Multi-tenant grouped dynamic cloud password computing resource allocation method and middleware device

Abstract

The invention discloses a multi-tenant grouped dynamic cloud cryptographic computing resource allocation method and a middleware device, and relates to the related technical field of cloud cryptographic services, the method comprises the following steps: configuring a first cryptographic computing resource component and a second cryptographic computing resource component; calculating a moving average resource use index of each tenant; clustering the tenants to output a plurality of groups of tenants; and judging whether the resource use indexes accumulated on the day of the tenant exceed the resource allocation threshold value corresponding to the group to which the tenant belongs, if not, sending the resource request to a first cryptographic computing resource component for resource allocation, and if yes, sending the resource request to a second cryptographic computing resource component for resource allocation. The technical problems that in the prior art, password computing resources cannot be flexibly and accurately distributed according to dynamically-changed resource requirements of tenants, consequently, the computing resource utilization efficiency is low, and tenant services are difficult to run normally are solved, and the technical effects that the computing resource utilization efficiency is improved, and normal running of the tenant services is guaranteed are achieved.

Description

Technical Field

[0001] The present application relates to the technical field related to cloud cryptographic services, and specifically to a dynamic cloud cryptographic computing resource allocation method and middleware device for multi-tenant groups. Background Art

[0002] In today's digital age, cloud computing technology has been widely used, and more and more companies and organizations choose to migrate their businesses to the cloud. In a multi-tenant environment, different tenants have significantly different demands for computing resources, and such demands often have dynamic characteristics. The traditional static resource allocation method can no longer meet the diverse and dynamic demands, resulting in low resource utilization efficiency. Some tenants have excess resources while others have insufficient resources. In addition, the reasonable allocation of cryptographic computing resources is particularly critical when processing sensitive information. On the one hand, the resource request pattern of tenants fluctuates over time. For example, the resource demand of e-commerce tenants will increase sharply during the promotion season, but will drop sharply during the off-season. On the other hand, different tenants have different resource usage habits and business characteristics. The current cryptographic computing resource allocation cannot accurately and flexibly allocate resources according to these dynamic changes, which not only causes resource waste, but may also affect the normal operation of tenants' businesses due to insufficient resources.

[0003] Therefore, in the current relevant technologies, there is a technical problem that cryptographic computing resources cannot be flexibly and accurately allocated according to the dynamically changing resource needs of tenants, resulting in inefficient utilization of computing resources and difficulty in the normal operation of tenant businesses. Summary of the invention

[0004] The present application solves the technical problem in the prior art that cryptographic computing resources cannot be flexibly and accurately allocated according to the dynamically changing resource requirements of tenants, resulting in low efficiency in computing resource utilization and difficulty in normal operation of tenant businesses, by providing a dynamic cloud cryptographic computing resource allocation method and middleware device for multi-tenant grouping. This achieves the technical effect of improving the efficiency of computing resource utilization and ensuring the normal operation of tenant businesses.

[0005] The present application provides a method for dynamic cloud cryptographic computing resource allocation for multi-tenant groups, the method comprising: configuring a first cryptographic computing resource component and a second cryptographic computing resource component, wherein the first cryptographic computing resource component and the second cryptographic computing resource component are respectively connected to the middleware through the RDMA protocol; inputting the historical resource request information of each tenant, and calculating the sliding average resource usage index of each tenant according to the historical resource request information; clustering each tenant with the sliding average resource usage index to output multiple groups of tenants, wherein the multiple groups of tenants correspond to multiple resource allocation thresholds; the middleware receives the resource request of the tenant, and determines whether the resource usage index accumulated by the tenant on that day exceeds the resource allocation threshold corresponding to the group to which it belongs. If it does not exceed the resource allocation threshold corresponding to the group to which the tenant belongs, the middleware sends the resource request to the first cryptographic computing resource component for resource allocation. If it exceeds the resource allocation threshold corresponding to the group to which the tenant belongs, the middleware sends the resource request to the second cryptographic computing resource component for resource allocation.

[0006] In a possible implementation, the dynamic cloud cryptographic computing resource allocation method for multi-tenant groups also performs the following processing: configuring a first cryptographic computing resource component and a second cryptographic computing resource component, the first cryptographic computing resource component is a resource component with a fixed quota, and the second cryptographic computing resource component is a resource component with a dynamic redundant quota based on the first cryptographic computing resource component; wherein the allocation priority of the first cryptographic computing resource component is greater than the allocation priority of the second cryptographic computing resource component.

[0007] In a possible implementation, the dynamic cloud cryptographic computing resource allocation method for multi-tenant groups also performs the following processing: calculating according to the multiple resource allocation thresholds and outputting a total resource allocation threshold; obtaining configuration parameter information of the first cryptographic computing resource component, the configuration parameter information including resource configuration parameter information, network configuration parameter information and access configuration parameter information; performing a load balancing test on the total resource allocation threshold with the configuration parameter information to obtain a first computing resource quota test sample based on load balancing, and performing a fixed quota for the first cryptographic computing resource component according to the first computing resource quota test sample.

[0008] In a possible implementation, the dynamic cloud cryptographic computing resource allocation method for multi-tenant grouping also performs the following processing: entering the historical resource request information of each tenant, and calculating the resource volatility of each tenant based on the sliding average resource usage indicator according to the historical resource request information; dividing the resource volatility set corresponding to each group of tenants according to the resource volatility corresponding to each tenant; calculating the total resource volatility threshold of each group of tenants based on the resource volatility set; performing a load balancing test on the total resource volatility threshold using the configuration parameter information of the second cryptographic computing resource component to obtain a second computing resource quota test sample based on load balancing, and performing dynamic quotas for the second cryptographic computing resource component according to the second computing resource quota test sample.

[0009] In a possible implementation, the dynamic cloud cryptographic computing resource allocation method for multi-tenant grouping also performs the following processing: obtaining a sliding average resource usage indicator set corresponding to each group of tenants; performing time series fusion processing on the sliding average resource usage indicator set to obtain a time series-sliding average resource usage indicator set, performing curve fitting according to the time series-sliding average resource usage indicator set to obtain a sliding average resource usage curve; and allocating corresponding multiple resource allocation thresholds to the multiple groups of tenants according to the sliding average resource usage curve.

[0010] In a possible implementation, the dynamic cloud cryptographic computing resource allocation method for multi-tenant grouping also performs the following processing: detecting a set of inflection points in the sliding average resource usage curve corresponding to each group of tenants whose amplitude change is greater than a preset change amplitude; assigning weights to the inflection point set through exponentially weighted moving average to obtain an EWMA weight set, calculating the mean value of each inflection point in the inflection point set according to the EWMA weight set, and outputting the resource allocation threshold corresponding to each group of tenants.

