A mobile application workbench configuration method

Abstract

The present invention discloses a mobile application workbench configuration method, which relates to the field of update configuration technology and solves the problem of performing associated updates by not setting a method of finding an optimal update time period. The present invention specifically analyzes the related update amounts and specific update rates of different update items of the mobile application workbench, and performs associated confirmation on the update average speed intervals of the related items to be updated. Subsequently, based on the confirmed specific time interval, the specified items to be updated are confirmed in the past application time periods, and based on the related intersection situations of multiple different application time periods, the related intersection time periods are determined. After the intersection time periods are processed, the corresponding intersection time period sequence is locked, and then the corresponding update time period is locked from the intersection time period sequence, so that the corresponding items to be updated can execute the corresponding update process within the specific update time period, thereby completing the specific update effect and facilitating the associated update of the corresponding items to be updated within the specified time period.

Description

Technical Field

[0001] The present invention relates to the technical field of update configuration, and in particular to a mobile application workbench configuration method. Background Art

[0002] The mobile application workbench is like a powerful command center, integrating various applications and functions to provide users with a convenient operation experience. It allows users to easily access multiple applications on one interface without frequent switching, greatly improving work efficiency. However, to truly exert the power of the mobile application workbench, it is inseparable from the support of data.

[0003] The application with publication number CN106789164A discloses a network parameter update method, the method comprising: a network device obtains updated network parameters and generates a configuration file containing the updated network parameters; the network device carries the configuration file in an installation package, the installation package is data of a target application program that can be obtained by a mobile terminal to update itself; the network device sends the installation package carrying the configuration file to the mobile terminal, so that the mobile terminal updates its corresponding network parameters based on the configuration file in the installation package of the target application program. The embodiment of the present invention also discloses a network device and a mobile terminal.

[0004] When the relevant mobile application workbench is performing data update configuration, it generally monitors the relevant application items. When it detects that there is no associated application process, it will automatically execute the relevant update process. However, this original update method will cause the corresponding update process to be interrupted, which will cause the update effect to deteriorate and fail to achieve a better update effect. The associated update is not performed by setting the best update period to ensure that the corresponding update items are not interrupted during the update or the number of terminals is minimized. Summary of the invention

[0005] In view of the deficiencies of the prior art, the present invention provides a mobile application workbench configuration method, which solves the problem of performing associated updates without setting a method of finding an optimal update period.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: A mobile application workbench configuration method, comprising the following steps:

[0007] Step 1: Identify the items to be updated on the mobile application workbench, and simultaneously confirm the overall update amount of the items to be updated. Then, based on the historical update completion data of the items to be updated and the past update rate of the items to be updated, lock the relevant time interval for completing the associated updates of the items to be updated. The specific sub-steps are:

[0008] S11, based on the determined item to be updated, taking the current time as the calibration time, obtaining several groups of update rates generated in the past five groups of update processes from the historical update completion data of the item to be updated, performing average processing on multiple groups of update rates corresponding to a single group of update processes, determining the update average speed of the corresponding update process, and then determining five groups of update average speeds based on the five groups of update processes, and determining the update average speed interval based on the minimum and maximum values ​​of the five groups of update average speeds;

[0009] S12, based on the overall update amount of the item to be updated and the determined average update speed interval, determining a relevant time interval for completing the associated update of the item to be updated;

[0010] Step 2: Based on the past application time of the corresponding item to be updated, identify the unused time period of the item to be updated, and then based on the determined relevant time interval, lock the selected update time period in which the item to be updated can be associated and updated. The specific method is as follows:

[0011] S21, defining a group of extraction cycles T, where T is a preset value, identifying the application period of the item to be updated in the extraction period T from the past application time, wherein the application period adopts a 24-hour system, determining the crossover period from the identified groups of application periods, and sorting the determined groups of crossover periods in a manner from most to least according to the number of crossovers corresponding to the crossover periods, and determining the crossover period sequence. If there are crossover periods with the same number of crossovers, they can be randomly sorted;

