CN113722109A - Containerized edge computing intelligent service engine system - Google Patents
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- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
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- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
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Abstract
The invention discloses a containerized edge computing intelligent service engine system. The system comprises a containerized edge computing module and an edge application management platform, wherein: the containerized edge calculation module is configured to: containerizing edge intelligent service at an edge computing service node; monitoring and predicting the network in real time through an edge computing central node in the edge computing network, and reallocating network resources of an edge computing service node cluster by utilizing a container arrangement technology based on a monitoring result; and enabling different network nodes in the edge computing network to utilize different node functions; the edge application management platform is used for uniformly managing the containerized edge computing modules. The invention realizes more effective utilization of network resources and can meet the increasing network resource requirements.
Description
Technical Field
The invention relates to the technical field of internet, in particular to a containerized edge computing intelligent service engine system.
Background
The Internet of things is an expanded application and network extension of a communication network and the Internet, and the Internet of things utilizes a sensing technology and intelligent equipment to sense and identify the physical world, carries out calculation, processing and knowledge mining through network transmission and interconnection, realizes information interaction and seamless link between people and objects, and realizes the purposes of real-time control, accurate management and scientific decision making of the physical world.
With the rapid development of the related technologies of the industrial chain of the internet of things, the traditional industry and the internet of things become a necessary way and an effective way for upgrading and modifying the industry. With the continuous integration and innovation of the traditional industry and the internet of things, the number of the network edge side terminals is continuously increased, and the resource demand for the network is more and more. Due to the limited bandwidth carrying capacity of the network, the traditional cloud-based centralized computing processing mode has difficulty in meeting the requirements of a large number of edge devices. In order to solve the problem of network resource demand, an edge computing technology is introduced based on a traditional cloud centralized computing processing mode, and the problem of network resource demand is effectively solved. Edge computing means that an open platform integrating network, computing, storage and application core capabilities is adopted on one side close to an object or a data source to provide nearest-end services nearby. The application program is initiated at the edge side, so that a faster network service response is generated, and the basic requirements of the industry in the aspects of real-time business, application intelligence, safety, privacy protection and the like are met. The edge computing technology has the characteristics of low time delay, high speed and the like, and is widely realized in a plurality of application scenes of the internet of things nowadays.
However, although the edge calculation effectively solves the problem of network resource requirement, as the algorithm and application technology of the edge terminal gradually develop, the difficulty of adapting to the underlying device increases. Manual physical adaptation is time consuming, labor intensive and extremely costly. Meanwhile, the traditional application deploys and uses the virtual machine, and virtualization provided by the virtual machine needs to consume a large amount of resources, so that the whole system becomes heavy, and meanwhile, the function expansion is more limited, the expansion is difficult, and the service performance is reduced. Therefore, in order to solve the above problems, the container technology is adopted in combination with the edge calculation to effectively improve the network efficiency.
A container is a technology that a developer packages a developed application (system) and a required development environment, and then the application can run on different computers through the container without reconfiguring the relevant environment, except that each computer needs to configure a container engine for running the container. The container technology has the characteristics of extremely light weight, second-level deployment, easiness in transplantation, elastic expansion and the like. However, in the prior art, no efficient containerized edge computation engine exists.
Disclosure of Invention
The object of the present invention is to overcome the above mentioned drawbacks of the prior art, and to provide a containerized edge computing intelligent service engine system, which comprises: a containerized edge computing module and an edge application management platform, wherein:
the containerized edge calculation module is configured to: containerizing edge intelligent service at an edge computing service node; monitoring and predicting the network in real time through an edge computing central node in the edge computing network, and reallocating network resources of an edge computing service node cluster by utilizing a container arrangement technology based on a monitoring result; and enabling different network nodes in the edge computing network to utilize different node functions;
the edge application management platform is used for uniformly managing the containerized edge computing modules.
Compared with the prior art, the invention has the advantages that the containerization edge computing intelligent service engine is designed by combining the technical characteristics of containerization and edge computing, so that the network resources are more effectively utilized, the network performance is improved, and the increasing network resource requirements can be met. The invention solves the problem of insufficient network resources caused by the access of large-scale industrial edge equipment to the network.
Other features of the present invention and advantages thereof will become apparent from the following detailed description of exemplary embodiments thereof, which proceeds with reference to the accompanying drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description, serve to explain the principles of the invention.