[0011] In a possible implementation, the dynamic cloud cryptographic computing resource allocation method for multi-tenant groups also performs the following processing: the first cryptographic computing resource component and the middleware include a second NB-IOT communication module, and the transmission between the second cryptographic computing resource component and the middleware includes a second NB-IOT communication module.

[0012] In a possible implementation, the dynamic cloud cryptographic computing resource allocation method for multi-tenant groups also performs the following processing: detecting that the resource idle time of the tenant exceeds a preset threshold, triggering a resource recovery instruction; and recovering the computing resources obtained by the tenant to the first cryptographic computing resource component or the second cryptographic computing resource component according to the resource recovery instruction.

[0013] In a possible implementation, the dynamic cloud cryptographic computing resource allocation method for multi-tenant groups also performs the following processing: when the resource recovery instruction is triggered, the computing resources obtained by the tenant are desensitized according to the desensitizing module to obtain the desensitized computing resources; the desensitized computing resources are correspondingly recovered to the first cryptographic computing resource component or the second cryptographic computing resource component.

[0014] The present application also provides a dynamic cloud cryptographic computing resource allocation middleware device for multi-tenant grouping, including: a computing resource component configuration unit, used to configure a first cryptographic computing resource component and a second cryptographic computing resource component, wherein the first cryptographic computing resource component and the second cryptographic computing resource component are respectively connected to the middleware through the RDMA protocol; a sliding average resource usage index calculation unit, used to input the historical resource request information of each tenant, and calculate the sliding average resource usage index of each tenant according to the historical resource request information; a tenant clustering output unit, used to cluster each tenant with the sliding average resource usage index to output multiple groups of tenants, wherein the multiple groups of tenants correspond to multiple resource allocation thresholds; a resource allocation unit, used to receive the resource request of the tenant by the middleware, determine whether the resource usage index accumulated by the tenant on that day exceeds the resource allocation threshold corresponding to the group to which it belongs, if it does not exceed the resource allocation threshold corresponding to the group to which the tenant belongs, the middleware sends the resource request to the first cryptographic computing resource component for resource allocation, if it exceeds the resource allocation threshold corresponding to the group to which the tenant belongs, the middleware sends the resource request to the second cryptographic computing resource component for resource allocation.

[0015] The dynamic cloud cryptographic computing resource allocation method and middleware device for multi-tenant grouping proposed in this application are to configure the first cryptographic computing resource component and the second cryptographic computing resource component; input the historical resource request information of each tenant, calculate the sliding average resource usage index of each tenant; cluster each tenant and output multiple groups of tenants; the middleware receives the resource request of the tenant, determines whether the cumulative resource usage index of the tenant on that day exceeds the resource allocation threshold corresponding to the group to which it belongs, and if not, sends the resource request to the first cryptographic computing resource component for resource allocation; if exceeded, sends it to the second cryptographic computing resource component for resource allocation. This solves the technical problem that cryptographic computing resources in the prior art cannot be flexibly and accurately allocated according to the dynamically changing resource requirements of tenants, resulting in low efficiency in computing resource utilization and difficulty in normal operation of tenant services, and achieves the technical effect of improving the efficiency of computing resource utilization and ensuring the normal operation of tenant services. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solution of the embodiment of the present disclosure, the accompanying drawings of the embodiment of the present disclosure will be briefly introduced below. A flow chart is used in the present application to illustrate the operations performed by the device according to the embodiment of the present application. It should be understood that the previous or following operations are not necessarily performed precisely in order. On the contrary, various steps can be processed in reverse order or simultaneously as needed. At the same time, other operations can also be added to these processes, or one or more operations can be removed from these processes.

[0017] Figure 1 A flowchart of a method for allocating dynamic cloud cryptographic computing resources for multi-tenant groups provided in an embodiment of the present application.

[0018] Figure 2 A schematic diagram of the structure of a dynamic cloud cryptographic computing resource allocation middleware device for multi-tenant groups provided in an embodiment of the present application.

[0019] Description of the accompanying drawings: computing resource component configuration unit 10, sliding average resource usage indicator calculation unit 20, tenant clustering output unit 30, resource allocation unit 40. DETAILED DESCRIPTION

[0020] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0021] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0022] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict, and the terms "first\second" involved are merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "including" and "having" and any variations are intended to cover non-exclusive inclusions, for example, a process, method, device, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by technicians in the technical field of this application. The terms used herein are for the purpose of describing the embodiments of the present application only.

[0023] The present application embodiment provides a method for allocating dynamic cloud cryptographic computing resources for multi-tenant groups, such as Figure 1 As shown, the method includes: Step S100: configuring a first cryptographic computing resource component and a second cryptographic computing resource component, wherein the first cryptographic computing resource component and the second cryptographic computing resource component are respectively connected to the middleware for communication via an RDMA protocol.

[0024] Preferably, the cryptographic computing resource component is a set of software and hardware for performing cryptographic computing. In a cloud computing environment, cryptographic computing involves operations such as data encryption, decryption, digital signature, and key exchange, which are used to ensure data security and privacy. The first cryptographic computing resource component and the second cryptographic computing resource component are two relatively independent cryptographic computing resource pools, which may be composed of multiple servers, computing nodes, or virtual machines, and have the ability to process cryptographic computing tasks to meet the needs of tenants for cryptographic computing resources in different situations. The first cryptographic computing resource component and the second cryptographic computing resource component can process tenants' resource requests in parallel to improve the overall processing capability and response speed. The RDMA (Remote Direct Memory Access) protocol is used to achieve high-performance data transmission in computer networks. Different from traditional network data transmission methods, RDMA allows computers to directly transfer data between the memory of a remote server and the local memory without going through the operating system kernel, significantly reducing CPU involvement and data transmission latency to improve data transmission bandwidth and efficiency. In multi-tenant cloud cryptographic computing resource allocation, the use of the RDMA protocol can ensure that when processing a large number of cryptographic computing tasks, the first cryptographic computing resource component, the second cryptographic computing resource component and the middleware can communicate data quickly and efficiently, reducing the time overhead of data transmission and improving overall performance.

[0025] Preferably, the middleware is responsible for receiving tenants' resource requests and allocating these requests to appropriate cryptographic computing resource components for processing. It can monitor and manage tenants' resource usage to ensure reasonable allocation and utilization of resources. The first cryptographic computing resource component and the second cryptographic computing resource component respectively establish communication connections with the middleware through the RDMA protocol, which means that each component can independently interact with the middleware for data. The middleware can send the tenant's resource request to the first cryptographic computing resource component or the second cryptographic computing resource component for processing according to actual conditions, so that cryptographic computing resources can be flexibly and accurately allocated according to the dynamic needs of tenants.

[0026] Furthermore, step S100 also includes configuring a first cryptographic computing resource component and a second cryptographic computing resource component, wherein the first cryptographic computing resource component is a resource component with a fixed quota, and the second cryptographic computing resource component is a resource component with a dynamic redundant quota based on the first cryptographic computing resource component; wherein the allocation priority of the first cryptographic computing resource component is greater than the allocation priority of the second cryptographic computing resource component.