[0012] S22, based on the different application time periods generated every day, identify the total proportion value Z of the application time periods within a single day k , where k represents different days, and Z k = total of application period ÷ 24h, the number of groups Z generated within this extraction period T k Perform mean processing to determine the mean value of the correlation ratio JZ, and use 24h×JZ=XG to lock the correlation value;

[0013] S23, based on the correlation value, remove some cross-periods whose values ​​are less than (correlation value×0.7) from the cross-period sequence, and mark the cross-period sequence after the removal process as a sequence to be selected;

[0014] S24, identifying the unused time periods corresponding to different intersecting time periods in the sequence to be selected, and based on the specific durations of the different unused time periods, marking the unused time periods whose specific durations exceed the relevant time interval as the update time periods to be selected; if there is no unused time period whose specific duration exceeds the relevant time interval, marking the unused time period belonging to the relevant time interval as the update time period to be selected;

[0015] Step 3: Based on the determined update period to be selected and the determined unused period, data of the item to be updated is updated, and the specific period of the update is within the update period to be selected and the unused period. The sub-steps are:

[0016] S31, identifying whether the item to be updated has a waiting update period:

[0017] If there is a waiting update period, the data of the waiting update item is updated from the waiting update period closest to the current time. If the update is not completed in this waiting update period, it is identified whether there is a subsequent waiting update period. If so, the update is continued. If not, the nearest unused period is selected for data update until the data update process is completed;

[0018] If there is no update period to be selected, the data of the item to be updated is updated from the unused period closest to the current time. If the update is not completed, the data is updated continuously using the unused periods confirmed in succession until the data update process is completed;

[0019] Step 4: When different items to be updated have update processes in the same period, based on the update rate of the corresponding items to be updated, it is determined whether the items to be updated can complete the update process within the determined relevant time interval. If they can be completed, no relevant processing is performed. If they cannot be completed, computing power is allocated. The specific method is as follows:

[0020] S41. Based on multiple update processes existing in the same period, a monitoring period is defined, wherein the monitoring period is a preset period, and the average update rate Jq generated by the corresponding item to be updated in the monitoring period is identified, wherein q represents different items to be updated, and then the remaining update amount of the corresponding item to be updated is identified and calibrated as SYq, and the remaining update time Tq of the item to be updated is determined by using SYq÷Jq=Tq, and based on the update time Gq of the partially updated item, whether the associated time (Tq+Gq) of the corresponding item to be updated belongs to the corresponding related time interval is identified:

[0021] If they are both, no relevant processing will be performed and the original update process can be maintained;

[0022] Otherwise, step S42 is executed to allocate computing power;

[0023] S42, mark the to-be-updated item whose associated time belongs to the corresponding relevant time interval as the to-be-allocated item, determine the maximum time value Ttmax of the to-be-allocated item corresponding to the relevant time interval, use SYq÷(Ttmax-Gq)=Jqmin to determine the minimum update rate Jqmin of the to-be-allocated item, reduce the relevant computing power of the to-be-allocated item, and stop when the update rate of the to-be-allocated item reaches Jqmin, and allocate the reduced relevant computing power to the to-be-allocated items that are not marked as the to-be-allocated items;

[0024] For other items to be updated that are not marked as items to be allocated, the same processing method is adopted to identify the minimum update rate Jqmin of these items to be updated. When the corresponding update rate of the items to be updated reaches Jqmin after the computing power is allocated, the allocation is stopped. If Jqmin cannot be reached, the different items to be updated are adjusted to the same load balancing state and stopped.

[0025] Preferably, in step S24, if there is neither an unused period whose specific duration exceeds the relevant time interval nor an unused period whose specific duration exceeds the relevant time interval, no calibration is performed.

