CN114500539A - Edge application deployment method and device in intelligent street lamp system and readable storage medium - Google Patents

Edge application deployment method and device in intelligent street lamp system and readable storage medium Download PDF

Info

Publication number
CN114500539A
CN114500539A CN202210386954.5A CN202210386954A CN114500539A CN 114500539 A CN114500539 A CN 114500539A CN 202210386954 A CN202210386954 A CN 202210386954A CN 114500539 A CN114500539 A CN 114500539A
Authority
CN
China
Prior art keywords
edge
node
target
application
lamp
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202210386954.5A
Other languages
Chinese (zh)
Other versions
CN114500539B (en
Inventor
项冀胤
杨征
方堃
陈哲
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Hangzhou Reqe Information Technology Co ltd
Original Assignee
Zhejiang Dayun Iot Technology Co ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Zhejiang Dayun Iot Technology Co ltd filed Critical Zhejiang Dayun Iot Technology Co ltd
Priority to CN202210386954.5A priority Critical patent/CN114500539B/en
Publication of CN114500539A publication Critical patent/CN114500539A/en
Application granted granted Critical
Publication of CN114500539B publication Critical patent/CN114500539B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/10—Protocols in which an application is distributed across nodes in the network
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F8/00—Arrangements for software engineering
    • G06F8/60—Software deployment
    • G06F8/61—Installation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/50—Network service management, e.g. ensuring proper service fulfilment according to agreements
    • H04L41/5041—Network service management, e.g. ensuring proper service fulfilment according to agreements characterised by the time relationship between creation and deployment of a service
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/34—Network arrangements or protocols for supporting network services or applications involving the movement of software or configuration parameters 
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B20/00—Energy efficient lighting technologies, e.g. halogen lamps or gas discharge lamps
    • Y02B20/40—Control techniques providing energy savings, e.g. smart controller or presence detection

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Software Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Stored Programmes (AREA)
  • Lighting Device Outwards From Vehicle And Optical Signal (AREA)

Abstract

The application provides an edge application deployment method, an edge application deployment device and a readable storage medium in an intelligent street lamp system, wherein a resource utilization rate of each single lamp edge node corresponding to an area identifier is obtained by receiving an edge application deployment instruction, and at least one target edge node is determined from each edge cloud node and each single lamp edge node corresponding to the area identifier based on a data volume level and a dependency relationship corresponding to an edge application to be deployed and the resource utilization rate of each single lamp edge node; for each target edge node, determining the target resource type of the target edge node and the target quantity of the edge applications to be deployed, which need to be installed by the target edge node, and issuing the target quantity of the edge application installation packages to be deployed to the target edge node so as to complete the edge application deployment at the target edge node. The scheme can realize efficient large-scale edge application deployment in the intelligent street lamp system.

Description

Edge application deployment method and device in intelligent street lamp system and readable storage medium
Technical Field
The application relates to the technical field of Internet of things and edge computing, in particular to an edge application deployment method and device in an intelligent street lamp system and a readable storage medium.
Background
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 computation is between the physical entity and the industrial connection, or on top of the physical entity.
The intelligent street lamp system also utilizes an edge computing technology, and comprises a cloud management platform and edge gateways which can be respectively communicated with the cloud management platform and are arranged on the street lamps, one or more edge computing applications are deployed on the edge gateways of the street lamps according to actual requirements, and then the edge computing applications are utilized to execute specific functions to provide corresponding services.
In the prior art, when edge application deployment is performed, different edge nodes are deployed respectively in a manual deployment mode, or batch deployment of edge nodes adopting container resource types is realized through a container technology, however, a huge number of edge nodes (edge gateways or edge clouds) are included in the smart street lamp system, and the edge computing resource types adopted by the huge number of edge nodes are often different, so that if an existing manual deployment mode or a deployment mode for container resources is adopted, the problems that deployment efficiency is low and comprehensive deployment cannot be realized are brought. Meanwhile, in the existing deployment manner, when the idle resources of the edge node are insufficient, the performance of the edge application running on the edge node is affected, and in order to implement efficient large-scale edge application deployment in the intelligent street lamp system and ensure the performance of the deployed edge application, a new edge deployment method is urgently needed.