[0027] Preferably, the first cryptographic computing resource component is configured as a resource component with a fixed quota. Specifically, a fixed amount of resources is set for the first cryptographic computing resource component, which may be computing power (such as the number of CPU cores, the number of computing threads), storage capacity, network bandwidth, etc. In any case, the total amount of resources that can be provided is the set fixed amount of resources. The setting of fixed quotas provides tenants with stable resource guarantees. For those tenants who have relatively stable expectations and demands for resource usage, the first cryptographic computing resource component can meet their daily basic cryptographic computing needs and ensure the smooth operation of the business.

[0028] Preferably, the second cryptographic computing resource component is configured as a resource component that performs dynamic redundant quota based on the first cryptographic computing resource component. Specifically, the resource quota of the second cryptographic computing resource component is associated with the first cryptographic computing resource component, and mainly exists as a redundant supplement mechanism, that is, when the resources of the first cryptographic computing resource component cannot meet the needs of the tenants, the second cryptographic computing resource component will dynamically allocate additional resources according to actual conditions. For example, when the tenant's resource request exceeds the fixed quota of the first cryptographic computing resource component, the second cryptographic computing resource component can dynamically provide a certain number of CPU cores or storage capacity to meet the demand based on the excess part. The setting of dynamic redundant quota can better cope with the sudden increase in tenant resource demand. In a multi-tenant environment, the business of different tenants has different peak and trough periods. Dynamic redundant quota can improve resource utilization and avoid idleness and waste of resources.

[0029] Preferably, the allocation priority of the first cryptographic computing resource component is greater than the allocation priority of the second cryptographic computing resource component. Specifically, when the middleware receives a resource request from a tenant, it will first allocate the request to the first cryptographic computing resource component for processing. If the remaining resources of the first cryptographic computing resource component are insufficient to meet the tenant's request, the middleware will allocate the remaining resource request to the second cryptographic computing resource component; the priority setting goal is to make full use of the fixed quota of the first cryptographic computing resource component to ensure the stability and predictability of resource allocation. At the same time, the second cryptographic computing resource component is used as a backup resource to provide additional support when necessary to cope with sudden resource demands, thereby ensuring that the system can run efficiently and stably under different resource demand conditions.

[0030] Preferably, assuming that tenant A's resource request requires 50 CPU cores for cryptographic computing tasks, the middleware will prioritize checking whether the first cryptographic computing resource component has sufficient remaining resources (assuming its fixed quota is 100 CPU cores, and currently 60 are remaining). If so, the resource request will be allocated to the first cryptographic computing resource component; but if tenant A subsequently requests an additional 30 CPU cores, and at this time the first cryptographic computing resource component has only 10 remaining computing resources and cannot fully meet the demand, then the middleware will allocate 10 resources to the first cryptographic computing resource component, and the remaining 20 resource requests will be allocated to the second cryptographic computing resource component for processing.

[0031] Further, step S100 also includes that the transmission between the first cryptographic computing resource component and the middleware includes a first NB-IOT communication module, and the transmission between the second cryptographic computing resource component and the middleware includes a second NB-IOT communication module.

[0032] Preferably, the NB-IOT communication module, namely the narrowband Internet of Things, is a low-power wide area network communication technology based on a cellular network. The first NB-IOT communication module is used to realize communication between the first cryptographic computing resource component and the middleware. The first NB-IOT communication module uses NB-IOT technology to transmit the data processed by the first cryptographic computing resource component or the required information to the middleware through the NB-IOT network, and can also receive instructions or data sent by the middleware to the first cryptographic computing resource component, thereby realizing two-way communication between the two; the second NB-IOT communication module has similar functions to the first NB-IOT communication module, and is responsible for data transmission between the second cryptographic computing resource component and the middleware. Through the NB-IOT network, the relevant data of the second cryptographic computing resource component is transmitted to the middleware, and the instructions or data of the middleware are passed to the second cryptographic computing resource component to realize the communication connection between the two.

[0033] Step S200 , inputting the historical resource request information of each tenant, and calculating the sliding average resource usage index of each tenant according to the historical resource request information.

[0034] Preferably, in a multi-tenant scenario in a cloud computing environment, each tenant generates multiple resource requests when using cloud cryptographic computing resources, and obtains historical resource request information from log files and databases related to cloud computing tasks, wherein the historical resource request information includes the tenant's use of cryptographic computing resources in the past period of time. Specific information may cover the time of the request, the type of resource requested (such as the number of CPU computing cores, memory capacity, storage bandwidth, etc.), and the number of resources requested, etc. For example, tenant A requested 10 CPU cores and 20GB of memory for cryptographic computing tasks at 10:00 on January 1, 2025, and requested 15 CPU cores and 30GB of memory at 14:00 on January 2, 2025. These detailed request records are all historical resource request information; the entry of each tenant's historical resource request information can be a regular batch import or a real-time collection and update to ensure the integrity and timeliness of the information.

[0035] Preferably, the sliding average resource usage indicator of each tenant is calculated according to the historical resource request information, wherein the sliding average is a commonly used statistical method that can smooth time series data to reflect the long-term trend and change of the data. When calculating the tenant's resource usage indicator, the sliding average can avoid the impact of individual sudden resource requests on the overall indicator and more accurately reflect the tenant's resource usage pattern; the sliding average resource usage indicator is used to measure and analyze the tenant's resource usage over a period of time, which can smooth out short-term fluctuations and outliers, and more accurately reflect the long-term trend and stability level of the tenant's resource usage, thereby improving the accuracy of cryptographic computing resource allocation. Specifically, we first determine a suitable time window, such as the past 7 days or 30 days. The time window slides over time, and the calculated data range is continuously updated. Then, within the set time window, we count and calculate the tenants' resource request information. For example, we take CPU core requests as an example. Assuming the time window is 7 days, the number of CPU cores requested by tenants every day during these 7 days are 10, 12, 15, 13, 11, 14, and 16, respectively. Then, the sliding average CPU core usage indicator for these 7 days is (10+12+15+13+11+14+16) ÷ 7 = 13. As time goes by, when the resources of a new day are When request information is added, the data of the earliest day will be removed and a new 7-day sliding average will be recalculated; if multiple resource types (such as CPU, memory, storage, etc.) are considered, the sliding average usage index of each resource can be calculated separately, and then the corresponding weights are assigned according to the importance of different resources, and finally the sliding average resource usage index is calculated comprehensively. For example, assuming that the weight of CPU resources is 0.6 and the weight of memory resources is 0.4, the calculated sliding average CPU usage index is 13, and the sliding average memory usage index is 25GB, then the comprehensive sliding average resource usage index is 13×0.6+25×0.4=17.8. By calculating the sliding average resource usage index of each tenant, we can better understand the tenant's resource usage habits and demand trends, and improve the accuracy of cryptographic computing resource allocation.

