A method and apparatus for expanding the associated storage device of a cloud mobile phone service

Abstract

This application discloses a method and apparatus for expanding the associated storage device of a cloud phone service. The method includes: determining a predicted expansion time based on the historical storage utilization rate of the cloud phone service and a preset storage utilization rate threshold; determining a target expansion coefficient based on the average storage utilization rate growth rate of the historical storage utilization rate; determining a basic expansion capacity and threshold adaptation coefficient based on the preset storage utilization rate threshold and the target expansion coefficient; determining a fragmentation optimization coefficient based on the current fragmentation rate of the associated storage device; multiplying the basic expansion capacity, threshold adaptation coefficient, and fragmentation optimization coefficient to obtain the predicted expansion capacity; and determining a target expansion time based on the predicted expansion time and the allowed expansion period of the cloud phone service. This technical solution, by accurately predicting the expansion time and expansion capacity, achieves accurate predictive expansion of the associated storage device while minimizing the impact of cloud phone service interruptions, balancing expansion execution efficiency and business continuity.

Description

Technical Field

[0001] This application belongs to the field of electronic digital data processing technology, specifically relating to a method and apparatus for expanding the associated storage device of a cloud mobile phone service. Background Technology

[0002] Cloud phone services rely on cloud computing architecture to realize the functionality of virtual mobile devices, providing users with a cross-terminal, elastically scalable mobile experience. As the application scenarios of cloud phone services become increasingly diverse, users' dynamic demands for cloud phone storage capacity are becoming more prominent. This dynamic demand often manifests as rapid growth in storage capacity; therefore, it is essential that the associated storage devices, as the core data carriers of cloud phone services, possess dynamic expansion capabilities.

[0003] Currently, the main methods for expanding the capacity of associated storage devices for cloud phone services are either to achieve a certain degree of elastic adjustment at the logical level through storage virtualization technology when the storage capacity of the associated storage devices is identified as approaching saturation, or to interrupt the cloud phone service for physical expansion. The first method can only achieve limited elastic adjustment, and the expansion range is limited by the underlying physical storage resources, failing to fundamentally solve the problem of insufficient storage capacity; the second method requires interrupting the cloud phone service to complete the operation, severely affecting business continuity and failing to meet the actual need for uninterrupted operation of cloud phone services. Summary of the Invention

[0004] This application provides a method and apparatus for expanding the associated storage device of a cloud phone service. The purpose is to achieve accurate predictive expansion of the associated storage device by accurately predicting the expansion time and capacity, while minimizing the impact of cloud phone service interruptions, and taking into account both expansion execution efficiency and business continuity.

[0005] In a first aspect, embodiments of this application provide a method for expanding the associated storage device of a cloud phone service, the method comprising:

[0006] Obtain the historical storage usage rate of the associated storage devices of the cloud phone service, and determine the predicted expansion time based on the historical storage usage rate and a preset storage usage rate threshold;

[0007] Calculate the average storage utilization rate growth rate based on the historical storage utilization rate, and determine the target expansion coefficient based on the average storage utilization rate growth rate;

[0008] Based on the preset storage utilization threshold and the target expansion coefficient, the basic expansion capacity and threshold adaptation coefficient are determined, the current fragmentation rate of the associated storage device is obtained, and the fragmentation optimization coefficient is determined according to the current fragmentation rate. The predicted expansion capacity is obtained by multiplying the basic expansion capacity, the threshold adaptation coefficient, and the fragmentation optimization coefficient.

[0009] Obtain the allowed expansion period of the cloud phone service, and determine the target expansion time based on the predicted expansion time and the allowed expansion period;

[0010] Based on the target expansion time and the predicted expansion capacity, expansion plan information is generated, and when the expansion plan information is detected to have been executed, the storage space allocation information of the associated storage device for the cloud phone service is updated synchronously.

[0011] Furthermore, determining the target expansion coefficient based on the average storage utilization growth rate includes:

[0012] The basic expansion coefficient is determined based on the average storage utilization growth rate.

[0013] Obtain the real-time storage utilization rate growth rate and calculate the ratio of the real-time storage utilization rate growth rate to the average storage utilization rate growth rate as the growth rate deviation coefficient;

[0014] Obtain the adjustment weighting factor, and calculate the target expansion coefficient based on the basic expansion coefficient, the adjustment weighting factor, and the growth rate deviation coefficient.

[0015] Furthermore, obtaining the adjustment weighting factor includes:

[0016] Obtain the current number of online instances of the cloud phone service and the preset instance number threshold;

[0017] The ratio of the current number of online instances to the preset instance number threshold is calculated as an adjustment weight factor.

[0018] Furthermore, determining the basic expansion capacity and threshold adaptation coefficient based on the preset storage utilization threshold and the target expansion coefficient includes:

[0019] Obtain the current total storage capacity of the associated storage device, and determine the basic expansion capacity based on the current total storage capacity and the target expansion coefficient;

[0020] The threshold approximation frequency is determined based on the historical storage usage rate and the preset storage usage rate threshold, and the threshold adaptation coefficient is determined based on the threshold approximation frequency.

[0021] Furthermore, the permitted expansion period for obtaining the cloud phone service includes:

[0022] Obtain the historical service load intensity and service interruption sensitivity level of each cloud phone instance in the cloud phone service;

[0023] The service off-peak periods for each cloud mobile phone instance are determined based on the historical service load intensity, and the service impact weighting coefficient for each cloud mobile phone instance is determined based on the service interruption sensitivity level.

[0024] The allowable expansion period for the cloud phone service is calculated by weighting the low-traffic periods of each cloud phone instance based on the business impact weighting coefficient.

[0025] Furthermore, determining the service impact weighting coefficient for each cloud phone instance based on the service interruption sensitivity level includes:

[0026] The baseline weighting coefficient is determined based on the aforementioned service interruption sensitivity level;

[0027] Obtain the total read / write time and total runtime of the cloud phone instance during the off-peak business period, and calculate the ratio of the total read / write time to the total runtime of the instance as the storage dependency.

[0028] The business impact weight coefficient of the cloud phone instance is obtained by multiplying the baseline weight coefficient by the storage dependency.

[0029] Furthermore, determining the predicted expansion time based on the historical storage usage rate and a preset storage usage rate threshold includes:

[0030] Extract at least two time-dimensional subsequences of historical storage usage from the historical storage usage rate;

[0031] Based on each of the historical storage utilization rate subsequences, the time when the storage utilization rate of the associated storage device reaches the preset storage utilization rate threshold is predicted as the dimension prediction time corresponding to each of the historical storage utilization rate subsequences.