Disclosure of Invention
The purpose of this application aims at solving at least one of the above technical defects, and the technical solution provided by this application embodiment is as follows:
in a first aspect, an embodiment of the present application provides a method for deploying edge applications in an intelligent street lamp system, including:
receiving an edge application deployment instruction, wherein the edge application deployment instruction comprises an area identifier and an edge application identifier to be deployed;
acquiring edge cloud nodes and single-lamp edge nodes corresponding to the area identification, the subordination relation between each edge cloud node and each single-lamp edge node, the resource type of each edge cloud node and the resource type of each single-lamp edge node, and acquiring the data volume level corresponding to the edge application to be deployed corresponding to the edge application identification to be deployed;
acquiring the resource utilization rate of each single-lamp edge node corresponding to the area identifier, and determining at least one target edge node from each edge cloud node and each single-lamp edge node corresponding to the area identifier based on the data volume level and the dependency corresponding to the edge application to be deployed and the resource utilization rate of each single-lamp edge node;
for each target edge node, determining the target resource type of the target edge node based on the resource type of each edge cloud node corresponding to the area identifier and the resource type of each single-lamp edge node, acquiring an edge application installation package to be deployed matched with the target resource type, determining the target number of the edge applications to be deployed, which need to be installed by the target edge node, and issuing the target number of the edge application installation packages to be deployed to the target edge node, so as to complete edge application deployment at the target edge node.
In an optional embodiment, determining at least one target edge node from each edge cloud node and each single-light edge node corresponding to the area identifier based on the data volume level and the dependency corresponding to the edge application to be deployed and the resource utilization rate of each single-light edge node includes:
if the data volume level corresponding to the edge application to be deployed is not less than the preset level, determining each edge cloud node corresponding to the area identifier as a target edge node;
and if the data volume level corresponding to the edge application to be deployed is smaller than the preset level, determining at least one target edge node from each edge cloud node and each single-lamp edge node corresponding to the area identifier based on the dependency relationship and the resource utilization rate of each single-lamp edge node.
In an optional embodiment, if the data volume level corresponding to the edge node to be deployed is less than the preset level, determining at least one target edge node from each edge cloud node and each single-lamp edge node corresponding to the area identifier based on the dependency relationship and the resource utilization rate of each single-lamp edge node, including:
acquiring the resource utilization condition of each single-lamp edge node corresponding to the area identifier through each edge cloud node corresponding to the area identifier;
for any edge cloud node, acquiring each single-lamp edge node belonging to the edge cloud node based on the subordination relation, and if the resource utilization rate of the single-lamp edge nodes not less than a first preset number is not less than a first preset value in the single-lamp edge nodes belonging to the edge cloud node, determining the edge cloud node as a target edge node;
and if the resource utilization rate of only the single lamp edge nodes with the number less than the first preset number in the single lamp edge nodes subordinate to the edge cloud node is not less than the first preset value, determining the single lamp edge nodes subordinate to the edge cloud node as target edge nodes.
In an alternative embodiment, determining the target number of the edge applications to be deployed that need to be installed by the target edge node includes:
if the target edge nodes are edge cloud nodes, determining the number of single lamp edge nodes corresponding to the edge cloud nodes based on the membership relationship, and determining the number of targets based on the number of the edge nodes, wherein the number of the targets is in a direct proportion relationship with the number of the single lamp edge nodes corresponding to the edge cloud nodes;
and if the target edge nodes are single-lamp edge nodes, determining that the target number is 1.
In an alternative embodiment, the method further comprises:
before receiving an edge application deployment instruction, acquiring edge application installation packages of different resource types corresponding to each edge application identifier, marking each edge application installation package with the corresponding edge application identifier and the corresponding resource type, and storing the edge application installation packages to obtain a preset edge application installation package library;
correspondingly, obtaining the edge application installation package to be deployed matched with the target resource type comprises the following steps:
and acquiring the application installation package to be deployed from a preset edge application installation package library based on the edge application identifier to be deployed and the target resource type.
In an optional embodiment of the present application, issuing a target number of edge application installation packages to be deployed to the target edge node to complete edge application deployment at the target edge node includes:
if the resource type of the target edge node is a container type, installing target quantity of edge application installation packages to be deployed on the target edge node through a container cluster interface;
and if the resource type of the target edge node is the virtual machine type, installing the target number of edge application installation packages to be deployed on the target edge node through the corresponding proxy server.
In an alternative embodiment, the method further comprises:
before receiving an edge application deployment instruction, acquiring edge cloud nodes and single lamp edge nodes corresponding to each area identifier, a subordinate relationship between each edge cloud node and each single lamp edge node, a resource type of each edge cloud node and a resource type of each single lamp edge node, and correspondingly storing the edge cloud nodes and the single lamp edge nodes corresponding to each area identifier, the subordinate relationship between each edge cloud node and each single lamp edge node, the resource types of each edge cloud node and the resource types of each single lamp edge node to obtain a preset edge node relationship table;
updating a preset edge node relation table every a first preset period;
correspondingly, acquiring the edge cloud nodes and the single-lamp edge nodes corresponding to the area identifier, the membership between each edge cloud node and each single-lamp edge node, the resource types of each edge cloud node and the resource types of each single-lamp edge node includes:
based on the area identification, the edge cloud nodes and the single-lamp edge nodes corresponding to the area identification, the affiliation between each edge cloud node and each single-lamp edge node, the resource types of each edge cloud node and the resource types of each single-lamp edge node are obtained from a preset edge node relation table.