FIG. 1 is an architecture diagram of a containerized edge computing intelligence services engine according to one embodiment of the present invention;
FIG. 2 is a schematic diagram of a containerization technique for edge-based computing intelligence services according to one embodiment of the present invention;
FIG. 3 is a schematic diagram of a container orchestration technique based on edge computing intelligence services according to one embodiment of the invention;
FIG. 4 is a schematic diagram of an edge computing based container platform architecture, according to one embodiment of the invention.
Detailed Description
Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that: 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 invention unless specifically stated otherwise.
The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses.
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.
Referring to fig. 1, the provided containerized edge computing intelligent service engine system architecture includes an edge device side, a containerized edge computing module, and an edge application management platform. In this embodiment, the containerization edge calculation module generally includes a containerization module S2, a container orchestration module S3, and an edge computing container platform S4. The edge device can be various types of electronic devices, and when the edge device responds to the edge intelligent service, the containerized edge computing module is used for more effectively utilizing network resources, so that the network redundancy is effectively reduced, and the network performance is improved.
The containerization edge calculation module is used as a core module of the invention and mainly relates to a containerization technology, a container arrangement technology and the like. Referring to fig. 2, for the containerization module S2, the containerization technology is used to containerize the edge intelligent service at the edge computing service node, and based on the characteristics of the container technology, such as extreme light weight, second-level deployment, easy transplantation, and elastic expansion, the cost of the edge intelligent service can be effectively reduced, and the network throughput and performance can be improved. For example, container 1 is used for data analysis, container 2 is used for state awareness, container 3 is used for node self-inspection, container N is used for edge intelligence application services, and the like.
As shown in fig. 3, for the container arrangement module S3, the edge computation center node in the edge computation network monitors and predicts the network in real time by using the control module, and then reallocates the network resources of the edge computation service node cluster by using the container arrangement technology according to the monitoring result, so as to effectively utilize the network real-time resources. By organizing the containers and operating according to a plan, network resources can be reasonably scheduled in real time.
The architecture of the edge computing container platform S4 is shown in fig. 4, where nodes in a cluster are composed of edge intelligent devices, and can be divided into three types, i.e., edge center nodes, edge network nodes, and edge service nodes. Each node is provided with a Docker operating environment, for example, and operates different numbers of containers, and a container cluster is formed among the containers to provide services to the outside. Wherein the edge center node is responsible for controlling the orchestration of the distributed clusters. The control node is the brain of a node cluster in the converged network and is responsible for monitoring, managing and scheduling computing, storage and network resources in the network. The control node communicates with the edge intelligent device responsible for network forwarding through an OpenFlow protocol, and grasps the network topology in real time. The edge network node is an intelligent node responsible for network switching and provides a data switching function as a switching node in the cluster. And a network topology is constructed among the edge network nodes to complete platform networking. The edge network node can also construct a wireless AP as an access point of the network, and provides wireless network access capability. The edge service node is an intelligent node responsible for providing container services, is directly connected with the edge network node, operates and utilizes a virtualization function provided by the Docker engine to host the container-based Internet of things service.
It should be noted that, in the container platform architecture based on edge computing, in consideration that all containers in a single-node container cluster share resources such as memory and CPU on one host, a node needs to have higher resource configuration, and a node with low configuration cannot be effectively utilized. Based on the container platform architecture of the edge computing, different network nodes in the edge computing network are energized, and different node functions are utilized, so that cluster resources are effectively scheduled.
In summary, because the bandwidth carrying capacity of the network is limited, it is difficult for the traditional cloud-based centralized computing processing method to meet a large amount of requirements of the edge devices. The invention provides a containerized edge computing intelligent service engine, which solves the problem of the requirement of massive edge equipment on network resources by using edge computing and container technology and improves the network performance and the network resource utilization efficiency. In short, based on the container technology of the edge computing intelligent service, the edge computing intelligent service is containerized by using the characteristics of edge computing nodes, so that the intelligent service is more portable and lighter; based on the container arrangement technology of the edge computing intelligent service, the edge computing network architecture is utilized, and the container arrangement technology is used for edge computing in the network through the edge computing center node, so that each edge computing node can more effectively containerize the edge computing intelligent service, and the network resources of the edge computing nodes are more effectively utilized; furthermore, by expanding the single-node container cluster into a multi-node container cluster, the low-cost nodes are fully utilized to run the containerization edge cloud platform service.
The present invention may be a system, method and/or computer program product. The computer program product may include a computer-readable storage medium having computer-readable program instructions embodied therewith for causing a processor to implement various aspects of the present invention.