[0032] The predicted expansion time is obtained by weighting and fusing the predicted time of each of the historical storage usage rate subsequences.

[0033] Secondly, embodiments of this application provide a storage device expansion apparatus for cloud phone services, the apparatus comprising:

[0034] The time prediction module is used to obtain the historical storage usage rate of the associated storage devices of the cloud phone service, and determine the predicted expansion time based on the historical storage usage rate and the preset storage usage rate threshold.

[0035] The coefficient determination module is used to calculate the average storage utilization rate growth rate based on the historical storage utilization rate, and to determine the target expansion coefficient based on the average storage utilization rate growth rate.

[0036] The capacity prediction module is used to determine the basic expansion capacity and threshold adaptation coefficient based on the preset storage utilization threshold and the target expansion coefficient, obtain the current fragmentation rate of the associated storage device and determine the fragmentation optimization coefficient based on the current fragmentation rate, and multiply the basic expansion capacity, the threshold adaptation coefficient and the fragmentation optimization coefficient to obtain the predicted expansion capacity.

[0037] The time determination module is used to obtain the allowed expansion period of the cloud phone service, and determine the target expansion time based on the predicted expansion time and the allowed expansion period;

[0038] The expansion execution module is used to generate expansion plan information based on the target expansion time and the predicted expansion capacity, and synchronously update the storage space allocation information of the associated storage device for the cloud phone service when it is recognized that the expansion plan information has been executed.

[0039] Furthermore, the coefficient determination module is specifically used for:

[0040] The basic expansion coefficient is determined based on the average storage utilization growth rate.

[0041] Obtain the real-time storage utilization rate growth rate and calculate the ratio of the real-time storage utilization rate growth rate to the average storage utilization rate growth rate as the growth rate deviation coefficient;

[0042] Obtain the adjustment weighting factor, and calculate the target expansion coefficient based on the basic expansion coefficient, the adjustment weighting factor, and the growth rate deviation coefficient.

[0043] Furthermore, the coefficient determination module is specifically used for:

[0044] Obtain the current number of online instances of the cloud phone service and the preset instance number threshold;

[0045] The ratio of the current number of online instances to the preset instance number threshold is calculated as an adjustment weight factor.

[0046] Furthermore, the capacity prediction module is specifically used for:

[0047] Obtain the current total storage capacity of the associated storage device, and determine the basic expansion capacity based on the current total storage capacity and the target expansion coefficient;

[0048] The threshold approximation frequency is determined based on the historical storage usage rate and the preset storage usage rate threshold, and the threshold adaptation coefficient is determined based on the threshold approximation frequency.

[0049] Furthermore, the time determination module is specifically used for:

[0050] Obtain the historical service load intensity and service interruption sensitivity level of each cloud phone instance in the cloud phone service;

[0051] The service off-peak periods for each cloud mobile phone instance are determined based on the historical service load intensity, and the service impact weighting coefficient for each cloud mobile phone instance is determined based on the service interruption sensitivity level.

[0052] The allowable expansion period for the cloud phone service is calculated by weighting the low-traffic periods of each cloud phone instance based on the business impact weighting coefficient.

[0053] Furthermore, the time determination module is specifically used for:

[0054] The baseline weighting coefficient is determined based on the aforementioned service interruption sensitivity level;

[0055] Obtain the total read / write time and total runtime of the cloud phone instance during the off-peak business period, and calculate the ratio of the total read / write time to the total runtime of the instance as the storage dependency.

[0056] The business impact weight coefficient of the cloud phone instance is obtained by multiplying the baseline weight coefficient by the storage dependency.

[0057] Furthermore, the time prediction module is specifically used for:

[0058] Extract at least two time-dimensional subsequences of historical storage usage from the historical storage usage rate;

[0059] Based on each of the historical storage utilization rate subsequences, the time when the storage utilization rate of the associated storage device reaches the preset storage utilization rate threshold is predicted as the dimension prediction time corresponding to each of the historical storage utilization rate subsequences.

[0060] The predicted expansion time is obtained by weighting and fusing the predicted time of each of the historical storage usage rate subsequences.

[0061] Thirdly, embodiments of this application provide an electronic device including a processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein the program or instructions, when executed by the processor, implement the method described in the first aspect.

[0062] Fourthly, embodiments of this application provide a readable storage medium on which a program or instructions are stored, which, when executed by a processor, implement the method described in the first aspect.

[0063] In this embodiment, the historical storage usage rate of the associated storage device of the cloud phone service is obtained, and a predicted expansion time is determined based on the historical storage usage rate and a preset storage usage rate threshold; the average storage usage rate growth rate is calculated based on the historical storage usage rate, and a target expansion coefficient is determined based on the average storage usage rate growth rate; a basic expansion capacity and threshold adaptation coefficient are determined based on the preset storage usage rate threshold and the target expansion coefficient; the current fragmentation rate of the associated storage device is obtained, and a fragmentation optimization coefficient is determined based on the current fragmentation rate; the basic expansion capacity, the threshold adaptation coefficient, and the fragmentation optimization coefficient are multiplied to obtain the predicted expansion capacity; the allowed expansion period of the cloud phone service is obtained, and a target expansion time is determined based on the predicted expansion time and the allowed expansion period; expansion plan information is generated based on the target expansion time and the predicted expansion capacity, and when the expansion plan information is detected to have been executed, the storage space allocation information of the associated storage device for the cloud phone service is synchronously updated. The aforementioned method for expanding the associated storage devices of cloud phone services achieves accurate predictive expansion of associated storage devices by precisely predicting the expansion time and capacity, minimizing the impact of cloud phone service interruptions, and balancing expansion execution efficiency with business continuity. Attached Figure Description

[0064] Figure 1 This is a flowchart illustrating a method for expanding the associated storage device of a cloud phone service according to an embodiment of this application;

[0065] Figure 2 This is a flowchart illustrating another method for expanding the associated storage device of a cloud phone service provided in this application embodiment;

[0066] Figure 3 This is a flowchart illustrating another method for expanding the associated storage device of a cloud phone service provided in this application embodiment;

[0067] Figure 4 This is a schematic diagram of the structure of a cloud phone service associated storage device expansion device provided in an embodiment of this application;

[0068] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0069] To make the objectives, technical solutions, and advantages of this application clearer, specific embodiments of this application will be described in further detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely for explaining this application and not for limiting it. It should also be noted that, for ease of description, only the parts relevant to this application are shown in the drawings, not all of them. Before discussing exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe operations (or steps) as sequential processes, many of these operations can be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but may also have additional steps not included in the drawings. The process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0070] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0071] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0072] The method and apparatus for expanding the associated storage device of cloud mobile phone service provided in this application will be described in detail below with reference to the accompanying drawings, through specific embodiments and application scenarios.