[0026] The present invention provides a method for configuring a mobile application workstation. Compared with the prior art, the method has the following beneficial effects:

[0027] The present invention specifically analyzes the relevant update amounts and specific update rates of different update items of the mobile application workstation, associates and confirms the update average speed intervals of the relevant items to be updated, and subsequently confirms the application time periods of the specified items to be updated in the past based on the confirmed specific time intervals, and determines the relevant crossover time periods based on the relevant crossover situations of multiple different application time periods, and after processing the crossover time periods, locks the corresponding crossover time period sequence, and then locks the corresponding update time period from the crossover time period sequence, so that the corresponding items to be updated can execute the corresponding update process within the specific update time period, thereby completing the specific update effect, facilitating the associated update of the corresponding items to be updated within the specified time period, and will not affect the application process of the items to be updated;

[0028] When there are synchronous update processes in the same period, correlation analysis is performed on the relevant data of each different update process to evaluate whether the corresponding items to be updated can be updated within the specified time interval. Based on the specific numerical analysis results, the computing power of different items to be updated is reasonably allocated so that the corresponding items to be updated can achieve better update effects and the originally determined time intervals will not differ too much. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 It is a schematic diagram of the process of the present invention;

[0030] Figure 2 A schematic diagram of a flow chart for determining relevant time intervals according to the present invention. DETAILED DESCRIPTION

[0031] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0032] Example 1

[0033] See also Figure 1 , the present application provides a mobile application workbench configuration method, comprising the following steps:

[0034] Step 1: Identify the items to be updated of the mobile application workstation, and simultaneously confirm the overall update amount of the items to be updated, and then lock the relevant time interval for completing the associated updates of the items to be updated based on the historical update completion data of the items to be updated and the past update rate of the items to be updated. Specifically, the usage data of different usage items in the mobile application platform are prepared in advance by relevant personnel, and each different usage item needs to be updated in a timely manner during the subsequent trimming and configuration process. During the relevant update process of the items to be updated, the corresponding update time should be executed when the corresponding items to be updated are not in normal use, so as to avoid the application experience of the corresponding items to be updated during the data application process. Therefore, in order to achieve a better update execution effect, it is necessary to identify the unused time period of the associated items to be updated;

[0035] Among them, combined Figure 2 , the specific sub-steps for locking the relevant time interval of this item to be updated are:

[0036] S11. Based on the determined item to be updated, taking the current moment as the calibration moment, obtaining several groups of update rates generated in the past five groups of update processes from the historical update completion data of the item to be updated, performing average processing on the multiple groups of update rates corresponding to a single group of update processes, determining the update average speed of the corresponding update process, and then determining five groups of update average speeds based on the five groups of update processes, and determining the update average speed interval based on the minimum and maximum values ​​of the five groups of update average speeds. Specifically, the past five groups of update processes are not limited to only five groups, and groups with other values ​​can also be taken synchronously. The corresponding management personnel perform specific value settings, and the update average speed interval can effectively display its specific update characteristics, which is convenient for subsequent confirmation of specific time intervals.

[0037] S12, based on the overall update amount of the item to be updated, and based on the determined update average speed interval, determine the relevant time interval for completing the associated update of the corresponding item to be updated, and set the overall update amount to ZL, and its update average speed interval to [Jsmin, Jsmax], using ZL÷Jsmin=Tmax and ZL÷Jsmax=Tmin, and the corresponding relevant time interval is [Tmin, Tmax], and the overall update amount ZL is set to 1000 units of data; the update average speed interval is [20 units / minute, 50 units / minute], that is, Jsmin=20 units / minute, Jsmax=50 units / minute;

[0038] Calculate Tmax and Tmin:

[0039] Tmax=ZL÷Jsmin=1000÷20=50 minutes;

[0040] Tmin=ZL÷Jsmax=1000÷50=20 minutes;

[0041] Step 2: Based on the past application time of the corresponding item to be updated, identify the unused period of the item to be updated, and then based on the determined relevant time interval, lock the selected update period for the item to be updated to be associated and updated. Specifically, in order to enable the corresponding item to be updated to be associated and updated, it is necessary to perform the associated update in an unused state. When the update operation is performed in the used state, it will affect the specific data application process;

[0042] The specific method of locking the update period to be selected for the item to be updated is as follows:

[0043] S21. Define a set of extraction cycles T, where T is a preset value, and its specific value is determined by the operator based on experience, and T is generally set to 30 days. Identify the application period of the item to be updated in this extraction period T from the past application time, and the application period adopts a 24-hour system. Determine the crossover period from the identified groups of application periods, and sort the determined groups of crossover periods according to the number of crossovers corresponding to the crossover period in a manner from most to least according to the number of crossovers, and determine the crossover period sequence. If there are crossover periods with the same number of crossovers, they can be randomly sorted. For example: it is proposed that there are three application periods, namely 5-7, 6-8, and 6.5-8.5, then the generated crossover period includes multiple groups, and the one with three crossovers belongs to 6.5-7. This period is the group of crossover periods with the largest number of crossovers, so it is ranked first in the crossover period sequence. Because this crossover period appears in each application period, it means that the corresponding application party is basically in the state of being applied in this period;

[0044] S22, based on the different application time periods generated every day, identify the total proportion value Z of the application time periods within a single day k , where k represents different days, and Z k = total of application period ÷ 24h, the number of groups Z generated within this extraction period T k Perform mean processing to determine the mean value of the correlation ratio JZ, and use 24h×JZ=XG to lock the correlation value (this correlation value is the length of a period);

[0045] S23. Based on the correlation value, some crossover periods with a value less than (correlation value × 0.7) are removed from the crossover period sequence, and the crossover period sequence after the removal process is marked as a candidate sequence. The greater the deviation between the crossover period and the original correlation value, the less consideration it has, so it can be directly removed without any relevant consideration;

[0046] S24, identifying the unused time periods corresponding to different internal cross time periods from the sequence to be selected, that is, in 24 hours, if the cross time period is 5-10, then the unused time periods are 0-5 and 10-24, and whether the intersection point of the time period is selected or not selected here will not affect the specific execution process, so the interval representation is not used here, based on the specific duration of different unused time periods, the unused time periods with a specific duration exceeding this relevant time interval are marked as the update period to be selected, if there is no unused time period with a specific duration exceeding this relevant time interval, then the unused time period belonging to this relevant time interval is marked as the update period to be selected, if there is neither an unused time period with a specific duration exceeding this relevant time interval nor an unused time period with a specific duration exceeding this relevant time interval, then no marking is performed;

[0047] Specifically, the relevant determination of the corresponding update time period is carried out here so that the corresponding item to be updated can be updated at a more correct time and the relevant update process can be executed. By adopting the relevant processing method of the above-mentioned cross-time period, the relevant determination of the corresponding update time period can be basically completed in a faster time period, and the corresponding update time period can be determined with a great probability, so as to facilitate the data update of the corresponding item to be updated.

[0048] Step 3: Based on the determined update period to be selected and the determined unused period, data of the item to be updated is updated. The specific period of the update is within the update period to be selected and the unused period. The sub-steps associated with the specific selection logic of the specific period are:

[0049] S31, identifying whether the item to be updated has a waiting update period:

[0050] If there is a waiting update period, the data of the waiting update item is updated from the waiting update period closest to the current time. If the update is not completed in this waiting update period, it is identified whether there is a subsequent waiting update period. If so, the update is continued. If not, the nearest unused period is selected for data update until the data update process is completed;

[0051] If there is no update period to be selected, the data of the item to be updated will be updated from the unused period closest to the current time. If the update is completed, the entire data update process will be completed. If the update is not completed, the data will continue to be updated using the subsequently confirmed unused time periods until the data update process is completed.

[0052] Specifically, when updating data, priority is given to selecting from the candidate update time periods. If no relevant associated time period is selected, then an associated selection is made directly from the unused time period to complete the specific data update process and the specific data update processing.

