A virtual cloud cryptographic resource processing method and system

Abstract

The present application relates to the technical field of cryptographic cloud resources, and in particular to a virtual cloud cryptographic resource processing method and system. Establish a cloud cryptographic resource pool, and generate multiple resource groups based on the cloud cryptographic resource pool; obtain user demand parameters, generate resource demand quantities based on user demand parameters, and generate resource allocation parameters based on resource demand quantities; obtain the real-time load evaluation value of each resource group based on the feedback time node, and correct the resource allocation parameters based on the load evaluation value. By setting up multiple resource groups, the cloud cryptographic resource pool is dynamically divided, and virtual machines are established according to user needs, and deployed in sequence to ensure on-demand allocation of cryptographic resources and improve allocation efficiency. By presetting the feedback time node, the resource amount of the resource group is dynamically adjusted to avoid waste of resources due to excessively high resource vacancy rate of a single resource group, and at the same time avoid the reduction of task processing speed and operating efficiency due to excessive growth in user demand, so as to ensure load balancing of each resource group.

Description

Technical Field

[0001] The present application relates to the technical field of cryptographic cloud resources, and in particular to a virtual cloud cryptographic resource processing method and system. Background Art

[0002] With the continuous development of information system business, the application of cryptographic machines in business systems is increasing. For problems such as massive data encryption and user identity authentication in cloud computing environments, traditional discrete cryptographic servers can no longer meet the needs. It is necessary to integrate cryptographic servers that meet the requirements and are equipped with special hardware security modules to form a cryptographic resource pool, which will be centrally scheduled and managed by the cloud platform to meet the needs of large-scale cryptographic operations.

[0003] How to ensure that cryptographic resources are allocated on demand, deployed flexibly, and that each resource node is load balanced to maintain the smooth operation of the system has become a technical problem that needs to be solved urgently at this stage. Cryptographic resource scheduling has become a very critical part of cloud cryptographic resource pool management. Summary of the invention

[0004] The purpose of this application is: to solve the above technical problems, this application provides a virtual cloud cryptographic resource processing method and system, aiming to improve the allocation efficiency of cryptographic resources and ensure the system operation efficiency.

[0005] In some embodiments of the present application, the cloud cryptographic resource pool is dynamically divided by setting up multiple resource groups, and virtual machines are established according to user needs and deployed in sequence to ensure on-demand allocation of cryptographic resources and improve allocation efficiency.

[0006] In some embodiments of the present application, by presetting feedback time nodes, the resource amount of the resource group is dynamically adjusted according to the real-time load conditions of each first-level resource group, thereby avoiding resource waste due to excessive resource vacancy rate of a single resource group, and at the same time avoiding a decrease in task processing speed and operating efficiency due to excessive growth in user demand, thereby ensuring load balance among each resource group.

[0007] In some embodiments of the present application, a virtual cloud cryptographic resource processing method is provided, including:

[0008] Establishing a cloud cryptographic resource pool, and generating a plurality of resource groups according to the cloud cryptographic resource pool;

[0009] Acquire user demand parameters, generate resource demand quantities according to the user demand parameters, and generate resource allocation parameters according to the resource demand quantities;

[0010] A real-time load evaluation value of each resource group is obtained according to the feedback time node, and the resource allocation parameter is modified according to the load evaluation value.

[0011] In some embodiments of the present application, when generating multiple resource groups according to the password cloud resource pool, it includes:

[0012] Obtain the total amount of resources A in the password cloud resource pool;

[0013] Obtain the maximum value a1 of the resources required by a single historical user;

[0014] Set the number of resource groups m, where m = [A / 2a1];

[0015] Preset the first-level resource group and the second-level resource group;

[0016] Set the resource amount A1 of a single first-level resource group = A / m, and the resource amount A2 of a single second-level resource group = A / m;

[0017] Obtain the peak value b of historical user requirements;

[0018] Set the proportion c of the second-level resource group according to the peak value b of the historical user requirements.