[0073] First, this application applies to scenarios involving storage expansion for cloud phone services. Based on the above use case, it can be understood that the implementing entity of this application can be an associated storage device, specifically an integrated storage management module within the associated storage device.

[0074] In this context, cloud phone service can be a service that provides a virtual phone environment in the cloud; associated storage device can be a storage device used to provide storage support for cloud phone service, such as a NAS (Network Attached Storage) device; and integrated storage management module can be a software module in the associated storage device responsible for storage resource allocation and monitoring. Specifically, a NAS device can be a dedicated file storage device that connects to a network and provides file-level data storage services.

[0075] In this solution, the associated storage device runs a container engine, such as the Docker container engine. The volume plugin within the associated storage device abstracts the physical storage resources of the associated storage device into a logical storage resource pool. The container engine can be a software platform used to create, run, and manage containers. The volume plugin can be a dedicated functional plugin deployed between the container engine and the physical storage, responsible for implementing virtualization abstraction of physical storage resources, mapping of logical storage resources, and data read / write scheduling, such as a local or NFS driver. The logical storage resource pool can be a collection of virtualized storage spaces that can be dynamically allocated and used by the container engine, managed collaboratively by the volume plugin and the integrated storage management module.

[0076] Figure 1 This is a flowchart illustrating a method for expanding the associated storage device of a cloud phone service according to an embodiment of this application. Figure 1 As shown, the specific steps include the following:

[0077] S101, obtain the historical storage usage rate of the associated storage device of the cloud phone service, and determine the predicted expansion time based on the historical storage usage rate and the preset storage usage rate threshold.

[0078] Storage utilization rate can be the ratio of used storage capacity to total storage capacity. Correspondingly, historical storage utilization rate can be a sequence of storage utilization rate data recorded over a past period.

[0079] In one embodiment, the historical storage usage rate of the associated storage device of the cloud phone service can be obtained by periodically reading the log records of the associated storage device of the cloud phone service.

[0080] The preset storage utilization threshold can be a pre-set storage utilization threshold that triggers expansion, such as 70%, 80%, or 90%.

[0081] The predicted expansion time can be the time when the storage utilization rate is expected to reach a preset storage utilization rate threshold, which can be a specific date.

[0082] In one embodiment, the method of determining the predicted expansion time based on historical storage utilization and a preset storage utilization threshold can be achieved by using a time series prediction algorithm to predict the future storage utilization sequence based on historical storage utilization, and determining the time when the future storage utilization reaches the preset storage utilization threshold as the predicted expansion time.

[0083] In one embodiment, determining the predicted expansion time based on the historical storage utilization rate and a preset storage utilization rate threshold includes: extracting at least two time-dimensional historical storage utilization rate subsequences from the historical storage utilization rate; predicting the time when the storage utilization rate of the associated storage device reaches the preset storage utilization rate threshold based on each of the historical storage utilization rate subsequences as the dimension prediction time corresponding to each of the historical storage utilization rate subsequences; and weighting and fusing the dimension prediction times corresponding to each of the historical storage utilization rate subsequences to obtain the predicted expansion time.

[0084] The time dimension can be a time period granularity, such as a day, a week, or a month; the historical storage usage rate subsequence can be a subset extracted from the original historical storage usage rate sequence according to a specific time dimension, such as the storage usage rate sequence at the same time every day, the storage usage rate sequence on the same day every week, or the storage usage rate sequence on the same day every month.

[0085] Among them, the dimension prediction time can be the time point when the storage utilization rate reaches the preset storage utilization rate threshold, which is predicted based on the historical storage utilization rate subsequence of a specific time dimension.

[0086] In one embodiment, the method of predicting the time when the storage utilization rate of the associated storage device reaches a preset storage utilization rate threshold based on each historical storage utilization rate subsequence can be used as the dimension prediction time corresponding to each historical storage utilization rate subsequence. This can be achieved by using a time series prediction algorithm to predict the future storage utilization rate sequence based on each historical storage utilization rate subsequence, and determining the time when the future storage utilization rate reaches the preset storage utilization rate threshold as the dimension prediction time corresponding to each historical storage utilization rate subsequence.

[0087] In one embodiment, the weighted fusion of the predicted times for each historical storage usage subsequence to obtain the predicted expansion time can be achieved by multiplying the predicted times for each dimension by their respective weight coefficients and then summing the results to obtain the final predicted expansion time. As an example, the weight coefficients for the historical storage usage subsequences corresponding to the three time dimensions of one day, one week, and one month can be 0.7, 0.2, and 0.1, respectively.

[0088] The advantage of this approach is that by introducing multi-time-dimensional predictions and weighted fusion, it can more comprehensively capture the changing patterns of storage utilization over different periods, avoiding the one-sidedness of predictions based on a single time dimension. This improves the accuracy and robustness of predicting expansion time, making expansion plans more aligned with actual business needs.

[0089] S102, calculate the average storage utilization rate growth rate based on the historical storage utilization rate, and determine the target expansion coefficient based on the average storage utilization rate growth rate.

[0090] The average storage utilization rate growth rate can be the average growth rate of historical storage utilization.

[0091] In one embodiment, the average storage utilization growth rate can be calculated by performing a linear regression on the historical storage utilization rate and taking the slope as the average storage utilization growth rate.

[0092] The target expansion factor can be a proportional factor used to adjust the expansion capacity, that is, the ratio of the target basic total storage capacity to the current total storage capacity.

[0093] In one embodiment, a pre-established correlation between the average storage utilization rate growth rate and the expansion coefficient is used. The current average storage utilization rate growth rate is mapped to this correlation to obtain the target expansion coefficient. This correlation can be built based on historical expansion experience data or simulation experiments. As an example, the correlation between the average storage utilization rate growth rate and the expansion coefficient can be as follows: when the average storage utilization rate growth rate is below 5%, the corresponding target expansion coefficient is 1.2; when the average storage utilization rate growth rate is between 5% and 10%, the corresponding target expansion coefficient is 1.5; and when the average storage utilization rate growth rate is above 10%, the corresponding target expansion coefficient is 2.0.

[0094] S103, determine the basic expansion capacity and threshold adaptation coefficient based on the preset storage utilization threshold and the target expansion coefficient, obtain the current fragmentation rate of the associated storage device and determine the fragmentation optimization coefficient according to the current fragmentation rate, and multiply the basic expansion capacity, the threshold adaptation coefficient and the fragmentation optimization coefficient to obtain the predicted expansion capacity.

