[0011] The data recovery verification unit verifies the availability of backup data to ensure that when production data encounters problems and backup data needs to be restored, the backup data is intact and can be recovered.

[0012] In a preferred embodiment, the specific method for calculating the daily backup capacity value of resources is as follows:

[0013] The historical backup capacity of the statistical resource for the current day, i.e., RL. 1 RL 2 RL 3 ...RL u Where u represents the number of days in the statistics, and RL is calculated from the mean. p均 The calculation formula is as follows:

[0014] .

[0015] In a preferred embodiment, the priority sorting is performed as follows:

[0016] S1. First, assign a weight coefficient k to the monitored data based on the data's business type and importance. p p = 1, 2, 3, ..., n, representing different resources, and n representing the quantity of resources, i.e., SJ1, SJ2, ..., SJ nThe corresponding weight coefficients are k1, k2, ... k n , (k p The value can be from 1 to 10, with a larger number indicating higher resource importance. For example, databases are usually assigned the highest importance level, so the database weight coefficient can be set to level 10. Front-end servers, on the other hand, are for improving data security and data processing efficiency, and are relatively less important, so the front-end server weight coefficient can be set to level 4.

[0017] S2. Calculate the percentage of backup data for different resources on that day, ZB. p :

[0018] ;

[0019] S3. Set the percentage value coefficient to g, and assign the recovery importance weight corresponding to the percentage of lost resource data (the importance of resource data is related to the percentage of data loss. The higher the percentage of lost resource data, the more difficult it is to recover, and therefore the more important it is to recover).

[0020] S4. Based on the set resource weight coefficients and the proportion of lost data, calculate the importance value of the data to be recovered, i.e., the priority value YX, using a calculation formula. p The calculation formula is as follows:

[0021] ;

[0022] Will After substituting the formula, the calculation formula is as follows:

[0023] ;

[0024] S5. Based on the obtained priority value YX p Based on resource priority value YX p The resources are sorted in descending order of size.

[0025] In a preferred embodiment, the availability verification of backup data is mainly accomplished through the following means: establishing a corresponding backup data drill system, which specifically includes the scope of work and responsibilities of relevant personnel, backup monitoring, recovery drills, statistical analysis and prediction, security management, media management, policy management, and archive management, and conducting data recovery drills.

[0026] A method for using a task allocation system for disaster recovery includes the following steps:

[0027] Step 1: Use the disaster recovery resource monitoring unit to monitor different resource parameters and statuses, classify the monitored data, and label them as SJp;

[0028] Step 2: Calculate the backup data capacity monitored for different resources on the same day to obtain the corresponding resource capacity value RL. p And calculate the daily backup capacity value RL for the corresponding resource based on historical data. p均 ;

[0029] Step 3: Prioritize the lost data according to their importance, and prioritize the recovery of important resource data.

[0030] Step 4: After prioritizing the lost data according to its importance, the backup data is divided into critical backup data, important backup data, and general backup data. Based on this, the data is further classified according to priority to ensure that the most critical data is restored first.

[0031] Step 5: Based on the data priority sorting results, select the data to be restored according to the time point. Regardless of whether a full backup or an incremental backup was performed, the selected file restoration time point will be automatically merged to restore the complete data at that time point.

[0032] The technical effects and advantages of this invention are as follows:

[0033] This invention designs a comprehensive algorithm to prioritize resource data by judging the importance of the resource data itself and the proportion of data loss. This ensures that the most critical data is recovered first. Different data recovery strategies and tasks can be formulated at the table level to avoid critical data not being recovered in time. In the face of data disasters, it can respond smoothly, minimize losses, and enable resources with excessive data loss to be recovered in a timely manner. Attached Figure Description

[0034] Figure 1 This is a flowchart illustrating how to use a task allocation system for disaster recovery. Detailed Implementation

[0035] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments thereof. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0036] This invention provides a task allocation system for disaster recovery, comprising:

[0037] The disaster recovery resource monitoring unit monitors different resource parameters and statuses, including applications, databases, network devices, middleware, load balancers, and front-end servers. The monitored data is categorized and labeled as SJ.p p = 1, 2, 3, ..., n, where p represents different resources and n represents the quantity of resources;

[0038] The resource backup capacity calculation unit calculates the backup data capacity monitored for different resources on the same day, and obtains the corresponding resource capacity value RL. p p = 1, 2, 3, ..., n, where p represents different resources, and the daily backup capacity value RL of the corresponding resource is calculated based on historical data. p均 ,

[0039] The specific method for setting the daily backup capacity value for computing resources is as follows;

[0040] The historical backup capacity of the statistical resource for the current day, i.e., RL. 1 RL 2 RL 3 ...RL u Where u represents the number of days in the statistics, and RL is calculated from the mean. p均 The calculation formula is as follows:

[0041] ;

[0042] The data priority recovery sorting unit prioritizes the lost data according to their importance, and then prioritizes the recovery of important resource data.

[0043] The specific method for prioritizing is as follows:

[0044] S1. First, assign a weight coefficient k to the monitored data based on the data's business type and importance. p p = 1, 2, 3, ..., n, representing different resources, and n representing the quantity of resources, i.e., SJ1, SJ2, ..., SJ n The corresponding weight coefficients are k1, k2, ... k p , (k p The value can be from 1 to 10, with a larger number indicating higher resource importance. For example, databases are usually assigned the highest importance level, so the database weight coefficient can be set to level 10. Front-end servers, on the other hand, are for improving data security and data processing efficiency, and are relatively less important, so the front-end server weight coefficient can be set to level 4.

[0045] S2. Calculate the percentage of backup data for different resources on that day, ZB. p :

[0046] ;

[0047] S3. Set the percentage value coefficient to g, and assign the recovery importance weight corresponding to the percentage of lost resource data (the importance of resource data is related to the percentage of data loss. The higher the percentage of lost resource data, the more difficult it is to recover, and therefore the more important it is to recover).

[0048] S4. Based on the set resource weight coefficients and the proportion of lost data, calculate the importance value of the data to be recovered, i.e., the priority value YX, using a calculation formula. p The calculation formula is as follows:

[0049] ;

[0050] Will After substituting the formula, the calculation formula is as follows:

[0051] ;

[0052] S5. Based on the obtained priority value YX p Based on resource priority value YX p The resources are sorted in descending order of size.

[0053] After prioritizing the lost data based on its importance, the backup data is divided into critical backup data, important backup data, and general backup data. Based on this, the data is further classified according to priority to ensure that the most critical data is restored first.

[0054] The data recovery unit sorts data by priority and selects data to be recovered based on time points. Regardless of whether a full backup or an incremental backup was performed, the selected file recovery time point is automatically merged to restore the complete data at that time point.

[0055] The data recovery verification unit verifies the availability of backup data to ensure that when production data encounters problems and backup data needs to be restored, the backup data is intact and can be recovered. Backup data availability verification is primarily accomplished through the following methods: establishing corresponding backup data drill procedures, specifically including the scope of work and responsibilities of relevant personnel, backup monitoring, recovery drills, statistical analysis and prediction, security management, media management, policy management, and archive management; and conducting data recovery drills. This not only improves the skills of management personnel and verifies the correctness of backup data but also refines the data security management system, ensuring a smooth response in the event of a real data disaster and minimizing data loss.

[0056] This invention also discloses a method for using a task allocation system for disaster recovery, comprising the following steps:

[0057] Step 1: Use the disaster recovery resource monitoring unit to monitor different resource parameters and statuses, classify the monitored data, and label them as SJp;

[0058] Step 2: Calculate the backup data capacity monitored for different resources on the same day to obtain the corresponding resource capacity value RL. p And calculate the daily backup capacity value RL for the corresponding resource based on historical data. p均 ;

[0059] Step 3: Prioritize the lost data according to their importance, and prioritize the recovery of important resource data.