In an alternative embodiment, the method further comprises:
before receiving an edge application deployment instruction, acquiring a data volume level corresponding to an edge application corresponding to each edge application identifier, and correspondingly storing each edge application identifier and the data volume level corresponding to each edge application to obtain a preset edge application data volume level table;
updating a preset edge application data volume level table every second preset period;
correspondingly, acquiring the data volume level corresponding to the edge application to be deployed identifier includes:
and acquiring the data volume level corresponding to the edge application to be deployed from the preset edge application data volume level table based on the edge application identification to be deployed.
In a second aspect, an embodiment of the present application provides an edge application deployment device in an intelligent street lamp system, including:
the deployment instruction receiving module is used for receiving an edge application deployment instruction, and the edge application deployment instruction comprises an area identifier and an edge application identifier to be deployed;
the resource type determining module is used for acquiring the edge cloud nodes and the single-lamp edge nodes corresponding to the area identifiers, the subordination relation between each edge cloud node and each single-lamp edge node, the resource type of each edge cloud node and the resource type of each single-lamp edge node, and acquiring the data volume level corresponding to the edge application to be deployed corresponding to the edge application identifier to be deployed;
the target edge node determining module is used for acquiring the resource utilization rate of each single-lamp edge node corresponding to the area identifier, and determining at least one target edge node from each edge cloud node and each single-lamp edge node corresponding to the area identifier based on the data volume level and the dependency corresponding to the edge application to be deployed and the resource utilization rate of each single-lamp edge node;
and the application deployment module is used for determining the target resource type of each target edge node based on the resource type of each edge cloud node corresponding to the area identifier and the resource type of each single-lamp edge node, acquiring an edge application installation package to be deployed matched with the target resource type, determining the target number of the edge applications to be deployed, which need to be installed by the target edge node, and issuing the target number of the edge application installation packages to be deployed to the target edge node so as to complete edge application deployment at the target edge node.
In an optional embodiment, the target edge node determination module is further configured to:
if the data volume level corresponding to the edge application to be deployed is not less than the preset level, determining each edge cloud node corresponding to the area identifier as a target edge node;
and if the data volume level corresponding to the edge application to be deployed is smaller than the preset level, determining at least one target edge node from each edge cloud node and each single-lamp edge node corresponding to the area identifier based on the dependency relationship and the resource utilization rate of each single-lamp edge node.
In an optional embodiment, the target edge node determination module is further configured to:
acquiring the resource utilization condition of each single-lamp edge node corresponding to the area identifier through each edge cloud node corresponding to the area identifier;
for any edge cloud node, acquiring each single-lamp edge node subordinate to the edge cloud node based on the subordination relation, and if the resource utilization rate of the single-lamp edge nodes which are not less than a first preset number in the single-lamp edge nodes subordinate to the edge cloud node is not less than a first preset value, determining the edge cloud node as a target edge node;
and if the resource utilization rate of only the single lamp edge nodes with the number less than the first preset number in the single lamp edge nodes subordinate to the edge cloud node is not less than the first preset value, determining the single lamp edge nodes subordinate to the edge cloud node as target edge nodes.
In an optional embodiment, the application deployment module is further to:
if the target edge nodes are edge cloud nodes, determining the number of single lamp edge nodes corresponding to the edge cloud nodes based on the membership relationship, and determining the number of targets based on the number of the single lamp edge nodes, wherein the number of the targets is in a direct proportion relationship with the number of the single lamp edge nodes corresponding to the edge cloud nodes;
and if the target edge nodes are single-lamp edge nodes, determining that the target number is 1.
In an optional embodiment, the apparatus further comprises an installation package library building module configured to:
before receiving an edge application deployment instruction, acquiring edge application installation packages of different resource types corresponding to each edge application identifier, marking each edge application installation package with the corresponding edge application identifier and the corresponding resource type, and storing the edge application installation packages to obtain a preset edge application installation package library;
accordingly, the application deployment module is further to:
and acquiring the edge application installation package to be deployed from a preset edge application installation package library based on the edge application identifier to be deployed and the target resource type.
In an optional embodiment, the application deployment module is further to:
if the resource type of the target edge node is a container type, installing a target number of edge application installation packages to be deployed on the target edge node through a container cluster interface;
and if the resource type of the target edge node is the virtual machine type, installing the target number of edge application installation packages to be deployed on the target edge node through the corresponding proxy server.