[0095] Among them, the basic expansion capacity can be the basic expansion size calculated based on the current total storage capacity and the target expansion coefficient; the threshold adaptation coefficient can be a coefficient used to describe the degree of adaptation between the preset storage utilization threshold and the current expansion scenario.

[0096] In one embodiment, the method of determining the basic expansion capacity and threshold adaptation coefficient based on the preset storage utilization threshold and the target expansion coefficient can be achieved by obtaining the current total storage capacity of the associated storage device, determining the basic expansion capacity based on the current total storage capacity and the target expansion coefficient, determining the threshold approximation frequency based on the historical storage utilization rate and the preset storage utilization threshold, and determining the threshold adaptation coefficient based on the threshold approximation frequency.

[0097] The current total storage capacity can be the total storage space currently configured for the cloud phone service by the associated storage devices.

[0098] In one embodiment, the current total storage capacity of the associated storage device can be obtained by using a file system query command or by calling the query interface of the integrated storage management module.

[0099] In one embodiment, the method for determining the basic expansion capacity based on the current total storage capacity and the target expansion factor can be to multiply the current total storage capacity by the target expansion factor to obtain the target total storage capacity, and then subtract the current total storage capacity from the target total storage capacity to obtain the basic expansion capacity.

[0100] The threshold approach frequency can be defined as the frequency with which historical storage usage approaches a preset storage usage threshold.

[0101] In one embodiment, the method of determining the threshold approximation frequency based on historical storage usage rate and preset storage usage rate threshold can be as follows: determine the threshold approximation interval based on the preset storage usage rate threshold, record the number of storage usage rates in the historical storage usage rate that fall within the threshold approximation interval, and divide the number by the total number of historical storage usage rates to obtain the threshold approximation frequency.

[0102] In one embodiment, determining the threshold adaptation coefficient based on the threshold approximation frequency can be achieved by pre-establishing a correlation between the threshold approximation frequency and the threshold adaptation coefficient. This correlation allows mapping the current threshold approximation frequency to obtain the target threshold adaptation coefficient. The correlation between the threshold approximation frequency and the threshold adaptation coefficient can be constructed based on historical expansion effect feedback or simulation test data. As an example, the correlation between the threshold approximation frequency and the threshold adaptation coefficient can be as follows: when the threshold approximation frequency is below 10%, the corresponding threshold adaptation coefficient is 1.0; when the threshold approximation frequency is between 10% and 30%, the corresponding threshold adaptation coefficient is 1.2; and when the threshold approximation frequency is above 30%, the corresponding threshold adaptation coefficient is 1.5.

[0103] The advantage of this scheme is that by introducing a threshold approximation frequency to dynamically adjust the threshold adaptation coefficient, the capacity expansion can better match the actual storage usage pattern, thereby achieving efficient utilization of storage resources and optimization of expansion costs.

[0104] The current fragmentation rate can be the proportion of non-contiguous free blocks in the storage space; the fragmentation optimization coefficient can be an adjustment factor set to take into account the impact of fragmentation on storage efficiency.

[0105] In one embodiment, the current fragmentation rate of the associated storage device can be obtained by querying the file system or by using a fragmentation detection tool.

[0106] In one embodiment, a pre-established correlation between fragmentation rate and fragmentation optimization coefficient is used. The current fragmentation rate is mapped based on this correlation to obtain the target fragmentation optimization coefficient. This correlation can be constructed based on historical expansion experience data or simulation experiments. Alternatively, it can be constructed based on storage performance test data of associated storage devices. As an example, the correlation between fragmentation rate and fragmentation optimization coefficient can be as follows: when the fragmentation rate is below 5%, the corresponding fragmentation optimization coefficient is 1.0; when the fragmentation rate is between 10% and 30%, the corresponding fragmentation optimization coefficient is 1.2; and when the fragmentation rate is above 30%, the corresponding fragmentation optimization coefficient is 1.5.

[0107] The predicted expansion capacity can be the final, recommended increase in storage capacity.

[0108] In one embodiment, the method of multiplying the basic expansion capacity, the threshold adaptation coefficient, and the fragmentation optimization coefficient to obtain the predicted expansion capacity can be achieved by directly multiplying the basic expansion capacity, the threshold adaptation coefficient, and the fragmentation optimization coefficient to obtain the predicted expansion capacity.

[0109] S104, obtain the allowed expansion period of the cloud phone service, and determine the target expansion time based on the predicted expansion time and the allowed expansion period.

[0110] Among them, the allowed expansion period for cloud phone services can be the time of day during which the impact of cloud phone service interruption can be minimized.

[0111] In one embodiment, the allowed expansion period for the cloud phone service can be preset, for example, from 02:00 to 04:00 every day.

[0112] The target expansion time can be the specific time point at which the expansion operation is finally determined.

[0113] In one embodiment, the method of determining the target expansion time based on the predicted expansion time and the allowed expansion period can be to determine the predicted expansion time as the date in the target expansion time and the allowed expansion period as the specific time period in the target expansion time.

[0114] S105, based on the target expansion time and the predicted expansion capacity, generate expansion plan information, and when it is recognized that the expansion plan information has been executed, synchronously update the storage space allocation information of the associated storage device for the cloud phone service.

[0115] The expansion plan information can include the target expansion time and the predicted expansion capacity, and is used to remind staff that expansion is needed.

[0116] In one embodiment, the method of generating expansion plan information based on the target expansion time and the predicted expansion capacity can be achieved by filling the target expansion time and the predicted expansion capacity into a preset expansion plan template to obtain the expansion plan information.

[0117] The expansion plan information may also include standardized expansion processes, which may specifically include disk installation, data migration verification, and rollback contingency plans.

[0118] The completion of the expansion plan information can be defined as the successful completion of the expansion operation and the actual increase in storage capacity.

[0119] The storage space allocation information may include the storage capacity quota information of each cloud phone instance in the cloud phone service.

[0120] In one embodiment, the method for synchronously updating the storage space allocation information of associated storage devices for the cloud phone service can be achieved by using an integrated storage management module to reallocate the storage capacity quota of each cloud phone instance in the cloud phone service based on the expanded current total storage capacity, and updating the storage space allocation information. The integrated storage management module can also implement functions such as dynamic quota adjustment, data lifecycle management, and fault isolation.