[0036] Step S300: clustering each tenant with the sliding average resource usage index to output multiple groups of tenants, wherein the multiple groups of tenants correspond to multiple resource allocation thresholds.

[0037] Preferably, clustering each tenant to output multiple groups of tenants means that each tenant is divided into different groups using the sliding average resource usage index as the basis for measuring the similarity of tenants, that is, tenants with similar sliding average resource usage indicators will be classified into the same group, while tenants with large indicator differences will be divided into different groups. For example, K-means clustering is used to process each tenant. Specifically, first, the number of clusters K is determined according to business needs and experience, that is, the number of groups to be divided into is determined in advance. For example, based on previous resource usage patterns, it is found that tenants can be roughly divided into three groups: high, medium, and low. For resource usage level, K is set to 3, and K are randomly selected from the sliding average resource usage indicators of all tenants as the initial cluster centroids. Then, the distance between the sliding average resource usage indicator of each tenant and each centroid is calculated (Euclidean distance is commonly used), and the tenant is assigned to the cluster with the nearest centroid. For each cluster, the average of the sliding average resource usage indicators of all tenants in the cluster is recalculated, and the calculated average is used as the new centroid. The iteration is repeated, and tenants are repeatedly assigned to clusters and the centroids are updated until the centroid no longer changes significantly or the preset number of iterations is reached, and finally 3 groups of tenants are obtained.

[0038] Preferably, for each group of tenants output by clustering, a resource allocation threshold suitable for the group of tenants is determined based on the sliding average resource usage index of the group of tenants, as a reference standard for the resources required by the group of tenants under normal circumstances. For example, for a group of tenants with a higher sliding average resource usage index, a higher resource allocation threshold may be set to ensure that they have sufficient resources to meet business needs; while for a group with a lower index, a relatively low threshold will be set to avoid resource waste. By calculating the resource allocation threshold for each group of tenants, resources can be allocated more reasonably and resource utilization efficiency can be improved according to the actual resource demand characteristics of different tenant groups.

[0039] Furthermore, step S300 also includes step S310, obtaining a sliding average resource usage indicator set corresponding to each group of tenants; step S320, performing time series fusion processing on the sliding average resource usage indicator set to obtain a time series-sliding average resource usage indicator set, and performing curve fitting according to the time series-sliding average resource usage indicator set to obtain a sliding average resource usage curve; step S330, allocating corresponding multiple resource allocation thresholds to the multiple groups of tenants according to the sliding average resource usage curve.

[0040] Preferably, sliding average resource usage indicators of multiple groups of tenants are collected and obtained respectively, and each group of tenants has a corresponding sliding average resource usage indicator set, which may include the sliding average usage of resources such as CPU, memory, network bandwidth, etc. per hour in the past week, reflecting the average level and change of resource usage of this group of tenants over a period of time; then the sliding average resource usage indicator set is subjected to time series fusion processing, that is, the originally scattered sliding average resource usage indicators are integrated and associated in chronological order, and the indicators of each time point are fused in consideration of the continuity and correlation of resource usage at different time points, so that each indicator corresponds to a specific time point, and a time series-sliding average resource usage indicator set is obtained, which not only includes the indicator data of resource usage, but also clarifies the time series to which these data correspond. For example, the resource usage indicators per hour are arranged in chronological order to form a time series from the past to the present, so that the changing trend of resource usage over time can be clearly seen.

[0041] Preferably, curve fitting is performed based on the time series-sliding average resource usage indicator set, that is, the data in the time series-sliding average resource usage indicator set is analyzed and processed to find a curve that can best describe the trend of these data changes, such as using the least squares method to determine the parameters of the curve so that the error between the curve and the actual data points is minimized, and then a sliding average resource usage curve is obtained, which can intuitively show the change pattern of the resource usage of the tenant group over time, and help analyze the peak and trough periods of resource usage and the overall change trend. For example, if the curve shows periodic fluctuations, it means that the tenant's resource usage has a certain periodic pattern; if the curve gradually rises, it shows that the resource usage is increasing. Assume that the CPU resource sliding average usage indicator data of a group of tenants over a period of time is shown in Table 1: Table 1. Tenant CPU resource sliding average usage indicator data within 12 hours (CPU core number) Time (hours) Actual moving average CPU resource usage indicator (number of CPU cores) 1 8 2 10 3 13 4 15 5 12 6 10 7 8 8 9 9 11 10 14 11 16 12 18 Use the least squares method to fit a quadratic curve y=ax 2 +bx+c (where y represents the moving average CPU resource usage indicator and x represents time), and the parameters a, b, and c of the curve are calculated by the least squares method to minimize the error between the curve and the actual data points; that is, to minimize the sum of the squares of the curve errors, the partial derivatives of a, b, and c are calculated respectively, and the partial derivatives are set equal to 0, and the simultaneous equations are solved to obtain a, b, and c; assuming that a=0.2, b=−1.5, and c=9.5 are obtained by calculation, the equation of the fitted curve is y=0.2x 2 −1.5x+9.5. As shown in Table 2, the CPU resource usage index (CPU core number) of the fitting curve is: Table 2 CPU resource usage indicators of the fitting curve (number of CPU cores) Time (hours) Sliding average CPU resource usage indicator (number of CPU cores) of the fitting curve 1 15.4 2 17.6 3 119.6 4 21.4 5 23 6 24.4 7 25.6 8 26.6 9 27.4 10 28 11 36.7 12 47.3 Preferably, according to the shape, trend and fluctuation of the sliding average resource usage curve, a suitable resource allocation threshold is determined for each group of tenants. For example, for a tenant group with a large curve fluctuation and a high peak value, a higher resource allocation threshold is set to ensure that there are sufficient resources to support the business peak; while for a tenant group with a relatively stable curve and low resource usage, the allocated threshold is relatively low; and when configuring the resource allocation threshold, the tenant's business demand characteristics and resource costs are also combined. If the tenant's business has high requirements for the real-time and stability of resources, even if its resource usage curve does not fluctuate much, the resource allocation threshold may be appropriately increased to ensure the normal operation of the business; at the same time, the cost of resources is also taken into account to avoid excessive allocation of resources leading to increased costs. Through the reasonable configuration of the resource allocation threshold, the reasonable allocation and efficient use of resources are achieved, which not only meets the tenant's business needs, but also avoids waste and excessive use of resources, thereby improving the overall resource management efficiency and performance.

[0042] Furthermore, step S330 also includes step S331, detecting a set of inflection points in the sliding average resource usage curve corresponding to each group of tenants, whose amplitude change is greater than a preset change amplitude; step S332, assigning weights to the inflection point set through exponentially weighted moving average to obtain an EWMA weight set, calculating the mean value of each inflection point in the inflection point set according to the EWMA weight set, and outputting the resource allocation threshold corresponding to each group of tenants.