In an optional embodiment, the apparatus further comprises a node relation table building module configured to:
before receiving an edge application deployment instruction, acquiring edge cloud nodes and single lamp edge nodes corresponding to each area identifier, a subordinate relationship between each edge cloud node and each single lamp edge node, a resource type of each edge cloud node and a resource type of each single lamp edge node, and correspondingly storing the edge cloud nodes and the single lamp edge nodes corresponding to each area identifier, the subordinate relationship between each edge cloud node and each single lamp edge node, the resource types of each edge cloud node and the resource types of each single lamp edge node to obtain a preset edge node relationship table;
updating a preset edge node relation table every a first preset period;
accordingly, the resource type determination module is further configured to:
based on the area identification, the edge cloud nodes and the single lamp edge nodes corresponding to the area identification, the subordinate relations between the edge cloud nodes and the single lamp edge nodes, the resource types of the edge cloud nodes and the resource types of the single lamp edge nodes are obtained from a preset edge node relation table.
In an optional embodiment, the apparatus further comprises a data volume level table building module configured to:
before receiving an edge application deployment instruction, acquiring a data volume level corresponding to an edge application corresponding to each edge application identifier, and correspondingly storing each edge application identifier and the data volume level corresponding to each edge application to obtain a preset edge application data volume level table;
updating a preset edge application data volume level table every second preset period;
accordingly, the resource type determination module is further configured to:
and acquiring the data volume level corresponding to the edge application to be deployed and corresponding to the edge application to be deployed from a preset edge application data volume level table based on the edge application identification to be deployed.
In a third aspect, an embodiment of the present application provides an electronic device, including a memory and a processor;
the memory has a computer program stored therein;
a processor for executing a computer program for implementing the method provided in any of the alternative embodiments of the present application.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium storing a computer program, which when executed by a processor implements the method provided in any of the alternative embodiments of the present application.
The technical scheme that this application provided can bring following beneficial effect:
the method comprises the steps of determining edge cloud nodes and single-lamp edge nodes of an application deployment area, the subordination relation between each edge cloud node and each single-lamp edge node, the resource type of each edge cloud node and the resource type of each single-lamp edge node which need to be applied and deployed through an area identifier and an edge application identifier to be deployed in a received edge application deployment instruction, then determining at least one target edge node from each edge cloud node and each single-lamp edge node corresponding to the area identifier according to the data volume level and the subordination relation corresponding to the edge application to be deployed and the resource utilization rate of each single-lamp edge node, and installing an edge application installation package to be deployed of the corresponding resource type on each target edge node, so that deployment of the edge application of the intelligent street lamp system is achieved. According to the scheme, on one hand, in the process of determining the target edge node for deploying the edge application to be deployed, the data volume level corresponding to the edge application to be deployed and the resource utilization rate of each single-lamp edge node are considered, so that the target edge node can provide enough computing capacity and computing resources after the edge application to be deployed is deployed, and the performance of the edge application to be deployed is further ensured; on the other hand, the scheme can issue the matched edge application installation package to be deployed for the target edge node according to the resource type of the target edge node, so that the application deployment of the target edge node with different resource types can be realized. To sum up, this scheme can realize that high efficiency, large-scale edge application in wisdom street lamp system deploy.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings used in the description of the embodiments of the present application will be briefly described below.
Fig. 1 is an overall architecture diagram of an intelligent street lamp system according to an embodiment of the present disclosure;
fig. 2 is a schematic flowchart illustrating an edge application deployment method in an intelligent street lamp system according to an embodiment of the present disclosure;
fig. 3 is a partial schematic flow chart illustrating an edge application deployment method in an intelligent street lamp system according to another embodiment of the present disclosure;
fig. 4 is a partial schematic flowchart of an edge application deployment method in an intelligent street lamp system according to another embodiment of the present disclosure;
fig. 5 is a schematic diagram of a part of contents of a preset edge node relationship table according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of an edge application deployment device in an intelligent street lamp system according to an embodiment of the present disclosure;
fig. 7 is a schematic partial structural view of an edge application deployment device in an intelligent street lamp system according to another embodiment of the present application.
Detailed Description
Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary only for the purpose of explaining the present application and are not to be construed as limiting the present application.
As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may also be present. Further, "connected" or "coupled" as used herein may include wirelessly connected or wirelessly coupled. As used herein, the term "and/or" includes all or any element and all combinations of one or more of the associated listed items.
In view of the foregoing problems, embodiments of the present application provide a method, an apparatus, and a readable storage medium for deploying an edge application in an intelligent street lamp system. The following describes the technical solutions of the present application and how to solve the above technical problems with specific embodiments in conjunction with the accompanying drawings. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments.