[0121] In this embodiment, the historical storage usage rate of the associated storage device of the cloud phone service is obtained, and a predicted expansion time is determined based on the historical storage usage rate and a preset storage usage rate threshold; the average storage usage rate growth rate is calculated based on the historical storage usage rate, and a target expansion coefficient is determined based on the average storage usage rate growth rate; a basic expansion capacity and threshold adaptation coefficient are determined based on the preset storage usage rate threshold and the target expansion coefficient; the current fragmentation rate of the associated storage device is obtained, and a fragmentation optimization coefficient is determined based on the current fragmentation rate; the basic expansion capacity, the threshold adaptation coefficient, and the fragmentation optimization coefficient are multiplied to obtain the predicted expansion capacity; the allowed expansion period of the cloud phone service is obtained, and a target expansion time is determined based on the predicted expansion time and the allowed expansion period; expansion plan information is generated based on the target expansion time and the predicted expansion capacity, and when the expansion plan information is detected to have been executed, the storage space allocation information of the associated storage device for the cloud phone service is synchronously updated. The aforementioned method for expanding the associated storage devices of cloud phone services achieves accurate predictive expansion of associated storage devices by precisely predicting the expansion time and capacity, minimizing the impact of cloud phone service interruptions, and balancing expansion execution efficiency with business continuity.

[0122] Figure 2 This is a flowchart illustrating another method for expanding the associated storage device of a cloud phone service provided in this application embodiment. For example... Figure 2 As shown, the specific steps include the following:

[0123] S201, obtain the historical storage usage rate of the associated storage device of the cloud phone service, and determine the predicted expansion time based on the historical storage usage rate and the preset storage usage rate threshold.

[0124] S202, calculate the average storage utilization rate growth rate based on the historical storage utilization rate.

[0125] S203, determine the basic expansion coefficient based on the average storage utilization rate growth rate.

[0126] The basic expansion coefficient can be a benchmark expansion ratio factor determined based on the long-term average growth trend.

[0127] In one embodiment, the base expansion coefficient can be obtained by mapping the current average storage utilization growth rate to the above-mentioned correlation between the average storage utilization growth rate and the expansion coefficient.

[0128] S204, obtain the real-time storage utilization rate growth rate, and calculate the ratio of the real-time storage utilization rate growth rate to the average storage utilization rate growth rate as the growth rate deviation coefficient.

[0129] Among them, the real-time storage utilization rate growth rate can be the growth rate of storage utilization rate that reflects recent sudden changes.

[0130] In one embodiment, the real-time storage utilization rate growth rate can be obtained by performing a linear regression on the historical storage utilization rate within a recent time window (such as the last 7 days) and taking the slope as the real-time storage utilization rate growth rate.

[0131] The growth rate deviation coefficient can be a coefficient used to measure the degree to which the current growth trend deviates from the normal level. Specifically, it can be the ratio of the real-time storage utilization rate growth rate to the average storage utilization rate growth rate.

[0132] S205, obtain the adjustment weighting factor, and calculate the target expansion coefficient based on the basic expansion coefficient, the adjustment weighting factor, and the growth rate deviation coefficient.

[0133] Among them, the adjustment weighting factor can be a weighting parameter used to balance the influence of the basic expansion coefficient and the growth rate deviation coefficient on the target expansion coefficient.

[0134] In one embodiment, the weighting factor can be preset, for example, 0.3.

[0135] In one embodiment, obtaining the adjustment weight factor includes: obtaining the current number of online instances of the cloud phone service and a preset instance number threshold; and calculating the ratio of the current number of online instances to the preset instance number threshold as the adjustment weight factor.

[0136] The current number of online instances can be the total number of cloud phone instances currently running in the cloud phone service; the preset instance number threshold can be a key reference value for measuring the load level, pre-set according to the business capacity planning of the cloud phone service.

[0137] In one embodiment, the current number of online instances and the preset instance number threshold of the cloud phone service can be obtained by querying the current number of online instances and the preset instance number threshold through the data query interface provided by the cloud phone service.

[0138] The advantage of this solution is that by using the ratio of the current number of online instances of the cloud phone service to the preset instance number threshold as the adjustment weight factor, the adjustment of the expansion coefficient can be dynamically linked with the business load, realizing intelligent linkage between storage expansion and business load, and further improving resource utilization and service stability.

[0139] In one embodiment, the target expansion coefficient can be calculated based on the base expansion coefficient, the adjustment weight factor, and the growth rate deviation coefficient by multiplying the adjustment weight factor and the growth rate deviation coefficient to obtain a first intermediate result, summing 1 with the first intermediate result to obtain a second intermediate result, and multiplying the base expansion coefficient with the second intermediate result to obtain the target expansion coefficient.

[0140] S206, Based on the preset storage utilization threshold and the target expansion coefficient, determine the basic expansion capacity and threshold adaptation coefficient, obtain the current fragmentation rate of the associated storage device and determine the fragmentation optimization coefficient according to the current fragmentation rate, and multiply the basic expansion capacity, the threshold adaptation coefficient and the fragmentation optimization coefficient to obtain the predicted expansion capacity.

[0141] S207, obtain the allowed expansion period of the cloud phone service, and determine the target expansion time based on the predicted expansion time and the allowed expansion period.

[0142] S208, based on the target expansion time and the predicted expansion capacity, generate expansion plan information, and when it is recognized that the expansion plan information has been executed, synchronously update the storage space allocation information of the associated storage device for the cloud phone service.

[0143] The advantage of this scheme is that by introducing a growth rate deviation coefficient, it can dynamically capture sudden changes in storage utilization, making the determination of the target expansion coefficient more sensitive and accurate. By combining the basic expansion coefficient and the growth rate deviation coefficient, and introducing an adjustment weight factor for balance, it can avoid the problems of over-expansion due to short-term fluctuations or under-expansion due to ignoring sudden growth, thereby achieving more accurate and adaptive expansion capacity prediction.

[0144] Figure 3 This is a flowchart illustrating another method for expanding the associated storage device of a cloud phone service provided in this application embodiment. For example... Figure 3 As shown, the specific steps include the following:

[0145] S301, obtain the historical storage usage rate of the associated storage device of the cloud phone service, and determine the predicted expansion time based on the historical storage usage rate and the preset storage usage rate threshold.

[0146] S302, calculate the average storage utilization rate growth rate based on the historical storage utilization rate, and determine the target expansion coefficient based on the average storage utilization rate growth rate.

[0147] S303, based on the preset storage utilization threshold and the target expansion coefficient, determine the basic expansion capacity and threshold adaptation coefficient, obtain the current fragmentation rate of the associated storage device and determine the fragmentation optimization coefficient according to the current fragmentation rate, and multiply the basic expansion capacity, the threshold adaptation coefficient and the fragmentation optimization coefficient to obtain the predicted expansion capacity.

