CN112311834A - Method and system for describing and distributing multi-stage computing of edge cloud - Google Patents
Method and system for describing and distributing multi-stage computing of edge cloud Download PDFInfo
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Abstract
The invention provides a method and a system for describing and distributing multi-level computing of an edge cloud, which are used for realizing the distribution of different resource requirements and computing logic requirements to different hierarchical resource nodes by analyzing a computing service description template and controlling hierarchical node resources and computing logic resources, realizing the load balance of each hierarchical node in the system, effectively improving the computing capacity of the edge cloud and better supporting the requirements of user services.
Description
Technical Field
The invention relates to the field of cloud computing, in particular to a method and a system for describing and distributing multilevel computing of an edge cloud.
Background
With the development of the internet and big data technology, the traditional central computing mode can not meet the requirement of processing mass data, and the cloud computing technology based on distributed computing is developed. The cloud computing technology is a product of development and fusion of traditional computer and network technologies such as distributed computing, parallel computing, utility computing, network storage, virtualization, load balancing, hot backup redundancy and the like, and changes and evolves continuously along with explosive increase of data processing capacity. The 5G and the coming of the internet of things era, the existing cloud computing technology cannot meet the requirements of 'large bandwidth, high speed and low time delay' on the terminal side, and therefore the concept of edge cloud computing is generated. The appearance of the edge computing technology marks that the cloud computing is developed to the next stage, the cloud computing capability is expanded to the edge side closest to the terminal, and the cloud computing service is sunk through the unified management and control of the cloud edge side, so that the end-to-end cloud service is provided.
At present, the edge cloud technology has been gradually applied to a plurality of fields such as function computation and multi-level computation. In the existing scheme, the multi-stage computation of the edge cloud generally comprises a combination of function computation, a container and a container arrangement technology, which are all schemes in a public cloud large cluster, and the defects mainly comprise the following three points: the method has the advantages that firstly, a unified resource and calculation integration tool is not used for describing user service forms in a unified mode so as to meet user requirements, secondly, hierarchical resource management and calculation logic management are not used, and thirdly, heterogeneous nodes are not used for managing different calculation logic environments. Therefore, as no unified tool and business template is used for managing the resources and the computing logic of the edge cloud, the essence of the multi-stage computing of the edge cloud is that the management mode of the resources and the computing logic of the traditional cloud computing is still used, and the computing efficiency cannot be effectively improved. Therefore, a description and distribution method for multi-level computing of an edge cloud is needed, which can distribute different resource requirements and computing logic requirements to different hierarchical resource nodes by controlling a computing service description template, hierarchical node resources and computing logic resources.
Disclosure of Invention
In view of this, the present invention provides a method and a system for describing and distributing multi-level computing of an edge cloud, which are used to solve the problem that there is no unified resource and computing integration tool to uniformly describe a user service form to meet a user requirement, implement load balancing of each hierarchical node in the system, and effectively improve computing capability of the edge cloud to better support the user service requirement.
In order to solve the above technical problems, the proposed solution is as follows:
a method for describing and distributing multi-level computation of an edge cloud comprises the following steps:
the cloud analysis component receives and analyzes the calculation service description template sent by the user, generates a hierarchical node resource requirement and a calculation logic deployment requirement, and sends the hierarchical node resource requirement and the calculation logic deployment requirement to the cloud distribution deployment component;
the cloud distribution deployment component determines a hierarchical node matched with the hierarchical node resource demand, acquires hierarchical node resources and computational logic resources based on the hierarchical node resource demand and the computational logic deployment demand, and distributes the hierarchical node resources and the computational logic resources to the matched hierarchical node;
and the terminal deployment component of the hierarchical node initializes the computing environments of the hierarchical nodes of different types according to the received hierarchical node resources, and locally stores, loads and processes the computing logic resources.
Preferably, the computation service description template defines computation power required to be used by the user, computation logic resources used, and whether flexible scalability is required.
Preferably, a hierarchical node matched with the hierarchical node resource demand is searched and determined according to the hierarchical node resource demand, a hierarchical node resource corresponding to the hierarchical node resource demand is acquired from a node resource management component, a computational logic resource corresponding to the computational logic deployment demand is acquired from a computational logic storage component, and the hierarchical node resource and the computational logic resource are distributed to the matched hierarchical node.