[0053] Example 2

[0054] In the specific implementation process, compared with the above-mentioned embodiment, the specific difference of this embodiment is that this embodiment mainly targets the associated processes of different items to be updated that are updated synchronously in the same period, and based on the corresponding computing power allocation, ensures that each associated process can guarantee its related update rate;

[0055] Step 4: When different items to be updated have update processes in the same period, based on the update rate of the corresponding items to be updated, it is evaluated whether the items to be updated can complete the update process within the determined relevant time interval. If it can be completed, no relevant processing is performed. If it cannot be completed, computing power is allocated to ensure that the different items to be updated can complete the corresponding update process within the corresponding relevant time interval. The specific sub-steps of the evaluation are:

[0056] S41. Based on multiple update processes existing in the same period, a monitoring period is defined. The monitoring period is a preset period, which is prepared in advance by relevant personnel based on experience. Generally, the value is 1 minute or even shorter. The average update rate (that is, the average of multiple groups of update rates) Jq generated by the corresponding items to be updated in this monitoring period is identified, where q represents different items to be updated. Then, the remaining update amount of the corresponding items to be updated is identified and calibrated as SYq. SYq÷Jq=Tq is used to determine the remaining update time Tq of the items to be updated. Based on the update time Gq of the partially updated items, it is identified whether the associated time (Tq+Gq) of the corresponding items to be updated belongs to the corresponding related time interval:

[0057] If they are both, no relevant processing will be performed and the original update process can be maintained;

[0058] Otherwise, step S42 is executed to allocate computing power;

[0059] S42, mark the to-be-updated item whose associated time belongs to the corresponding relevant time interval as the to-be-allocated item, determine the maximum time value Ttmax of the to-be-allocated item corresponding to the relevant time interval, use SYq÷(Ttmax-Gq)=Jqmin to determine the minimum update rate Jqmin of the to-be-allocated item, reduce the relevant computing power of the to-be-allocated item, and stop when the update rate of the to-be-allocated item reaches Jqmin, and allocate the reduced relevant computing power to the to-be-allocated items that are not marked as the to-be-allocated items;

[0060] For other items to be updated that are not marked as items to be allocated, the same processing method is adopted to identify the minimum update rate Jqmin of these items to be updated. When the corresponding update rate of the items to be updated reaches Jqmin after the computing power is allocated, the allocation is stopped. If Jqmin cannot be reached all the time, the different items to be updated are adjusted to the same load balancing state and stopped. The so-called same load balancing state is that multiple items to be updated are in the state of the same update load, and the distance difference between their corresponding update rates and their corresponding Jqmin is the same. Then this kind of state is the same load balancing state, and the allocation process is based on the computing power allocated to other items to be allocated. Therefore, it is best if they can be completed completely within the relevant time interval. If it still cannot be completed, it is best to adjust several items to be updated to a synchronized load balancing state to achieve a better adjustment processing method.

[0061] Some of the data in the above formulas are dimensionless and numerically calculated. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0062] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A method for configuring a mobile application workstation, characterized in that: The following steps are involved: Step 1: Identify the items to be updated on the mobile application workbench, and simultaneously confirm the overall update amount of the items to be updated. Then, based on the historical update completion data of the items to be updated and the past update rate of the items to be updated, lock the relevant time interval for completing the associated updates of the items to be updated. The specific sub-steps are: S11, based on the determined item to be updated, taking the current time as the calibration time, obtaining several groups of update rates generated in the past five groups of update processes from the historical update completion data of the item to be updated, performing average processing on multiple groups of update rates corresponding to a single group of update processes, determining the update average speed of the corresponding update process, and then determining five groups of update average speeds based on the five groups of update processes, and determining the update average speed interval based on the minimum and maximum values ​​of the five groups of update average speeds; S12, based on the overall update amount of the item to be updated and the determined average update speed interval, determining a relevant time interval for completing the associated update of the item to be updated; Step 2: Based on the past application time of the corresponding item to be updated, identify the unused time period of the item to be updated, and then based on the determined relevant time interval, lock the selected update time period in which the item to be updated can be associated and updated. The specific method is as follows: S21, defining a group of extraction cycles T, where T is a preset value, identifying the application period of the item to be updated in the extraction period T from the past application time, wherein the application period adopts a 24-hour system, determining the crossover period from the identified groups of application periods, and sorting the determined groups of crossover periods in a manner from most to least according to the number of crossovers corresponding to the crossover periods, and determining the crossover period sequence. If there are crossover periods with the same number of crossovers, they can be randomly sorted; S22, based on the different application time periods generated every day, identify the total proportion value Z of the application time periods within a single day k , where k represents different days, and Z k = total of application period ÷ 24h, the number of groups Z generated within this extraction period T k Perform mean processing to determine the mean value of the correlation ratio JZ, and use 24h×JZ=XG to lock the correlation value; S23, based on the correlation value, remove some cross-periods whose value is less than the correlation value×0.7 from the cross-period sequence, and mark the cross-period sequence after the removal process as a sequence to be selected; S24, identifying the unused time periods corresponding to different intersecting time periods in the sequence to be selected, and based on the specific durations of the different unused time periods, marking the unused time periods whose specific durations exceed the relevant time interval as the update time periods to be selected; if there is no unused time period whose specific duration exceeds the relevant time interval, marking the unused time period belonging to the relevant time interval as the update time period to be selected; Step 3: based on the determined update period to be selected and the determined unused period, update the data of the item to be updated, wherein the specific period of the update is within the update period to be selected and the unused period; Step 4: When different items to be updated have update processes in the same period, whether the items to be updated can complete the update process within the determined relevant time interval is evaluated based on the update rate of the corresponding items to be updated. If it can be completed, no relevant processing is performed. If it cannot be completed, computing power is allocated.