[0019] In some embodiments of the present application, when setting the proportion of the second-level resource group according to the peak value a2 of the historical user requirements, it includes:

[0020] Preset the peak value matrix B of historical user requirements, and set B(B1, B2, B3, B3, B4), where B1 is the preset first peak value of historical user requirements, B2 is the preset second peak value of historical user requirements, B3 is the preset third peak value of historical user requirements, B4 is the preset fourth peak value of historical user requirements, and B1 < B2 < B3 < B4;

[0021] Preset the proportion matrix C of the second-level resource group, and set C(C1, C2, C3), where C1 is the preset first proportion of the second-level resource group, C2 is the preset second proportion of the second-level resource group, C3 is the preset third proportion of the second-level resource group, and C1 < C2 < C3;

[0022] If b < B1, set the proportion c of the second-level resource group as the preset first proportion C1 of the second-level resource, that is, c = C1;

[0023] If B1 < b < B2, set the proportion c of the second-level resource group as the preset second proportion C2 of the second-level resource, that is, c = C2;

[0024] If B2 < b < B3, set the proportion c of the second-level resource group as the preset third proportion C3 of the second-level resource, that is, c = C3;

[0025] If b > B3, set the proportion c of the second-level resource group as the preset fourth proportion C4 of the second-level resource, that is, c = C4.

[0026] In some embodiments of the present application, when generating the resource demand according to the user demand parameter, it includes:

[0027] Generate initial resource demand d1 based on user demand parameters;

[0028] Get the user service level e, according to the user service level e generates a compensation coefficient n;

[0029] Generate a primary resource demand d2 according to the compensation coefficient n;

[0030] Establishing a demand forecasting model, and generating an expected growth amount d3 of user demand resources according to the demand forecasting model;

[0031] Generate resource demand d, where d=d2+d3.

[0032] In some embodiments of the present application, the generating of the compensation coefficient n according to the user service level e includes:

[0033] A preset user service level matrix E is set as E(E1, E2, E3, E4), where E1 is a preset first-level service user, E2 is a preset second-level service user, E3 is a preset third-level service user, and E4 is a preset fourth-level service user;

[0034] The preset compensation coefficient matrix N is set to N(n1, n2, n3, n4), where n1 is the preset first compensation coefficient, n2 is the preset second compensation coefficient, n3 is the preset third compensation coefficient, n4 is the preset fourth compensation coefficient, and 1 <n1<n2<n3<n4;

[0035] If e=E1, set the compensation coefficient n=n1, and the user resource demand d2=n1*d1;

[0036] If e=E2, set the compensation coefficient n=n2, and the user resource demand d2=n2*d1;

[0037] If e=E3, set the compensation coefficient n=n3, and the user resource demand d2=n3*d1;

[0038] If e=E4, set the compensation coefficient n=n4, and the user resource demand d2=n4*d1.

[0039] In some embodiments of the present application, when generating resource allocation parameters according to the resource demand, it includes:

[0040] Generate a virtual machine according to the resource demand d;

[0041] Get the virtual machine sequence H of all users, (h1,h2,h3…hi), where i is the number of users;

[0042] Generate deployment order based on virtual machine demand time series;

[0043] Set the first-level resource group corresponding to the virtual machine according to the deployment order.

[0044] In some embodiments of the present application, when correcting the resource allocation parameters according to the load evaluation value, it includes:

[0045] Set the correction coefficient k according to the real-time load evaluation value j of the first-level resource group;

[0046] Correct the resource amount A1 of the first-level resource group according to the correction coefficient;

[0047] Preset a load evaluation value matrix J, set J(J1, J2, J3, J4), where J1 is the preset first load evaluation value, J2 is the preset second load evaluation value, J3 is the preset third load evaluation value, J4 is the preset fourth load evaluation value, and J1 < J2 < J3 < J4;

[0048] Preset a correction coefficient matrix K, set K(k1, k2, k3, k4), where k1 is the preset first correction coefficient, k2 is the preset second correction coefficient, k3 is the preset third correction coefficient, k4 is the preset fourth correction coefficient, and k1 < k2 < 1 < k3 < k4;

[0049] If j < J1, set the correction coefficient k = k1, and the resource amount A1 of the corrected first-level resource group = k1 * A / m;

[0050] If J1 < j < J2, set the correction coefficient k = k2, and the resource amount A1 of the corrected first-level resource group = k2 * A / m;

[0051] If J1 < j < J2, do not set the correction coefficient;

[0052] If J3 < j < J4, set the correction coefficient k = k3, and the resource amount A1 of the corrected first-level resource group = k3 * A / m;

[0053] If j > J4, set the correction coefficient k = k4, and the resource amount A1 of the corrected first-level resource group = k4 * A / m.