[0148] S304, Obtain the historical service load intensity and service interruption sensitivity level of each cloud mobile phone instance in the cloud mobile phone service.

[0149] Among them, historical business load intensity can refer to the comprehensive utilization of computing, network and storage resources by cloud mobile phone instances during historical operation; business interruption sensitivity level can be a level label that is classified according to the importance of the business carried by the cloud mobile phone instance or the user level, and is used to measure the impact of possible interruptions caused by expansion operations on the business.

[0150] In one embodiment, the method for obtaining the historical service load intensity and service interruption sensitivity level of each cloud mobile instance in the cloud mobile service can be as follows: the historical load data of each cloud mobile instance is collected through the monitoring module of the cloud mobile service, and the historical service load intensity is obtained by comprehensively evaluating the historical load data. The preset service interruption sensitivity level of each cloud mobile instance is read from the service configuration information of the cloud mobile service.

[0151] S305, determine the low-end service periods for each cloud mobile phone instance based on the historical service load intensity, and determine the service impact weighting coefficient for each cloud mobile phone instance based on the service interruption sensitivity level.

[0152] Among them, the low-business period can be a continuous period of time when the business load intensity of the cloud mobile instance is lower than a preset intensity threshold.

[0153] In one embodiment, the method for determining the low-end periods of each cloud mobile phone instance based on historical service load intensity can be to perform statistical analysis on the historical service load intensity sequence and identify the periods in each day or week where the historical service load intensity is consistently lower than a preset intensity threshold as the low-end periods.

[0154] Among them, the business impact weighting coefficient can be a weighted coefficient used to measure the degree of business impact caused by the service interruption of cloud phone instances.

[0155] In one embodiment, a pre-established correlation between business interruption sensitivity level and business impact weight coefficient is used to map the business interruption sensitivity level of a cloud phone instance based on this correlation, thereby obtaining the business impact weight coefficient of the cloud phone instance. The correlation between the business interruption sensitivity level and the business impact weight coefficient can be constructed based on the degree of impact of business interruption on user experience, service level agreement requirements, and historical interruption event impact assessment data. As an example, the correlation between the business interruption sensitivity level and the business impact weight coefficient can be specifically divided into five levels: Level 1 (extremely low sensitivity, such as test instances) corresponds to a business impact weight coefficient of 0.2; Level 2 (low sensitivity, such as personal entertainment instances) corresponds to a business impact weight coefficient of 0.4; Level 3 (medium sensitivity, such as ordinary office instances) corresponds to a business impact weight coefficient of 0.6; Level 4 (high sensitivity, such as enterprise critical business instances) corresponds to a business impact weight coefficient of 0.8; and Level 5 (extremely high sensitivity, such as financial transactions or medical emergency instances) corresponds to a business impact weight coefficient of 1.0.

[0156] In one embodiment, determining the service impact weight coefficient of each cloud phone instance based on the service interruption sensitivity level includes: determining a baseline weight coefficient based on the service interruption sensitivity level; obtaining the total read / write time and total runtime of the cloud phone instance during the service off-peak period, and calculating the ratio of the total read / write time to the total runtime as storage dependency; multiplying the baseline weight coefficient by the storage dependency to obtain the service impact weight coefficient of the cloud phone instance.

[0157] The benchmark weight coefficient can be an initial weight value directly determined based on the business interruption sensitivity level, reflecting the basic degree of impact of the business interruption sensitivity level on the business.

[0158] In one embodiment, the method for determining the baseline weight coefficient based on the service interruption sensitivity level can be to map the service interruption sensitivity level of a cloud phone instance according to the correlation between the aforementioned service interruption sensitivity level and the service impact weight coefficient, thereby obtaining the baseline weight coefficient of the cloud phone instance.

[0159] The total read / write time can be the total cumulative time that the cloud phone instance performs disk read / write operations during off-peak hours; the total instance runtime can be the cumulative time that the cloud phone instance is in a running state during off-peak hours.

[0160] In one embodiment, the method to obtain the total read / write duration and total runtime of a cloud phone instance during off-peak hours can be as follows: collect the disk I / O event logs of each cloud phone instance through the monitoring module of the cloud phone service, calculate the sum of the durations of read / write events during off-peak hours as the total read / write duration, and obtain the runtime of the cloud phone instance during off-peak hours from the instance lifecycle management module as the total instance runtime.

[0161] Storage dependency can be a coefficient used to measure the degree to which a cloud phone instance depends on storage resources. The storage dependency of a cloud phone instance is the ratio of the total read and write time of the cloud phone instance to the total runtime of the instance.

[0162] In one embodiment, the business impact weight coefficient of a cloud phone instance can be obtained by directly multiplying its base weight coefficient by its storage dependency coefficient.

[0163] The advantage of this solution is that by introducing storage dependency to correct the baseline weight coefficient, it can more accurately reflect the actual dependence of cloud phone instances on storage resources during off-peak business periods, avoid expansion operations during periods of high storage activity, thereby further reducing the impact of expansion on business and improving the accuracy of expansion timing and business assurance capabilities.

[0164] S306, calculate the weighted average of the low-traffic periods of each cloud phone instance based on the business impact weighting coefficient to obtain the allowable expansion period of the cloud phone service.

[0165] In one embodiment, the allowable expansion period of cloud phone service is obtained by calculating the weighted average of the business off-peak periods of each cloud phone instance based on the business impact weight coefficient. This can be achieved by multiplying the start and end times of the business off-peak periods of each cloud phone instance by the corresponding business impact weight coefficient, summing them, and then averaging them to obtain the weighted average allowable expansion start and end times, i.e., the allowable expansion period.

[0166] S307, determine the target expansion time based on the predicted expansion time and the allowed expansion period.

[0167] S308, based on the target expansion time and the predicted expansion capacity, generate expansion plan information, and when it is recognized that the expansion plan information has been executed, synchronously update the storage space allocation information of the associated storage device for the cloud phone service.

[0168] The advantage of this solution is that by incorporating the historical business load intensity and business interruption sensitivity level of each cloud phone instance, the determination of the allowable expansion period is upgraded from a static preset to a dynamic adaptive decision. This fully considers the differences in business characteristics and importance of different cloud phone instances and can accurately calculate the expansion period with the least impact on the overall business.

[0169] Figure 4 This is a schematic diagram of the structure of a cloud phone service associated storage device expansion device provided in an embodiment of this application. Figure 4 As shown, the device includes:

[0170] The time prediction module 410 is used to obtain the historical storage usage rate of the associated storage device of the cloud phone service, and determine the predicted expansion time based on the historical storage usage rate and the preset storage usage rate threshold.

