CN113381868A - Network arranging method and device and computer readable storage medium - Google Patents
Network arranging method and device and computer readable storage medium Download PDFInfo
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- H04L41/14—Network analysis or design
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
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Abstract
The present disclosure relates to a network orchestration method and apparatus, and a computer-readable storage medium. The network arranging method comprises the following steps: designing and loading a network model; collecting various network data in real time; analyzing the network data to generate a network arrangement event; triggering a network adjustment strategy according to a network scheduling event; driving network service arrangement through a network adjustment strategy, and executing network model instantiation; and calling network capacity according to the instantiation requirement of the network model to execute network control. According to the method and the system, through diversified design of a network model and dynamic loading as required, business requirements can be quickly adapted, and the data-driven network service arrangement is flexible and dynamic to adjust the network for optimization.
Description
Technical Field
The present disclosure relates to the field of network technologies, and in particular, to a network arrangement method and apparatus, and a computer-readable storage medium.
Background
The related art network service arrangement is a flow template which is described in advance based on a networking scheme and service requirements, and although the service logic executed by the flow can also participate in dynamic operation through rules and links, the agility and the openness are not sufficient.
Disclosure of Invention
The inventor finds out through research that: in the related art, a Network adjustment model mainly depends on experience accumulation, the scene description richness is limited, diversified and differentiated services and operation requirements cannot be met, uncovered scenes need manual processing, the Network adjustment model cannot adapt to complicated Network operation and maintenance requirements of hierarchical deployment of a data center due to cloud, SDN (Software Defined Network), and NFV (Network Functions Virtualization), and the flexible, dynamic and instant end-to-end Network arrangement requirements are difficult to meet.
In view of at least one of the above technical problems, the present disclosure provides a network orchestration method and apparatus, and a computer-readable storage medium, which can implement diversified design and on-demand dynamic loading of a network model.
According to an aspect of the present disclosure, there is provided a network orchestration method, comprising:
designing and loading a network model;
collecting various network data in real time;
analyzing the network data to generate a network arrangement event;
triggering a network adjustment strategy according to a network scheduling event;
driving network service arrangement through a network adjustment strategy, and executing network model instantiation;
and calling network capacity according to the instantiation requirement of the network model to execute network control.
In some embodiments of the present disclosure, the designing and loading the network model comprises:
designing a network model, wherein the network model comprises at least one of a network topology structure, a network elastic scaling strategy and a network adjustment scheme;
and dynamically loading the network model to a network service arranging module according to the service requirement.
In some embodiments of the present disclosure, the designing the network model comprises:
and designing a network model based on the network data and the network capacity, wherein the network model design can comprise at least one of 5G network slice model design and cloud network fusion model design.
In some embodiments of the present disclosure, the analyzing the network data and generating the network orchestration event includes:
analyzing the acquired network data by adopting artificial intelligence and big data analysis technology;
and analyzing the network operation condition to generate a network scheduling event.
In some embodiments of the present disclosure, the triggering the network adjustment policy according to the network orchestration event includes:
and triggering a network adjustment strategy according to the network arrangement event and by combining the service requirement and the network state, wherein the network adjustment strategy can comprise at least one of fault diagnosis and treatment, network expansion and contraction capacity, network flow scheduling and network optimization.
In some embodiments of the present disclosure, the triggering the network adjustment policy according to the network orchestration event includes:
and driving network service arrangement through a network adjustment strategy, dynamically generating a network topology and a network arrangement flow according to a network model, and instantiating the network model.
According to another aspect of the present disclosure, there is provided a network orchestration device comprising:
the network model design module is used for designing a network model;
the data acquisition module is used for acquiring various network data in real time;
the intelligent analysis module is used for analyzing the network data and generating a network arrangement event;
the strategy execution module is used for triggering a network adjustment strategy according to the network scheduling event;
the network service arrangement module is used for loading the network model; network service arrangement is driven through a network adjustment strategy, and network model instantiation is executed;
and the network control execution module is used for calling network capacity to execute network control according to the instantiation requirement of the network model.
In some embodiments of the present disclosure, the network orchestration device is configured to perform operations for implementing the network orchestration method according to any one of the above embodiments.
According to another aspect of the present disclosure, there is provided a network orchestration device comprising:
a memory to store instructions;
a processor configured to execute the instructions to enable the network orchestration device to perform operations for implementing the network orchestration method according to any one of the above embodiments.
According to another aspect of the present disclosure, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, which when executed by a processor, implement the network orchestration method according to any one of the embodiments described above.