[0054] In some embodiments of the present application, a virtual cloud password resource processing system is provided, including:

[0055] A central control unit, which is used to establish a cloud password resource pool and generate multiple resource groups according to the cloud password resource pool;

[0056] A resource processing unit, which is used to obtain user demand parameters, generate resource demand quantities according to the user demand parameters, and generate resource allocation parameters according to the resource demand quantities;

[0057] A resource monitoring unit, wherein a user presets a feedback time node for the resource monitoring unit, and the resource monitoring unit also obtains a real-time load evaluation value of each resource group according to the feedback time node, and modifies the resource allocation parameter according to the load evaluation value.

[0058] In some embodiments of the present application, the resource processing unit includes:

[0059] The first processing module generates an initial resource requirement d1 according to user demand parameters;

[0060] A second processing module, wherein the second processing module obtains a user service level e, generates a compensation coefficient n according to the user service level e, and generates a primary resource demand d2 according to the compensation coefficient n;

[0061] The third processing module is used to establish a demand forecasting model, and generate an expected growth amount d3 of user demand resources according to the demand forecasting model. The third processing module is also used to generate a resource demand d, where d=d2+d3;

[0062] A fourth processing module, configured to generate a virtual machine according to the resource demand d;

[0063] The fourth processing module is further used to obtain a virtual machine sequence H of all users (h1, h2, h3 ... hi), where i is the number of users; generate a deployment sequence according to a virtual machine demand time sequence; and set a primary resource group corresponding to the virtual machine according to the deployment sequence.

[0064] In some embodiments of the present application, the resource monitoring unit includes:

[0065] The first monitoring module is used to set a feedback time node;

[0066] The first correction module is used to set a correction coefficient k according to a real-time load evaluation value j of the primary resource group. The first correction module is also used to correct the resource amount A1 of the primary resource group according to the correction coefficient k.

[0067] Compared with the prior art, the virtual cloud cryptographic resource processing method and system of the present application embodiment has the following beneficial effects:

[0068] By setting up multiple resource groups, the cloud password resource pool is dynamically divided. At the same time, virtual machines are established according to user needs and deployed in sequence to ensure on-demand allocation of password resources and improve allocation efficiency.

[0069] By presetting feedback time nodes, the resource amount of the resource group is dynamically adjusted according to the real-time load conditions of each first-level resource group to avoid resource waste due to excessive resource vacancy rate of a single resource group, and to avoid reduction in task processing speed and operating efficiency due to excessive growth in user demand, thereby ensuring load balance among each resource group. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Figure 1 It is a flow chart of a virtual cloud cryptographic resource processing method in a preferred embodiment of the present application. DETAILED DESCRIPTION

[0071] The specific implementation methods of the present application are further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present application but are not intended to limit the scope of the present application.

[0072] In the description of the present application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0073] The terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, unless otherwise specified, "plurality" means two or more.

[0074] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0075] like Figure 1 As shown, a virtual cloud cryptographic resource processing method of a preferred embodiment of the present application includes:

[0076] S101: Establish a cloud password resource pool, and generate multiple resource groups according to the cloud password resource pool;

[0077] S102: Obtain user requirement parameters, generate resource demand quantities according to the user requirement parameters, and generate resource allocation parameters according to the resource demand quantities;

[0078] S103: Obtain the real-time load evaluation values of each resource group according to the feedback time nodes, and correct the resource allocation parameters according to the load evaluation values.

[0079] Specifically, when generating multiple resource groups according to the password cloud resource pool, it includes:

[0080] Obtain the total amount of resources A of the password cloud resource pool;

[0081] Obtain the maximum value a1 of the resources required by a single historical user;

[0082] Set the number of resource groups m, where m = [A / 2a1];

[0083] Preset the first-level resource group and the second-level resource group;

[0084] Set the resource amount A1 of a single first-level resource group = A / m, and the resource amount A2 of a single second-level resource group = A / m;

[0085] Obtain the historical peak demand b of users;

[0086] Set the proportion c of the second-level resource group according to the historical peak demand b of users.

