Information processing method and apparatus, computer-readable storage medium and device

Abstract

Disclosed in the embodiments of the present application are an information processing method and apparatus, a computer-readable storage medium and a device. The method comprises: on the basis of a general information model and a domain information model which are used for policy management, analyzing a policy instance and / or executing a policy instance, wherein the general information model is used for describing common features of policies in different domains and / or different levels, and the domain information model is used for describing the information related to policy operation environments and / or interactions in each domain.

Description

Information processing method, device, computer-readable storage medium, and apparatus

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application is based on the Chinese patent application with application number 202410007685.6 and application date of January 2, 2024, and claims the priority of the Chinese patent application. The entire content of the Chinese patent application is hereby introduced into this application as a reference. Technical Field

[0003] The present application relates to the field of communication technologies, and in particular to an information processing method, apparatus, computer-readable storage medium, and device. Background Art

[0004] The "Self-Intelligent Network" was born in response to the development of a digital and intelligent society. Through the digital transformation and upgrade of network operations and maintenance itself, it meets the higher requirements of digital products for network experience and agile support, driving information services to a new level. It aims to build automated and intelligent operations and maintenance capabilities throughout the network lifecycle, providing consumers and vertical industry customers with "zero wait, zero failure, zero contact" new network and information and communication technology (ICT) services, and build digital and intelligent operations and maintenance capabilities for "self-configuration, self-repair, and self-optimization" for intelligent network operations and maintenance.

[0005] Rules and policies are key features of self-intelligent networks. Currently, the average level across the entire network is L2. L2 is typically characterized by static rule injection, with policy implementation encompassing an automated closed-loop process of state monitoring, condition analysis, and action execution. Furthermore, self-intelligent networks can be further categorized into L3, L4, and L5 levels. L3 is typically characterized by dynamic decoupling of rules, L4 by artificial intelligence (AI)-assisted rule generation, and L5 by adaptive evolution. Therefore, the self-intelligent network policy management technology system needs to be expanded to enhance policy rule expression, systematic management, and evolutionary capabilities. Summary of the Invention

[0006] To solve the technical problems existing in the related technologies, the embodiments of the present application provide an information processing method, apparatus, computer-readable storage medium and device.

[0007] To achieve the above objectives, the technical solution of the embodiment of the present application is implemented as follows:

[0008] In a first aspect, an embodiment of the present application provides an information processing method, including:

[0009] Policy instances are parsed and / or executed based on a general information model and a domain information model for policy management, wherein the general information model is used to describe the common characteristics of policies in different domains and / or at different levels, and the domain information model is used to describe information related to the policy operating environment and / or interaction of each domain.

[0010] In a second aspect, an embodiment of the present application also provides an information processing device, including an execution module, configured to parse policy instances and / or execute policy instances based on a general information model and a domain information model for policy management, wherein the general information model is configured to describe common characteristics of policies in different domains and / or different levels, and the domain information model is configured to describe information related to each domain and the policy operating environment and / or interaction.

[0011] In a third aspect, an embodiment of the present application further provides a computer-readable storage medium on which a computer program is stored, which implements the steps of the aforementioned information processing method when executed by a processor.

[0012] In a fourth aspect, an embodiment of the present application further provides a computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the aforementioned information processing method when executing the program.

[0013] The information processing method, apparatus, computer-readable storage medium, and device provided in the embodiments of the present application parse policy instances and / or execute policy instances based on general information models and domain information models, and adopt a policy modeling method based on model union. It can separately plan and manage general information models and domain information models related to the policy operation context environment and / or interaction for the operation and maintenance management strategies of various fields, hierarchical, and cross-domains of the self-intelligent network, realize unified policy modeling and flexible on-demand expansion, and enhance systematic management and dynamic evolution capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] FIG1 is a schematic diagram of a flow chart of an information processing method according to an embodiment of the present application;

[0015] FIG2 is a schematic diagram illustrating the relationship between various information elements in a Network Function Virtualization (NFV)-Management and Orchestration (MANO) policy information model according to an embodiment of the present application;

[0016] FIG3 is a schematic diagram of the structure of an information processing device according to an embodiment of the present application;

[0017] FIG4 is a schematic diagram of the structure of a computer device according to an embodiment of the present application. DETAILED DESCRIPTION

[0018] Before introducing the information processing solution of the embodiment of the present application, a brief introduction to the network management related concepts in the related technology is first given.

[0019] Management-related concepts include management, managed entities, and management domains, which are described below.

[0020] Management: The set of processes responsible for describing, organizing, controlling access to, and managing the lifecycle requirements of information and organizational entities.

[0021] Managed entity: A manageable object associated with a product, service and / or resource.

[0022] Administrative domain: A domain that uses a common set of management mechanisms to manage its contents. An administrative domain is a managed entity with three key characteristics: 1) a defined set of administrators who perform management operations on the managed entities it contains; 2) a defined set of applications responsible for different management operations (e.g., monitoring, configuration, etc.); and 3) a defined set of common management mechanisms, such as policy rules, that govern the behavior of the managed entities contained within the administrative domain.

[0023] Concepts related to policies include policies and imperative policies, which are introduced in detail below.

[0024] Policy: A set of rules that governs and controls changes to and / or maintenance of the state of one or more managed objects. Organizations are policy-driven entities, and 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.

[0025] Imperative policies: A type of policy that uses statements to explicitly change the state of a set of target objects. Imperative policies explicitly define the order of statements that make up the policy.

[0026] Model-related concepts include information model and policy model, which are introduced in detail below.

[0027] Information model: Represents concepts relevant to a specific environment in a form that is independent of the data repository, data definition language, query language, implementation language, and protocol.

[0028] Policy Model: In the various embodiments of this application, unless explicitly stated otherwise, policy refers to a class of imperative policies, namely policies composed of events, conditions, and actions. An event is anything that occurs on a timeline that is important to the management system (e.g., a change to the managed system and / or its environment); a condition is a set of attributes, characteristics, and / or values ​​that are compared to a set of known attributes, characteristics, and / or values ​​to determine the decision to be made; and an action is a set of operations that can be performed on a set of management entities, representing a transformation or processing in the system being modeled.

[0029] Among related technologies, rules / policies are important features for improving the capabilities of self-intelligent networks. Currently, the average level of the entire network is L2. The typical feature of L2 is static injection of rules, and the policy implementation includes an automatic closed loop of status monitoring, condition analysis, and execution of actions. Furthermore, self-intelligent networks can be divided into L3, L4, L5, etc. Among them, the typical feature of L3 is dynamic decoupling of rules. Operation and maintenance personnel can dynamically edit and import policy rules according to the formalization of policies 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; the typical feature of L4 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 L5 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.

[0030] It can be seen from this that the self-intelligent network policy management technology system needs to be expanded to achieve standardized formal expression of policy rules, systematic management and dynamic evolution capabilities.

[0031] The present application is further described below in conjunction with the accompanying drawings and specific embodiments. It is apparent that the embodiments described are only a portion of the embodiments of the present application, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments in this application without inventive effort are also within the scope of protection of this application.

[0032] In the description of this application, it should be noted that the terms "first," "second," "third," etc. are used for descriptive purposes only and should not be understood as indicating or implying relative importance. These terms are only used to distinguish one element (or threshold or application or instruction or operation) from another element (or threshold or application or instruction or operation). For example, a first operation can be referred to as a second operation, and a second operation can be referred to as a first operation without departing from the scope of this application. The first operation and the second operation are both operations, but they are not the same operation.

[0033] The term "and / or" in the embodiments of the present application refers to any and all possible combinations of one or more of the associated listed items. It should also be noted that when used in this specification, "include / comprise" specifies the presence of the stated features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements and / or components and / or groups thereof.