Preferably, the different types of hierarchical nodes are heterogeneous network nodes, including strong nodes and weak nodes.
Preferably, the end deployment component of the hierarchical node initializes the computing environments of the hierarchical nodes of different types according to the received hierarchical node resources, and locally stores and loads the computing logic resources, specifically including: the capacity of virtual machine (kvm), container (docker) and container arrangement (k8s) is provided at the strong node, and the capacity of function calculation and native application is provided at the weak node.
Preferably, the different types of hierarchical nodes include at least one of: internet data center IDC node, mobile edge computing MEC node, end node.
Preferably, the distribution is performed by using a normal file download or an accelerated transmission network.
A system for describing and distributing multi-level computing of edge clouds, comprising: the cloud and different types of hierarchical nodes; wherein, the cloud includes at least:
the cloud analysis component is used for receiving and analyzing the computing service description template sent by the user, generating a hierarchical node resource requirement and a computing logic deployment requirement and sending the hierarchical node resource requirement and the computing logic deployment requirement to the cloud distribution deployment component;
the cloud distribution and deployment component is used for determining a hierarchical node matched with the hierarchical node resource demand, acquiring hierarchical node resources and computational logic resources based on the hierarchical node resource demand and the computational logic deployment demand, and distributing the hierarchical node resources and the computational logic resources to the matched hierarchical node;
the hierarchical node includes at least:
and the end deployment component is used for receiving the hierarchical node resources and the computational logic resources sent by the cloud end, initializing the computational environments of the hierarchical nodes of different types according to the hierarchical node resources, and locally storing, loading and processing the computational logic resources.
Preferably, the cloud further comprises:
the node resource management component is used for being responsible for storage, detection and matching of the hierarchical node resources;
and the computation logic storage component is used for being responsible for storage, authentication and matching of the computation logic resources.
A device for describing and distributing edge cloud multi-level computing comprises a memory, a processor and a computer program which is stored in the memory and can run on the processor, and is characterized in that the processor realizes the steps of the method for describing and distributing edge cloud multi-level computing when executing the computer program.
A computer-readable storage medium, storing a computer program which, when executed by a processor, implements the steps of a method of describing and distributing edge cloud multi-level computing.
According to the technical scheme, the method for describing and distributing the edge cloud multistage computing provided by the embodiment of the application uses a standard computing service description template to manage requirements, uses a unified resource and computing integration tool to manage and control hierarchical node resources and computing logic resources, and configures different resources and computing logic for different types of hierarchical nodes, so that different resource requirements and computing logic requirements are distributed to different hierarchical resource nodes, the load of each hierarchical node in the system is balanced, the efficiency of the edge cloud multistage computing is effectively improved, and various types of service requirements of different users are better supported.
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In order to more clearly illustrate the embodiments of the present invention 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 embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
Fig. 1 is a schematic structural diagram of a multi-stage computing and distributing apparatus of an edge cloud according to the present invention.
FIG. 2 is a flow chart of a method of describing and distributing edge cloud multi-level computing of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The method for describing and distributing the edge cloud multistage computing is suitable for the field of cloud computing, in particular to the field of edge cloud multistage computing.
Cloud Computing (Cloud Computing), an augmentation, usage and interaction model for internet-based related services, typically involves providing dynamically scalable and often virtualized resources over the internet. Cloud Computing is a product of development and fusion of traditional computer and Network Technologies, such as Distributed Computing (Distributed Computing), Parallel Computing (Parallel Computing), Utility Computing (Utility Computing), Network Storage (Network Storage Technologies), Virtualization (Virtualization), Load balancing (Load Balance), hot backup redundancy (High Available), and the like.
The edge cloud is a cloud computing technology, and is a cloud computing platform constructed on an edge infrastructure based on the core and edge computing capability of the cloud computing technology. An elastic cloud platform with comprehensive computing, network, storage, safety and other capabilities at the edge position is formed, an end-to-end technical framework of 'cloud edge end three-body cooperation' is formed with a central cloud and an internet of things terminal, and by putting network forwarding, storage, computing, intelligent data analysis and other works on the edge for processing, response delay is reduced, cloud pressure is relieved, bandwidth cost is reduced, and cloud services such as whole network scheduling and computing power distribution are provided.