According to the method and the system, through diversified design of a network model and dynamic loading as required, business requirements can be quickly adapted, and the data-driven network service arrangement is flexible and dynamic to adjust the network for optimization.
Drawings
In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a schematic diagram of some embodiments of a network orchestration method according to the present disclosure.
Fig. 2 is a schematic diagram of some embodiments of a network orchestration device according to the present disclosure.
Fig. 3 is a schematic diagram of another embodiment of a network orchestration device according to the present disclosure.
Detailed Description
The technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are only a part of the embodiments of the present disclosure, and not all of the embodiments. The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the disclosure, its application, or uses. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the protection scope of the present disclosure.
The relative arrangement of the components and steps, the numerical expressions, and numerical values set forth in these embodiments do not limit the scope of the present disclosure unless specifically stated otherwise.
Meanwhile, it should be understood that the sizes of the respective portions shown in the drawings are not drawn in an actual proportional relationship for the convenience of description.
Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate.
In all examples shown and discussed herein, any particular value should be construed as merely illustrative, and not limiting. Thus, other examples of the exemplary embodiments may have different values.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, further discussion thereof is not required in subsequent figures.
Fig. 1 is a schematic diagram of some embodiments of a network orchestration method according to the present disclosure. Preferably, the present embodiment may be performed by the network orchestration device according to the present disclosure. The method comprises the following steps 11-16, wherein:
and step 11, designing and loading a network model.
In some embodiments of the present disclosure, step 11 may include step 111 and step 112, wherein:
step 111, designing a network model, wherein the network model comprises at least one of a network topology structure, a network elastic scaling strategy, a network fault processing scheme, a network adjusting scheme and the like.
In some embodiments of the present disclosure, step 111 may comprise: and designing a network model based on the network data and the network capacity, wherein the network model design can comprise at least one of 5G network slice model design, cloud network fusion model design and the like.
And step 112, dynamically loading the network model to a network service arranging module according to the business requirement.
And step 12, collecting various network data in real time.
In some embodiments of the present disclosure, step 12 may comprise: the method comprises the steps of collecting various network data from a 5G network in real time, wherein the 5G network can comprise network equipment such as a wireless network, a core network, a bearer network, an edge cloud and a core cloud.
In some embodiments of the present disclosure, the network data may include traffic data, network topology data, and network operational data.
In some embodiments of the present disclosure, the network data may include: broadband usage awareness data, network topology, network performance, alarms, network rate, etc.
And step 13, analyzing the network data to generate a network arrangement event.
In some embodiments of the present disclosure, step 13 may include step 131 and step 132, wherein:
step 131, analyzing the collected network data by adopting artificial intelligence AI and big data analysis technology so as to continuously optimize and enrich the network model.
Step 132, analyze the network operation to generate a network orchestration event. For example: and generating network scheduling events such as faults, alarms and the like.
And step 14, triggering a network adjustment strategy according to the network scheduling event.
In some embodiments of the present disclosure, step 14 may comprise: according to a network scheduling event, triggering a network adjustment strategy by combining conditions such as service requirements and network states, wherein the network adjustment strategy can comprise at least one of strategies such as fault diagnosis and treatment, network expansion and contraction capacity, network traffic scheduling and network optimization.
And step 15, driving network service arrangement through a network adjustment strategy, and executing network model instantiation.
In some embodiments of the present disclosure, step 15 may comprise: and driving network service arrangement through a network adjustment strategy, dynamically generating a network topology and a network arrangement flow according to a network model, and instantiating the network model.
And step 16, calling network capacity according to the instantiation requirement of the network model to execute network control.
In some embodiments of the present disclosure, step 16 may comprise: and providing an Open API (Application Programming Interface) of a network element for arranging, calling and executing network control by the network service.
In some embodiments of the present disclosure, step 16 may comprise: and calling network capabilities according to the instantiation requirement of the network model to execute network control on the 5G network, wherein the 5G network can comprise network equipment such as a wireless network, a core network, a bearer network, an edge cloud, a core cloud and the like.
The network arranging method provided by the embodiment of the disclosure can be used for designing network models in a diversified manner and dynamically loading the models as required, quickly adapting to business requirements, and flexibly and dynamically adjusting the network for optimizing data-driven network service arrangement.
The above embodiment of the present disclosure adopts a technical scheme of separating a design state and an operation state, strengthens the design of the design state on the basis of network data and network capacity to the network topology, service logic, arrangement strategy, and the like, dynamically loads the design state to the operation state in a network model manner, and data drives the network service arrangement to instantiate the network model.