[0034] The steps in the embodiments of the present application do not necessarily have to be processed in the order of the described steps. The steps can be selectively rearranged as needed, or the steps in the embodiments can be deleted, or the steps in the embodiments can be added. The step descriptions in the embodiments of the present application are only optional sequence combinations and do not represent all step sequence combinations in the embodiments of the present application. The order of the steps in the embodiments cannot be considered as a limitation of the present application.

[0035] The present invention provides an information processing method. FIG1 is a flow chart of the information processing method according to the present invention. As shown in FIG1 , the method includes:

[0036] Step 101: Parse policy instances and / or execute policy instances based on a general information model and a domain information model for policy management, wherein the general information model is used to describe the common characteristics of policies in different domains and / or different levels, and the domain information model is used to describe information related to the policy operating environment and / or interaction of each domain.

[0037] In this embodiment, both the general information model and the domain information model represent concepts related to a specific environment in a form that is independent of the data repository, data definition language, query language, implementation language, and protocol. The general information model represents the common characteristics of policies across different domains and / or different levels, such as the common characteristics of policies across different management domains, different levels, or across domains and levels. The domain information model represents information related to the policy execution environment and / or interactions within each domain, such as information related to the policy execution context and policy execution context interactions within each management domain.

[0038] In step 101, a policy instance is parsed based on the general information model and the domain information model, and / or a policy instance is executed based on the general information model and the domain information model. In this embodiment, the policy instance is an instance used for policy operation and maintenance management, parsing the policy instance is determining which elements / parameters of the general information model and the domain information model correspond to the policy instance, and executing the policy instance is executing the policy instance by the execution engine corresponding to each domain according to the elements / parameters of the general information model and the domain information model corresponding to the policy instance.

[0039] The information processing method of the embodiment of the present application parses policy instances and / or executes policy instances based on the general information model and the domain information model, that is, adopts a policy modeling method based on model union, which can separately plan and manage the general information model and the domain information model related to the policy operation context environment and / or interaction for the operation and maintenance management strategies of various fields, hierarchical and cross-domains of the self-intelligent network, and realize unified policy modeling and flexible on-demand expansion, thereby enhancing the systematic management and dynamic evolution capabilities.

[0040] In one embodiment of the present application, the general information model may include at least one of intention information, basic information, instruction element information, target range information and expected effect information.

[0041] In this embodiment, the communication information model may include, but is not limited to, intent information, basic information, instruction element information, target scope information, and expected outcome information. For example, intent information may be used to describe the intent of a policy. Intent is a service description method that abstractly defines network requirements and provides a set of expectations about a network or service without specifying specific technical details. Basic information may be used to describe information such as the name, type, source, and version of the policy. Instruction element information may be used to describe information related to policy execution. Target scope information may be used to describe information related to the scope of application of the policy. Expected outcome information may be used to describe information related to evaluating the effectiveness of policy execution.

[0042] In some embodiments, the intent information may include at least one of the following: target domain information indicating the domain to which the policy is applied; object scope information indicating the managed objects to which the policy is applied; and expected effect information indicating the expected effectiveness of policy execution. In this embodiment, the general information model may include, but is not limited to, intent information such as target domain information, object scope information, and expected effect information. The target domain information may be used to describe the domain to which the policy is applied, such as the management domain type and management domain name to which the policy is applied; the object scope information may be used to describe the managed objects to which the policy is applied, such as the instance identifier of the policy application object; and the expected effect information may be used to describe the expected effectiveness of policy execution, such as expected effectiveness indicators.

[0043] As an example, the intent information may be added to the description portion of the general information model.

[0044] In some embodiments, the basic information may include at least one of the following information related to the lifecycle management of the policy: policy name, policy type, policy source, and version information. Exemplarily, the policy name may be a string or identifier used to uniquely identify and accurately reference the corresponding policy model in a specific context; the policy type may be an enumerated value or string used to distinguish different types of directive policies, for example, "ECA" may represent a policy of the "Event-Condition-Action" type, "MEDA" may represent a policy of the "Match-Estimate-Decide-Act" type, etc.; the policy source may be an enumerated value or string used to distinguish directive policies from different sources, for example, "Cloud" represents professional telecom cloud operation and maintenance personnel, "RAN" represents professional wireless operation and maintenance personnel, etc.; the version information may be a string used to specify the update relationship between different versions of the policy. It should be noted that the basic information may not include the policy type or the field corresponding to the policy type is empty, and the default value is the default type, such as the "ECA" type; the basic information may not include the policy source or the field corresponding to the policy source is empty, and the default value is the default value, such as "NULL (which can represent empty)".

[0045] Taking the common information element Policy as an example, Table 1 is an exemplary description of the parameters related to the basic information contained in the common information model in the common information element Policy. The "Parameter" column in Table 1 indicates the parameters contained in the information element; the "Qualifier" column indicates whether the corresponding parameter can be supported by the system, where "M" indicates mandatory support and "O" indicates optional support; the "Cardinality" column indicates the multiplicity of the corresponding parameter (i.e., the cardinality "how much" and the selectivity "may or must"), where "1" indicates only one (the corresponding parameter is required), "0..1" indicates zero or one (the corresponding parameter is optional), "1..N" indicates 1 to N (N>1) (the corresponding parameter can be repeatedly defined), and "0..N" indicates zero to N (N>1) (the corresponding parameter can be repeatedly defined); the "Content" column indicates the data type of the corresponding parameter, where "String" indicates a string and "Enum" indicates an enumeration type; the "Description" column indicates the description information of the corresponding parameter.

[0046] As shown in Table 1, the value of the parameter policyFunctionName can describe the function or name of this policy, such as scaling, self-healing, virtual resource optimization, etc., and the value type is a string; the value of the parameter policyFlavour can describe the type of the policy, and the value range can include {ECA, OODA, MEDA, Other}, where ECA represents the event-condition-action policy type, OODA represents the observe-orient-decide-act (Observe-Orient-Decide-Act) policy type, MEDA represents the match-evaluate-decision-action policy type, and Other represents other policy types; the value of the parameter policySource can describe the source of the policy, and the value type is a string; the value of the parameter policyVersion can describe the version information of the policy, etc., and the value type is a string.

[0047] Table 1

[0048] In some embodiments, the instruction element information may include one or more logical units describing policy execution. Exemplarily, the logical units are used to describe trigger events, evaluation conditions, action decisions, etc. for policy execution, wherein the trigger events can be referenced by the corresponding model in the domain information model of a specific domain to specify the set of directive policy trigger events and their combination methods; the evaluation conditions can be referenced by the corresponding model in the domain information model of a specific domain to specify the set of conditions required to be evaluated for directive policy action decisions and their combination methods; the action decisions can be referenced by the corresponding model in the domain information model of a specific domain to determine the specific operations or actions to be performed based on the trigger events and the evaluation conditions, which can be used to change or maintain the specific state of the managed object.

[0049] Taking a meta-policy in the form of an ECA imperative policy as an example, this meta-policy is used to monitor, evaluate, and dynamically update policies. The corresponding meta-policy application domain consists of three sub-modules: event triggering, condition evaluation, and action execution, forming the automatic closed loop of the meta-policy's application to policy knowledge management. Taking the construction of this meta-policy using information elements as an example, parameters related to the instruction element information contained in the general information model include, but are not limited to, policy elements (which can be expressed as Policy in English), state elements (which can be expressed as State in English), task elements (which can be expressed as Task in English), context set elements (which can be expressed as ContextMap in English), and context elements (which can be expressed as Context in English). These are introduced below based on Tables 2.1 through 2.5.

