CN118784481A - A strategy management method, system and readable storage medium - Google Patents

Abstract

The invention provides a policy management method, a policy management system and a readable storage medium, and relates to the technical field of communication. The method comprises the following steps: acquiring application data of an application strategy; under the condition that the application data meets the event triggering condition of the meta-strategy, carrying out condition evaluation on the application data according to the execution condition corresponding to the meta-strategy to obtain a condition evaluation result; wherein, the meta-policy is a management rule corresponding to the application policy; and executing management of the application strategy according to the result of the condition evaluation and the strategy decision corresponding to the meta strategy. The scheme of the invention can solve the problems that the existing strategy management technology has no universality and is difficult to carry out deep mining and iterative optimization.

Description

A strategy management method, system and readable storage medium

Technical Field

The present invention relates to the field of communication technology, and in particular to a policy management method, system and readable storage medium.

Background Art

"Self-intelligent network" is born in response to the development of digital society. Through the digital transformation and upgrading of network operation and maintenance itself, it meets the higher requirements of digital products for network experience and agile support, and drives information services to a new level. It aims to build automated and intelligent operation and maintenance capabilities for the entire life cycle of the network, provide consumers and vertical industry customers with "zero waiting, zero failure, zero contact" new network and information and communications technology (ICT) services, and create "self-configuration, self-repair, self-optimization" digital operation and maintenance capabilities for network intelligent operation and maintenance.

The typical feature of self-intelligent network policy management is dynamic decoupling of rules. Operation and maintenance personnel can dynamically edit and import policy rules according to the policy formalization specifications during the system execution phase. This means that the system needs to have the ability to systematically manage policy rules with a larger number, wider sources, and more complex relationships. Furthermore, the typical feature of intelligent self-intelligent network policy management is AI-assisted rule generation, which means that the policy rules themselves need to be automatically iterated through application monitoring and effectiveness evaluation. The typical feature of fully autonomous self-intelligent network policy management is adaptive evolution, which means that policy rules need to dynamically adapt to changes in the internal and external environment of the system and adaptively evolve according to the dynamically evolving system goals. To this end, it is necessary to enhance the standardized formal expression, systematic management, and dynamic evolution capabilities of the self-intelligent network policy management technology system.

Existing policy management technologies are all domain-specific solutions that are too deeply tied to professional domain details, are not universal, and are difficult to deeply explore and iteratively optimize.

Summary of the invention

The purpose of the present invention is to provide a policy management method, system and readable storage medium to solve the problem that the existing policy management technology is not universal and difficult to perform deep mining and iterative optimization.

To achieve the above object, an embodiment of the present invention provides a policy management method, including:

Get application data for application policies;

When it is determined that the application data meets the event triggering condition of the meta-policy, conditional evaluation is performed on the application data according to the execution condition corresponding to the meta-policy to obtain a result of the conditional evaluation; wherein the meta-policy is the management rule corresponding to the application policy;

The application policy is managed according to the result of the condition evaluation and the policy decision corresponding to the meta-policy.

Optionally, performing conditional evaluation on the application data according to the execution condition corresponding to the meta-policy to obtain a result of the conditional evaluation includes:

When condition evaluation is performed on the application data and it is determined that the execution condition corresponding to the meta-policy is satisfied, determining that the result of the condition evaluation is that the execution condition is satisfied;

and/or,

When condition evaluation is performed on the application data and it is determined that the execution condition corresponding to the meta-policy is not satisfied, the result of the condition evaluation is determined as not satisfying the execution condition.

Optionally, the managing the application policy according to the result of the condition evaluation and the policy decision corresponding to the meta-policy includes:

Obtaining a decision result of the application policy according to a result of the condition evaluation and a policy decision corresponding to the meta-policy;

The application policy is managed according to the decision result.

Optionally, the executing management of the application policy includes at least one of the following:

generating an optimization strategy for the application strategy;

updating the application policy;

The application policy is maintained.

Optionally, the policy management method further includes:

External strategies for obtaining external input;

In the case that there is a conflict between the external policy and the application policy, the external policy and the application policy are merged to obtain a merged application policy.

Optionally, the external policy and the application policy are fused to obtain a fused application policy including at least one of the following:

Merging the external strategy and the application strategy to obtain a merged application strategy;

updating the application policy according to the external policy, and determining the updated application policy as the fused application policy;

The external policy is updated and accepted, and the updated external policy is determined as the integrated application policy.

Optionally, the application data of the application policy includes at least one of the following:

Enabling the original application data generated by the application policy;

Monitoring monitoring data generated by the application strategy;

External event information;

External data sources.

Optionally, the policy management method further includes:

Get policy application request;

According to the policy application request, the application policy is matched from a policy knowledge base; or, according to the policy application request, the application policy is generated.

The embodiment of the present invention further provides a policy management system, including:

A collection module is used to obtain application data of application policies;

An evaluation module, configured to, when determining that the application data satisfies the event triggering condition of the meta-policy, perform conditional evaluation on the application data according to the execution condition corresponding to the meta-policy to obtain a result of the conditional evaluation; wherein the meta-policy is a management rule corresponding to the application policy;

A management module is used to manage the application policy according to the result of the condition evaluation and the policy decision corresponding to the meta-policy.

An embodiment of the present invention also provides a policy management system, comprising: a transceiver, a processor, a memory, and a program or instruction stored in the memory and executable on the processor; when the processor executes the program or instruction, the steps of the policy management method described above are implemented.

An embodiment of the present invention further provides a readable storage medium on which a program or instruction is stored. When the program or instruction is executed by a processor, the steps of the policy management method described above are implemented.

The embodiment of the present invention further provides a policy management system, including:

The data domain module is used to send event-triggered notification information to the information domain module when it is determined that the application data of the application policy meets the event triggering condition of the meta-policy; wherein the meta-policy is the management rule corresponding to the application policy;

The information domain module is used to, upon receiving the event trigger notification information, perform conditional evaluation on the application data based on the execution condition corresponding to the meta-strategy, and send the result of the conditional evaluation to the knowledge domain module;

The knowledge domain module is used to manage the application policy based on the result of the condition evaluation and the policy decision of the meta-policy.

Optionally, the data domain module is further used for:

The application data of the application policy is preprocessed, and the preprocessed data is sent to the information domain module.

Optionally, the information domain module is further used for:

When condition evaluation is performed on the application data and it is determined that the execution condition corresponding to the meta-strategy is satisfied, the result of the condition evaluation is sent to the knowledge domain module;

and/or,

When condition evaluation is performed on the application data and it is determined that the execution condition corresponding to the meta-strategy is not satisfied, the result of the condition evaluation not being satisfied is sent to the knowledge domain module.

Optionally, the knowledge domain module includes:

An action decision submodule, used for obtaining a decision result of the application strategy based on the result of the condition evaluation and the strategy decision corresponding to the meta-strategy, and sending the decision result to the strategy fusion submodule;

The policy fusion submodule is used to manage the application policy according to the decision result.