The embodiments of the present disclosure adopt data-driven network model design, such as 5G network slice model design and cloud network fusion model design.
The network models of the embodiments of the present disclosure are dynamically loaded as needed, and the corresponding network models are quickly matched according to business requirements.
The above embodiments of the present disclosure adopt policy-driven network service orchestration, dynamically generate network topology, and automatically execute network control.
Fig. 2 is a schematic diagram of some embodiments of a network orchestration device according to the present disclosure. As shown in fig. 2, the network orchestration device of the present disclosure may include a network model design module 21, a network service orchestration module 25, and a network control execution module 26, wherein:
and the network model design module 21 is used for designing a network model.
In some embodiments of the present disclosure, the network model design module 21 may be used to design network topology adjustment schemes, perform actions, and adjust policies.
In some embodiments of the present disclosure, the network model design module 21 may be configured to design a network model, wherein the network model includes at least one of a network topology, a network elastic scaling strategy, a network fault handling scheme, a network tuning scheme, and the like; and dynamically loading the network model to a network service arranging module according to the service requirement.
In some embodiments of the present disclosure, the network model design module 21 may be configured to design a network model based on network data and network capabilities, wherein the network model design may include at least one of a 5G network slice model design and a cloud network fusion model design.
And the network service arranging module 25 is used for loading the network model.
And the network control execution module 26 is used for calling the network capability according to the instantiation requirement of the network model to execute network control.
In some embodiments of the disclosure, the present disclosure may implement dynamic closed-loop orchestration of network services, instantiate a data-driven network model, dynamically construct a network topology, flexibly select a network path, be simple in operation, support cross-domain and cross-vendor network adjustment, and save network operation cost.
Thus, in some embodiments of the present disclosure, as shown in fig. 2, the network orchestration device of the present disclosure may further include a data collection module 22, an intelligent analysis module 23, and a policy enforcement module 24, wherein:
and the network model design module 21 is used for designing a network model.
And the data acquisition module 22 is used for acquiring various network data in real time.
In some embodiments of the present disclosure, as shown in fig. 2, the data collecting module 22 may be configured to collect various network data in real time from a 5G network, where the 5G network may include network devices such as a wireless network, a core network, a bearer network, an edge cloud, and a core cloud.
In some embodiments of the present disclosure, the network data may include traffic data, network topology data, and network operational data.
In some embodiments of the present disclosure, the network data may include: broadband usage awareness data, network topology, network performance, alarms, network rate, etc.
And the intelligent analysis module 23 is used for analyzing the network data and generating a network arrangement event.
In some embodiments of the present disclosure, the intelligent analysis module 23 may be configured to trigger a network tuning event based on the AI and the majority analysis network operating conditions.
In some embodiments of the present disclosure, the intelligent analysis module 23 may be configured to analyze the collected network data using artificial intelligence AI and big data analysis techniques to continuously optimize and enrich the network model; and analyzing the network operation condition to generate a network scheduling event. For example: and generating network scheduling events such as faults, alarms and the like.
And the policy execution module 24 is configured to trigger a network adjustment policy according to the network orchestration event.
In some embodiments of the present disclosure, policy enforcement module 24 may be configured to perform network orchestration actions based on network adjustment events matching network adjustment policies.
In some embodiments of the present disclosure, the policy execution module 24 may be configured to trigger a network adjustment policy according to a network orchestration event, in combination with conditions such as service requirements and network states, where the network adjustment policy may include at least one of fault diagnosis, network scaling, network traffic scheduling, network optimization, and other policies.
And the network service arranging module 25 is used for driving network service arrangement through a network adjusting strategy and executing network model instantiation.
In some embodiments of the present disclosure, network services orchestration module 25 may be used to dynamically load a network model, data driven network model instantiation to perform network tuning.
In some embodiments of the present disclosure, the network service orchestration module 25 may be configured to dynamically generate a network topology and a network orchestration procedure from a network model by driving the network service orchestration through a network tuning policy, instantiating the network model.
And the network control execution module 26 is used for calling the network capability according to the instantiation requirement of the network model to execute network control.
In some embodiments of the present disclosure, as shown in fig. 2, the network control execution module 26 may be configured to invoke a network capability according to a network model instantiation requirement to execute network control on a 5G network, where the 5G network may include a wireless network, a core network, a bearer network, an edge cloud, a core cloud, and other network devices.
In some embodiments of the present disclosure, the network control execution module 26 may be configured to provide a network element Open API for a network service orchestration call to execute network control.