[0050] Table 2.1 is an exemplary description of the parameters related to the instruction element information in the policy element. In the "Content" column of Table 2.1, "ContextMap" indicates that the corresponding parameter value is a context collection element, and "State" indicates that the corresponding parameter value is a state element. As shown in Table 2.1, the value of the parameter globalContext can describe the execution elements reflected by the system context when the policy is executed, such as the relevant system variables of the event / condition / action required for the execution of the ECA policy, the access interface of the service interface, access parameters, access rights, etc., and the value type is a context collection element. The value of the parameter firstState can describe the first state of the policy execution, such as the event (which can be expressed as Event in English) state of the ECA policy, and the value type is a state element.

[0051] Table 2.1

[0052] Table 2.2 is an exemplary description of the parameters related to the instruction element information in the state element. In Table 2.2, "Identifier" in the "Content" column indicates that the corresponding parameter value is an identifier, "Enum" indicates that the corresponding parameter value is an enumeration type, "Task" indicates that the corresponding parameter value is a task element, and "Logic" indicates that the corresponding parameter value is a logic element. As shown in Table 2.2, the value of the parameter stateType can represent the type of policy state, and should be selected based on the parameter policyFlavour contained in the information element Policy shown in Table 1. The value type of the parameter stateType is an enumeration type, and the value range may include {Event, Condition, Action, Other}, where Event represents an event, Condition represents a condition, Action represents an action, and Other represents other state types; the value of the parameter taskItem can describe the information of each task contained in the current state, where each state (which can be expressed as state in English) contains at least one task (which can be expressed as task in English), and the value type is Task; the value of the parameter taskSelectionLogic is used to describe the selection logic of how to select a task from the state to complete this state migration based on the current context when the state contains more than one task, and the value type is Logic; the value of the parameter nextState can describe the identifier of the next state.

[0053] Table 2.2

[0054] Table 2.3 is an exemplary description of the parameters related to the instruction element information in the task element. As shown in Table 2.3, the value of the parameter taskType can describe the task type. When the policy type is ECA type, the value range is {EventTask, ConditionTask, ActionTask, Other}, where EventTask represents an event task, ConditionTask represents a conditional task, ActionTask represents an action task, and Other represents other task types; the value of the parameter taskInput can represent the input parameter of the task, and the value type is a context set. When taskType is EventTask, the value of the parameter taskInput can describe the policy triggering event, such as various alarms, prompts, reports, and other events that the NFV-MANO component can collect / feedback / receive; the value of the parameter taskLogic is used to describe the calculation logic of how to obtain the output taskOutput from the task input taskInpu based on the context; the value of the parameter taskOutput can be used to describe the output result of the task. When taskType is ActionTask, taskOutput is used to describe the policy execution action.

[0055] Table 2.3

[0056] Table 2.4 provides exemplary descriptions of parameters related to instruction elements within a context collection element. The "Context" column in Table 2.4 indicates that the corresponding parameter value is a context element. As shown in Table 2.4, the value of the mapName parameter describes the function of the context collection element; the value of the contextItem parameter describes the specific context variables contained within it, and its value type is a context element.

[0057] Table 2.4

[0058] Table 2.5 is an exemplary description of the parameters related to the instruction element information in the context element. As shown in Table 2.5, the value of the parameter contextName can describe the function of the context element; the value of the parameter contextAccess can describe the access address of the context element; the value of the parameter contextParameter can describe the access parameters of the context element, for example, it can be a set of key-value pair (KVP, KeyValuePair) sequence requirements, where the key value is the parameter name and the value is the access input parameter of the context.

[0059] Table 2.5

[0060] In some embodiments, the target scope information may include one or more domains and / or managed objects that describe the scope of policy application. Exemplarily, the domain of the policy application scope may reference a corresponding model in a domain information model of a specific domain to uniquely identify and accurately reference a specific management domain used by the policy model in a specific context. The managed objects of the policy application scope may reference a corresponding model in a domain information model of a specific domain to uniquely identify and accurately reference a specific set of managed objects in the management domain used by the policy model in a specific context.

[0061] Taking the Policy information element as an example, parameters related to target scope information in the Policy information element include, but are not limited to, the management domain identifier (domainID), the management domain type (domainType), the managed object identifier (objectID), and the managed object type (objectType). When the relevant attributes are not present, the policy's target scope may default to the entire system (all domains / managed objects).

[0062] Table 3 is an exemplary description of parameters related to target scope information in the information element Policy. As shown in Table 3, the value of the parameter targetDomainType can describe the type of management domain to which the policy is applied. In this embodiment, the names and meanings of all management domains should be uniformly planned by the network operator based on the actual production network. For example, they can be combined based on geographical areas, professional fields, computer room identifications, equipment types, etc. The default value can be the current management domain. The value range of the parameter targetDomainType can include {RAN, TN, CN, NFV-MANO, Other}, where RAN represents the access network, TN represents the transmission network, CN represents the core network, NFV-MANO represents the network function virtualization management and orchestration, and Other represents other management domains; the parameter targetDomainType The value of inID can describe the identifier of the management domain to which the policy is applied; the value of the parameter targetObjectType can describe the type of the managed object to which the policy is applied, which may depend on the type of management domain. Different management domain types correspond to different managed object types. For example, when the management domain value is "RAN", the value of the managed object type may include "base station", "cell", "link" or others; the value of the parameter targetObjectID can describe the instance identifier of the managed object to which the policy is applied. In this embodiment, the names and meanings of all managed objects should be uniformly planned by the network operator based on the actual production network. For example, the equipment number in the unified resource management system can be obtained by combining the geographical area, professional field, computer room identification, equipment type, equipment identification, etc. The default value can be all managed objects in the current management domain.

[0063] Table 3

[0064] In some embodiments, the expected performance information may include one or more metrics that describe the effect of the policy application. Exemplarily, the metrics are functional indicators, performance indicators, availability indicators, etc. that describe the effect of the policy application, wherein the functional indicators can be used to describe the set of functional indicators and their combinations that the policy application expects to achieve by referencing the corresponding model in the specific management domain extension model, and the modeling method of the evaluation conditions in the reusable instruction element information. The performance indicators can be used to describe the set of performance indicators and their combinations that the policy application expects to achieve by referencing the corresponding model in the specific management domain extension model, and the modeling method of the evaluation conditions in the reusable instruction element information. The availability indicators can be used to describe the set of availability indicators and their combinations that the policy application expects to achieve by referencing the corresponding model in the specific management domain extension model, and the modeling method of the evaluation conditions in the reusable instruction element information.

[0065] Taking the Policy information element as an example, Table 4.1 provides exemplary descriptions of parameters related to expected performance information in the Policy information element. As shown in Table 4.1, the parameters related to expected performance information in the Policy information element include, but are not limited to, funcExpectation, perfExpectation, and stabExpectation. The value of the funcExpectation parameter describes the expected functional indicators of the policy application, the value of the perfExpectation parameter describes the expected performance indicators of the policy application, and the value of the stabExpectation parameter describes the expected availability indicators of the policy application.

[0066] Table 4.1

[0067] The aforementioned parameters, funcExpectation, perfExpectation, and stabExpectation, can be used to describe the expected indicator evaluation conditions for policy applications through the use of logic elements (logic) in the domain information model. Table 4.2 provides exemplary descriptions of parameters related to expected performance information within logic. As shown in Table 4.2, the value of the parameter logicName describes the function of the logic, the value of the parameter logicDsl describes the domain-specific language that implements the logic element, such as Shell, Python, or Java, and the value of the parameter logicCode describes the logic code implemented using the programming language specified by the parameter logicDsl.

[0068] Table 4.2

[0069] In one embodiment of the present application, the domain information model may include at least one of the following: a domain information model corresponding to each domain and related to instruction element information; a domain information model corresponding to each domain and related to expected outcome information; and a domain information model corresponding to each domain and related to target range information. In this embodiment, the domain information model may include, but is not limited to, three types of domain information models: a domain information model corresponding to each domain and related to instruction element information, a domain information model corresponding to each domain and related to expected outcome information, and a domain information model corresponding to each domain and related to target range information.