Optionally, the management of the application policy includes at least one of the following:

generating an optimization strategy for the application strategy;

updating the application policy;

The application policy is maintained.

Optionally, the strategy fusion submodule is further used for:

In the case that there is a conflict between the external policy input from the outside and the application policy, the external policy and the application policy are fused to obtain a fused application policy.

Optionally, the strategy fusion submodule is further used for at least one of the following:

Merging the application strategy and the external strategy to obtain a merged application strategy;

updating the application policy according to the external policy, and determining the updated application policy as the fused application policy;

The external policy is updated and accepted, and the updated external policy is determined as the integrated application policy.

Optionally, the policy management system further includes:

The policy management application domain module is used to enable the application policy and send the application data of the application policy to the data domain module and the information domain module.

Optionally, the application data of the application policy includes at least one of the following:

The policy management application domain module enables the original application data generated by the application policy;

The policy management application domain module monitors the monitoring data generated by the application policy;

External monitoring event information of the policy management system;

The policy management system manages external monitoring data sources.

Optionally, the policy management system further includes:

The policy knowledge base is used to store application policies and/or meta-policies corresponding to the application policies.

Optionally, the policy management system further includes:

The policy recommendation submodule is used to provide the policy management application domain module with an application policy that matches the policy application request according to the policy application request of the policy management application domain module.

Optionally, the strategy recommendation submodule is further used to:

In the case where it is determined that there is an application policy matching the policy application request after querying the policy knowledge base, providing the application policy matching the policy application request in the policy knowledge base to the policy management application domain module;

and/or,

When it is determined that there is no application policy matching the policy application request after querying the policy knowledge base, an application policy matching the policy application request is generated, and the generated application policy is provided to the policy management application domain module.

The beneficial effects of the above technical solution of the present invention are as follows:

The policy management method of the embodiment of the present invention obtains application data of the application policy, and when determining the event triggering conditions that meet the meta-policy based on the application data, conditionally evaluates the application data according to the execution conditions corresponding to the meta-policy, and executes management of the application policy according to the results of the conditional evaluation and the policy decision of the meta-policy, thereby realizing status monitoring, effectiveness evaluation and on-demand active iterative update of the application policy by supporting the meta-policy. Compared with the policy management of only field-related specific technologies in the prior art, this solution can realize policy management applied to related technologies in multiple fields based on the optimization and update of the application policy based on the meta-policy, thereby solving the problem that the existing policy management technology is not universal and difficult to perform deep mining and iterative optimization.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a schematic diagram of a basic functional architecture of knowledge management according to an embodiment of the present invention;

FIG2 is a schematic diagram of a functional architecture of active knowledge management according to an embodiment of the present invention;

FIG3 is a flow chart of a knowledge-driven policy management method according to an embodiment of the present invention;

FIG4 is a block diagram of a knowledge-driven policy management system according to an embodiment of the present invention;

FIG5 is a second block diagram of the knowledge-driven policy management system according to an embodiment of the present invention;

FIG6 is a third block diagram of the knowledge-driven policy management system according to an embodiment of the present invention;

FIG. 7 is a schematic diagram of a knowledge-driven policy management system according to an embodiment of the present invention;

FIG8 is a second schematic diagram of the architecture of the knowledge-driven policy management system according to an embodiment of the present invention;

FIG. 9 is a third schematic diagram of the architecture of the knowledge-driven policy management system according to an embodiment of the present invention.

DETAILED DESCRIPTION

In order to make the technical problems, technical solutions and advantages to be solved by the present invention more clear, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

It should be understood that the references to "one embodiment" or "an embodiment" throughout the specification mean that the specific features, structures, or characteristics associated with the embodiment are included in at least one embodiment of the present invention. Therefore, the references to "in one embodiment" or "in an embodiment" appearing throughout the specification do not necessarily refer to the same embodiment. In addition, these specific features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

In various embodiments of the present invention, it should be understood that the size of the serial numbers of the following processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

Additionally, the terms "system" and "network" are often used interchangeably herein.

In the embodiments provided in the present application, it should be understood that "B corresponding to A" means that B is associated with A, and B can be determined according to A. However, it should also be understood that determining B according to A does not mean determining B only according to A, and B can also be determined according to A and/or other information.

As shown in Figure 1, the embodiment of the present invention provides a basic functional architecture for knowledge management. The general basic functional architecture for knowledge management in the self-intelligent network supports the static import, application, mining and updating of knowledge. Specifically, it includes five sub-modules: data processing, information extraction, knowledge generation, knowledge fusion, and knowledge storage. Through the collaborative closed loop of each module, the functions of knowledge import, generation, processing, updating, and application are completed.

Among them, the data processing submodule preprocesses the data provided by the data source (data cleaning, data filtering, etc.), and sends the processed available data to the information extraction submodule of the information domain. The information extraction submodule extracts basic knowledge elements such as entities, attributes and relationships from the data and sends them to the knowledge generation submodule. This process can apply the extraction algorithm, model and other knowledge provided by the knowledge storage. Based on the basic knowledge elements, the knowledge generation submodule completes the correct correspondence with the existing knowledge in the knowledge storage through technologies such as entity linking, generates knowledge, and sends the generated knowledge to the knowledge fusion submodule. This process can apply the generation algorithm, model and other knowledge provided by the knowledge storage. The knowledge fusion submodule compares and merges the input knowledge with the existing knowledge in the knowledge storage to eliminate potential conflicts and inconsistencies. Furthermore, based on the original knowledge of the knowledge storage combined with the new input knowledge, through knowledge reasoning, knowledge mining and other technologies, it combines, infers and creates derivative new knowledge to improve the completeness of knowledge. Knowledge storage realizes the storage and reading functions of knowledge.

Optionally, based on the basic functional architecture of knowledge management, it further supports the status monitoring, effectiveness evaluation and on-demand active iterative update of application knowledge. By superimposing the management functions and interface interactions corresponding to the knowledge application meta-knowledge on each module of the basic functional architecture of knowledge management, including five steps of monitoring data processing (knowledge application report), status information extraction, effectiveness evaluation, updated knowledge generation, and updated knowledge storage, the functions of importing, generating, processing, updating, and applying the corresponding meta-knowledge are completed collaboratively, realizing the extended functions of knowledge management.

As shown in Figure 2, an embodiment of the present invention provides a knowledge active management functional architecture. The knowledge active management functional architecture of the self-intelligent network adds a knowledge recommendation sub-module on the basis of the knowledge management functional infrastructure (supporting the import, application, mining and updating of knowledge), further supports knowledge needs based on the knowledge management application domain, actively mines and recommends new knowledge, and monitors the status of the application of recommended knowledge, evaluates its effectiveness and actively iterates and updates it on demand.