[0171] The coefficient determination module 420 is used to calculate the average storage utilization rate growth rate based on the historical storage utilization rate, and to determine the target expansion coefficient based on the average storage utilization rate growth rate.

[0172] The capacity prediction module 430 is used to determine the basic expansion capacity and threshold adaptation coefficient based on the preset storage utilization threshold and the target expansion coefficient, obtain the current fragmentation rate of the associated storage device and determine the fragmentation optimization coefficient based on the current fragmentation rate, and multiply the basic expansion capacity, the threshold adaptation coefficient and the fragmentation optimization coefficient to obtain the predicted expansion capacity.

[0173] The time determination module 440 is used to obtain the allowed expansion period of the cloud mobile phone service, and determine the target expansion time based on the predicted expansion time and the allowed expansion period;

[0174] The expansion execution module 450 is used to generate expansion plan information based on the target expansion time and the predicted expansion capacity, and synchronously update the storage space allocation information of the associated storage device for the cloud phone service when it is recognized that the expansion plan information has been executed.

[0175] Furthermore, the coefficient determination module 420 is specifically used for:

[0176] The basic expansion coefficient is determined based on the average storage utilization growth rate.

[0177] Obtain the real-time storage utilization rate growth rate and calculate the ratio of the real-time storage utilization rate growth rate to the average storage utilization rate growth rate as the growth rate deviation coefficient;

[0178] Obtain the adjustment weighting factor, and calculate the target expansion coefficient based on the basic expansion coefficient, the adjustment weighting factor, and the growth rate deviation coefficient.

[0179] Furthermore, the coefficient determination module 420 is specifically used for:

[0180] Obtain the current number of online instances of the cloud phone service and the preset instance number threshold;

[0181] The ratio of the current number of online instances to the preset instance number threshold is calculated as an adjustment weight factor.

[0182] Furthermore, the capacity prediction module 430 is specifically used for:

[0183] Obtain the current total storage capacity of the associated storage device, and determine the basic expansion capacity based on the current total storage capacity and the target expansion coefficient;

[0184] The threshold approximation frequency is determined based on the historical storage usage rate and the preset storage usage rate threshold, and the threshold adaptation coefficient is determined based on the threshold approximation frequency.

[0185] Furthermore, the time determination module 440 is specifically used for:

[0186] Obtain the historical service load intensity and service interruption sensitivity level of each cloud phone instance in the cloud phone service;

[0187] The service off-peak periods for each cloud mobile phone instance are determined based on the historical service load intensity, and the service impact weighting coefficient for each cloud mobile phone instance is determined based on the service interruption sensitivity level.

[0188] The allowable expansion period for the cloud phone service is calculated by weighting the low-traffic periods of each cloud phone instance based on the business impact weighting coefficient.

[0189] Furthermore, the time determination module 440 is specifically used for:

[0190] The baseline weighting coefficient is determined based on the aforementioned service interruption sensitivity level;

[0191] Obtain the total read / write time and total runtime of the cloud phone instance during the off-peak business period, and calculate the ratio of the total read / write time to the total runtime of the instance as the storage dependency.

[0192] The business impact weight coefficient of the cloud phone instance is obtained by multiplying the baseline weight coefficient by the storage dependency.

[0193] Furthermore, the time prediction module 410 is specifically used for:

[0194] Extract at least two time-dimensional subsequences of historical storage usage from the historical storage usage rate;

[0195] Based on each of the historical storage utilization rate subsequences, the time when the storage utilization rate of the associated storage device reaches the preset storage utilization rate threshold is predicted as the dimension prediction time corresponding to each of the historical storage utilization rate subsequences.

[0196] The predicted expansion time is obtained by weighting and fusing the predicted time of each of the historical storage usage rate subsequences.

[0197] In this embodiment, the time prediction module is used to obtain the historical storage usage rate of the associated storage device of the cloud phone service, and determine the predicted expansion time based on the historical storage usage rate and a preset storage usage rate threshold; the coefficient determination module is used to calculate the average storage usage rate growth rate based on the historical storage usage rate, and determine the target expansion coefficient based on the average storage usage rate growth rate; the capacity prediction module is used to determine the basic expansion capacity and threshold adaptation coefficient based on the preset storage usage rate threshold and the target expansion coefficient, obtain the current fragmentation rate of the associated storage device and determine the fragmentation optimization coefficient based on the current fragmentation rate, and multiply the basic expansion capacity, the threshold adaptation coefficient and the fragmentation optimization coefficient to obtain the predicted expansion capacity; the time determination module is used to obtain the allowed expansion period of the cloud phone service, and determine the target expansion time based on the predicted expansion time and the allowed expansion period; the expansion execution module is used to generate expansion plan information based on the target expansion time and the predicted expansion capacity, and synchronously update the storage space allocation information of the associated storage device for the cloud phone service when the expansion plan information is detected to have been executed. The aforementioned cloud phone service's associated storage device expansion device accurately predicts expansion time and capacity, minimizing the impact of cloud phone service interruptions while achieving precise predictive expansion of associated storage devices, balancing expansion execution efficiency and business continuity.

[0198] The cloud phone service associated storage device expansion device in this application embodiment can be a device, or a component, integrated circuit, or chip in a terminal. The device can be a mobile electronic device or a non-mobile electronic device. For example, mobile electronic devices can be mobile phones, tablets, laptops, PDAs, in-vehicle electronic devices, wearable devices, ultra-mobile personal computers (UMPCs), netbooks, or personal digital assistants (PDAs), etc., while non-mobile electronic devices can be servers, network attached storage (NAS), personal computers (PCs), televisions (TVs), ATMs, or self-service machines, etc. This application embodiment does not impose specific limitations.

[0199] The storage device expansion device associated with the cloud phone service in this embodiment can be a device with an operating system. This operating system can be Android, iOS, or other possible operating systems; this embodiment does not specifically limit the specific operating system.

[0200] The cloud phone service associated storage device expansion device provided in this application embodiment can realize the various processes implemented in the above embodiments. To avoid repetition, it will not be described again here.

[0201] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. For example... Figure 5 As shown, this application embodiment also provides an electronic device 500, including a processor 501, a memory 502, and a program or instructions stored in the memory 502 and executable on the processor 501. When the program or instructions are executed by the processor 501, they implement the various processes of the above-mentioned cloud mobile phone service associated storage device expansion method embodiment and can achieve the same technical effect. To avoid repetition, they will not be described again here.