[0060] Step 4: After prioritizing the lost data according to its importance, the backup data is divided into critical backup data, important backup data, and general backup data. Based on this, the data is further classified according to priority to ensure that the most critical data is restored first.

[0061] Step 5: Based on the data priority sorting results, select the data to be restored according to the time point. Regardless of whether a full backup or an incremental backup was performed, the selected file restoration time point will be automatically merged to restore the complete data at that time point.

[0062] Some of the data in the above formulas are numerical calculations with dimensions removed, and the contents not described in detail in this specification are all prior art known to those skilled in the art.

[0063] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. A task allocation system for disaster recovery, characterized in that: include The disaster recovery resource monitoring unit monitors different resource parameters and statuses, including applications, databases, network devices, middleware, load balancers, and front-end servers. The monitored data is categorized and labeled as SJ. p ; The resource backup capacity calculation unit calculates the backup data capacity monitored for different resources on the same day, and obtains the corresponding resource capacity value RL. p And calculate the daily backup capacity value RL for the corresponding resource based on historical data. p均 The specific method for calculating the daily backup capacity of computing resources is as follows: The historical backup capacity of the statistical resource for the current day, i.e., RL. 1 RL 2 RL 3 ...RL u Where u represents the number of days in the statistics, and RL is calculated from the mean. p均 The calculation formula is as follows: ； The data priority recovery sorting unit prioritizes the lost data based on their importance, obtains the data priority sorting results, and prioritizes the recovery of important resource data. The data recovery unit sorts data by priority and selects data to be recovered based on time points. Regardless of whether a full backup or an incremental backup was performed, the selected file recovery time point is automatically merged to restore the complete data at that time point. The data recovery verification unit verifies the availability of backup data, ensuring that when production data encounters problems and backup data needs to be restored, the backup data is not corrupted and can be recovered. The specific method for prioritizing is as follows: S1. First, assign a weight coefficient k to the monitored data based on the data's business type and importance. p p = 1, 2, 3, ..., n, representing different resources, and n representing the quantity of resources, i.e., SJ1, SJ2, ..., SJ n The corresponding weight coefficients are k1, k2, ... k n k p The value ranges from 1 to 10, with larger numbers indicating higher resource importance. S2. Calculate the percentage of backup data for different resources on that day, ZB. p : ； S3. Set the percentage value coefficient to g, and assign the recovery importance weight corresponding to the percentage of lost data. S4. Based on the set resource weight coefficients and the proportion of lost data, calculate the importance value of the data to be recovered, i.e., the priority value YX, using a calculation formula. p The calculation formula is as follows: ； Will After substituting the formula, the calculation formula is as follows: ; S5. Based on the obtained priority value YX p Based on resource priority value YX p The resources are sorted in descending order of size.

2. The task allocation system for disaster recovery according to claim 1, characterized in that: The availability verification of backup data is carried out in the following ways: a corresponding backup data exercise system is established, which includes the scope of work and responsibilities of relevant personnel, backup monitoring, recovery exercises, statistical analysis and prediction, security management, media management, policy management, and archive management, and data recovery exercises are conducted.

3. A task allocation method for disaster recovery, characterized in that: Based on a task allocation system for disaster recovery as described in any one of claims 1-2, the method includes the following steps: Step 1: Use the disaster recovery resource monitoring unit to monitor different resource parameters and statuses, classify the monitored data, and label them as SJp; Step 2: Calculate the backup data capacity monitored for different resources on the same day to obtain the corresponding resource capacity value RL. p And calculate the daily backup capacity value RL for the corresponding resource based on historical data. p均 ; Step 3: Prioritize the lost data according to their importance, and prioritize the recovery of important resource data. Step 4: After prioritizing the lost data according to its importance, the backup data is divided into critical backup data, important backup data, and general backup data. Based on this, the data is further classified according to priority to ensure that the most critical data is restored first. Step 5: Based on the data priority sorting results, select the data to be restored according to the time point. Regardless of whether a full backup or an incremental backup was performed, the selected file restoration time point will be automatically merged to restore the complete data at that time point.

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