The knowledge recommendation submodule recommends and provides corresponding knowledge based on the knowledge requirements of the knowledge management application domain. When the knowledge recommendation submodule receives a knowledge application request from the knowledge management application domain, it searches for corresponding knowledge in the knowledge storage according to the application requirements.

The embodiment of the present invention provides a policy management method, which is optionally a knowledge-driven policy management method, as shown in FIG3 , and specifically includes the following steps:

Step 31: Obtain application data of the application policy;

Step 32: When it is determined that the application data meets the event triggering condition of the meta-policy, condition evaluation is performed on the application data according to the execution condition corresponding to the meta-policy to obtain a result of the condition evaluation; wherein the meta-policy is a management rule corresponding to the application policy, and is used to make decisions on the management of the application policy;

Step 33: Execute management of the application policy according to the result of the condition evaluation and the policy decision corresponding to the meta-policy.

Optionally, the policy management method in this embodiment can be implemented based on the above-mentioned knowledge management functional architecture, that is, policy management is implemented through knowledge-driven.

Optionally, the application data of the application policy includes at least one of the following: original application data generated by enabling the application policy; monitoring data generated by monitoring the application policy; external event information; external data source. For example, the application policy can be enabled based on a knowledge-driven policy management architecture (also referred to as a policy management system) to generate original application data, or monitor the application policy to generate monitoring data, etc., or an external module of the policy management system can monitor and provide event information and/or data source, etc. The embodiments of the present invention are not limited to this.

Optionally, a meta-policy is a decision rule formulated for a certain application policy, such as deciding when to trigger the management of the application policy, whether the management of the application policy needs to be executed, how to execute the management of the application policy, etc. The embodiments of the present invention are not limited to this.

For example, events may include but are not limited to time events, indicator events, external events, etc. Obtain event-related parameters (such as time, measurement parameters, etc.) in the application data of the application strategy. If the parameters related to the event match the event, it is determined that the event trigger condition is met, otherwise it is determined that the event trigger condition is not met (for example, taking a time event as an example, if the time parameter in the application data meets the time in the event, it is determined that the event trigger condition is met, otherwise it is determined that the event trigger condition is not met; for example, taking an indicator event as an example, if the measurement parameter in the application data meets the indicator of the event (for example, the indicator can be a set threshold, etc.), it is determined that the event trigger condition is met, otherwise it is determined that the event trigger condition is not met, etc.), and the embodiments of the present invention are not limited thereto.

Specifically, the event triggering condition is the triggering condition for the conditional evaluation of the execution of the meta-policy, and the conditional evaluation of the meta-policy is the execution condition of the policy decision. For example, the application policy 1 is "the A-class resource virtual machine will shrink by 40% at 4 pm every day", and the corresponding meta-policy is "once there are two repeated expansions and contractions within 30 minutes after the application of policy 1 is reduced, an oscillation event will be formed. If the above-mentioned oscillation event occurs for more than 4 consecutive days in a week and for more than 2 consecutive weeks in a month, a new optimization policy 1 will be actively generated". Among them, the execution condition is "the above-mentioned oscillation event occurs for more than 4 consecutive days in a week and for more than 2 consecutive weeks in a month", and the policy decision is "actively generate a new optimization policy 1", and the triggering condition of the policy decision is "two repeated expansions and contractions occur within 30 minutes after the application of policy 1 is reduced".

It should be noted that the contents of the application policy and its corresponding meta-policy are all exemplary descriptions. The contents of the application policy applied by the policy management method of the embodiment of the present invention, as well as the event triggering conditions, execution conditions and policy decisions of the meta-policy should not be limited to this.

In this embodiment, by obtaining application data of the application policy, when it is determined that the application data meets the event triggering condition of the meta-policy, the application data is conditionally evaluated according to the execution condition corresponding to the meta-policy, and management of the application policy is performed based on the result of the conditional evaluation and the policy decision of the meta-policy, thereby achieving status monitoring, effectiveness evaluation and on-demand active iterative update of the application policy by supporting meta-policy. Compared with the policy management of only field-related specific technologies in the prior art, this solution can achieve policy management applied to related technologies in multiple fields based on the optimization and update of application policies based on meta-policies, thereby solving the problem that the existing policy management technology is not universal and difficult to perform deep mining and iterative optimization.

It should be noted here that, when it is determined that the application data of the application policy does not meet the event triggering condition of the meta-policy, the condition evaluation and policy decision of the meta-policy will not be executed. For example, the status of the application policy can continue to be maintained (for example: when the application policy is currently in use, the use of the application policy can continue to be maintained, etc.), and the embodiments of the present invention are not limited to this.

Optionally, performing conditional evaluation on the application data according to the execution condition corresponding to the meta-policy to obtain a result of the conditional evaluation includes:

When condition evaluation is performed on the application data and it is determined that the execution condition corresponding to the meta-policy is satisfied, determining that the result of the condition evaluation is that the execution condition is satisfied;

and/or,

When condition evaluation is performed on the application data and it is determined that the execution condition corresponding to the meta-policy is not satisfied, the result of the condition evaluation is determined as not satisfying the execution condition.

Specifically, the result of the condition evaluation may include only the result of satisfying the condition evaluation, that is, the corresponding result of satisfying the condition evaluation is sent only when the application data satisfies the execution condition of the meta-policy. Alternatively, the result of the condition evaluation may include the result of satisfying the condition evaluation or the result of not satisfying the condition evaluation, that is, the corresponding result of satisfying the condition evaluation is sent when the application data satisfies the execution condition of the meta-policy, or the corresponding result of not satisfying the condition evaluation is sent when the application data does not satisfy the execution condition of the meta-policy.

For example, the execution condition may include but is not limited to: the frequency of event occurrence, the duration of the event, the occurrence mode of the event, or a logical combination of at least two of the above. When the event is determined to have occurred based on the judgment of the above event triggering condition, it can be further determined whether the execution condition is met according to the parameters related to the event in the application data (for example, taking a time-type event as an example, if the time parameter in the application data satisfies the frequency of the time in the event and the frequency of the event occurrence that meets the execution condition, it is determined as the result of satisfying the condition evaluation, otherwise it is determined as the result of not satisfying the condition evaluation; for example, taking an indicator-type event as an example, if the measurement parameter in the application data meets the duration of the indicator of the event and the duration of the event that meets the execution condition, it is determined as the result of satisfying the condition evaluation, otherwise it is determined as the result of not satisfying the condition evaluation, etc.), and the embodiments of the present invention are not limited thereto.

Specifically, continuing to take the above-mentioned application strategy 1 and the corresponding meta-strategy as an example, its execution condition is "the above-mentioned oscillation event occurs for more than 4 consecutive days within a week and for more than 2 consecutive weeks within a month". According to the execution condition, the result of the condition evaluation can be obtained, that is: if the oscillation event of repeated expansion and contraction occurs twice within 30 minutes after the Class A resource virtual machine is reduced by 40%, and it occurs for more than 4 consecutive days within a week and for more than 2 consecutive weeks within a month, it is determined that the result of the condition evaluation is met; otherwise, it is determined that the result of the condition evaluation is not met.