[0087] Specifically, the first-level resource group is a task processing resource group, and the second-level resource group is a standby resource. When the resource growth of the user virtual machines in the first-level resource group is relatively high and causes the current first-level resource group to run overloaded, the resources in the second-level resource group are called.

[0088] Specifically, when setting the proportion of the second-level resource group according to the historical peak demand a2 of users, it includes:

[0089] Preset the historical peak demand matrix B of users, and set B(B1, B2, B3, B3, B4), where B1 is the preset first historical peak demand of users, B2 is the preset second historical peak demand of users, B3 is the preset third historical peak demand of users, B4 is the preset fourth historical peak demand of users, and B1 < B2 < B3 < B4;

[0090] Preset the proportion matrix C of the second-level resource group, and set C(C1, C2, C3), where C1 is the preset first proportion of the second-level resource group, C2 is the preset second proportion of the second-level resource group, C3 is the preset third proportion of the second-level resource group, and C1 < C2 < C3;

[0091] If b < B1, set the proportion c of the second-level resource group as the preset first proportion C1 of the second-level resource, that is, c = C1;

[0092] If B1 < b < B2, set the proportion c of the secondary resource group as the preset second secondary resource proportion C2, i.e., c = C2;

[0093] If B2 < b < B3, set the proportion c of the secondary resource group as the preset third secondary resource proportion C3, i.e., c = C3;

[0094] If b > B3, set the proportion c of the secondary resource group as the preset fourth secondary resource proportion C4, i.e., c = C4.

[0095] It can be understood that in the above embodiments, by setting multiple resource groups, the cloud password resource pool is dynamically divided. At the same time, virtual machines are established according to user requirements and deployed in sequence to ensure the on-demand allocation of password resources, improve the allocation efficiency. At the same time, by establishing the primary resource group and the secondary resource group, the resource data of the cloud password resource pool is dynamically called in a timely manner to ensure the load balance of each resource group.

[0096] In the preferred embodiment of the present application, when generating the resource demand according to the user demand parameters, it includes:

[0097] Generate the initial resource demand d1 according to the user demand parameters;

[0098] Obtain the user service level e, and generate the compensation coefficient n according to the user service level e;

[0099] Generate the primary resource demand d2 according to the compensation coefficient n;

[0100] Establish a demand prediction model, and generate the expected growth amount d3 of the user demand resources according to the demand prediction model;

[0101] Generate the resource demand d, where d = d2 + d3.

[0102] Specifically, establish a demand prediction model according to the user historical demand data to predict the growth amount of resources required by the user during the task operation. And generate the initial resource demand by obtaining the real-time demand parameters of the user, and set different compensation coefficients according to different user levels to correct the initial resource demand, and finally generate the resource demand, and the resource demand includes the basic resource amount and the spare resource amount.

[0103] Specifically, when generating the compensation coefficient n according to the user service level e, it includes:

[0104] Preset the user service level matrix E, set E(E1, E2, E3, E4), where E1 is the preset first-level service user, E2 is the preset second-level service user, E3 is the preset third-level service user, and E4 is the preset fourth-level service user;

[0105] The preset compensation coefficient matrix N is set to N(n1, n2, n3, n4), where n1 is the preset first compensation coefficient, n2 is the preset second compensation coefficient, n3 is the preset third compensation coefficient, n4 is the preset fourth compensation coefficient, and 1 <n1<n2<n3<n4;

[0106] If e=E1, set the compensation coefficient n=n1, and the user resource demand d2=n1*d1;

[0107] If e=E2, set the compensation coefficient n=n2, and the user resource demand d2=n2*d1;

[0108] If e=E3, set the compensation coefficient n=n3, and the user resource demand d2=n3*d1;

[0109] If e=E4, set the compensation coefficient n=n4, and the user resource demand d2=n4*d1.

[0110] Specifically, the user service level is set based on factors such as the user identity authority in the user's historical parameters, the user's historical average resource usage, etc. According to their importance, the fourth-level service user is higher than the third-level service user, which is higher than the second-level service user, which is higher than the first-level service user.

[0111] Specifically, when generating resource allocation parameters according to resource demand, it includes:

[0112] Generate a virtual machine according to the resource demand d;

[0113] Get the virtual machine sequence H of all users, (h1,h2,h3…hi), where i is the number of users;

[0114] Generate deployment order based on virtual machine demand time series;

[0115] Set the primary resource group corresponding to the virtual machine according to the deployment order.