According to the position distinction, the edge cloud is composed of multi-level nodes and comprises Internet data center IDC nodes, mobile edge computing MEC nodes, end nodes and the like. Besides the positions of the nodes, the node capabilities are different, and the bearable services are different.
As shown in fig. 1, the present invention provides a system for describing and distributing edge cloud multi-level computing, where the system includes: a cloud 100 and different types of hierarchical nodes 200.
The cloud 100 specifically includes: the cloud analysis component 101, the cloud distribution deployment component 102, the node resource management component 103, and the computation logic storage component 104.
The hierarchical node 200 includes an end deployment component 201.
The cloud analysis component 101 is configured to receive a computation service description template sent by a user, analyze the computation service description template, generate a hierarchical node resource requirement and a computation logic deployment requirement, and send the hierarchical node resource requirement and the computation logic deployment requirement to the cloud distribution deployment component 102.
The computing service description template defines the computing capacity required by the user, the used computing logic resource, whether the elastic expansion capacity is required or not and other contents, and can be realized by json or xml or other dynamic description languages.
Specifically, a computing service template defines the use mode of a multi-level resource node aiming at the characteristics of an edge cloud; dividing the requirements of users into the use of different resource nodes according to the types of service requirements; in addition, different computing logic capabilities are provided according to different resource nodes.
Different types of hierarchical nodes are heterogeneous network nodes, including strong nodes and weak nodes. The strong and weak nodes can run on different protocols to support different functions or applications or have different load balancing capabilities.
Different computational logic capabilities are provided at different types of hierarchical nodes, and specifically, capabilities such as virtual machine (kvm), container (docker), container orchestration (k8s) are provided in strong node clusters, and function computation, native application capabilities are provided in weak nodes.
The use of the calculation service template realizes the unified description of the user service form, can meet the requirements of users and simultaneously improves the service processing efficiency.
A KVM Virtual Machine, a Kernel-based Virtual Machine for short, is an open-source system virtualization module, has few core source codes, needs hardware support for virtualization, and is hardware-based complete virtualization.
Docker is an open source application container engine, is a tool for starting and stopping containers, and enables developers to pack their applications and dependency packages into a portable container, and then distribute the container to any popular Linux machine, and also can realize virtualization, and the containers completely use a sandbox mechanism and do not have any interface with each other.
Container orchestration is to meet the need to manage containers deployed on multiple hosts. The container orchestration tool provides techniques for scheduling and clustering, providing a basic mechanism for container-based application extensibility. The container orchestration tool uses container services and orchestrates them to decide how to interact between containers, extends lifecycle management capabilities to complex, multi-container workloads deployed across large clusters of machines, providing an abstraction layer for developers and infrastructure teams to handle large-scale containerized deployments.
The hierarchical node resource requirements mainly include local resource requirements and network resource requirements, specifically:
the local resource requirements include requirements for hardware devices such as a memory and a central processing unit CPU, such as how much computing power is required, how much memory is required to be consumed when a system runs, how much cache space is required for system data management, and the like.
Network resource requirements include what network resource reservations are needed, how large network transmission rates, network security issues, network billing issues, etc.
The computing logic deployment requirement mainly refers to what computing units need to be deployed.
And the cloud distribution and deployment component 102 is configured to determine hierarchical nodes 200 matching with hierarchical node resource requirements from different types of hierarchical nodes, acquire the hierarchical node resources and the computational logic resources based on the hierarchical node resource requirements and the computational logic deployment requirements, and distribute the hierarchical nodes 200 to the matched hierarchical nodes.
Specifically, the cloud distribution deployment component 102 searches and determines the hierarchical node 200 matched with the hierarchical node resource demand according to the hierarchical node resource demand, acquires the hierarchical node resource corresponding to the hierarchical node resource demand from the node resource management component 103, acquires the computation logic resource corresponding to the computation logic deployment demand from the computation logic storage component 104, and distributes the hierarchical node resource and the computation logic resource to the matched hierarchical node 200.