[0070] In some embodiments, the domain information model associated with instruction element information can be used to provide information element definitions related to policy execution. Exemplarily, the domain information model associated with instruction element information is used to provide all specific information element definitions related to instruction element information that are well-defined and confidently executable in various domains, such as specific information element definitions related to trigger events, evaluation conditions, and action decisions.

[0071] In some embodiments, the domain information model related to expected outcome information is used to provide information element definitions related to policy application effectiveness evaluation. Exemplarily, the domain information model related to expected outcome information is used to provide well-defined and executable specific information element definitions related to all expected outcome information in various domains, such as specific information element definitions related to policy application functional indicators, performance indicators, available indicator sets, and combinations thereof.

[0072] In some embodiments, the domain information model related to target scope information is used to provide information element definitions related to the policy application scope. Exemplarily, the domain information model related to target scope information is used to provide all specific information element definitions related to object scope information that are well-defined in various domains and are believed to be interoperable through the current policy management application domain, such as specific information element definitions related to the management domain and / or the set of managed objects to which the policy is applied.

[0073] The information processing method of the embodiment of the present application adopts a policy modeling method based on model union, which can separately plan and manage the general information model and the domain information model for the operation and maintenance management strategies of various fields, hierarchies and cross-domains of the self-intelligent network, and realize unified modeling of strategies and flexible on-demand expansion; at the same time, the intent information can be extended in the general information model, and policy modeling extension information for target domain information (such as management domain), object scope information (such as managed objects), and expected effect information (such as performance indicators, etc.) can be added, which can provide a formal description and registration and interaction mechanism for distributed policy modeling elements (such as trigger events, action execution, condition evaluation), so as to provide reference indicators for the applicability and feasibility evaluation of policy applications required for dynamic automatic iteration and adaptive evolution of policy management.

[0074] As an implementation method, the method may further include: obtaining capability information corresponding to all fields, the capability information being used to determine the field information model; the capability information including at least one of the following: information element definitions, code implementations and service interfaces corresponding to instruction element information of each field; information element definitions, code implementations and service interfaces corresponding to expected performance information of each field; information element definitions, code implementations and service interfaces corresponding to target scope information of each field.

[0075] In this embodiment, the capability registration corresponding to instruction element information, expected results information, target range information, etc. in each field can also be realized. For example, the sub-management domain can register capabilities to the superior management domain step by step, or the global centralized registration capability can be adopted.

[0076] Exemplarily, capability information related to instruction element information can be used to provide all specific information element definitions, code implementations, service interfaces, etc. related to instruction element information that have been well defined and are believed to be executable in the corresponding management domain, such as information element definitions, code implementations, service interfaces, etc. that describe trigger events, evaluation conditions, action decisions, etc.; capability information related to expected performance information can be used to provide all specific information element definitions, code implementations, service interfaces that have been well defined and are believed to be executable in the corresponding management domain, such as information element definitions, code implementations, service interfaces that describe functions, performance, available indicator sets and their combinations; capability information related to target scope information can be used to provide all specific information element definitions, code implementations, service interfaces for all management domains / managed object sets that have been well defined in the corresponding management domain and are believed to be able to be connected to the management domain through policy application.

[0077] Based on the aforementioned embodiment, the embodiment of the present application further provides an information processing method. In this embodiment, the parsing of policy instances and / or executing policy instances based on the general information model and domain information model for policy management may include: determining a domain model instance based on the domain information model, and updating the description portion of the general information model contained in the policy instance; the domain model instance is used to provide the context environment and / or context interaction information for the operation of the policy instance; and parsing the policy instance and / or executing the policy instance based on the updated general information model and the domain model instance.

[0078] In this embodiment, the domain model instance corresponding to the policy instance can be determined based on the information element definition related to policy execution (i.e., the domain information model related to instruction element information), the information element definition related to policy application effect evaluation (i.e., the domain information model related to expected effectiveness information), and the information element definition related to the policy application scope (i.e., the domain information model related to target scope information) provided by the domain information model; at the same time, the description part of the model constructed using the general information model in the policy instance can be updated; and the policy instance can be parsed and / or executed based on the updated general information model and domain model instance.

[0079] Exemplarily, information related to the policy source, policy version, policy application management domain, policy application managed objects, expected policy results, etc. may be added to the description part.

[0080] In some embodiments, updating the description portion of the general information model contained in the policy instance may include: obtaining the intent of the policy; adding corresponding intent information in the description portion of the general information model based on the intent, the intent information including at least one of the following: target domain information representing the domain of policy application, object scope information representing the managed objects of policy application, and expected effect information representing the expected results of policy execution.

[0081] In some embodiments, parameters related to target domain information, object range information, expected effect information, etc. can be added to the information element Policy shown in Table 1, such as parameters describing the management domain type, parameters describing the management domain identifier, parameters describing the managed object type, parameters describing the managed object identifier, parameters describing the expected functional indicators, parameters describing the expected performance indicators, parameters describing the expected availability indicators, etc.

[0082] In this embodiment, the description model of the existing directive policy can be expanded based on intent in the general information model, and extended information for the target (such as the management domain), the scope of application of the policy (such as the managed object), and the expected effect (such as the performance indicator) can be added. On the one hand, it provides background knowledge for the identification and resolution of potential policy conflicts required for the systematization of policy management. On the other hand, it provides reference indicators for the monitoring and evaluation of the applicability, feasibility and effectiveness of policy applications required for the dynamic automatic iteration and adaptive evolution of policy management.

[0083] In one embodiment of the present application, the policy instance parsing and / or execution policy instance based on the updated general information model and the domain information model may include: information elements related to at least one of instruction element information, target range information and expected performance information contained in the corresponding policy instance parsed based on the general information model; parameter values ​​of the information elements contained in the corresponding policy instance parsed based on the domain information model.

[0084] For example, referring to Tables 2.1 to 2.5 above, information elements related to instruction element information may include policy elements, status elements, task elements, context set elements and context elements, etc. Referring to Table 3, elements related to target range information may include parameters targetDomainType, targetDomainID, targetObjectType, targetObjectID, etc. in the information element Policy, and referring to Tables 4.1 to 4.2, information elements related to expected performance information may include parameters funcExpectation, perfExpectation, stabExpectation, etc. in the information element Policy.

[0085] In some embodiments, the domain model instance includes a first model instance corresponding to the context element and / or a second model instance corresponding to the logical element; parsing the policy instance and / or executing the policy instance based on the updated general information model and the domain model instance may include: determining the parameters of the context element by referencing the first model instance, and / or determining the parameters of the logical element by referencing the second model instance; parsing the policy instance and / or executing the policy instance based on the parameters of the context element and / or the parameters of the logical element.

[0086] For example, the parameters funcExpectation, perfExpectation, stabExpectation, and the taskLogic parameter in the task element can be determined by using the corresponding logic elements in the domain information model to determine their corresponding parameter values. The parameters contextItem in the context collection element can be determined by using the corresponding context elements in the domain information model to determine their corresponding parameter values. Thus, context elements and logic elements can be used to achieve a combination of the general information model and the domain information model.

[0087] In one embodiment of the present application, the information elements related to the instruction element information include at least one of the following: a state element, which is used to describe the state information of the policy from triggering to execution; a task element, which is used to describe the information of each task that the policy engine needs to perform in each state; and a logic element, which is used to describe the processing logic of the policy execution engine to perform each task. In this embodiment, the logic element (Logic) can be used by the policy execution engine to parse and execute policy tasks. Each management domain can directly use the context element (Context) to define the specific instance of each domain interaction context as needed, and use the Logic information element to define the specific logical instance of the domain policy task using a domain-specific language. The state element and the task element can be referred to as shown in Table 2.2 and Table 2.3. To save space, they will not be repeated here.