[0116] It can be understood that in the above embodiment, automated scheduling decisions are made based on the usage of the cloud cryptographic resource pool and the resource group load data, and the user's cryptographic service needs are allocated to the most appropriate virtual cryptographic device, ensuring that the system cryptographic resources are in a load-balanced state, thereby improving the stability of system operation.

[0117] In a preferred embodiment of the present application, when modifying the resource allocation parameters according to the load evaluation value, it includes:

[0118] Set the correction factor k according to the real-time load evaluation value j of the primary resource group;

[0119] Correct the resource quantity A1 of the first-level resource group according to the correction coefficient;

[0120] Specifically, the load evaluation value is set according to parameters such as the usage of the virtual cryptographic machine, CPU utilization rate, and memory utilization rate of the current first-level resource group. The higher the load evaluation value, the higher the operating load of the current first-level resource group.

[0121] Preset a load evaluation value matrix J, and set J(J1, J2, J3, J4), where J1 is the preset first load evaluation value, J2 is the preset second load evaluation value, J3 is the preset third load evaluation value, J4 is the preset fourth load evaluation value, and J1 < J2 < J3 < J4;

[0122] Preset a correction coefficient matrix K, and set K(k1, k2, k3, k4), where k1 is the preset first correction coefficient, k2 is the preset second correction coefficient, k3 is the preset third correction coefficient, k4 is the preset fourth correction coefficient, and k1 < k2 < 1 < k3 < k4;

[0123] If j < J1, set the correction coefficient k = k1, and the resource amount A1 of the corrected first-level resource group = k1 * A / m;

[0124] If J1 < j < J2, set the correction coefficient k = k2, and the resource amount A1 of the corrected first-level resource group = k2 * A / m;

[0125] If J1 < j < J2, no correction coefficient is set;

[0126] If J3 < j < J4, set the correction coefficient k = k3, and the resource amount A1 of the corrected first-level resource group = k3 * A / m;

[0127] If j > J4, set the correction coefficient k = k4, and the resource amount A1 of the corrected first-level resource group = k4 * A / m.

[0128] It can be understood that in the above embodiments, by setting the correction coefficient matrix and the load evaluation value matrix, the correction coefficient is set according to the real-time load evaluation value of the first-level resource group, and the resource occupancy is dynamically adjusted, avoiding resource waste caused by too high a resource vacancy rate of a single resource group, and at the same time avoiding a decrease in task processing speed and operating efficiency caused by too large an increase in user demand, ensuring load balancing of each resource group.

[0129] Based on another preferred embodiment of the virtual cloud password resource processing method in any of the above preferred embodiments, a virtual cloud password resource processing is provided in this embodiment, including:

[0130] A central control unit, which is used to establish a cloud password resource pool and generate multiple resource groups according to the cloud password resource pool;

[0131] The resource processing unit obtains user demand parameters, generates resource demand quantities according to the user demand parameters, and generates resource allocation parameters according to the resource demand quantities;

[0132] Resource monitoring unit: The user of the resource monitoring unit presets a feedback time node. The resource monitoring unit also obtains the real-time load evaluation value of each resource group according to the feedback time node, and modifies the resource allocation parameters according to the load evaluation value.

[0133] Specifically, the resource processing unit includes:

[0134] The first processing module generates an initial resource requirement d1 according to user demand parameters;

[0135] The second processing module, in which the user obtains the user service level e, generates a compensation coefficient n according to the user service level e, and generates a first-level resource demand d2 according to the compensation coefficient n;

[0136] The third processing module is used to establish a demand prediction model, and generate an expected growth amount d3 of user demand resources according to the demand prediction model. The third processing module is also used to generate a resource demand d, where d=d2+d3;

[0137] A fourth processing module, used for generating a virtual machine according to the resource demand d;

[0138] The fourth processing module is also used to obtain the virtual machine sequence H of all users (h1, h2, h3...hi), where i is the number of users; generate a deployment sequence according to the virtual machine demand time series; and set the primary resource group corresponding to the virtual machine according to the deployment sequence.