The cloud distribution deployment component 102, as a component for interaction between the cloud 100 and the hierarchical nodes 200, specifically implements the following three functions: 1. analyzing the node resource requirement, and searching a proper graded resource node; 2. initializing the resource nodes according to the requirement of the computing service of the user; 3. and distributing the computing logic resource of the user to the corresponding hierarchical resource node.
Specifically, the implementation of the above functions includes the following steps:
firstly, obtaining a result obtained after analyzing a computing service description template, namely a hierarchical node resource requirement and a computing logic deployment requirement.
Next, the cloud distribution deployment component 102 searches all hierarchical nodes 200 in the network according to the hierarchical node resource requirement, and determines related hierarchical nodes 200 whose loads can be matched or hierarchical nodes 200 that have the qualification of acquiring the hierarchical node resource.
Then, the cloud distribution deployment component 102 sends the hierarchical node resource demand to the node resource management component 103, and receives a result of analyzing and matching the hierarchical node resource demand, that is, a hierarchical node resource corresponding to the hierarchical node resource demand, from the node resource management component 103. Meanwhile, the computation logic deployment requirement is sent to the computation logic storage component 104, and the result of analyzing and matching the computation logic deployment requirement, that is, the computation logic resource corresponding to the computation logic deployment requirement, is received from the computation logic storage component 104.
Finally, the obtained hierarchical node resources and the computation logic resources are distributed to the determined matched hierarchical node 200.
The edge cloud multistage computing description and distribution system has the advantages that a special device is used for processing and analyzing hierarchical node resource requirements and computing logic deployment requirements, namely the node resource management component 103 and the computing logic storage component 104, meanwhile, the cloud distribution deployment component 102 integrates all types of resources and distributes the resources to different hierarchical nodes 200 in a unified mode, and the processing of the resources of edge cloud hierarchical computing by using unified resources and a computing integration tool is achieved.
And the node resource management component 103 is located at the cloud 100 and is responsible for functions of allocation, detection, inventory management and the like of hierarchical node resources.
The node resources include physical resources and logical resources, and may be specifically divided into two types:
a node resource class and a network resource class.
The node resource classes comprise link bandwidth, a memory, a Central Processing Unit (CPU) and the like.
The CPU resource management mainly manages the scheduling execution of the packets, i.e., how to rapidly schedule and execute the packets arriving at the node.
The memory management mainly relates to the management of a system buffer area and the management of memory consumed by the operation of an active packet.
The network resource category includes network resource reservation, network congestion control and flow control, network Qos guarantee, network security, network charging, etc., and mainly how to reasonably allocate limited bandwidth resources.
The node resource management component 103 includes a database, in which a corresponding table of hierarchical node resource requirements and hierarchical node resources is stored, and the hierarchical node resources can be updated according to the change of the resources.
The node resource management component 103 receives the hierarchical node resource requirement from the cloud distribution deployment component 102, performs table lookup from the database to match the hierarchical node resource requirement with the hierarchical node resource, and feeds back the matched hierarchical node resource to the cloud distribution deployment component 102.
And the computation logic storage component 104 is located at the cloud 100 and is responsible for functions of storing, managing, authenticating and the like of the computation logic resources of the user.
Logical operations (also known as boolean operations) are numerical symbolic logic deductions including union, intersection, subtraction. Logic algebra is used in circuitry and logic operations are often used to test for true and false values. The most common logical operation is the processing of a loop to determine whether the instruction leaves the loop or continues to execute within the loop.
The computation logic storage component 104 includes a database, in which a corresponding table of the computation logic deployment requirement and the computation logic resource is stored, and the computation logic resource can be updated according to the change of the resource.
The computation logic storage component 104 receives the computation logic deployment requirement from the cloud distribution deployment component 102, performs table lookup from a database to match the computation logic deployment requirement with the computation logic resource, and feeds back the matched computation logic resource to the cloud distribution deployment component 102.
Meanwhile, the computation logic storage component 104 further includes a user authentication module for auditing the qualification of the user to acquire the computation logic resource.
The hierarchical node 200 includes an end deployment component 201 that has multi-level node hierarchical management capabilities, hierarchical deployment capabilities, and management and distribution capabilities for different computing logics.