Optionally, the managing the application policy according to the result of the condition evaluation and the policy decision corresponding to the meta-policy includes:

Obtaining a decision result of the application policy according to a result of the condition evaluation and a policy decision corresponding to the meta-policy;

The application policy is managed according to the decision result.

Specifically, the decision result includes executing the policy decision or not executing the policy decision. If the decision result is executing the policy decision, the management of the application policy is executed according to the policy decision; if the decision result is not executing the policy result, the management of the application policy can be maintained or the management of the application policy can be executed according to a predetermined processing method, etc. For example: in the case of determining that the result of the condition evaluation is satisfied, the management of the application policy can be executed based on the policy decision of the meta-policy; if the result of the condition evaluation is not satisfied, the processing can be not executed (such as maintaining the application policy) or the predetermined processing can be executed, etc. The embodiments of the present invention are not limited to this.

For example: the policy decision is the management rule for the application policy, such as optimizing the application policy, maintaining the application policy, changing the application policy, etc., and the embodiments of the present invention are not limited to this. The management of the application policy according to the policy decision is executed, that is, it is triggered when the above-mentioned execution conditions are met. Specifically, continuing to take the above-mentioned application policy 1 and the corresponding meta-policy as an example, its policy decision is "actively generate a new optimization strategy 1", that is, based on the result of the conditional evaluation, a new optimization strategy 1 is actively generated (that is, the management of application strategy 1 is to optimize the application strategy 1). Correspondingly, if the result of the conditional evaluation is not met, the plan of actively generating a new optimization strategy 1 will not be executed. For example, the application strategy can be maintained, or other predetermined processing can also be performed, etc., and the embodiments of the present invention are not limited to this.

Optionally, the executing management of the application policy includes at least one of the following:

Generate an optimization strategy for the application strategy; for example, based on the strategy decision of the meta-strategy, optimize the application strategy, and then generate a new strategy.

Updating the application policy; for example: based on the policy decision of the meta-policy, updating the application policy, at this time, a new policy may not be generated, but the original application policy is changed (such as optimization change, etc.).

Maintain the application policy; for example, based on the policy decision of the meta-policy, the original application policy may not be changed, that is, the application policy is maintained.

Optionally, the policy management method further includes:

External strategies for obtaining external input;

In the case that the external policy and the application policy conflict, the external policy and the application policy are merged to obtain a merged application policy. For example, the application policy in step 31 above may be the merged application policy.

The policy management method in this embodiment can support the input of external policies, that is, an external module or a human can input external policies into the policy management system that implements the policy management method. In this way, when there is an external policy input, if the external policy conflicts with the existing application policy of the system, it is necessary to perform fusion processing to avoid the conflict caused by the external input application policy.

Optionally, the external policy and the application policy are fused to obtain a fused application policy including at least one of the following:

The external policy and the application policy are merged to obtain a fused application policy; for example, when there is a conflict between the external policy and the existing application policy of the system, the conflicting policies can be merged to eliminate the conflicting impact.

The application policy is updated according to the external policy, and the updated application policy is determined as the integrated application policy; for example: when the external policy conflicts with the existing application policy of the system, the existing policy of the system can be updated according to the external policy, and the conflict is resolved by changing the existing policy.

The external strategy is updated and accepted, and the updated external strategy is determined as the integrated application strategy; for example, when the external strategy conflicts with the existing application strategy of the system, the external strategy can be updated to ensure that the conflict can be resolved when the system accepts the external strategy.

Optionally, the policy management method further includes:

Get policy application request;

According to the policy application request, the application policy is matched from a policy knowledge base; or, according to the policy application request, the application policy is generated.

Specifically, the policy application request can be used to indicate relevant information of the requested policy, such as the function of the required policy, etc., so that based on the policy application request, the application policy that meets the corresponding requirements is preferentially matched from the policy knowledge base (i.e., the application policies already available in the system). For example: when matching the corresponding application policy from the policy knowledge base, the application policy that fully meets the corresponding requirements can be preferentially matched. If there is no application policy that fully meets the corresponding requirements in the policy knowledge base, the application policy that meets the matching requirements can be selected from the policy knowledge base according to the matching requirements of the requirements. Alternatively, if there is no application policy that fully meets the corresponding requirements in the policy indication library, or there is no application policy that meets the matching requirements, etc., an application policy that fully meets the corresponding requirements or an application policy that meets the matching requirements can also be generated according to the policy application request, and the embodiments of the present invention are not limited to this.

The embodiment of the present invention provides a policy management system, as shown in FIG4 , wherein the policy management system 400 is optionally a knowledge-driven policy management system, specifically including the following modules:

A collection module 410 is used to obtain application data of the application policy;

An evaluation module 420 is used to, when it is determined that the application data meets the event triggering condition of the meta-policy, perform condition evaluation on the application data according to the execution condition corresponding to the meta-policy to obtain a result of the condition evaluation; wherein the meta-policy is a management rule corresponding to the application policy, which is used to decide on the management of the application policy;

The management module 430 is used to manage the application policy according to the result of the condition evaluation and the policy decision corresponding to the meta-policy.

Optionally, the evaluation module 420 includes:

a positive evaluation unit, configured to, when condition evaluation is performed on the application data and it is determined that the execution condition corresponding to the meta-policy is satisfied, determine that a result of the condition evaluation is that the execution condition is satisfied;

and/or,

The negative evaluation unit is used to perform condition evaluation on the application data and determine that the execution condition corresponding to the meta-policy is not satisfied, and then determine the result of the condition evaluation as not satisfying the execution condition.

Optionally, the management module 430 includes:

A decision unit, configured to obtain a decision result of the application policy according to a result of the condition evaluation and a policy decision corresponding to the meta-policy;

An execution unit is used to execute management of the application policy according to the decision result.

Optionally, the executing management of the application policy includes at least one of the following:

generating an optimization strategy for the application strategy;

updating the application policy;

The application policy is maintained.

Optionally, the policy management system 400 further includes:

Input module, an external strategy for obtaining external input;

The fusion module is used to fuse the external policy and the application policy to obtain a fused application policy when there is a conflict between the external policy and the application policy.

Optionally, the performing policy fusion (e.g., conflict resolution) processing on the external policy and the application policy to obtain a fused application policy includes at least one of the following:

Merging the external strategy and the application strategy to obtain a merged application strategy;

updating the application policy according to the external policy, and determining the updated application policy as the fused application policy;

The external policy is updated and accepted, and the updated external policy is determined as the integrated application policy.