In some embodiments of the present disclosure, the network orchestration device is configured to perform operations for implementing the network orchestration method according to any one of the embodiments described above (e.g., the embodiment of fig. 1).
The network arrangement device provided based on the above embodiment of the present disclosure is a closed-loop automatic network arrangement device based on artificial intelligence. The embodiment of the disclosure belongs to a network operation system in the technical field of IT.
The above embodiments of the present disclosure aim to solve the problems of flexible design and dynamic loading of a network model, and dynamic adjustment of a network topology by data-driven network service orchestration, and the tasks to be completed are as follows:
according to the embodiments of the present disclosure, through network model design and dynamic loading, a network topology adjustment scheme, an execution action, an adjustment strategy, and the like are designed, and a corresponding network model can be obtained according to a network scene which needs to be arranged.
The network service dynamic closed-loop arrangement and the data-driven network model instantiation of the embodiment of the invention can dynamically construct a network topology, flexibly select a network path, have simple operation, support cross-domain and cross-manufacturer network adjustment and save network operation cost.
The embodiment of the disclosure automatically triggers through a network adjustment event, collects network data in real time, and automatically generates the network adjustment event by adopting artificial intelligence and analyzing the network operation condition by a large number;
the network control of the above embodiment of the present disclosure is automatically executed, the network element capability pool is opened, the network service arrangement is called as required, and the adjustment is flexible.
Fig. 3 is a schematic diagram of another embodiment of a network orchestration device according to the present disclosure. As shown in fig. 2, the network orchestration device of the present disclosure may include a memory 31 and a processor 32, wherein:
a memory 31 for storing instructions.
A processor 32, configured to execute the instructions, so that the network orchestration device performs operations of implementing the network orchestration method according to any one of the embodiments described above (for example, the embodiment of fig. 1).
In some embodiments of the present disclosure, the processor 32 is configured to execute the instructions to cause the network orchestration device to execute the network orchestration method according to at least one of the following steps 1 to 6:
step 1, designing and loading a network model, such as a network topological structure, a network elastic expansion and contraction capacity strategy, a network adjustment scheme and the like, and dynamically loading the network model to a network service arranging module according to business needs;
step 2, collecting service data, network topology data and network operation data in real time, such as broadband use perception data, network topology, network performance, alarm, network rate and other data;
step 3, adopting artificial intelligence and big data analysis technology to analyze the adopted network data, continuously optimizing and enriching the network model, simultaneously analyzing the network operation condition, and generating network arrangement events, such as faults, alarms and the like;
step 4, triggering network adjustment strategies such as fault diagnosis and treatment, capacity expansion and contraction and the like according to network arrangement events by combining conditions such as service requirements, network states and the like;
step 5, network adjustment strategy driving network service arrangement, dynamically generating network topology and network arrangement flow according to the network model, and instantiating the network model;
and 6, calling network capacity to execute network control according to the instantiation requirement of the network model, and finishing network adjustment.
The arrangement object of the above embodiment of the present disclosure is wider and is not limited to cross-vendor network arrangement in the fields of NFV, SDN, cloud, and the like.
The network model design of the above embodiments of the present disclosure is designed based on network data and network capabilities, and is dynamically loaded into the network service orchestration as needed.
The arrangement of the above embodiments of the present disclosure is driven by a policy, and is dynamically and automatically generated based on network data, without manual configuration.
The network service orchestration of the above embodiments of the present disclosure calls network capabilities to perform network control based on a network service topology dynamic instantiation network model.
According to another aspect of the present disclosure, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, which when executed by a processor, implement the network orchestration method according to any one of the embodiments (for example, the embodiment of fig. 1) above.
In some embodiments of the present disclosure, the instructions, when executed by the processor, implement the network orchestration method according to at least one of the following steps 41-46:
step 41, designing and loading a network model, such as a network topology structure, a network elastic expansion and contraction capacity strategy, a network fault processing scheme and the like, and dynamically loading the network model to a network service arranging module according to business needs;
step 42, collecting network topology data and network operation data in real time;
step 43, adopting artificial intelligence and big data analysis technology to analyze the network operation condition and generate network arrangement events, such as faults, alarms and the like;
step 44, triggering network adjustment strategies by events, such as fault diagnosis and treatment, capacity expansion and contraction, flow scheduling, network optimization and the like;
step 45, strategy-driven network service arrangement, dynamic generation of network topology, and execution of network model instantiation;
and step 46, calling network capacity according to the instantiation requirement of the network model to execute network control, and finishing network adjustment.