Fig. 1 is an overall architecture diagram of an intelligent street lamp system according to an embodiment of the present disclosure. The edge application deployment scheme provided by the present application can be implemented based on this architecture. This wisdom street lamp system can include: the system comprises a cloud management platform 101 and edge gateways 102 (namely single-lamp edge nodes) arranged on each street lamp, wherein each edge gateway 102 can be in communication connection with the cloud management platform 101 in various ways, and operation and maintenance personnel can issue various management commands to each edge gateway 102 by logging in the cloud management platform 101. In addition, the smart street lamp system may further include a plurality of edge clouds 103 (i.e., edge cloud nodes), each edge cloud 103 communicates with a plurality of edge gateways 102 belonging to the edge cloud 103, and generally, the computing capacity of the edge cloud 103 is much higher than that of the edge gateways 102, so as to undertake an edge computing task with a large computing amount.
Fig. 2 is a schematic flow chart illustrating an edge application deployment method in an intelligent street lamp system according to an embodiment of the present disclosure. The execution subject of the method can be the cloud management platform shown in fig. 1. As shown in fig. 2, the method may include the steps of:
step S201, receiving an edge application deployment instruction, where the edge application deployment instruction includes an area identifier and an edge application identifier to be deployed.
The edge application deployment instruction can be sent to the cloud management platform by a single-lamp edge node or an edge cloud node when a preset trigger condition is triggered, or can be triggered by operation and maintenance personnel after logging in the cloud management platform according to actual requirements.
Specifically, after receiving the edge application deployment instruction, the cloud management platform can acquire the area where application deployment is required and what kind of edge application deployment is required according to the area identifier and the edge application identifier to be deployed included in the application deployment instruction. Wherein, the region that street lamp set up in the wisdom street lamp system can be divided into a plurality of regions in advance, and then this regional sign can include a plurality of fields, for example, regional sign includes following field in proper order: the method comprises a province field, a city field, an administrative district field and a street field, wherein the fields can be used for determining a street needing application deployment, further determining edge cloud nodes and single-lamp edge nodes contained in the street, and then needing edge application deployment in the nodes.
Step S202, obtaining edge cloud nodes and single-lamp edge nodes corresponding to the area identifiers, the affiliation between each edge cloud node and each single-lamp edge node, the resource type of each edge cloud node and the resource type of each single-lamp edge node, and obtaining the data volume level corresponding to the edge application to be deployed corresponding to the edge application identifier to be deployed.
The resource types of the single-lamp edge nodes or the edge cloud nodes may include a container type or a virtual machine type, and the deployment modes and the types of the installation packages adopted by different resource types when the edge application is deployed are different.
The data magnitude level corresponding to the edge application refers to the magnitude level of the data magnitude required to be processed by the edge application when the edge application provides the service, the data magnitude required to be processed by each edge application when the edge application provides the service can be counted in advance, the level division can be carried out, and the data magnitude level corresponding to the larger data magnitude is higher. For example, the data volume level of the image recognition class edge application is set higher than the data volume level of the data preprocessing class edge application.
Specifically, after the cloud management platform learns the edge cloud nodes and the single-lamp edge cloud nodes included in the area where the cloud application needs to be deployed according to the received edge application deployment instruction, the resource types of the edge cloud nodes and the single-lamp edge nodes are further acquired, and the dependency relationship between the edge cloud nodes and the single-lamp edge nodes is acquired. Based on the dependency relationship, which single-lamp edge nodes can communicate with which corresponding edge cloud node can be known. Meanwhile, after the cloud management platform knows what to-be-deployed edge application needs to be deployed according to the received edge application deployment instruction, the data volume level of the to-be-deployed edge application is further determined.
Step S203, obtaining resource utilization rates of the single-lamp edge nodes corresponding to the area identifier, and determining at least one target edge node from each edge cloud node and each single-lamp edge node corresponding to the area identifier based on the data volume level and the dependency relationship corresponding to the edge application to be deployed and the resource utilization rate of each single-lamp edge node.
Specifically, the resource utilization rate of each single-lamp edge node in the area where the edge application deployment is required is further obtained. And then, according to the obtained data volume level and the membership corresponding to the edge application to be deployed and the resource utilization rate of each single-lamp edge node, determining one or more target edge nodes from each edge cloud node and each single-lamp edge node in the area needing edge application deployment. The target edge node is an edge node to be finally installed by the edge application installation package to be deployed.
Specifically, in the process of determining the target edge node, firstly, the data volume level corresponding to the edge application to be deployed is considered, and in order to ensure that the edge application to be deployed can be matched with enough computing capacity, if the data volume level is higher, because the computing capacity of the edge cloud nodes is stronger, each edge cloud node can be preferentially determined as the target edge node; if the data level is low, each single-lamp edge node can be determined as a target edge node. Meanwhile, in order to ensure that the edge application to be deployed can be matched with enough computing resources, the resource utilization rate of each single-lamp edge node is further considered, if the resource utilization rate of the single-lamp edge node is too high and is not enough to support the normal operation of the edge application to be deployed, the edge cloud node to which the single-lamp edge node belongs is found according to the dependency relationship, and the corresponding edge cloud node is used as the target edge node. In other words, in the process of determining the target edge node, the above factors need to be considered, so that the edge application to be deployed can be matched with sufficient computing power and computing resources after being installed, and it is further ensured that each street lamp which needs to acquire the application service can acquire the service provided by the edge application to be deployed through a single lamp edge node.