[0088] In one embodiment of the present application, the information elements related to the instruction element information included in the domain information model further include at least one of the following: a context element for describing the input and output context of each policy element, state element, or task element; and a context collection element for describing each context element. In this embodiment, the Context element can be used for execution context modeling of the general information model corresponding to the policy modeling. For details, please refer to Table 2.5. To save space, it is not further described here.

[0089] In one embodiment of the present application, adding corresponding intent information to the description part of the general information model based on the intent includes: updating the description part based on the intent, and the updated description part includes at least one of the following: parameters for describing the domain type of policy application; parameters for describing the domain identifier of policy application; parameters for describing the managed object type of policy application; parameters for describing the managed object identifier of policy application; parameters for describing the expected results of policy execution.

[0090] For example, new parameters such as targetDomainType, targetDomainID, targetObjectType, targetObjectID, and Expectations may be added to the information element Policy shown in Table 1, wherein the value of the parameter targetDomainType may describe the type of domain to which the policy is applied, the value of the parameter targetDomainID may describe the identifier of the domain to which the policy is applied, the value of the parameter targetObjectType may describe the type of managed object to which the policy is applied, the value of the parameter targetObjectID may describe the identifier of the managed object to which the policy is applied, and the value of the parameter Expectations may describe the expected results of the policy execution.

[0091] The information processing scheme of the embodiment of the present application is described below in conjunction with specific application scenarios.

[0092] Figure 2 is a schematic diagram illustrating the relationship between the various information elements in the NFV-MANO policy information model according to an embodiment of the present application. As shown in Figure 2, the general information model in the NFV-MANO policy information model includes the information elements Policy, State, and Task, and the domain information model includes the information elements Context, ContextMap, and Logic. The Policy information element can reference the ContextMap information element via the parameter localContext; the ContextMap information element can be associated with the Context information element; the State information element can reference the Logic information element via the parameters taskSelectionLogic and stateFinalizerLogic; and the Task information element can reference the ContextMap information element via the parameters taskInput / taskOutput and the parameter taskLogic.

[0093] The following Tables 5.1 to 5.6 respectively introduce the information elements Policy, State, Task, Logic, ContextMap, and Context.

[0094] Table 5.1 provides an example description of the parameters included in the Policy information element in this example. As shown in Table 5.1, the Policy information element is a deployment template that describes the deployment of a policy. It contains the basic information required for a policy and information about the policy's constituent items. The value of the policyFunctionDescription parameter describes the policy's functionality, such as scaling, self-healing, and virtual resource optimization. The value of the policyFlavour parameter describes the policy's expression, such as ECA, OODA, or MEDA. The value type is an enumeration with a range of {ECA, OODA, MEDA, Other}, where "Other" indicates other expression forms of the policy besides ECA, OODA, and MEDA. The value of the targetType parameter describes the policy's scope. If the policy is universal and applies to all managed objects, the value can be Common. If the policy applies only to specific managed objects, the value can be Specific. The value of the firstState parameter specifies the first state of policy execution, such as the Event state for an ECA policy. The value of the globalContext parameter describes the global context of policy execution, such as the access interfaces, parameters, and permissions for system variables, service interfaces, and events / conditions / actions required for ECA policy execution. The value of the localContext parameter describes the internal context of policy execution, used for variable transfer and parameter sharing between different states / tasks. For example, when executing an ECA policy, the specific results of conditional evaluation serve as branch conditions for selecting the specific action to execute.

[0095] Referring to Table 5.1, this embodiment may extend the information element Policy by adding parameters policySource, policyVersion, targetDomainType, targetDomainID, targetObjectType, targetObjectID, and expectations. The value of the policySource parameter may describe the policy source, and the value of the policyVersion parameter may describe the policy version information.

[0096] The value of the targetDomainType parameter describes the policy application management domain type. In this example, the names and meanings of all management domains should be centrally planned by the network operator based on the actual production network. For example, they can be jointly assigned based on geographic region, professional field, equipment room identifier, equipment type, and other combinations. The default value can be the current management domain. For example, the value range is {RAN, TN, CN, NFV-MANO, Other}, where RAN represents the access network, TN represents the transport network, CN represents the core network, NFV-MANO represents the Network Function Virtualization Manager and Orchestrator, and Other represents other management domain types. The value of the targetDomainID parameter describes the policy application management domain identifier.

[0097] The value of the parameter targetObjectType describes the type of managed object to which the policy is applied. This parameter depends on the management domain type; that is, different management domain types correspond to different managed objects. For example, when the management domain type is "RAN," the range of managed object types can be {base station, cell, link, other}. Alternatively, when the management domain type is "NFV-MANO," the range of managed object types can be {NS, VNF, VNFC, VR, Other}, where NS represents network service, VNF represents virtual network function, VNFC represents virtual network function component, VR represents virtual resource, and Other represents other managed object types. The value of the parameter targetObjectID describes the instance identifier of the object to which the policy is applied. When targetType is Specific, this parameter targetObjectID is mandatory and defaults to all managed objects in the current management domain. In this example, the names and meanings of all managed objects should be uniformly planned by the network operator based on the actual production network. For example, the device ID in the unified resource management system can be obtained by combining geographical region, professional area, equipment room ID, device type, device ID, and other combinations thereof.

[0098] The value of the expectations parameter can describe the expected indicators of policy application, including but not limited to indicators such as function, performance, and availability.

[0099] Table 5.1

[0100] The information element State describes the specific state of the policy from triggering to execution. In the context of ECA policy expressions, events, conditions, and actions are three examples of states, which can be expressed by the common parameters of this information element. Table 5.2 is an exemplary description of the parameters included in the information element State in this example. As shown in Table 5.2, the value of the parameter stateType can describe the type of policy state; the value of the parameter taskItem can describe the information of each task contained in the current state; the value of the parameter taskSelectionLogic can describe the selection logic of how to select a task from the state to complete the current state migration based on the current context when the state contains more than one task; the value of the parameter nextState can describe the identifier of the next state.

[0101] Table 5.2

[0102] The information element Task expresses the specific information of each task that the policy state requires the policy engine to execute. In the context of an ECA policy expression, multiple event sub-entries under events, multiple condition sub-entries under conditions, and multiple action sub-entries under actions can all be expressed by the parameters of this information element. Table 5.3 shows an exemplary description of the parameters included in the information element Task in this example. As shown in Table 5.3, the value of the parameter taskType can describe the task type; the value of the parameter taskInput can describe the input parameters of the task. When taskType = EventTask, taskInput is used to describe the policy triggering event, that is, the various alarms, prompts, reports, and other events that the NFV-MANO component can collect / feedback / receive; the value of the parameter taskLogic can describe the calculation logic of how to obtain the output taskOutput from the task input taskInput based on the context; the value of the parameter taskOutput can describe the output result of the task. When taskType = ActionTask, taskOutput is used to describe the policy execution action.

[0103] Table 5.3

[0104] The information element Logic is used to support the description of various types of processing logic. Table 5.4 shows an example description of the parameters included in the information element Logic in this example. As shown in Table 5.4, the value of the parameter logicName can describe the logic function; the value of the parameter logicDsl can describe the domain-specific language of the logic, such as Shell, Python, Java, etc.; and the value of the parameter logicCode can describe the logic code implemented in the programming language specified by logicDsl.

[0105] Table 5.4

[0106] The ContextMap information element is used to support the description of the input and output contexts of various policies, states, and tasks. Table 5.5 shows an example description of the parameters included in the ContextMap information element in this example. As shown in Table 5.5, the value of the mapName parameter describes the function of the context set (which can be expressed as "map" in English); the value of the contextItem parameter describes the specific context variables included (such as the Context information element).