2. A method for configuring a mobile application workstation according to claim 1, characterized in that: In the step S24, if there is neither an unused period whose specific duration exceeds the relevant time interval nor an unused period whose specific duration exceeds the relevant time interval, no calibration is performed.

3. A method for configuring a mobile application workstation according to claim 1, characterized in that: In step 3, the sub-steps associated with the specific selection logic of the specific time period are: S31, identifying whether the item to be updated has a waiting update period: If there is a waiting update period, the data of the waiting update item is updated from the waiting update period closest to the current time. If the update is not completed in this waiting update period, it is identified whether there is a subsequent waiting update period. If so, the update is continued. If not, the nearest unused period is selected for data update until the data update process is completed; If there is no update period to be selected, the data of the item to be updated will be updated from the unused period closest to the current time. If the update is not completed, the data will be updated continuously using the subsequently confirmed unused periods until the data update process is completed.

4. A method for configuring a mobile application workstation according to claim 1, characterized in that: In step 4, the specific method of evaluating whether the item to be updated can complete the update process within the determined relevant time interval is: S41. Based on multiple update processes existing in the same period, a monitoring period is defined, and the monitoring period is a preset period. The average update rate Jq generated by the corresponding item to be updated in the monitoring period is identified, where q represents different items to be updated. The remaining update amount of the corresponding item to be updated is then identified and calibrated as SYq. The remaining update time Tq of the item to be updated is determined using SYq÷Jq=Tq. Based on the update time Gq of the partially updated item, it is identified whether the associated time Tq+Gq of the corresponding item to be updated belongs to the corresponding related time interval: If they are both, no relevant processing will be performed and the original update process can be maintained; Otherwise, step S42 is executed to allocate computing power; S42, mark the to-be-updated item whose associated time belongs to the corresponding relevant time interval as the to-be-allocated item, determine the maximum time value Ttmax of the to-be-allocated item corresponding to the relevant time interval, use SYq÷(Ttmax-Gq)=Jqmin to determine the minimum update rate Jqmin of the to-be-allocated item, reduce the relevant computing power of the to-be-allocated item, and stop when the update rate of the to-be-allocated item reaches Jqmin, and allocate the reduced relevant computing power to the to-be-allocated items that are not marked as the to-be-allocated items; For other items to be updated that are not marked as items to be allocated, the same processing method is adopted to identify the minimum update rate Jqmin of these items to be updated. When the corresponding update rate of the items to be updated reaches Jqmin after the computing power is allocated, the allocation is stopped. If Jqmin cannot be reached, the different items to be updated are adjusted to the same load balancing state and stopped.

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