It is to be understood that the target edge node may be one or more, and may include both an edge cloud node and a single-light edge node.
Step S204, for each target edge node, determining the target resource type of the target edge node based on the resource type of each edge cloud node corresponding to the area identifier and the resource type of each single-lamp edge node, acquiring an edge application installation package to be deployed matched with the target resource type, determining the target number of the edge applications to be deployed, which need to be installed by the target edge node, and issuing the target number of the edge application installation packages to be deployed to the target edge node so as to complete edge application deployment at the target edge node.
Specifically, after the target edge nodes are determined in the previous step, the deployment of the edge application can be completed only by installing the edge application installation packages to be deployed on each target edge node. Because the resource types of the target edge nodes are different and the types of the edge application installation packages to be deployed installed corresponding to the target edge nodes are also different, before the edge application installation packages to be deployed are obtained, the resource types of the target edge nodes and the target number of the edge applications to be deployed which need to be installed need to be determined, and then the target number of the edge application installation packages to be deployed are issued to the target edge nodes, so that the edge application deployment is completed at the target edge nodes.
According to the scheme provided by the embodiment of the application, the edge cloud nodes and the single lamp edge nodes of the area needing to be applied and deployed, the subordination between each edge cloud node and each single lamp edge node, the resource types of each edge cloud node and each single lamp edge node are determined according to the area identifier and the edge application identifier to be deployed in the received edge application deployment instruction, then at least one target edge node is determined from each edge cloud node and each single lamp edge node corresponding to the area identifier according to the data volume level and the subordination corresponding to the edge application to be deployed and the resource utilization rate of each single lamp edge node, an edge application installation package to be deployed corresponding to the resource types is installed on each target edge node, and therefore edge application deployment of the intelligent street lamp system is achieved. According to the scheme, on one hand, in the process of determining the target edge node for deploying the edge application to be deployed, the data volume level corresponding to the edge application to be deployed and the resource utilization rate of each single-lamp edge node are considered, so that the target edge node can provide enough computing capacity and computing resources after the edge application to be deployed is deployed, and the performance of the edge application to be deployed is further ensured; on the other hand, the scheme can issue the matched edge application installation package to be deployed for the target edge node according to the resource type of the target edge node, so that the application deployment of the target edge node with different resource types can be realized. To sum up, this scheme can realize that high efficiency, large-scale edge application in wisdom street lamp system deploy.
In an optional embodiment of the present application, as shown in fig. 3, determining at least one target edge node from each edge cloud node and each single-light edge node corresponding to the area identifier based on a data volume level and an affiliation corresponding to the edge application to be deployed and a resource utilization rate of each single-light edge node includes:
step S301, if the data volume level corresponding to the edge application to be deployed is not less than the preset level, determining each edge cloud node corresponding to the area identifier as a target edge node;
step S302, if the data volume level corresponding to the edge application to be deployed is smaller than a preset level, determining at least one target edge node from each edge cloud node and each single-lamp edge node corresponding to the area identifier based on the dependency relationship and the resource utilization rate of each single-lamp edge node.
Specifically, if the data volume level corresponding to the edge application to be deployed is not less than the preset level, it is considered that the edge application needs a larger computing capacity (for example, image recognition application for license plate recognition) when providing a service, and it can be considered that the computing capacity of the edge cloud node is much stronger than that of a single-lamp edge node, so that the edge cloud node is deployed on each edge cloud node corresponding to the area identifier instead of each single-lamp edge node, that is, each edge cloud node corresponding to the area identifier determines the target edge node. When the edge application to be deployed runs on the edge cloud node, each street lamp can acquire the service provided by the application to be deployed from the subordinate edge cloud node through the single lamp edge node.
If the data volume level corresponding to the edge application to be deployed is less than the preset level, the computing capacity required by the edge application to be deployed when the edge application provides the service is considered to be not large (for example, the data preprocessing application for data statistics), and at this time, the edge application to be deployed may be deployed at each edge cloud node corresponding to the area identifier, or may be deployed at each single-lamp edge node corresponding to the area identifier. Specifically, for each edge cloud node corresponding to the area identifier and each single-lamp edge node subordinate to the edge cloud node, whether the edge cloud node is determined as a target edge node or each single-lamp edge node is determined as a target edge node needs to be considered. It can be understood that the preset level may be set according to actual requirements, and the present application is not limited specifically.