Based on the computer readable storage medium provided by the above embodiment of the present disclosure, the network model can be designed in a diversified manner and dynamically loaded as required, the service requirements can be adapted quickly, and the data-driven network service arrangement is flexible and the network can be dynamically adjusted to optimize.
The above embodiment of the present disclosure adopts a technical scheme of separating a design state and an operation state, strengthens the design of the design state on the basis of network data and network capacity to the network topology, service logic, arrangement strategy, and the like, dynamically loads the design state to the operation state in a network model manner, and data drives the network service arrangement to instantiate the network model.
The embodiments of the present disclosure adopt data-driven network model design, such as 5G network slice model design and cloud network fusion model design.
The network models of the embodiments of the present disclosure are dynamically loaded as needed, and the corresponding network models are quickly matched according to business requirements.
The above embodiments of the present disclosure adopt policy-driven network service orchestration, dynamically generate network topology, and automatically execute network control.
The network orchestration devices described above may be implemented as a general purpose processor, a Programmable Logic Controller (PLC), a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any suitable combination thereof, for performing the functions described herein.
Thus far, the present disclosure has been described in detail. Some details that are well known in the art have not been described in order to avoid obscuring the concepts of the present disclosure. It will be fully apparent to those skilled in the art from the foregoing description how to practice the presently disclosed embodiments.
It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program instructing relevant hardware to implement the above embodiments, where the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a magnetic disk, an optical disk, or the like.
The description of the present disclosure has been presented for purposes of illustration and description, and is not intended to be exhaustive or limited to the disclosure in the form disclosed. Many modifications and variations will be apparent to practitioners skilled in this art. The embodiment was chosen and described in order to best explain the principles of the disclosure and the practical application, and to enable others of ordinary skill in the art to understand the disclosure for various embodiments with various modifications as are suited to the particular use contemplated.
Claims (10)
1. A network orchestration method, comprising:
designing and loading a network model;
collecting various network data in real time;
analyzing the network data to generate a network arrangement event;
triggering a network adjustment strategy according to a network scheduling event;
driving network service arrangement through a network adjustment strategy, and executing network model instantiation;
and calling network capacity according to the instantiation requirement of the network model to execute network control.
2. The network orchestration method according to claim 1, wherein the designing and loading a network model comprises:
designing a network model, wherein the network model comprises at least one of a network topology structure, a network elastic scaling strategy and a network adjustment scheme;
and dynamically loading the network model to a network service arranging module according to the service requirement.
3. The network orchestration method according to claim 2, wherein the designing the network model comprises:
and designing a network model based on the network data and the network capacity, wherein the network model design can comprise at least one of 5G network slice model design and cloud network fusion model design.
4. The network orchestration method according to any one of claims 1-3, wherein analyzing the network data and generating the network orchestration event comprises:
analyzing the acquired network data by adopting artificial intelligence and big data analysis technology;
and analyzing the network operation condition to generate a network scheduling event.
5. The network orchestration method according to any one of claims 1-3, wherein triggering a network adjustment policy according to a network orchestration event comprises:
and triggering a network adjustment strategy according to the network arrangement event and by combining the service requirement and the network state, wherein the network adjustment strategy can comprise at least one of fault diagnosis and treatment, network expansion and contraction capacity, network flow scheduling and network optimization.
6. The network orchestration method according to any one of claims 1-3, wherein triggering a network adjustment policy according to a network orchestration event comprises:
and driving network service arrangement through a network adjustment strategy, dynamically generating a network topology and a network arrangement flow according to a network model, and instantiating the network model.
7. A network orchestration device, comprising:
the network model design module is used for designing a network model;
the data acquisition module is used for acquiring various network data in real time;
the intelligent analysis module is used for analyzing the network data and generating a network arrangement event;
the strategy execution module is used for triggering a network adjustment strategy according to the network scheduling event;
the network service arrangement module is used for loading the network model; network service arrangement is driven through a network adjustment strategy, and network model instantiation is executed;
and the network control execution module is used for calling network capacity to execute network control according to the instantiation requirement of the network model.
8. The network orchestration device according to claim 7, wherein the network orchestration device is configured to perform operations to implement the network orchestration method according to any one of claims 2-6.
9. A network orchestration device, comprising:
a memory to store instructions;
a processor for executing the instructions to cause the network orchestration device to perform operations to implement the network orchestration method according to any one of claims 1-6.
10. A computer-readable storage medium storing computer instructions which, when executed by a processor, implement the network orchestration method according to any one of claims 1-6.
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