The computer readable storage medium may be a tangible device that can hold and store the instructions for use by the instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a Static Random Access Memory (SRAM), a portable compact disc read-only memory (CD-ROM), a Digital Versatile Disc (DVD), a memory stick, a floppy disk, a mechanical coding device, such as punch cards or in-groove projection structures having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media as used herein is not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., optical pulses through a fiber optic cable), or electrical signals transmitted through electrical wires.
The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to a respective computing/processing device, or to an external computer or external storage device via a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. The network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing/processing device.
The computer program instructions for carrying out operations of the present invention may be assembler instructions, Instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C + +, Python, or the like, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, aspects of the present invention are implemented by personalizing an electronic circuit, such as a programmable logic circuit, a Field Programmable Gate Array (FPGA), or a Programmable Logic Array (PLA), with state information of computer-readable program instructions, which can execute the computer-readable program instructions.
Aspects of the present invention are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.
These computer-readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, 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/acts specified in the flowchart and/or block diagram block or blocks. These computer-readable program instructions may also be stored in a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer-readable medium storing the instructions comprises an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions. It is well known to those skilled in the art that implementation by hardware, by software, and by a combination of software and hardware are equivalent.
Having described embodiments of the present invention, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein. The scope of the invention is defined by the appended claims.
Claims (10)
1. A containerized edge computing smart service engine system comprising: a containerized edge computing module and an edge application management platform, wherein:
the containerized edge calculation module is configured to: containerizing edge intelligent service at an edge computing service node; monitoring and predicting the network in real time through an edge computing central node in the edge computing network, and reallocating network resources of an edge computing service node cluster by utilizing a container arrangement technology based on a monitoring result; and enabling different network nodes in the edge computing network to utilize different node functions;
the edge application management platform is used for uniformly managing the containerized edge computing modules.
2. The system of claim 1, wherein the containerization edge computing module comprises a containerization module, a container arrangement module, and an edge computing container platform, wherein the containerization module is configured to containerize an edge intelligence service to obtain a plurality of containers; the container arranging module is used for reallocating network resources of the edge computing service node cluster by using a container arranging technology so as to allocate the obtained multiple containers to target nodes for operation; the edge computing container platform is used to energize different network nodes in an edge computing network to utilize different node functions.
3. The system of claim 2, wherein the containerization module divides the services implemented by each container and the dependent resources according to the functions of the edge intelligent services.
4. The system according to claim 2, wherein the nodes in the edge computing container platform cluster are composed of edge intelligent devices, and are divided into edge center nodes, edge network nodes, and edge service nodes according to functions, and each node runs different numbers of containers, and the containers form a container cluster between the containers to provide services to the outside.
5. The system of claim 4, wherein the edge center node is responsible for controlling orchestration of distributed clusters; the edge network node is an intelligent node responsible for network exchange and is used as an exchange node in the cluster to provide a data exchange function; the edge service node is an intelligent node responsible for providing container services, is directly connected with the edge network node, operates and utilizes a virtualization function provided by a Docker engine to host a container-based Internet of things service.
6. The system according to claim 4, wherein the control node in the edge center node is a brain of a node cluster in the converged network, and is responsible for monitoring, managing and scheduling computing, storage and network resources in the network; and the control node communicates with the edge intelligent device responsible for network forwarding through an OpenFlow protocol, and grasps the network topology in real time.
7. The system of claim 5, wherein a network topology is constructed between the edge network nodes to complete platform networking, or the edge network nodes construct a wireless AP as an access point of a network to provide wireless network access capability.
8. The system of claim 4, wherein the edge computing container platform comprises a control module and an edge center node module, the control module is configured to perform real-time monitoring and prediction on a network and feed back a monitoring result to the container arrangement module, and the edge center node module controls and arranges the distributed cluster by interacting with the container arrangement module.
9. A computer-readable storage medium, on which a computer program is stored, wherein the program, when executed by a processor, performs the steps of:
containerizing edge intelligent service at an edge computing service node;
monitoring and predicting the network in real time through an edge computing central node in the edge computing network, and reallocating network resources of an edge computing service node cluster by utilizing a container arrangement technology based on a monitoring result;
and enabling different network nodes in the edge computing network to utilize different node functions.
10. A computer device comprising a memory and a processor, on which memory a computer program is stored that is executable on the processor, wherein the processor implements a containerized edge computing module and an edge application management platform in the system of any one of claims 1 to 8 when executing the program.
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