Further, as shown in fig. 4, if the data volume level corresponding to the edge application to be deployed is less than the preset level, determining at least one target edge node from each edge cloud node and each single-light edge node corresponding to the area identifier based on the dependency relationship and the resource utilization rate of each single-light edge node, including:
step S401, acquiring resource utilization conditions of each single-lamp edge node corresponding to the area identifier through each edge cloud node corresponding to the area identifier;
step S402, for any edge cloud node, acquiring each single-lamp edge node belonging to the edge cloud node based on the subordination relation, and if the resource utilization rate of the single-lamp edge nodes not less than a first preset number in the single-lamp edge nodes belonging to the edge cloud node is not less than a first preset value, determining the edge cloud node as a target edge node;
in step S403, if only the resource utilization rate of the single-lamp edge nodes less than the first preset number is not less than the first preset value among the single-lamp edge nodes belonging to the edge cloud node, all the single-lamp edge nodes belonging to the edge cloud node are determined as the target edge node.
Specifically, if the data volume level corresponding to the edge application to be deployed is smaller than the preset level, the resource utilization rate of each single-lamp edge node corresponding to each edge cloud node corresponding to the area identifier needs to be further considered.
Specifically, for each edge cloud node, if the resource utilization rate of the single-lamp edge nodes not less than the first preset number among the single-lamp edge nodes belonging to the edge cloud node exceeds the first preset value, it may be considered that the resource utilization rate of the single-lamp edge nodes not less than the first preset number among the single-lamp edge nodes belonging to the edge cloud node is too high, and the number of the single-lamp edge nodes which cannot match the running resource requirement of the edge application to be deployed is large, so to ensure the resource requirement of the application to be deployed, the application to be deployed may be deployed at the edge cloud node, that is, the edge cloud node is determined as the target edge node.
If only the resource utilization rate of the single lamp edge nodes smaller than the first preset number exceeds the first preset value among the single lamp edge nodes belonging to the edge cloud node, it can be considered that the number of the single lamp edge nodes which cannot match the running resource demand of the edge application to be deployed is small, and the resource demand of the application to be deployed can be basically guaranteed, so that the application to be deployed can be deployed at the single lamp edge nodes belonging to the edge cloud node, that is, the single lamp edge nodes belonging to the edge cloud node are determined as target edge nodes.
It should be noted that each edge cloud node may obtain the resource utilization condition of each single-lamp edge node subordinate thereto, and then the cloud management platform obtains the resource utilization condition of each single-lamp edge node subordinate to each edge cloud node through each edge cloud node corresponding to the area identifier.
In an optional embodiment of the present application, determining a target number of edge applications to be deployed, which need to be installed by the target edge node, includes:
if the target edge nodes are edge cloud nodes, determining the number of single lamp edge nodes corresponding to the edge cloud nodes based on the subordination relation, and determining the number of targets based on the number of the single lamp edge nodes, wherein the number of the targets and the number of the single lamp edge nodes corresponding to the edge cloud nodes are in a direct proportion relation;
and if the target edge nodes are single-lamp edge nodes, determining that the target number is 1.
Specifically, after the target edge nodes are determined, the number of the edge applications to be deployed that need to be deployed in each target edge node needs to be further determined. Specifically, if the target edge node is a single-lamp edge node, one to-be-deployed edge application is directly deployed on the single-lamp edge node, and one to-be-deployed edge application can meet the application service requirement of the street lamp corresponding to the single-lamp edge node. If the target edge node is an edge cloud node, when determining the number of the edge applications to be deployed that need to be deployed, the number of the single-lamp edge nodes belonging to the edge cloud node needs to be considered, that is, the target number is proportional to the number of the single-lamp edge nodes belonging to the edge cloud node. Obviously, the larger the number of single-lamp edge nodes subordinate to the edge cloud node is, the larger the target number is, so as to ensure the real-time performance of the service provided by the edge application.
In an optional embodiment of the present application, the method may further comprise:
before receiving an edge application deployment instruction, acquiring edge application installation packages of different resource types corresponding to each edge application identifier, marking each edge application installation package with the corresponding edge application identifier and the corresponding resource type, and storing the edge application installation packages to obtain a preset edge application installation package library;
correspondingly, the obtaining of the edge application installation package to be deployed matched with the target resource type includes:
and acquiring the edge application installation package to be deployed from a preset edge application installation package library based on the edge application identifier to be deployed and the target resource type.