Meanwhile, the end deployment component 201 can support different virtual computing environments according to the capabilities of the hierarchical heterogeneous nodes, such as the capability of providing virtual machines (kvm), containers (docker), and container arrangement (k8s) in a strong node cluster, and the capability of providing function computation and native application in a weak node. Therefore, management of different computing logic environments by the heterogeneous nodes is achieved, loads of all hierarchical nodes in the system are balanced, and the efficiency of edge cloud multi-level computing is effectively improved.
The end deployment component 201 is configured to receive the hierarchical node resources and the computation logic resources sent by the cloud 100, initialize the computing environments of the hierarchical nodes of different types according to the hierarchical node resources, and locally store, load, and process the computation logic resources. The method specifically comprises the following steps:
1. receiving a cloud deployment component instruction, and initializing different computing environments according to business requirements; 2. receiving the cloud deployment component instruction, downloading and storing the computing logic resource of the user to the local, and carrying out corresponding loading processing. This distribution process may be performed using normal file downloads, or may be performed using an accelerated transport network, such as a P2P network.
Since the hierarchical nodes are of different types, different computing environments are initialized according to the different types of nodes. Wherein the different types of hierarchical nodes include at least one of: internet data center IDC node, mobile edge computing MEC node, end node.
IDC, which is an Internet Data Center, which is abbreviated as IDC room, and is a place for placing computer systems and related components and providing basic network services, such as host hosting, bandwidth leasing, and the like.
MEC, known as Mobile Edge Computing, is a technology based on 5G evolution architecture and for deeply fusing a Mobile access network and an internet service. The MEC can provide services and cloud computing functions required by IT of telecommunication users nearby by using the wireless access network, so as to create a telecommunication service environment with high performance, low delay and high bandwidth, accelerate the rapid downloading of various contents, services and applications in the network, and enable consumers to enjoy continuous high-quality network experience.
Based on the same concept of the edge cloud multi-level computing description and distribution system provided in the foregoing description, the present invention further provides an edge cloud multi-level computing description and distribution method provided in the present invention, as shown in fig. 2, the method is applied to the edge cloud multi-level computing description and distribution system, and specifically includes the following steps:
The computation service description template defines the computation power needed by the user, the computation logic resource used and whether flexible scalability is needed.
And 102, determining a hierarchical node matched with the hierarchical node resource demand from different types of hierarchical nodes by the cloud distribution and deployment component, acquiring the hierarchical node resource and the computational logic resource based on the hierarchical node resource demand and the computational logic deployment demand, and distributing to the matched hierarchical node.
Specifically, the cloud distribution and deployment component searches all hierarchical nodes in the network according to the hierarchical node resource requirements, and determines related hierarchical nodes of which the loads can match the requirements or the hierarchical nodes with the qualification of acquiring the hierarchical node resources.
The cloud distribution deployment component sends the hierarchical node resource demand to the node resource management component, the node resource management component searches a corresponding table of the hierarchical node resource demand and the hierarchical node resource from a local database, matches the hierarchical node resource demand with the hierarchical node resource, and feeds the matched hierarchical node resource back to the cloud distribution deployment component.
Meanwhile, the cloud distribution deployment component sends the calculation logic deployment requirement to the calculation logic storage component, the calculation logic storage component searches a corresponding table of the calculation logic deployment requirement and the calculation logic resource from a local database, the calculation logic deployment requirement is matched with the calculation logic resource, and the matched calculation logic resource is fed back to the cloud distribution deployment component.
Wherein, the distribution process is to use ordinary file downloading or accelerated transmission network transmission.
And 103, initializing computing environments of different types of hierarchical nodes by the end deployment component of the hierarchical nodes according to the received hierarchical node resources, and locally storing and loading processing computing logic resources.
The different types of hierarchical nodes include at least one of: internet data center IDC node, mobile edge computing MEC node, end node.