[0107] Table 5.5

[0108] Table 5.6 is an exemplary description of the parameters included in the information element Context in this example. As shown in Table 5.6, the value of the parameter contextName can describe the function of the context element (context); the value of the parameter contextAccess can describe the access address of the context; the value of the parameter contextPara can describe the access parameters of the context, such as a set of KVP key-value pair sequence requirements, where the key value is the parameter name and the value is the access input parameter of the context.

[0109] Table 5.6

[0110] Taking the NFV-MANO policy information model shown in Figure 2 as an example to construct a specific policy instance, it is assumed that the operation and maintenance personnel expect to use a simple automatic scaling policy to achieve the expected goal of ensuring that the VNF utilization efficiency in the computer room is less than 60% (that is, the intention of the policy).

[0111] In an embodiment of the present application, the relationship between the various information elements in an NFV-MANO automatic scaling (which can be expressed as "scaling" in English) policy can be as follows: Context and Logic information elements in the public model are used to realize the union of the general information model and the domain information model in this example. Specifically, Context is used to model the execution context of the policy modeling public model, and Logic is used by the policy execution engine to parse and execute policy tasks. Each management domain can directly use the Context information element to define a specific instance of the domain interaction context as needed, and use the Logic information element and a domain-specific language to define a specific logical instance of the domain policy task.

[0112] The following describes the parameter values ​​of each information element in conjunction with Tables 6.1 to 6.11.

[0113] Table 6.1 shows the specific values ​​of the parameters in the information element Policy of this example. As shown in Table 6.1, the value of the parameter firstState is EventState, which can be specifically adopted from the information element State shown in Table 5.2. The specific value of the information element EventState can be referred to in Table 6.2; the value of the parameter nextState in the information element EventState is ConditionState, which can also be adopted from the information element State shown in Table 5.2. The specific value of the information element ConditionState can be referred to in Table 6.3; the value of the parameter nextState in the information element ConditionState is ActionState, which can also be adopted from the information element State shown in Table 5.2. The specific value of the information element ActionState can be referred to in Table 6.4; the value of the parameter nextState in the information element ActionState is NULL (empty).

[0114] Table 6.1

[0115] Table 6.2 shows the specific values ​​of the parameters in the information element EventState of this example. Referring to Table 6.2, the information element EventState can reference the information element EventTask through the parameter taskItem. The information element EventTask can specifically adopt the information element Task shown in Table 5.3. The specific values ​​can be referred to in Table 6.5.

[0116] Table 6.2

[0117] Table 6.3 shows the specific values ​​of the parameters in the information element ConditionState of this example. Referring to Table 6.3, the information element ConditionState can reference the information element ConditionTask through the parameter taskItem. The information element ConditionTask can specifically adopt the information element Task shown in Table 5.3. The specific values ​​can be referred to in Table 6.6.

[0118] Table 6.3

[0119] Table 6.4 shows the specific values ​​of the parameters in the information element ActionState of this example. Referring to Table 6.4, the information element ActionState can reference the information element ActionTask through the parameter taskItem. The information element ActionTask can specifically adopt the information element Task shown in Table 5.3. The specific values ​​can be referred to in Table 6.7.

[0120] Table 6.4

[0121] Table 6.5 shows the specific values ​​of the parameters in the information element EventTask of this example. Referring to Table 6.5, the information element EventTask can reference the specific domain instance model vnfIndicator.utilization provided in the domain information model through the parameter taskInput. The domain instance model vnfIndicator.utilization can specifically use the information element ContextMap shown in Table 5.5.

[0122] Table 6.5

[0123] Table 6.6 shows the specific values ​​of the parameters in the information element ConditionTask of this example. Referring to Table 6.6, the information element ConditionTask can reference the specific domain instance model ConditionLogic provided in the domain information model through the parameter taskLogic. The domain instance model ConditionLogic can specifically adopt the information element Logic shown in Table 5.4. The specific values ​​can be referred to in Table 6.8.

[0124] Table 6.6

[0125] Table 6.7 shows the specific values ​​of the parameters in the information element ActionTask of this example. Referring to Table 6.7, the information element ActionTask can reference the specific domain instance model ScaleContextMap provided in the domain information model through the parameter taskOutput. The domain instance model ScaleContextMap can specifically use the information element ContextMap shown in Table 5.5. The specific values ​​can be referred to in Table 6.9.

[0126] Table 6.7

[0127] Table 6.8 shows the specific values ​​of the parameters in the information element ConditionLogic of this example. Referring to Table 6.8, the value of the parameter logicCode in the information element ConditionLogic is "(utilization_vnf_indicator>=60)and call_proc_scale_level<3)", which is the scaling condition in this example.

[0128] Table 6.8

[0129] Table 6.9 shows the specific values ​​of the parameters in the information element ScaleContextMap of this example. Referring to Table 6.9, the information element ScaleContextMap references the domain instance model ScaleContext in the domain information model through the parameter contextItem. The domain instance model ScaleContext can specifically use the information element Context shown in Table 5.6. The specific values ​​can be referred to in Table 6.10.

[0130] Table 6.9

[0131] Table 6.10 shows the specific values ​​of the parameters in the information element ScaleContext of this example. Referring to Table 6.10, the value of the parameter contextAccess in the information element ScaleContext is "Vnflcm.scale", and the value of the parameter contextPara is "type:scale_out; aspect:call_proc; number_of_steps:1".

[0132] Table 6.10

[0133] As shown in Table 6.1, the Policy information element can reference the UtilityExpectationLogic domain instance model in the domain information model through the Expectations parameter. This domain instance model table UtilityExpectationLogic can use the Logic information element shown in Table 5.4. Table 6.11 shows the specific values ​​for the parameters in the UtilityExpectationLogic information element. As shown in Table 6.11, the value of the logicCode parameter is "vnfindicator.utilization <= 60%", which means that the expected goal is to ensure that the VNF utilization efficiency in the computer room is less than 60%.

[0134] Table 6.11

[0135] In this example, the intention of the strategy can be conveyed to the corresponding strategy through the expected outcome domain model (as shown in Table 6.11), providing reference indicators for subsequent monitoring and evaluation of the applicability, feasibility, and effectiveness of the strategy application.

[0136] It should be noted that intent management provides a simplified way for Operation Support System / Business Support System (OSS / BSS) to use NFV-MANO services. Only NFV-related requirements and constraints need to be specified, without the need to understand how NFV-MANO performs operations converted from NFV intents. For example, the intent owner (such as OSS / BSS) requests to update an existing intent, which contains expectations for updating the performance of a network service (NS) instance, such as increasing / decreasing the incoming data rate of a specific service access point (SAP). Based on the intent expectations, the intent processor converts the updated intent into corresponding policies and ultimately executes corresponding NS operations (such as expanding the capacity of an existing NS) through the policies to meet the intent requirements.

[0137] According to the intent modeling approach, specific expressions of (functions, performance, available metric sets, and their combinations) can be constructed through the expectations of the general intent model. In the intent management system, these expectations regarding functions, performance, available metric sets, and their combinations are ultimately converted into specific information element definitions, code implementations, and service interfaces for ensuring that all expected outcomes (functions, performance, available metric sets, and their combinations) can be executed. For example, the expectation of updating NS instance performance is to maintain the VNF's utilization efficiency within a fixed threshold. Ultimately, this is converted into specific information element definitions and code implementations, as shown in Table 6.11 for the UtilityExpectationLogic.