[0043] Preferably, a sliding average resource usage curve is used to describe the changes in tenant resource usage over time. The inflection point on the curve refers to the point where the slope of the curve changes significantly, that is, the point where the rate of change of resource usage changes significantly. The preset change amplitude is a threshold preset based on historical data, which is used to judge the significance of the inflection point. When the amplitude change of the curve at a certain point is greater than the preset change amplitude, the point is regarded as an inflection point. By detecting the inflection point, the moment when the tenant resource usage changes significantly is obtained, and an inflection point set is obtained; the inflection point set is then weighted by exponentially weighted moving average, wherein the exponentially weighted moving average assigns different weights to data at different times, the more recent the data, the greater the weight, and the more distant the data, the smaller the weight; for each inflection point in the inflection point set, the EWMA method is used to assign weights according to its time sequence and its distance relationship with the current moment, and a larger weight is assigned to the recent inflection point, highlighting that the recent resource usage can better reflect the current and future resource demand trends of the tenants, and finally an EWMA weight set is obtained, and corresponding to the inflection point set, each inflection point has a corresponding weight value.

[0044] Preferably, the EWMA weight set is finally combined with the value of each inflection point in the inflection point set to perform mean calculation. Specifically, the value of each inflection point is multiplied by its corresponding weight, and then all the products are added together and divided by the sum of the weights to obtain a weighted average, i.e., the resource allocation threshold corresponding to each group of tenants. The inflection point information with large amplitude changes in the sliding average resource usage curve is comprehensively considered, and weighted processing is performed according to the time distance of these inflection points. This can more reasonably reflect the resource usage characteristics and needs of the tenants, thereby improving the accuracy of resource allocation, so that resource allocation can better adapt to the actual situation of the tenants and avoid the problem of over-allocation or under-allocation of resources.

[0045] Furthermore, step S300 also includes step S340, calculating according to the multiple resource allocation thresholds and outputting a total resource allocation threshold; step S350, obtaining configuration parameter information of the first cryptographic computing resource component, the configuration parameter information including resource configuration parameter information, network configuration parameter information and access configuration parameter information; step S360, performing a load balancing test on the total resource allocation threshold with the configuration parameter information to obtain a first computing resource quota test sample based on load balancing, and performing a fixed quota for the first cryptographic computing resource component according to the first computing resource quota test sample.

[0046] Preferably, a weighted summation is performed on multiple resource allocation thresholds to output a total resource allocation threshold, which represents the overall upper limit of resource allocation for all tenants, reflecting the total amount of resources that are expected to be provided while meeting the normal business needs of all tenants; the configuration parameter information of the first cryptographic computing resource component is obtained through the application programming interface (API) provided by the first cryptographic computing resource component, wherein the configuration parameter information includes resource configuration parameter information, network configuration parameter information, and access configuration parameter information. Specifically, the resource configuration parameter information mainly refers to the computing resources possessed by the first cryptographic computing resource component itself, such as the number of CPU cores it possesses, the size of memory capacity, the capacity of storage devices, and performance parameters, which determines the ability and scale of the component to handle computing tasks.

[0047] Preferably, the network configuration parameter information includes various parameters related to the network, such as the size of the network bandwidth, which determines the speed of data transmission between the component and other parts (such as middleware, tenants, etc.); network latency, which affects the timeliness of data transmission; and network topology, etc., which affects the efficiency and stability of data interaction between the component and the outside world; access configuration parameter information includes access permission settings for the component, such as which tenants or system modules have permission to access the component; the type of access protocol, such as which encryption protocol is used to ensure the security of data transmission; and restrictions on access frequency, etc., to prevent excessive access from causing component performance degradation or security issues.

[0048] Preferably, the total resource allocation threshold is load balancing tested with configuration parameter information, which means that based on the resource configuration, network configuration, access configuration and other parameter information of the first cryptographic computing resource component, various situations in which the component handles tenant resource requests under the restriction of the total resource allocation threshold are simulated to ensure that resources can be reasonably allocated and used, and to avoid the situation where some components are overloaded while other components are idle; for example, based on the network bandwidth and delay parameters, the time and efficiency of data transmission between the component and the middleware are simulated; based on the resource configuration parameters, the computing and processing capabilities of the component under different load conditions are simulated, and relevant data indicators are collected through simulation tests, such as the component's CPU utilization, memory occupancy, response time, success rate of processing requests, etc. These data constitute the first computing resource quota test sample based on load balancing, which records the performance and resource usage of the first cryptographic computing resource component in processing resource allocation tasks under different conditions.

[0049] Preferably, the first computing resource quota test sample is analyzed to observe the changing trend of the indicators under different resource allocation conditions, and to determine at what resource usage level the component can maintain stable and efficient operation, and then comprehensively consider the performance indicators, resource usage, overall stability and efficiency of the component to determine the key indicators. For example, CPU utilization and response time are relatively key indicators. If the CPU utilization is too high for a long time, it may cause component overheating, performance degradation, or even system crash; and too long response time will affect user experience and the overall efficiency of the system; then, based on the analysis results of the key indicators, combined with the overall needs and business goals, a fixed quota is set for the first cryptographic computing resource component. For example, if it is found that when the memory usage reaches 6GB, the performance of the component begins to decline significantly, and considering that there are other components that also need to use memory resources, the fixed memory quota of the first cryptographic computing resource component is set to 4GB to ensure stable operation.

[0050] Furthermore, step S300 also includes step S370, entering the historical resource request information of each tenant, and calculating the resource volatility of each tenant based on the sliding average resource usage indicator according to the historical resource request information; step S380, dividing the resource volatility set corresponding to each group of tenants according to the resource volatility corresponding to each tenant; step S390, calculating the total resource volatility threshold of each group of tenants based on the resource volatility set; step S3100, performing a load balancing test on the total resource volatility threshold with the configuration parameter information of the second cryptographic computing resource component, obtaining a second computing resource quota test sample based on load balancing, and performing dynamic quota for the second cryptographic computing resource component according to the second computing resource quota test sample.

[0051] Preferably, resource request data of each tenant in the past period of time is collected, including the requested resource type (such as CPU, memory, bandwidth, etc.), the request time, the requested resource amount, etc., and the resource volatility of each tenant is calculated based on the sliding average resource usage indicator, that is, it is obtained by calculating the rate of change of the sliding average resource usage in adjacent time intervals, which is used to measure the magnitude of the change in the tenant's resource usage; then, according to the resource volatility of each tenant, the tenants are divided into different groups, and the tenants in each group have similar resource volatility characteristics. For example, they can be grouped according to the size of the resource volatility, and the tenants with volatility within a certain range are grouped together, and then the total resource volatility threshold of each group of tenants is calculated, such as by counting the average, median, maximum and other statistical quantities of the resource volatility of the tenants in the group, to determine the total resource volatility threshold, such as taking the 95% quantile of the resource volatility in the group as the total threshold, that is, the resource volatility of 95% of the tenants in the group is less than or equal to this threshold.