[0202] It should be noted that the electronic devices in the embodiments of this application include the mobile electronic devices and non-mobile electronic devices described above.

[0203] This application also provides a readable storage medium storing a program or instructions. When the program or instructions are executed by a processor, they implement the various processes of the above-described cloud phone service associated storage device expansion method embodiment and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0204] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0205] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0206] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0207] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

[0208] The above description is merely a preferred embodiment and the technical principles employed in this application. This application is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions that can be made by those skilled in the art will not depart from the scope of protection of this application. Therefore, although this application has been described in detail through the above embodiments, this application is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of this application, the scope of which is determined by the scope of the claims.

Claims

1. A method for expanding the storage of an associated device of a cloud phone service, characterized in that, The method includes: Obtain the historical storage usage rate of the associated storage devices of the cloud phone service, and determine the predicted expansion time based on the historical storage usage rate and a preset storage usage rate threshold; Perform linear regression on the historical storage utilization rate and take the slope as the average storage utilization rate growth rate, and determine the target expansion coefficient based on the average storage utilization rate growth rate; The process involves obtaining the current total storage capacity of the associated storage device, determining the basic expansion capacity based on the current total storage capacity and the target expansion coefficient, determining the threshold approximation frequency based on the historical storage utilization rate and the preset storage utilization rate threshold, determining the threshold adaptation coefficient based on the threshold approximation frequency, obtaining the current fragmentation rate of the associated storage device, mapping the current fragmentation rate based on the pre-built correlation between the fragmentation rate and the fragmentation optimization coefficient to obtain the fragmentation optimization coefficient, and multiplying the basic expansion capacity, the threshold adaptation coefficient, and the fragmentation optimization coefficient to obtain the predicted expansion capacity. Obtain the allowed expansion period of the cloud phone service, and determine the target expansion time based on the predicted expansion time and the allowed expansion period; Based on the target expansion time and the predicted expansion capacity, expansion plan information is generated, and when the expansion plan information is detected to have been executed, the storage space allocation information of the associated storage device for the cloud phone service is updated synchronously.

2. The method for expanding the associated storage device of cloud mobile phone service according to claim 1, characterized in that, The determination of the target expansion coefficient based on the average storage utilization growth rate includes: The basic expansion coefficient is determined based on the average storage utilization growth rate. Obtain the real-time storage utilization rate growth rate and calculate the ratio of the real-time storage utilization rate growth rate to the average storage utilization rate growth rate as the growth rate deviation coefficient; Obtain the adjustment weighting factor, and calculate the target expansion coefficient based on the basic expansion coefficient, the adjustment weighting factor, and the growth rate deviation coefficient.

3. The method for expanding the associated storage device of cloud mobile phone service according to claim 2, characterized in that, The process of obtaining the adjustment weighting factor includes: Obtain the current number of online instances of the cloud phone service and the preset instance number threshold; The ratio of the current number of online instances to the preset instance number threshold is calculated as an adjustment weight factor.

4. The method for expanding the associated storage device of cloud mobile phone service according to any one of claims 1-3, characterized in that, The permitted expansion period for obtaining the cloud phone service includes: Obtain the historical service load intensity and service interruption sensitivity level of each cloud phone instance in the cloud phone service; The service off-peak periods for each cloud mobile phone instance are determined based on the historical service load intensity, and the service impact weighting coefficient for each cloud mobile phone instance is determined based on the service interruption sensitivity level. The allowable expansion period for the cloud phone service is calculated by weighting the low-traffic periods of each cloud phone instance based on the business impact weighting coefficient.

5. The method for expanding the associated storage device of cloud mobile phone service according to claim 4, characterized in that, The determination of the service impact weighting coefficient for each cloud phone instance based on the service interruption sensitivity level includes: The baseline weighting coefficient is determined based on the aforementioned service interruption sensitivity level; Obtain the total read / write time and total runtime of the cloud phone instance during the off-peak business period, and calculate the ratio of the total read / write time to the total runtime of the instance as the storage dependency. The business impact weight coefficient of the cloud phone instance is obtained by multiplying the baseline weight coefficient by the storage dependency.

6. The method for expanding the associated storage device of cloud mobile phone service according to claim 1, characterized in that, The step of determining the predicted expansion time based on the historical storage usage rate and a preset storage usage rate threshold includes: Extract at least two time-dimensional subsequences of historical storage usage from the historical storage usage rate; Based on each of the historical storage utilization rate subsequences, the time when the storage utilization rate of the associated storage device reaches the preset storage utilization rate threshold is predicted as the dimension prediction time corresponding to each of the historical storage utilization rate subsequences. The predicted expansion time is obtained by weighting and fusing the predicted time of each of the historical storage usage rate subsequences.

7. A storage device expansion device associated with a cloud phone service, characterized in that, The device includes: The time prediction module is used to obtain the historical storage usage rate of the associated storage devices of the cloud phone service, and determine the predicted expansion time based on the historical storage usage rate and the preset storage usage rate threshold. The coefficient determination module is used to perform linear regression on the historical storage utilization rate and take the slope as the average storage utilization rate growth rate, and determine the target expansion coefficient based on the average storage utilization rate growth rate. The capacity prediction module is used to obtain the current total storage capacity of the associated storage device, determine the basic expansion capacity based on the current total storage capacity and the target expansion coefficient, determine the threshold approximation frequency based on the historical storage utilization rate and the preset storage utilization rate threshold, determine the threshold adaptation coefficient based on the threshold approximation frequency, obtain the current fragmentation rate of the associated storage device, map the current fragmentation rate according to the pre-built correlation between the fragmentation rate and the fragmentation optimization coefficient to obtain the fragmentation optimization coefficient, and multiply the basic expansion capacity, the threshold adaptation coefficient and the fragmentation optimization coefficient to obtain the predicted expansion capacity. The time determination module is used to obtain the allowed expansion period of the cloud phone service, and determine the target expansion time based on the predicted expansion time and the allowed expansion period; The expansion execution module is used to generate expansion plan information based on the target expansion time and the predicted expansion capacity, and synchronously update the storage space allocation information of the associated storage device for the cloud phone service when it is recognized that the expansion plan information has been executed.

8. An electronic device, characterized in that, It includes a processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein when the program or instructions are executed by the processor, they implement the associated storage device expansion method for the cloud phone service as described in any one of claims 1-6.

9. A readable storage medium, characterized in that, The readable storage medium stores a program or instructions, which, when executed by a processor, implement the associated storage device expansion method for the cloud phone service as described in any one of claims 1-6.

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