[0138] Based on the NFV-MANO policy information model shown in Tables 5.1 to 5.6, by defining the above-mentioned intent expectations, the corresponding imperative policy description model can be extended (that is, the description part of the general information model included in the policy instance is updated). As shown in Table 6.1, the indicator Expectations about expected results is added. This parameter can reference the domain information model UtilityExpectation corresponding to the defined intent expectations.

[0139] In this example, after the execution of the intent-based strategy, the execution effect needs to be continuously guaranteed and optimized. At this time, the extended performance indicator of expected results (UtilityExpectation) can be used to provide a reference indicator for evaluating the feasibility of the strategy application. For example, the domain information model of UtilityExpectation defined in the intent can be referenced based on Expectations, and the UtilityExpectationLogic can be implemented with the code corresponding to the model as a reference indicator for the relevant performance indicators. According to the gap analysis between the actual effect after the strategy execution and the reference indicator, the strategy execution effect can be further guaranteed and optimized accordingly.

[0140] This example adopts a policy modeling approach based on model federation. It can separately plan and manage a unified model of common elements for policy modeling (i.e., a general information model) and domain-specific modeling domain models (i.e., domain information models) related to interactions with the policy operation context environment for various domains, hierarchies, and cross-domains of the self-intelligent network's operation and maintenance management policies, thereby achieving unified policy modeling and flexible on-demand expansion. In the public model, the existing imperative policy description model is expanded based on intent, adding policy modeling extensions for targets (management domains), policy scopes (managed objects), and expected effects (effectiveness indicators). On the one hand, this can provide background knowledge for the identification and resolution of potential policy conflicts required for policy systematization. On the other hand, it can provide reference indicators for monitoring and evaluating the applicability, feasibility, and effectiveness of policy applications required for dynamic, automatic iteration, and adaptive evolution of policy management. This example can provide a formal description, registration, and interaction mechanism for distributed policy modeling elements (e.g., trigger events, action execution, and conditional evaluation) to provide reference indicators for evaluating the applicability and feasibility of policy applications required for dynamic, automatic iteration, and adaptive evolution of policy management.

[0141] The present application also provides an information processing device. Figure 3 is a schematic diagram of the structure of the information processing device according to the present application. As shown in Figure 3, the information processing device 20 includes an execution module 21, which is configured to parse policy instances and / or execute the policy instances based on a general information model and a domain information model for policy management. The general information model is configured to describe the common features of policies in different domains and / or at different levels, and the domain information model is configured to describe information related to the policy operation environment and / or interaction of each domain.

[0142] In one embodiment of the present application, the general information model includes at least one of intention information, basic information, instruction element information, target range information and expected effect information.

[0143] In one embodiment of the present application, the intent information includes at least one of the following: target domain information indicating the domain to which the policy is applied; object scope information indicating the managed objects to which the policy is applied; and expected effect information indicating the expected effectiveness of the policy execution.

[0144] In an embodiment of the present application, the basic information includes at least one of the following information related to policy lifecycle management: policy name, policy type, policy source, and version information.

[0145] In one embodiment of the present application, the instruction element information includes one or more logic units describing policy execution.

[0146] In an embodiment of the present application, the target scope information includes one or more domains and / or managed objects that describe the application scope of the policy.

[0147] In an embodiment of the present application, the expected effectiveness information includes one or more metrics describing the effect of applying the policy.

[0148] In one embodiment of the present application, the domain information model includes at least one of the following: a domain information model corresponding to each domain and related to instruction element information; a domain information model corresponding to each domain and related to expected results information; and a domain information model corresponding to each domain and related to target range information.

[0149] In one embodiment of the present application, the domain information model related to instruction element information is used to provide information element definitions related to policy execution.

[0150] In one embodiment of the present application, the domain information model related to the expected effectiveness information is used to provide information element definitions related to the policy application effect evaluation.

[0151] In an embodiment of the present application, the domain information model related to the target scope information is used to provide information element definitions related to the policy application scope.

[0152] In one embodiment of the present application, the execution module 21 is configured to determine a domain model instance based on the domain information model, and to update the description portion of the general information model contained in the policy instance; the domain model instance is used to provide the context environment and / or context interaction information for the operation of the policy instance; and to parse the policy instance and / or execute the policy instance based on the updated general information model and the domain model instance.

[0153] In one embodiment of the present application, the execution module 21 is configured to obtain the intention of the policy; based on the intention, corresponding intention information is added to the description part of the general information model, and the intention information includes at least one of the following: target domain information representing the field of policy application, object scope information representing the managed objects of policy application, and expected effect information representing the expected results of policy execution.

[0154] In one embodiment of the present application, the execution module 21 is configured to parse the information elements related to at least one of the instruction element information, target range information and expected performance information contained in the corresponding policy instance based on the general information model; and parse the parameter values ​​of the information elements contained in the corresponding policy instance based on the domain information model.

[0155] In one embodiment of the present application, the information elements related to the instruction element information include at least one of the following: a state element, which is used to describe the state information of the policy from triggering to execution; a task element, which is used to describe the information of each task that the policy engine needs to perform in each state; and a logic element, which is used to describe the processing logic of the policy execution engine to perform each task.

[0156] In one embodiment of the present application, the information elements related to the instruction element information contained in the domain information model also include at least one of the following: a context element, used to describe the input and output context of each policy element, state element or task element; a context collection element, used to describe each context element.

[0157] In one embodiment of the present application, the execution module 21 is configured to update the description part based on the intention, and the updated description part includes at least one of the following: parameters for describing the domain type of policy application; parameters for describing the domain identifier of policy application; parameters for describing the managed object type of policy application; parameters for describing the managed object identifier of policy application; parameters for describing the expected results of policy execution.

[0158] In one embodiment of the present application, the domain model instance includes a first model instance corresponding to the context element and / or a second model instance corresponding to the logic element; the execution module 21 is configured to determine the parameters of the context element by referencing the first model instance, and / or, determine the parameters of the logic element by referencing the second model instance; and parse the policy instance and / or execute the policy instance based on the parameters of the context element and / or the parameters of the logic element.

[0159] In one embodiment of the present application, the device also includes an acquisition module configured to obtain capability information corresponding to all domains, and the capability information is used to determine the domain information model; the capability information includes at least one of the following: information element definitions, code implementations and service interfaces corresponding to instruction element information of each domain; information element definitions, code implementations and service interfaces corresponding to expected results information of each domain; information element definitions, code implementations and service interfaces corresponding to target range information of each domain.

[0160] In the embodiment of the present application, the execution module 21 in the information processing device 20 can be implemented by a central processing unit (CPU), a digital signal processor (DSP), a microcontroller unit (MCU) or a field-programmable gate array (FPGA) in actual applications.

[0161] It should be noted that the information processing device provided in the above embodiments is illustrated only by the division of the above-mentioned program modules when performing information processing. In actual applications, the above-mentioned processing can be assigned to different program modules as needed, that is, the internal structure of the device can be divided into different program modules to complete all or part of the above-described processing. In addition, the information processing device provided in the above embodiments and the information processing method embodiment are based on the same concept. The specific implementation process is detailed in the method embodiment and is not repeated here.

[0162] An embodiment of the present application also provides a computer device. FIG4 is a schematic diagram of the structure of a computer device according to an embodiment of the present application. As shown in FIG4 , the computer device 30 includes: at least one processor 31, a memory 32, and at least one network interface 33. The various components in the computer device 30 are coupled together via a bus system 34. It is understood that the bus system 34 is used to achieve connection and communication between these components. In addition to including a data bus, the bus system 34 also includes a power bus, a control bus, and a status signal bus. However, for the sake of clarity, in FIG4 , all various buses are labeled as the bus system 34.