[0052] Preferably, the configuration parameter information of the second cryptographic computing resource component is used to perform a load balancing test on the total threshold of resource volatility, wherein the configuration parameter information includes resource configuration parameters (such as the number of CPU cores, memory size, etc.), network configuration parameters (such as network bandwidth, IP address, etc.) and access configuration parameters (such as access rights, authentication method, etc.); by adjusting these configuration parameters, different load conditions are simulated, and the performance under the total threshold of resource volatility is observed, such as response time, throughput, resource utilization, etc., and based on the load balancing test results, a second computing resource quota test sample based on load balancing is obtained, which includes the performance data and resource usage of the system under different configuration parameters and load conditions; finally, according to these test samples, the second cryptographic computing resource component is dynamically allocated, that is, according to the actual load conditions and the resource requirements of the tenants, the resource allocation is flexibly adjusted, for example, when the load is high, appropriately increase the resource allocation to the second cryptographic computing resource component to ensure its performance; when the load is low, the resource allocation can be reduced to improve the resource utilization; thereby improving the accuracy and flexibility of computing resource allocation.

[0053] Step S400, the middleware receives the resource request of the tenant, and determines whether the resource usage index of the tenant accumulated on that day exceeds the resource allocation threshold corresponding to the group to which it belongs. If it does not exceed the resource allocation threshold corresponding to the group to which the tenant belongs, the middleware sends the resource request to the first cryptographic computing resource component for resource allocation. If it exceeds the resource allocation threshold corresponding to the group to which the tenant belongs, the middleware sends the resource request to the second cryptographic computing resource component for resource allocation.

[0054] Preferably, the middleware receives resource requests from tenants. Specifically, when the tenant needs to obtain cryptographic computing-related resources (such as computing power, storage resources, etc.) when running its business, it will send a resource request to the middleware, which includes the tenant's specific resource demand information, such as how many CPU cores and memory space are required; it is determined whether the tenant's cumulative resource usage index for the day exceeds the resource allocation threshold corresponding to the group to which it belongs, wherein the tenant's cumulative resource usage index for the day refers to the real-time record of the amount of resources used by each tenant on that day, and the calculated corresponding index, which can be a comprehensive reflection of the usage of multiple resources; then the tenant's cumulative resource usage index for the day is compared with the resource allocation threshold corresponding to the group to which the tenant belongs to determine whether the tenant's current resource usage exceeds the limit of its group.

[0055] Preferably, if the tenant's cumulative resource usage index for the day does not exceed the resource allocation threshold corresponding to the group to which it belongs, indicating that the tenant's resource usage is within the normal range, the middleware will send the tenant's resource request to the first cryptographic computing resource component, process the tenant's request according to the pre-set resource configuration, and allocate corresponding resources to the tenant to meet the tenant's business needs; if the tenant's cumulative resource usage index for the day exceeds the resource allocation threshold corresponding to the group to which it belongs, indicating that the tenant's resource demand has exceeded the normal allocation range of its group, the middleware will send the tenant's resource request to the second cryptographic computing resource component, and dynamically allocate additional resources based on the tenant's excess resource demand to ensure that the tenant's business can continue to operate normally, while also avoiding business interruptions due to insufficient resources.

[0056] Furthermore, step S400 also includes step S410, detecting that the idle time of the tenant's resources exceeds a preset threshold, triggering a resource recovery instruction; step S420, recycling the computing resources obtained by the tenant to the first cryptographic computing resource component or the second cryptographic computing resource component according to the resource recovery instruction.

[0057] Preferably, the usage status of the computing resources (such as CPU cores, memory space, storage capacity, etc.) obtained by each tenant is monitored in real time, and the tenant's resource idle time is obtained, that is, the length of time these computing resources are not used (idle) by the tenant. If it is detected that the tenant's resource idle time exceeds a preset threshold, a resource recovery instruction is automatically generated to perform a recovery operation on the tenant's idle resources to improve resource utilization and avoid resource waste. The preset threshold is a pre-set time standard used to determine whether the idle state of the resource has reached a level that requires recovery. For example, the preset threshold is set to 30 minutes, that is, if a computing resource of a tenant has not been used for 30 consecutive minutes, it is considered that the idle time of the resource exceeds the preset threshold, and a resource recovery operation is performed on it.

[0058] Preferably, a specific resource recovery action is performed according to the triggered resource recovery instruction, that is, the currently idle computing resources of the tenant are recovered from the tenant so that they are no longer occupied by the tenant. Specifically, the recovered computing resources are returned to the first cryptographic computing resource component or the second cryptographic computing resource component according to the resource management policy (such as the original resource allocation source, the current resource status of the component, etc.). For example, if the tenant initially obtained the resources from the first cryptographic computing resource component and the component currently has sufficient capacity to receive the recovered resources, the resources are recovered to the first cryptographic computing resource component; if the first cryptographic computing resource component is full or the resources need to be recovered to the second cryptographic computing resource component according to the policy to achieve a better resource balance, the resources are recovered to the second cryptographic computing resource component. Assume that tenant C obtains 10 CPU cores and 50GB of memory for cryptographic computing tasks. After running for a period of time, it is detected that 2 of the CPU cores and 20GB of memory have not been used by tenant C for 40 consecutive minutes (exceeding the preset 30-minute threshold). The resource recycling instruction is triggered, and the 2 CPU cores and 20GB of memory are recovered from tenant C. According to the resource management policy, they are recycled to the first cryptographic computing resource component or the second cryptographic computing resource component.

[0059] Furthermore, step S420 also includes step S421, wherein the middleware is connected to the desensitizing module, and when the resource recovery instruction is triggered, the computing resources obtained by the tenant are desensitized according to the desensitizing module to obtain the desensitized computing resources; and step S422, the desensitized computing resources are correspondingly recovered to the first cryptographic computing resource component or the second cryptographic computing resource component.

[0060] Preferably, in addition to being responsible for interacting with the tenant, the first cryptographic computing resource component and the second cryptographic computing resource component, the middleware also establishes a connection with the desensitizing module, so that the middleware can call the function of the desensitizing module to implement desensitizing operations on relevant data or resources, wherein the desensitizing module is used to process the data so that its sensitive information is removed or converted into a non-sensitive form; when it is detected that the tenant's resource idle time exceeds a preset threshold and the resource recovery instruction is triggered, the middleware uses the connection with the desensitizing module to send the computing resources obtained by the tenant (which may contain data information related to the tenant's business, such as temporary data generated during the cryptographic calculation process, etc.) to the desensitizing module, and the desensitizing module processes the sensitive information in these computing resources. For example, for data containing sensitive content such as tenant personal identity information, business confidential data, etc., the desensitizing module may use data shielding (such as replacing sensitive fields with specific symbols), data generalization (such as expanding the specific numerical range), data encryption, etc. to convert it into desensitized computing resources, so that these resources will not leak the tenant's sensitive information after being recycled. Finally, the desensitized computing resources are recycled to the first cryptographic computing resource component or the second cryptographic computing resource component; thereby realizing the redistribution and utilization of resources and ensuring the security of data during resource recycling, thereby improving the flexibility and accuracy of computing resource allocation and ensuring the normal and stable operation of tenant business.