Optionally, the application data of the application policy includes at least one of the following:

Enabling the original application data generated by the application policy;

Monitoring monitoring data generated by the application strategy;

External event information;

External data sources.

Optionally, the policy management system further includes:

A receiving module, used for receiving a policy application request;

The processing module is used to match the application policy from a policy knowledge base according to the policy application request; or to generate the application policy according to the policy application request.

The policy management system of the embodiment of the present invention and the above-mentioned policy management method are based on the same inventive concept. The embodiments of the two can refer to each other and can achieve the same technical effect. To avoid repetition, they will not be described here.

A policy management system of another embodiment of the present invention, for example, a knowledge-driven policy management system, as shown in FIG5 , includes a transceiver 510, a processor 500, a memory 520, and a program or instruction stored in the memory 520 and executable on the processor 500; when the processor 500 executes the program or instruction, the steps applied to the policy management method are implemented, and the same technical effect can be achieved. To avoid repetition, they are not described here.

The transceiver 510 is used to receive and send data under the control of the processor 500 .

Wherein, in FIG5, the bus architecture may include any number of interconnected buses and bridges, specifically one or more processors represented by processor 500 and various circuits of memory represented by memory 520 are linked together. The bus architecture may also link together various other circuits such as peripherals, voltage regulators, and power management circuits, which are well known in the art and are therefore not further described herein. The bus interface provides an interface. The transceiver 510 may be a plurality of components, i.e., including a transmitter and a receiver, providing a unit for communicating with various other devices on a transmission medium. The processor 500 is responsible for managing the bus architecture and general processing, and the memory 520 may store data used by the processor 500 when performing operations.

A readable storage medium according to an embodiment of the present invention stores a program or instruction thereon. When the program or instruction is executed by a processor, the steps in the policy management method as described above are implemented and the same technical effect can be achieved. To avoid repetition, it will not be described here.

The processor is the processor in the policy management system described in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

Based on the above knowledge management functional architecture, an embodiment of the present invention provides a policy management system. For example, the policy management system may be a knowledge-driven policy management system. As shown in FIG6 , the policy management system may implement the policy management method in the above embodiment. The system specifically includes:

The data domain module is used to send the event triggering notification information to the information domain module when it is determined that the application data of the application policy meets the event triggering condition of the meta policy; wherein the meta policy is the management rule corresponding to the application policy, which is used to decide the management of the application policy;

The information domain module is used to, upon receiving the event trigger notification information, perform conditional evaluation on the application data based on the execution condition of the meta-strategy, and send the result of the conditional evaluation to the knowledge domain module;

The knowledge domain module is used to manage the application policy based on the result of the condition evaluation and the policy decision of the meta-policy.

Optionally, the application policy can be any existing and applicable policy in the policy management system, and the meta-policy is a decision rule formulated for the application policy, such as deciding when to trigger the management of the application policy, whether it is necessary to execute the management of the application policy, how to execute the management of the application policy, etc.

Optionally, the condition evaluation is to determine whether the application data of the application policy satisfies the corresponding execution condition formulated by the meta-policy based on the application data of the application policy.

Optionally, the policy decision rule is how to perform management on the application policy, that is, a specific way of performing management on the application policy.

Management refers to a set of processes responsible for describing, organizing, controlling access to, and managing the lifecycle requirements of information and organizational entities. Correspondingly, managed entities refer to manageable objects associated with products, services, and/or resources. Management domains refer to domains whose contents are managed using a common set of management mechanisms.

Among them, policy is a set of rules used to manage and control the change and/or maintenance of the state of one or more managed objects. Organizations are policy-driven entities. Policy is a natural way to express behavioral rules and restrictions and then automatically enforce them. The purpose of policy is to ensure that consistent decisions are made to govern the behavior of the system.

Specifically, an imperative policy refers to a type of policy that uses statements to explicitly change the state of a set of target objects. The order of statements that make up the policy is clearly defined. In this document, unless explicitly stated, a policy will refer to a class of imperative policies, namely policies consisting of events, conditions, and operations. Among them, an event refers to anything that occurs on a timeline that is important to the management system (for example, changes to the managed system and/or its environment). A condition refers to a set of attributes, characteristics, and/or values that are compared with a set of known attributes, characteristics, and/or values to determine the decision to be made; or a condition can also be a combination of some characteristics, and the decision to be made is determined based on the characteristics, etc., which is not limited to the embodiments of the present invention. An action refers to a set of operations that can be performed on a set of management entities. It represents a transformation or processing in the system being modeled.

The policy management system of the embodiment of the present invention, when the data domain module determines that the application data of the application policy satisfies the event triggering condition of the meta-policy based on the application policy, sends the event triggering notification information to the information domain module, and when the information domain module receives the event triggering notification information, it performs conditional evaluation on the application data based on the execution condition of the meta-policy, and sends the result of the conditional evaluation to the knowledge domain module, so that the knowledge domain module executes the management of the application policy based on the result of the conditional evaluation and the policy decision rule of the meta-policy, thereby realizing status monitoring, effectiveness evaluation and on-demand active iterative update of policy applications by supporting meta-policies. Compared with the policy management of only field-related specific technologies in the prior art, this solution can realize policy management applied to related technologies in multiple fields based on the optimization and update of application policies based on meta-policies, thereby solving the problem that the existing policy management technology is not universal and difficult to perform deep mining and iterative optimization.

Specifically, an embodiment of the present invention also provides an architectural diagram of a policy management system, as shown in Figure 7, which implements knowledge-driven policy management based on the above-mentioned knowledge management basic functional architecture (supporting static import, application and passive update of policies), and implements status monitoring, effectiveness evaluation and on-demand active iterative updates of policy applications by defining and supporting "meta-policies" in the policy knowledge management domain.

Among them, the data domain module includes a data processing submodule (or event triggering submodule), which is used to monitor the event triggering of the meta-strategy; the information domain module includes an information extraction submodule (or condition evaluation submodule), which is used to determine whether the execution conditions of the meta-strategy are met; the knowledge domain module includes a policy update submodule (or action decision submodule), which is used to make decisions on whether to report abnormalities and update policies. Based on the above basic functional architecture, the management function and interface interaction corresponding to the policy application meta-knowledge are superimposed, so as to achieve policy management. That is, the management function of the policy application meta-knowledge specifically includes the event triggering of the meta-strategy, the condition evaluation of the meta-strategy, and the action decision of the meta-strategy, and cooperates with the policy fusion and policy knowledge base modules to complete the import, generation, processing, update, and application of the corresponding application policy.

In addition, the policy management system can further introduce knowledge-driven business logic based on rules, policies or models in the execution process of each module of the original policy application domain and the policy fusion function module, and the relevant knowledge is uniformly stored in the policy knowledge base.

Specifically, the data domain module is also used for:

The application data of the application policy is preprocessed, and the preprocessed data is sent to the information domain module.