[0139] Specifically, the resource monitoring unit includes:

[0140] The first monitoring module is used to set a feedback time node;

[0141] The first correction module is used to set a correction coefficient k according to the real-time load evaluation value j of the primary resource group. The first correction module is also used to correct the resource amount A1 of the primary resource group according to the correction coefficient k.

[0142] According to the first concept of the present application, by setting up multiple resource groups, the cloud cryptographic resource pool is dynamically divided, and at the same time, virtual machines are established according to user needs and deployed in sequence to ensure on-demand allocation of cryptographic resources and improve allocation efficiency.

[0143] According to the second concept of the present application, by presetting feedback time nodes, the resource amount of the resource group is dynamically adjusted according to the real-time load conditions of each first-level resource group, so as to avoid waste of resources due to excessive resource vacancy rate of a single resource group, and at the same time avoid reduction in task processing speed and operating efficiency due to excessive growth in user demand, thereby ensuring load balance of each resource group.

[0144] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and substitutions can be made without departing from the technical principles of the present application. These improvements and substitutions should also be regarded as the scope of protection of the present application.

Claims

1. A virtual cloud cryptographic resource processing method, characterized in that: Including: Establish a cloud password resource pool and generate multiple resource groups according to the cloud password resource pool; Obtain user demand parameters, generate a resource demand quantity according to the user demand parameters, and generate a resource allocation parameter according to the resource demand quantity; Obtain the real-time load evaluation value of each resource group according to the feedback time node, and correct the resource allocation parameter according to the load evaluation value; When generating multiple resource groups according to the cloud password resource pool, it includes: Obtain the total amount of resources A in the cloud password resource pool; Obtain the maximum value a1 of the resources required by a single historical user; Set the number of resource groups m, where m = [A / 2a1]; Preset a primary resource group and a secondary resource group; The primary resource group is a task processing resource group, and the secondary resource group is a standby resource group. When there is a resource increase in the user virtual machine in the primary resource group causing the current primary resource group to operate overloaded, the resources in the secondary resource group are called; Set the resource amount A1 of a single primary resource group = A / m, and the resource amount A2 of a single secondary resource group = A / m; Obtain the historical user demand peak value b; Set the proportion c of the secondary resource group according to the historical user demand peak value b; When setting the proportion of the secondary resource group according to the historical user demand peak value b, it includes: Preset a historical user demand peak value matrix B, and set B = (B1, B2, B3, B4), where B1 is the preset first historical user demand peak value, B2 is the preset second historical user demand peak value, B3 is the preset third historical user demand peak value, B4 is the preset fourth historical user demand peak value, and B1 < B2 < B3 < B4; Preset a secondary resource group proportion matrix C, and set C = (C1, C2, C3, C4), where C1 is the preset first secondary resource group proportion value, C2 is the preset second secondary resource group proportion value, C3 is the preset third secondary resource group proportion value, C4 is the preset fourth secondary resource group proportion value; and C1 < C2 < C3 < C4; If b < B1, set the proportion c of the secondary resource group as the preset first secondary resource proportion value C1, that is, c = C1; If B1 < b < B2, set the proportion c of the secondary resource group as the preset second secondary resource proportion value C2, that is, c = C2; If B2 < b < B3, set the proportion c of the secondary resource group as the preset third secondary resource proportion value C3, that is, c = C3; If b > B3, set the proportion c of the secondary resource group as the preset fourth secondary resource proportion value C4, that is, c = C4.

2. The virtual cloud cryptographic resource processing method according to claim 1, characterized in that: When generating the resource demand quantity according to the user demand parameter, it includes: Generate an initial resource demand quantity d1 according to the user demand parameter; Obtain the user service level e, and generate a compensation coefficient n according to the user service level e; Generate a primary resource demand quantity d2 according to the compensation coefficient n; Establish a demand prediction model, and generate an expected growth quantity d3 of the user demand resources according to the demand prediction model; Generate a resource demand quantity d, where d = d2 + d3.