[0061] In the above, refer to Figure 1 The following describes in detail the dynamic cloud cryptographic computing resource allocation method for multi-tenant grouping according to an embodiment of the present invention. Figure 2 A dynamic cloud cryptographic computing resource allocation middleware device for multi-tenant grouping according to an embodiment of the present invention is described.

[0062] The multi-tenant grouping dynamic cloud cryptographic computing resource allocation middleware device according to the embodiment of the present invention is used to solve the technical problem that cryptographic computing resources cannot be flexibly and accurately allocated according to the dynamically changing resource requirements of tenants in the prior art, resulting in low computing resource utilization efficiency and difficulty in normal operation of tenant services, thereby achieving the technical effect of improving computing resource utilization efficiency and ensuring normal operation of tenant services. Figure 2 As shown, the dynamic cloud cryptographic computing resource allocation middleware device for multi-tenant grouping includes: a computing resource component configuration unit 10, a sliding average resource usage indicator calculation unit 20, a tenant clustering output unit 30, and a resource allocation unit 40.

[0063] A computing resource component configuration unit 10 is used to configure a first cryptographic computing resource component and a second cryptographic computing resource component, wherein the first cryptographic computing resource component and the second cryptographic computing resource component are respectively connected to the middleware through the RDMA protocol; a sliding average resource usage index calculation unit 20 is used to input the historical resource request information of each tenant, and calculate the sliding average resource usage index of each tenant according to the historical resource request information; a tenant clustering output unit 30 is used to cluster each tenant with the sliding average resource usage index and output multiple groups of tenants, wherein the multiple groups of tenants correspond to multiple resource allocation thresholds; a resource allocation unit 40 is used to receive the resource request of the tenant by the middleware, and determine whether the resource usage index accumulated by the tenant on that day exceeds the resource allocation threshold corresponding to the group to which the tenant belongs. If it does not exceed the resource allocation threshold corresponding to the group to which the tenant belongs, the middleware sends the resource request to the first cryptographic computing resource component for resource allocation. If it exceeds the resource allocation threshold corresponding to the group to which the tenant belongs, the middleware sends the resource request to the second cryptographic computing resource component for resource allocation.

[0064] The specific configuration of the computing resource component configuration unit 10 will be described in detail below. The computing resource component configuration unit 10 further includes: configuring a first cryptographic computing resource component and a second cryptographic computing resource component, wherein the first cryptographic computing resource component is a resource component with a fixed quota, and the second cryptographic computing resource component is a resource component with a dynamic redundant quota based on the first cryptographic computing resource component; wherein the allocation priority of the first cryptographic computing resource component is greater than the allocation priority of the second cryptographic computing resource component.

[0065] The specific configuration of the tenant clustering output unit 30 will be described in detail below. The tenant clustering output unit 30 further includes: performing calculations based on the multiple resource allocation thresholds and outputting a total resource allocation threshold; obtaining configuration parameter information of the first cryptographic computing resource component, the configuration parameter information including resource configuration parameter information, network configuration parameter information and access configuration parameter information; performing a load balancing test on the total resource allocation threshold with the configuration parameter information to obtain a first computing resource quota test sample based on load balancing, and performing a fixed quota for the first cryptographic computing resource component according to the first computing resource quota test sample.

[0066] The specific configuration of the tenant clustering output unit 30 will be described in detail below. The tenant clustering output unit 30 further includes: inputting the historical resource request information of each tenant, calculating the resource volatility of each tenant based on the sliding average resource usage indicator according to the historical resource request information; dividing the resource volatility set corresponding to each group of tenants according to the resource volatility corresponding to each tenant; calculating the total resource volatility threshold of each group of tenants based on the resource volatility set; performing a load balancing test on the total resource volatility threshold with the configuration parameter information of the second cryptographic computing resource component, obtaining a second computing resource quota test sample based on load balancing, and performing a dynamic quota for the second cryptographic computing resource component according to the second computing resource quota test sample.

[0067] The specific configuration of the tenant clustering output unit 30 will be described in detail below. The tenant clustering output unit 30 further includes: obtaining a sliding average resource usage indicator set corresponding to each group of tenants; performing time series fusion processing on the sliding average resource usage indicator set to obtain a time series-sliding average resource usage indicator set, performing curve fitting according to the time series-sliding average resource usage indicator set to obtain a sliding average resource usage curve; and allocating corresponding multiple resource allocation thresholds to the multiple groups of tenants according to the sliding average resource usage curve.

[0068] The specific configuration of the tenant clustering output unit 30 will be described in detail below. The tenant clustering output unit 30 further includes: allocating corresponding multiple resource allocation thresholds for the multiple groups of tenants according to the sliding average resource usage curve, wherein the method of allocating corresponding resource allocation thresholds for each group of tenants includes: detecting a set of inflection points whose amplitude change is greater than a preset amplitude in the sliding average resource usage curve corresponding to each group of tenants; weighting the inflection point set by exponentially weighted moving average to obtain an EWMA weight set, calculating the average value of each inflection point in the inflection point set according to the EWMA weight set, and outputting the resource allocation threshold corresponding to each group of tenants.

[0069] The specific configuration of the computing resource component configuration unit 10 will be described in detail below. The computing resource component configuration unit 10 further includes: the first cryptographic computing resource component and the middleware include a second NB-IOT communication module, and the transmission of the second cryptographic computing resource component and the middleware includes a second NB-IOT communication module.

[0070] The specific configuration of the resource allocation unit 40 will be described in detail below. The resource allocation unit 40 further includes: detecting that the idle time of the tenant's resources exceeds a preset threshold, triggering a resource recycling instruction; and recycling the computing resources obtained by the tenant to the first cryptographic computing resource component or the second cryptographic computing resource component according to the resource recycling instruction.

[0071] The specific configuration of the resource allocation unit 40 will be described in detail below. The resource allocation unit 40 further includes: when the resource recovery instruction is triggered, the computing resources acquired by the tenant are desensitized according to the desensitization module to obtain the desensitized computing resources; and the desensitized computing resources are correspondingly recovered to the first cryptographic computing resource component or the second cryptographic computing resource component.

[0072] The dynamic cloud cryptographic computing resource allocation middleware device for multi-tenant groups provided in an embodiment of the present invention can execute the dynamic cloud cryptographic computing resource allocation method for multi-tenant groups provided in any embodiment of the present invention, and has functional modules and beneficial effects corresponding to the execution method.