For example, the data domain module (or the data processing submodule therein) preprocesses the policy application monitoring provided by the policy management application domain or other external systems, and sends the processed available data to the information domain module (such as the information extraction submodule therein). The preprocessing may include but is not limited to: data cleaning, data filtering, etc.

Optionally, the policy management system further includes:

The policy management application domain module is used to enable application policies and send application data of the application policies to the data domain module and the information domain module.

Optionally, the application data of the application policy includes at least one of the following:

The policy management application domain module enables the original application data generated by the application policy;

The policy management application domain module monitors the monitoring data generated by the application policy;

External monitoring event information of the policy management system;

The policy management system manages external monitoring data sources.

For example, the original application data for enabling the application policy includes, but is not limited to, various network management data, business data, and environmental data. The monitoring data for monitoring the application policy includes, but is not limited to, performance statistics such as rule/policy application frequency, success rate, and response time. The external monitoring event information or data source of the policy management system includes, but is not limited to, structured data, semi-structured data, and unstructured data. For data with inconsistent formats, format conversion should be performed before collection and processing.

Optionally, the policy management system further includes: a policy knowledge base, used to store application policies and/or meta-policies corresponding to the application policies.

Specifically, the policy knowledge base implements the storage and reading functions of policy knowledge, wherein the policy reading scenarios of the policy knowledge base include at least one of the following:

Respond to policy application requests from various submodules within the policy management system and provide corresponding application policies;

Respond to the policy sharing requirements of external systems and provide corresponding application policies.

Optionally, the above-mentioned data domain module (or the conditional trigger submodule therein) may apply knowledge such as rules and policies provided by the policy knowledge base when performing event or data processing.

Optionally, the information domain module is further used for:

When condition evaluation is performed on the application data of the application policy and it is determined that the execution condition of the meta-policy is satisfied, the result of the condition evaluation is sent to the knowledge domain module;

and/or,

When condition evaluation is performed on the application data of the application policy and it is determined that the execution condition of the meta-policy is not satisfied, the result of the condition evaluation not being satisfied is sent to the knowledge domain module.

The knowledge domain module is also used to:

In the case of receiving a result satisfying the condition evaluation, management of the application policy is performed based on the policy decision of the meta-policy.

Specifically, the result of the condition evaluation may include only the result of satisfying the condition evaluation, that is, the corresponding result of satisfying the condition evaluation is sent only when the application data of the application policy meets the execution condition of the meta-policy. Alternatively, the result of the condition evaluation may include the result of satisfying the condition evaluation or the result of not satisfying the condition evaluation, that is, the corresponding result of satisfying the condition evaluation is sent when the application data of the application policy meets the execution condition of the meta-policy, or the corresponding result of not satisfying the condition evaluation is sent when the application data of the application policy does not meet the execution condition of the meta-policy.

Correspondingly, when the knowledge domain module receives a result that satisfies the conditional evaluation, it manages the application policy based on the policy decision of the meta-policy; if it receives a result that does not satisfy the conditional evaluation, it does not execute any processing or executes a predetermined processing, etc. The embodiments of the present invention are not limited to this.

In this embodiment, the information domain module (or the condition evaluation submodule therein) can evaluate whether the corresponding conditions are met from the events or data according to the execution conditions formulated by the meta-strategy, and send the evaluation results to the knowledge domain module (such as the action decision submodule therein). This process can apply the rules, policies and other knowledge provided by the policy knowledge base.

Optionally, the knowledge domain module includes:

An action decision submodule (or policy update submodule), configured to obtain a decision result of the application policy based on the result of the condition evaluation and the policy decision of the meta-policy, and send the decision result to the policy fusion submodule;

The policy fusion submodule is used to manage the application policy according to the decision result.

Specifically, the knowledge domain module (such as the action decision submodule) can make decisions on whether to report anomalies and update policies based on the policy decision of the meta-policy and the analysis and evaluation results given by the condition evaluation submodule. This process can apply the policy generation algorithm, decision optimization model and other knowledge provided by the policy knowledge base.

Optionally, the management of the application policy includes at least one of the following:

generating an optimization strategy for the application strategy;

updating the application policy;

The application policy is maintained.

Specifically, the policy fusion submodule compares and merges the new policy rules imported or generated from outside the policy management system with the existing policies in the policy knowledge base to eliminate potential conflicts and inconsistencies. Furthermore, based on the original policy rule knowledge in the policy knowledge base and combined with the new input policy rule knowledge, through knowledge reasoning, knowledge mining and other technologies, new policy knowledge is derived and created to improve the completeness of policy knowledge. For example, the policy fusion submodule executes the management of the application policy by generating a new policy (i.e., the second policy) according to the application policy, completing the update of the application policy, or directly updating the application policy when the information domain module indicates that the corresponding execution conditions are met. Alternatively, when the information domain module indicates that the corresponding execution conditions are not met, no processing may be performed, i.e., the application policy is maintained.

The source of new knowledge fused by the strategy fusion submodule specifically includes at least one of the following:

The internal policy rule knowledge is the updated policy rules sent by the action execution (policy knowledge update) submodule of the original policy application domain;

External knowledge includes strategic knowledge imported by experts and strategic knowledge imported from external system strategic knowledge base.

Optionally, the strategy fusion submodule is further used for:

In the case that there is a conflict between the external policy input from the outside and the application policy, the external policy and the application policy are fused to obtain a fused application policy.

Optionally, the strategy fusion submodule is further used for at least one of the following:

Merging the application strategy and the external strategy to obtain a merged application strategy;

updating the application policy according to the external policy, and determining the updated application policy as the fused application policy;

The external policy is updated and accepted, and the updated external policy is determined as the integrated application policy.

The embodiment of the present invention also provides a schematic diagram of the architecture of a policy management system, as shown in FIG8 , which implements knowledge-driven policy management based on the above-mentioned knowledge management basic functional architecture, that is, the policy management system can support static import, application and update of policies. Specifically, it includes a policy fusion submodule and a policy knowledge base. It supports the import, application and passive update of policy knowledge of operation and maintenance experts and external systems.

Optionally, the policy management system further comprises: a policy recommendation submodule, configured to provide the policy management application domain module with an application policy that matches the policy application request according to the policy application request of the policy management application domain module.

Specifically, the policy recommendation submodule recommends and provides corresponding policy knowledge based on the policy knowledge application requirements of the policy management application domain module. When the policy recommendation submodule receives a policy application request from the policy management application domain module, it searches the policy knowledge base for the corresponding policy according to the application requirements.