According to the method for describing and distributing the edge cloud multistage computation, the standard computation business description template is used for managing the requirements, the unified resources and the computation integration tool are used for managing and controlling the hierarchical node resources and the computation logic resources, different resources and computation logic are configured according to different hierarchical node types, so that different resource requirements and computation logic requirements are distributed to different hierarchical resource nodes, the efficiency of edge cloud multistage computation is effectively improved, and various types of business requirements of different users are better supported.
Finally, it should also be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, the use of the phrase "comprising a. -. said" to define an element does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the device-like embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of methods, apparatus, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart and block diagrams may represent a module, segment, or portion of code, which comprises one or more computer-executable instructions for implementing the logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. It will also be noted that each block of the block diagrams and flowchart illustrations, and combinations of blocks in the block diagrams and flowchart illustrations, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Claims (11)
1. A method for describing and distributing edge cloud multi-level computing, the method comprising:
the cloud analysis component receives and analyzes the calculation service description template sent by the user, generates a hierarchical node resource requirement and a calculation logic deployment requirement, and sends the hierarchical node resource requirement and the calculation logic deployment requirement to the cloud distribution deployment component;
the cloud distribution deployment component determines a hierarchical node matched with the hierarchical node resource demand, acquires hierarchical node resources and computational logic resources based on the hierarchical node resource demand and the computational logic deployment demand, and distributes the hierarchical node resources and the computational logic resources to the matched hierarchical node;
and the terminal deployment component of the hierarchical node initializes the computing environments of the hierarchical nodes of different types according to the received hierarchical node resources, and locally stores, loads and processes the computing logic resources.
2. The method of claim 1, wherein the computation service description template defines the computation power needed by the user, the computation logic resources used, and whether resilient scalability is needed.
3. The method according to claim 1, comprising in particular: searching and determining a matched hierarchical node according to the hierarchical node resource demand, acquiring a hierarchical node resource corresponding to the hierarchical node resource demand from a node resource management component, acquiring a computational logic resource corresponding to the computational logic deployment demand from a computational logic storage component, and distributing the hierarchical node resource and the computational logic resource to the matched hierarchical node.
4. The method of claim 1, wherein the different types of hierarchical nodes are heterogeneous network nodes, including strong nodes and weak nodes.
5. The method according to claim 1, wherein the end deployment component of the hierarchical node initializes the computing environments of the different types of hierarchical nodes according to the received hierarchical node resources, and locally stores and loads the processing of the computing logic resources, specifically comprising: the capacity of virtual machine (kvm), container (docker) and container arrangement (k8s) is provided at the strong node, and the capacity of function calculation and native application is provided at the weak node.
6. The method of claim 1, wherein the different types of hierarchical nodes include at least one of: internet data center IDC node, mobile edge computing MEC node, end node.
7. The method of claim 1, wherein the distribution is performed using normal file downloading or accelerated transmission over a network.
8. A system for describing and distributing multi-level computing of an edge cloud, the system comprising: the cloud and different types of hierarchical nodes; wherein, the cloud includes at least:
the cloud analysis component is used for receiving and analyzing the computing service description template sent by the user, generating a hierarchical node resource requirement and a computing logic deployment requirement and sending the hierarchical node resource requirement and the computing logic deployment requirement to the cloud distribution deployment component;
the cloud distribution and deployment component is used for determining a hierarchical node matched with the hierarchical node resource demand, acquiring hierarchical node resources and computational logic resources based on the hierarchical node resource demand and the computational logic deployment demand, and distributing the hierarchical node resources and the computational logic resources to the matched hierarchical node;
the hierarchical node includes at least:
and the end deployment component is used for receiving the hierarchical node resources and the computational logic resources sent by the cloud end, initializing the computational environments of the hierarchical nodes of different types according to the hierarchical node resources, and locally storing, loading and processing the computational logic resources.
9. The system of claim 8, wherein the cloud further comprises:
the node resource management component is used for being responsible for storage, detection and matching of the hierarchical node resources;
and the computation logic storage component is used for being responsible for storage, authentication and matching of the computation logic resources.
10. A device for describing and distributing multi-level computing of an edge cloud, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any one of claims 1 to 6 when executing the computer program.
11. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 6.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113300854A (en) * | 2021-05-21 | 2021-08-24 | 重庆紫光华山智安科技有限公司 | Edge node capability expansion method, system and expansion box |
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