[0073] Although the present application makes various references to certain modules in the device according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0074] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included in the protection scope of this application.

Claims

1. A method for allocating dynamic cloud cryptographic computing resources for multi-tenant groups, characterized in that: The method comprises: Configure a first cryptographic computing resource component and a second cryptographic computing resource component, wherein the first cryptographic computing resource component and the second cryptographic computing resource component are respectively connected to the middleware for communication through the RDMA protocol; Enter the historical resource request information of each tenant, and calculate the sliding average resource usage index of each tenant according to the historical resource request information; Clustering each tenant using the sliding average resource usage indicator to output multiple groups of tenants, wherein the multiple groups of tenants correspond to multiple resource allocation thresholds; The middleware receives the tenant's resource request and determines whether the tenant's cumulative resource usage index for the day exceeds the resource allocation threshold corresponding to the group to which it belongs. If it does not exceed the resource allocation threshold corresponding to the group to which the tenant belongs, the middleware sends the resource request to the first cryptographic computing resource component for resource allocation. If it exceeds the resource allocation threshold corresponding to the group to which the tenant belongs, the middleware sends the resource request to the second cryptographic computing resource component for resource allocation.

2. The method for allocating dynamic cloud cryptographic computing resources for multi-tenant groups according to claim 1, characterized in that: Configure a first cryptographic computing resource component and a second cryptographic computing resource component, wherein the first cryptographic computing resource component is a resource component with a fixed quota, and the second cryptographic computing resource component is a resource component with a dynamic redundant quota based on the first cryptographic computing resource component; Among them, the allocation priority of the first cryptographic computing resource component is greater than the allocation priority of the second cryptographic computing resource component.

3. The method for allocating dynamic cloud cryptographic computing resources for multi-tenant groups as claimed in claim 2, characterized in that: The method of configuring the first cryptographic computing resource component includes: Calculate according to the multiple resource allocation thresholds and output a total resource allocation threshold; Obtaining configuration parameter information of the first cryptographic computing resource component, the configuration parameter information including resource configuration parameter information, network configuration parameter information, and access configuration parameter information; A load balancing test is performed on the total resource allocation threshold using the configuration parameter information to obtain a first computing resource quota test sample based on load balancing, and a fixed quota is performed for the first cryptographic computing resource component according to the first computing resource quota test sample.

4. The method for allocating dynamic cloud cryptographic computing resources for multi-tenant groups according to claim 1, characterized in that: The method of configuring the second cryptographic computing resource component includes: Entering historical resource request information of each tenant, and calculating the resource fluctuation rate of each tenant based on the sliding average resource usage indicator according to the historical resource request information; According to the resource volatility rates corresponding to each tenant, divide the resource volatility rate set corresponding to each group of tenants; Calculating a total resource fluctuation rate threshold for each group of tenants based on the resource fluctuation rate set; A load balancing test is performed on the total resource volatility threshold using the configuration parameter information of the second cryptographic computing resource component to obtain a second computing resource quota test sample based on load balancing, and a dynamic quota is performed for the second cryptographic computing resource component based on the second computing resource quota test sample.

5. The method for allocating dynamic cloud cryptographic computing resources for multi-tenant groups according to claim 1, characterized in that: Allocating corresponding multiple resource allocation thresholds to the multiple groups of tenants, the method comprising: Get the sliding average resource usage indicator set corresponding to each group of tenants; Performing time series fusion processing on the sliding average resource usage indicator set to obtain a time series-sliding average resource usage indicator set, and performing curve fitting according to the time series-sliding average resource usage indicator set to obtain a sliding average resource usage curve; Corresponding multiple resource allocation thresholds are allocated to the multiple groups of tenants according to the sliding average resource usage curve.

6. The method for allocating dynamic cloud cryptographic computing resources for multi-tenant groups as claimed in claim 5, characterized in that: According to the sliding average resource usage curve, a plurality of corresponding resource allocation thresholds are allocated to the plurality of groups of tenants, wherein the method of allocating a corresponding resource allocation threshold to each group of tenants comprises: Detecting a set of inflection points in the sliding average resource usage curve corresponding to each group of tenants, where the change is greater than a preset change; The inflection point set is weighted by exponentially weighted moving average to obtain an EWMA weight set, and the value of each inflection point in the inflection point set is averaged according to the EWMA weight set to output the resource allocation threshold corresponding to each group of tenants.

7. The method for allocating dynamic cloud cryptographic computing resources for multi-tenant groups according to claim 1, characterized in that: The first cryptographic computing resource component and the middleware include a second NB-IOT communication module, and the transmission between the second cryptographic computing resource component and the middleware includes the second NB-IOT communication module.

8. The method for allocating dynamic cloud cryptographic computing resources for multi-tenant groups according to claim 1, characterized in that: After the middleware sends the resource request to the first cryptographic computing resource component or the second cryptographic computing resource component for resource allocation, the method further includes: Detecting that the idle time of the tenant's resources exceeds a preset threshold, triggering a resource recycling instruction; According to the resource recycling instruction, the computing resources acquired by the tenant are recycled to the first cryptographic computing resource component or the second cryptographic computing resource component.

9. The method for allocating dynamic cloud cryptographic computing resources for multi-tenant groups as claimed in claim 8, characterized in that: The middleware is connected to the desensitization module, and the method includes: When the resource recovery instruction is triggered, the computing resources acquired by the tenant are desensitized according to the desensitization module to obtain desensitized computing resources; The desensitized computing resources are recycled to the first cryptographic computing resource component or the second cryptographic computing resource component accordingly.

10. A multi-tenant grouped dynamic cloud cryptographic computing resource allocation middleware device, characterized in that: The device is used to implement the multi-tenant grouping dynamic cloud cryptographic computing resource allocation method according to any one of claims 1 to 9, and the device includes: A computing resource component configuration unit, used to configure a first cryptographic computing resource component and a second cryptographic computing resource component, wherein the first cryptographic computing resource component and the second cryptographic computing resource component are respectively connected to the middleware through an RDMA protocol; A sliding average resource usage index calculation unit, used to input the historical resource request information of each tenant, and calculate the sliding average resource usage index of each tenant according to the historical resource request information; A tenant clustering output unit, configured to cluster each tenant according to the sliding average resource usage indicator to output multiple groups of tenants, wherein the multiple groups of tenants correspond to multiple resource allocation thresholds; A resource allocation unit is used for the middleware to receive the resource request of the tenant, and determine whether the resource usage index of the tenant accumulated on that day exceeds the resource allocation threshold corresponding to the group to which the tenant belongs. If it does not exceed the resource allocation threshold corresponding to the group to which the tenant belongs, the middleware sends the resource request to the first cryptographic computing resource component for resource allocation; if it exceeds the resource allocation threshold corresponding to the group to which the tenant belongs, the middleware sends the resource request to the second cryptographic computing resource component for resource allocation.

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