Optionally, the strategy recommendation submodule is further used to:

When the policy knowledge base is queried to determine whether there is a policy that matches the policy application request, the application policy in the policy knowledge base that matches the policy application request is provided to the policy management application domain module; that is, when the corresponding application policy is queried, the application policy is sent to the policy management application domain module.

and/or,

When the policy knowledge base is queried and it is determined that there is no application policy that matches the policy application request, an application policy that matches the policy application request is generated, and the generated application policy is provided to the policy management application domain module. For example: an application policy that matches the policy application request is determined by policy rule recommendation calculation, and the application policy determined by policy rule recommendation calculation is provided to the policy management application domain module. That is, when the query is empty, a policy rule recommendation calculation is performed to generate a corresponding application policy, and the recommended calculated application policy is sent to the policy management application domain module.

Specifically, an embodiment of the present invention also provides an architectural diagram of a policy management system, as shown in Figure 9, which implements knowledge-driven policy management on the knowledge active management functional architecture, and adds a policy recommendation sub-module on the basis of supporting static import, application, monitoring, analysis and dynamic update of policies, further supports policy requirements based on the policy management application domain, actively mines and recommends new policies, and performs status monitoring, effectiveness evaluation and active iterative update on the application of recommended policies as required.

The functions of the policy management system according to the embodiment of the present invention are described below in conjunction with specific embodiments:

Specifically, the meta-strategy used to monitor, evaluate and dynamically update policies adopts the event-condition-action imperative policy form. The corresponding meta-strategy application domain is composed of an event triggering sub-module, a condition evaluation sub-module and an action decision sub-module to form an automatic closed loop of meta-strategy application for policy management. The following uses the network cloud resource management application scenario to illustrate the information interaction process between various functional modules in different scenarios.

For example, a knowledge base of edge resource pool management policies for a large customer campus in a certain city’s network cloud core network already has a medium priority policy 1, “Class A resource virtual machines shrink by 40% at 4 p.m. every day.”

Solution 1: Input strategy fusion (conflict resolution);

Input: The administrator creates a new high-priority policy 2 - "During the National Day holiday every year, Class A resource virtual machines operate at full capacity."

Step 1: The management expert imports the newly created strategy 2 into the strategy fusion submodule;

Step 2: The policy fusion submodule finds that there is a conflict between policy 1 and policy 2 (such as overlapping time, overlapping scope, and opposite actions) through lexical and grammatical analysis. It further compares the priorities of the two and eliminates the conflict by rewriting the first policy based on the principle that high-priority policies cover low-priority policies; (the rewritten medium-priority policy 1* - "Class A resource virtual machines will be reduced by 40% at 4 pm every day outside the National Day holiday").

Step 3: The policy management application domain module applies to the policy knowledge base to enable all existing policies for Class A resources.

In this solution, the above infrastructure supports static import, application and update of policies. Specifically, it includes policy fusion submodule and policy knowledge base. It supports import, application and passive update of policy knowledge by operation and maintenance experts and external systems.

Option 2: Strategic decision;

Input: The administrator creates a new meta-strategy 3 for the medium-priority strategy 1 - "Once two repeated expansions and contractions occur within 30 minutes after the reduction in strategy 1, an oscillation event occurs. If the above oscillation event occurs for more than 4 consecutive days in a week and for more than 2 consecutive weeks in a month, a new optimization strategy 1 will be actively generated."

Step 1: Management experts store the newly created meta-strategy 3 into the strategy knowledge base through the strategy fusion submodule;

Step 2: The policy management application domain module applies to the policy knowledge base to enable all existing policies for Class A resources.

Step 3: The strategy knowledge base feeds back strategy 1 to the management application domain module for activation. At the same time, the trigger events (i.e., the definition of the occurrence of oscillation events), evaluation conditions (continuous occurrence judgment conditions), action decisions (automatic scaling calculation optimization model) and other knowledge involved in the meta-strategy 3 corresponding to strategy 1 are decomposed and extracted from strategy 3 and published to the corresponding event trigger sub-module, condition evaluation sub-module and action decision sub-module, three knowledge management sub-modules of the "meta-strategy application domain".

Step 4: The knowledge management submodule of the meta-policy application domain parses the meta-policy knowledge published from the policy knowledge base and subscribes to relevant data/information updates from the policy management application domain module and/or the upstream submodule of the "meta-policy application domain".

Step 5: By subscribing to the time record data of the scaling operation of Class A resources to the policy management application domain module, the event trigger submodule can accurately identify and record the occurrence of the oscillation event. By subscribing to the oscillation event notification to the event trigger submodule, the condition evaluation submodule can determine whether it is necessary to actively optimize strategy 1 by comparing the complex logical combination relationship defined in the meta-strategy. The action decision module is responsible for actively generating a new optimization strategy 1** according to the established algorithm when triggered by the condition evaluation module, submitting it to the strategy fusion submodule and storing it in the strategy knowledge base.

In this solution, based on the above basic functional architecture (supporting static import, application and passive update of policies), the status monitoring, effectiveness evaluation and on-demand active iterative update of policy applications are further realized by defining and supporting "meta-policy" in the policy knowledge management domain. By superimposing the management functions and interface interactions corresponding to the meta-knowledge of policy application on the basic functional architecture of policy knowledge management, including three steps of meta-policy event triggering, meta-policy condition evaluation and meta-policy action decision, the corresponding meta-policy import, generation, processing, update and application functions are completed in collaboration with the above-mentioned policy fusion and policy knowledge base modules.

Solution 3: Strategy recommendation;

Input: The policy management application domain submits a policy request for Class A resources during the Mid-Autumn Festival to the policy knowledge base through the policy recommendation submodule.

Step 1: The strategy recommendation submodule queries the strategy knowledge base and finds out that there is no completely matching strategy in the current system;

Step 2: The policy recommendation submodule recommends the most similar policy 2 to the policy management application domain module, creates and adopts a high-priority policy 4 - "During the Mid-Autumn Festival holiday every year, Class A resource virtual machines are fully equipped to operate";

Step 3: The policy management application domain module learns that there is no matching policy and decides whether to adopt the recommended policy 4 as needed.

In the above solution, based on the extended functions of the above infrastructure (supporting static import, application, monitoring, analysis and dynamic update of policies), a new policy recommendation sub-module is added to further support policy requirements based on policy management application domains, actively explore and recommend new policies, and monitor the application status of recommended policies, evaluate their effectiveness and actively iterate and update them as needed.

The above-mentioned policy management system of the embodiment of the present invention plans and manages the operation and maintenance management strategies of various fields, layers and cross-fields of the self-intelligent network, including processes such as policy construction, policy processing, policy sharing, policy application, and policy update, while solving the needs of standardization of policy expression, systematic management of complex policies and dynamic evolution.

In the embodiment of the present invention, the module can be implemented with software so that it can be executed by various types of processors. For example, an executable code module of an identification can include one or more physical or logical blocks of computer instructions, for example, it can be constructed as an object, process or function. Nevertheless, the executable code of the identified module does not need to be physically located together, but can include different instructions stored in different positions, and when these instructions are logically combined together, it constitutes a module and realizes the specified purpose of the module.