[0163] It is understood that the memory 32 can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic random access memory (FRAM), a flash memory, a magnetic surface memory, an optical disk, or a compact disc read-only memory (CD-ROM); the magnetic surface memory can be a magnetic disk or a magnetic tape. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), synchronous static random access memory (SSRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct rambus random access memory (DRRAM).The memory 32 described in the embodiments of the present application is intended to include, but is not limited to, these and any other suitable types of memory.

[0164] The memory 32 in the embodiment of the present application is used to store various types of data to support the operation of the computer device 30. Examples of such data include any computer program for operating on the computer device 30, such as the program of the information processing method in the embodiment of the present application.

[0165] The methods disclosed in the above embodiments of the present application can be applied to the processor 31 or implemented by the processor 31. The processor 31 may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by the hardware integrated logic circuit in the processor 31 or by instructions in the form of software. The above processor 31 may be a general-purpose processor, a DSP, or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, etc. The processor 31 can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present application. The general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of the methods disclosed in the embodiments of the present application can be directly implemented as being executed by a hardware decoding processor, or can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium, which is located in the memory 32. The processor 31 reads the information in the memory 32 and completes the steps of the above method in combination with its hardware.

[0166] In an exemplary embodiment, the computer device 30 can be implemented by one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), FPGAs, general-purpose processors, controllers, MCUs, microprocessors, or other electronic components to execute the aforementioned method.

[0167] In an exemplary embodiment, the present application also provides a computer-readable storage medium, such as a memory 32 including a computer program. The computer program can be executed by a processor 31 of a computer device 30 to perform the steps of the aforementioned method. The computer-readable storage medium can be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface mount storage, optical disk, or CD-ROM; or various devices including any one or any combination of the aforementioned memories, such as a mobile phone, computer, tablet device, personal digital assistant, etc.

[0168] The methods disclosed in the several method embodiments provided in this application can be arbitrarily combined without conflict to obtain new method embodiments.

[0169] The features disclosed in the several product embodiments provided in this application can be arbitrarily combined without conflict to obtain new product embodiments.

[0170] The features disclosed in the several method or device embodiments provided in this application can be arbitrarily combined without conflict to obtain new method embodiments or device embodiments.

[0171] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0172] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0173] In addition, all functional units in the embodiments of the present application can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the above-mentioned integrated units can be implemented in the form of hardware or in the form of hardware plus software functional units.

[0174] Those skilled in the art will appreciate that all or part of the steps of the above-mentioned method embodiments may be implemented by hardware associated with program instructions, and the aforementioned program may be stored in a computer-readable storage medium. When the program is executed, the program executes the steps of the above-mentioned method embodiments. The aforementioned storage medium includes various media that can store program codes, such as mobile storage devices, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0175] Alternatively, if the above-mentioned integrated unit of the present application is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium and includes a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

[0176] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. An information processing method, the method comprising: Parsing a policy instance and / or executing a policy instance based on a general information model and a domain information model for policy management, wherein the general information model is used to describe common characteristics of policies in different domains and / or at different levels, and the domain information model is used to describe information related to the policy operation environment and / or interaction in each domain.

2. The method according to claim 1, wherein, The general information model includes at least one of intention information, basic information, instruction element information, target scope information, and expected effect information.

3. The method according to claim 2, wherein The intention information includes at least one of the following: Target domain information indicating the domain to which the policy is applied; Object scope information indicating the managed object to which the policy is applied; Expected effect information indicating the expected effect of policy execution.

4. The method according to claim 2, wherein, The basic information includes at least one of the following related to policy life cycle management: Policy name, policy type, policy source, version information.

5. The method according to claim 2, wherein, The instruction element information includes one or more logical units describing policy execution.

6. The method according to claim 2, wherein The target scope information includes one or more domains and / or managed objects describing the policy application scope.

7. The method according to claim 2, wherein, The expected effect information includes one or more metric indicators describing the policy application effect.

8. The method according to claim 1, wherein The domain information model includes at least one of the following: Domain information models corresponding to each domain and related to instruction element information; Domain information models corresponding to each domain and related to expected effect information; Domain information models corresponding to each domain and related to target scope information.

9. The method according to claim 8, wherein, The domain information model related to instruction element information is used to provide definitions of information elements related to policy execution.

10. The method according to claim 8, wherein, The domain information model related to expected effect information is used to provide definitions of information elements related to policy application effect evaluation.

11. The method according to claim 8, wherein, The domain information model related to target scope information is used to provide definitions of information elements related to policy application scope.

12. The method according to claim 1, wherein, The parsing of the policy instance and / or the execution of the policy instance based on the general information model and the domain information model for policy management includes: Determining a domain model instance according to the domain information model, and updating the description part of the general information model included in the policy instance; the domain model instance is used to provide the context environment and / or context interaction information for the operation of the policy instance; Parsing the policy instance and / or executing the policy instance based on the updated general information model and the domain model instance.

13. The method according to claim 12, wherein, The updating of the description part of the general information model included in the policy instance includes: Obtaining the intention of the policy; Adding corresponding intention information to the description part of the general information model based on the intention, the intention information including at least one of the following: target domain information indicating the domain to which the policy is applied, object scope information indicating the managed object to which the policy is applied, expected effect information indicating the expected effect of policy execution.

14. The method according to claim 12 or 13, wherein, The parsing of the policy instance and / or the execution of the policy instance based on the updated general information model and the domain information model includes: Parsing information elements related to at least one of instruction element information, target scope information, and expected effect information included in the corresponding policy instance based on the general information model; Parse the parameter values of the information elements included in the corresponding policy instance based on the domain information model.

15. The method according to claim 14, wherein, The information elements related to the instruction element information include at least one of the following: A status element, which is used to describe the status information of the policy from triggering to execution; A task element, which is used to describe the information of each task that the policy engine needs to execute in each state of the policy; A logic element, which is used to describe the processing logic for the policy execution engine to execute each task.

16. The method according to claim 15, wherein, The information elements related to the instruction element information included in the domain information model also include at least one of the following: A context element, which is used to describe the input and output context of each policy element, status element, or task element; A context set element, which is used to describe each context element.

17. The method according to claim 16, wherein The domain model instance includes a first model instance corresponding to the context element and / or a second model instance corresponding to the logic element; the parsing of the policy instance and / or the execution of the policy instance based on the updated general information model and the domain model instance includes: Determine the parameters of the context element by referring to the first model instance, and / or determine the parameters of the logic element by referring to the second model instance; Parse the policy instance and / or execute the policy instance based on the parameters of the context element and / or the parameters of the logic element.

18. The method according to claim 13, wherein, The adding of the corresponding intent information to the description part in the general information model based on the intent includes: Updating the description part based on the intent, and the updated description part includes at least one of the following at least: A parameter for describing the domain type to which the policy applies; A parameter for describing the domain identifier to which the policy applies; A parameter for describing the type of the managed object to which the policy applies; A parameter for describing the identifier of the managed object to which the policy applies; A parameter for describing the expected effect of policy execution.

19. The method according to claim 8, wherein, The method further includes: Obtain the capability information corresponding to each domain, where the capability information is used to determine the domain information model; the capability information includes at least one of the following: The definition, code implementation, and service interface of the information elements related to the instruction element information corresponding to each domain; The definition, code implementation, and service interface of the information elements related to the expected effect information corresponding to each domain; The definition, code implementation, and service interface of the information elements related to the target scope information corresponding to each domain.

20. An information processing apparatus, the apparatus includes an execution module configured to parse a policy instance and / or execute a policy instance based on a common information model and a domain information model for policy management, wherein, The general information model is configured to describe the common characteristics of policies in different domains and / or at different levels, and the domain information model is configured to describe the information related to the policy operation environment and / or interaction of each domain.

21. A computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of the method according to any one of claims 1 to 19 are implemented.

22. A computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the program, the steps of the method according to any one of claims 1 to 19 are implemented.

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