3. The virtual cloud cryptographic resource processing method according to claim 2, characterized in that: When generating the compensation coefficient n according to the user service level e, it includes: Preset user service level matrix E, set E(E1, E2, E3, E4), where E1 is the preset first-level service user, E2 is the preset second-level service user, E3 is the preset third-level service user, and E4 is the preset fourth-level service user; Preset compensation coefficient matrix N, set N=(n1, n2, n3, n4), where n1 is the preset first compensation coefficient, n2 is the preset second compensation coefficient, n3 is the preset third compensation coefficient, n4 is the preset fourth compensation coefficient, and 1 < n1 < n2 < n3 < n4; If e = E1, set the compensation coefficient n = n1, and the user resource demand d2 = n1 * d1; If e = E2, set the compensation coefficient n = n2, and the user resource demand d2 = n2 * d1; If e = E3, set the compensation coefficient n = n3, and the user resource demand d2 = n3 * d1; If e = E4, set the compensation coefficient n = n4, and the user resource demand d2 = n4 * d1.

4. The virtual cloud cryptographic resource processing method according to claim 2, characterized in that: When generating resource allocation parameters according to the resource demand, it includes; Generate virtual machines according to the resource demand d; Obtain the virtual machine sequence H of all users, H=(h1, h2, h3…hi), where i is the number of users; Generate the deployment order according to the virtual machine demand time series; Set the first-level resource group corresponding to the virtual machine according to the deployment order.

5. The virtual cloud cryptographic resource processing method according to claim 4, characterized in that: When correcting the resource allocation parameters according to the load evaluation value, it includes: Set the correction coefficient k according to the real-time load evaluation value j of the first-level resource group; Correct the resource amount A1 of the first-level resource group according to the correction coefficient; Preset load evaluation value matrix J, set J(J1, J2, J3, J4), where J1 is the preset first load evaluation value, J2 is the preset second load evaluation value, J3 is the preset third load evaluation value, J4 is the preset fourth load evaluation value, and J1 < J2 < J3 < J4; Preset correction coefficient matrix K, set K(k1, k2, k3, k4), where k1 is the preset first correction coefficient, k2 is the preset second correction coefficient, k3 is the preset third correction coefficient, k4 is the preset fourth correction coefficient, and k1 < k2 < 1 < k3 < k4; If j < J1, set the correction coefficient k = k1, and the resource amount A1 of the corrected first-level resource group = k1 * A / m; If J1 < j < J2, set the correction coefficient k = k2, and the resource amount A1 of the corrected first-level resource group = k2 * A / m; If J1 < j < J2, do not set the correction coefficient; If J3 < j < J4, set the correction coefficient k = k3, and the resource amount A1 of the corrected first-level resource group = k3 * A / m; If j > J4, set the correction coefficient k = k4, and the resource amount A1 of the corrected first-level resource group = k4 * A / m.

6. A virtual cloud cryptographic resource processing system, using the virtual cloud cryptographic resource processing method according to any one of claims 1 to 5, characterized in that: It includes: The central control unit, which is used to establish a cloud password resource pool and generate multiple resource groups according to the cloud password resource pool; The resource processing unit, which is used to obtain user demand parameters, generate resource demands according to the user demand parameters, and generate resource allocation parameters according to the resource demands; A resource monitoring unit, wherein a user presets a feedback time node for the resource monitoring unit, and the resource monitoring unit also obtains a real-time load evaluation value of each resource group according to the feedback time node, and modifies the resource allocation parameter according to the load evaluation value.

7. The virtual cloud cryptographic resource processing system according to claim 6, characterized in that: The resource processing unit comprises: The first processing module generates an initial resource requirement d1 according to user demand parameters; A second processing module, wherein the second processing module obtains a user service level e, generates a compensation coefficient n according to the user service level e, and generates a primary resource demand d2 according to the compensation coefficient n; The third processing module is used to establish a demand forecasting model, and generate an expected growth amount d3 of user demand resources according to the demand forecasting model. The third processing module is also used to generate a resource demand d, where d=d2+d3; A fourth processing module, configured to generate a virtual machine according to the resource demand d; The fourth processing module is also used to obtain the virtual machine sequence H of all users, H=(h1,h2,h3...hi), where i is the number of users; generate a deployment sequence according to the virtual machine demand time series; and set the primary resource group corresponding to the virtual machine according to the deployment sequence.

8. The virtual cloud cryptographic resource processing system according to claim 7, characterized in that: The resource monitoring unit comprises: The first monitoring module is used to set a feedback time node; The first correction module is used to set a correction coefficient k according to a real-time load evaluation value j of the primary resource group. The first correction module is also used to correct the resource amount A1 of the primary resource group according to the correction coefficient k.

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