In fact, executable code module can be a single instruction or many instructions, and can even be distributed on a plurality of different code segments, distributed among different programs, and distributed across a plurality of memory devices. Similarly, operating data can be identified in the module, and can be implemented and organized in the data structure of any appropriate type according to any appropriate form. The operating data can be collected as a single data set, or can be distributed in different locations (including on different storage devices), and can only be present on a system or network as an electronic signal at least in part.

When a module can be implemented by software, considering the level of existing hardware technology, a person skilled in the art can build a corresponding hardware circuit to implement the corresponding function of the module that can be implemented by software without considering the cost. The hardware circuit includes a conventional very large scale integration (VLSI) circuit or gate array and existing semiconductors such as logic chips, transistors, or other discrete components. The module can also be implemented by a programmable hardware device, such as a field programmable gate array, a programmable array logic, a programmable logic device, etc.

The above exemplary embodiments are described with reference to the accompanying drawings, and many different forms and embodiments are feasible without departing from the spirit and teachings of the present invention. Therefore, the present invention should not be constructed as a limitation of the exemplary embodiments proposed herein. More specifically, these exemplary embodiments are provided so that the present invention will be perfect and complete, and the scope of the present invention will be conveyed to those who are familiar with the technology. In these figures, the component sizes and relative sizes may be exaggerated for clarity. The terms used here are only based on the purpose of describing specific exemplary embodiments and are not intended to be limiting. As used herein, unless the text clearly indicates otherwise, the singular forms "one", "an" and "the" are intended to include these multiple forms. It will be further understood that the terms "including" and/or "comprising" when used in this specification indicate the presence of the features, integers, steps, operations, components and/or components, but do not exclude the presence or increase of one or more other features, integers, steps, operations, components, components and/or their groups. Unless otherwise indicated, when stated, a range of values includes the upper and lower limits of that range and any subranges therebetween.

The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims (18)

1. A method of policy management, comprising:

Acquiring application data of an application strategy;

Under the condition that the application data meets the event triggering condition of the meta-strategy, carrying out condition evaluation on the application data according to the execution condition corresponding to the meta-strategy to obtain a condition evaluation result; wherein, the meta-policy is a management rule corresponding to the application policy;

And executing management of the application strategy according to the result of the condition evaluation and the strategy decision corresponding to the meta strategy.

2. The policy management method according to claim 1, wherein the performing the management of the application policy according to the result of the condition evaluation and the policy decision corresponding to the meta policy includes:

Obtaining a decision result of the application strategy according to the result of the condition evaluation and the strategy decision corresponding to the meta strategy;

and executing management of the application strategy according to the decision result.

3. The policy management method according to claim 1 or 2, wherein said performing management of said application policy comprises at least one of:

generating an optimization strategy of the application strategy;

Updating the application policy;

Maintaining the application policy.

4. The policy management method according to claim 1, further comprising:

acquiring an external strategy of external input;

And under the condition that the external strategy and the application strategy have conflict, carrying out fusion processing on the external strategy and the application strategy to obtain the fused application strategy.

5. The policy management method according to claim 4, wherein the fusing the external policy and the application policy to obtain a fused application policy includes at least one of:

combining the external strategy and the application strategy to obtain a combined application strategy;

Updating the application strategy according to the external strategy, and determining the updated application strategy as the fused application strategy;

and updating and admitting the external strategy according to the application strategy, and determining the updated external strategy as the fused application strategy.

6. The policy management method according to claim 1, wherein the application data of the application policy includes at least one of:

Enabling the original application data generated by the application strategy;

Monitoring data generated by the application strategy;

external event information;

An external data source.

7. The policy management method according to claim 1, further comprising:

Acquiring a policy application request;

according to the policy application request, matching the application policy from a policy knowledge base; or generating the application policy according to the policy application request.

8. A policy management system, comprising:

the acquisition module is used for acquiring application data of the application strategy;

The evaluation module is used for carrying out condition evaluation on the application data according to the execution conditions corresponding to the meta-strategy under the condition that the application data is determined to meet the event triggering conditions of the meta-strategy, so as to obtain a condition evaluation result; wherein, the meta-policy is a management rule corresponding to the application policy;

And the management module is used for executing management of the application strategy according to the result of the condition evaluation and the strategy decision corresponding to the meta strategy.

9. A policy management system, comprising: a transceiver, a processor, a memory, and a program or instructions stored on the memory and executable on the processor; the method according to any one of claims 1 to 7, characterized in that the steps of the policy management method according to any one of claims 1 to 7 are implemented when the program or instructions are executed by the processor.

10. A readable storage medium having stored thereon a program or instructions, which when executed by a processor, implement the steps of the policy management method according to any of claims 1 to 7.

11. A policy management system, comprising:

the data domain module is used for sending the event-triggered notification information to the information domain module under the condition that the application data of the application strategy meets the event trigger condition of the meta-strategy; wherein, the meta-policy is a management rule corresponding to the application policy;

The information domain module is used for carrying out condition evaluation on the application data based on the execution conditions corresponding to the meta-strategy under the condition that the event trigger notification information is received, and sending the result of the condition evaluation to the knowledge domain module;

And the knowledge domain module is used for executing management of the application strategy based on the result of the condition evaluation and the strategy decision of the meta strategy.

12. The policy management system according to claim 11, wherein said data domain module is further configured to:

and preprocessing the application data of the application strategy and sending the preprocessed data to the information domain module.

13. The policy management system according to claim 11, wherein said knowledge domain module comprises:

The action decision sub-module is used for obtaining a decision result of the application strategy based on the result of the condition evaluation and the strategy decision corresponding to the meta strategy, and sending the decision result to the strategy fusion sub-module;

and the policy fusion sub-module is used for executing management of the application policy according to the decision result.

14. The policy management system according to claim 13, wherein said policy fusion submodule is further configured to:

And under the condition that the external strategy input externally conflicts with the application strategy, carrying out fusion processing on the external strategy and the application strategy to obtain the fused application strategy.

15. The policy management system according to claim 14, further comprising:

And the policy management application domain module is used for starting the application policy and sending the application data of the application policy to the data domain module and the information domain module.

16. The policy management system according to claim 15, further comprising:

and the policy knowledge base is used for storing the application policies and/or meta-policies corresponding to the application policies.

17. The policy management system according to claim 16, further comprising:

And the policy recommendation sub-module is used for providing the application policies matched with the policy application requests for the policy management application domain module according to the policy application requests of the policy management application domain module.

18. The policy management system according to claim 17, wherein said policy recommendation sub-module is further configured to:

providing an application policy matching the policy application request in the policy repository to the policy management application domain module if the policy repository is queried to determine that there is an application policy matching the policy application request;

And/or the number of the groups of groups,

And generating an application strategy matched with the strategy application request and providing the generated application strategy for the strategy management application domain module under the condition that the strategy knowledge base is queried to determine that the application strategy matched with the strategy application request does not exist.