Specifically, before the cloud management platform receives the edge application deployment instruction, operation and maintenance personnel may set a preset edge application installation package library on the cloud management platform in advance, where the preset edge application installation package library is used for storing installation packages of different edge applications, and each edge application stores installation packages matched with different resource types, for example, for the same application, a container type installation package and a virtual machine type installation package may be stored at the same time. Then, labeling corresponding edge application identifiers and resource type identifiers on each installation package. And then, after receiving the edge application deployment instruction, the cloud management platform analyzes the edge application identifier to be deployed in the edge application deployment instruction, acquires the target resource type of the target edge node, and acquires the application installation package to be deployed from a preset edge application installation package library based on the edge application identifier to be deployed and the target resource type.
In an optional embodiment of the present application, issuing a target number of edge application installation packages to be deployed to the target edge node to complete edge application deployment at the target edge node includes:
if the resource type of the target edge node is a container type, installing a target number of edge application installation packages to be deployed on the target edge node through a container cluster interface;
and if the resource type of the target edge node is the virtual machine type, installing the target number of edge application installation packages to be deployed on the target edge node through the corresponding proxy server.
Specifically, for target edge nodes of different resource types, the installation modes of the to-be-deployed application installation packages are different, specifically, if the resource type of the target edge node is a container type, installing the target number of the to-be-deployed edge application installation packages on the target edge node through a container cluster interface; and if the resource type of the target edge node is the virtual machine type, installing the target number of edge application installation packages to be deployed on the target edge node through the corresponding proxy server.
In an optional embodiment of the present application, the method may further comprise:
before receiving an edge application deployment instruction, acquiring edge cloud nodes and single lamp edge nodes corresponding to each area identifier, a subordinate relationship between each edge cloud node and each single lamp edge node, a resource type of each edge cloud node and a resource type of each single lamp edge node, and correspondingly storing the edge cloud nodes and the single lamp edge nodes corresponding to each area identifier, the subordinate relationship between each edge cloud node and each single lamp edge node, the resource types of each edge cloud node and the resource types of each single lamp edge node to obtain a preset edge node relationship table;
updating a preset edge node relation table every a first preset period;
correspondingly, acquiring the edge cloud nodes and the single-lamp edge nodes corresponding to the area identifier, the membership between each edge cloud node and each single-lamp edge node, the resource types of each edge cloud node and the resource types of each single-lamp edge node includes:
based on the area identification, the edge cloud nodes and the single-lamp edge nodes corresponding to the area identification, the affiliation between each edge cloud node and each single-lamp edge node, the resource types of each edge cloud node and the resource types of each single-lamp edge node are obtained from a preset edge node relation table.
Specifically, for example, fig. 5 shows a part of content of a preset edge node relationship table, the preset edge node relationship table is stored in the cloud management platform, two edge cloud nodes corresponding to the region identifier a shown in fig. 5 are respectively an edge cloud node X and an edge cloud node Y, a single-light edge node 1 and a single-light edge node 2 are provided for a single-light edge node subordinate to the edge cloud node X, and resource types of the two are container types. The single-light edge node subordinate to the edge cloud node Y has a single-light edge node 3 and a single-light edge node 4, and resource types of both of the single-light edge nodes are virtual machine types.
It can be understood that the operation and maintenance personnel can update the preset edge node relation table at intervals of a first preset period according to the actual street lamp setting condition in the intelligent street lamp system.
In an optional embodiment of the present application, the method may further comprise:
before receiving an edge application deployment instruction, acquiring a data volume level corresponding to an edge application corresponding to each edge application identifier, and correspondingly storing each edge application identifier and the data volume level corresponding to each edge application to obtain a preset edge application data volume level table;
updating the preset edge application data volume level table every second preset period;
correspondingly, the obtaining of the data volume level corresponding to the edge application to be deployed identifier includes:
and acquiring the data volume level corresponding to the edge application to be deployed from the preset edge application data volume level table on the basis of the edge application identification to be deployed.
Specifically, the preset edge application data volume level table may be stored in the cloud management platform.
Fig. 6 is a schematic structural diagram of an edge application deployment device in an intelligent street lamp system according to an embodiment of the present application. As shown in fig. 6, the apparatus 600 may include: a deployment instruction receiving module 601, a resource type determining module 602, a target edge node determining module 603, and an application deployment module 604, wherein:
the deployment instruction receiving module 601 is configured to receive an edge application deployment instruction, where the edge application deployment instruction includes an area identifier and an edge application identifier to be deployed.
The resource type determining module 602 is configured to obtain an edge cloud node and a single-lamp edge node corresponding to the area identifier, a dependency relationship between each edge cloud node and each single-lamp edge node, a resource type of each edge cloud node and a resource type of each single-lamp edge node, and obtain a data volume level corresponding to the edge application to be deployed corresponding to the edge application identifier to be deployed.
The target edge node determining module 603 is configured to obtain a resource utilization rate of each single-lamp edge node corresponding to the area identifier, and determine at least one target edge node from each edge cloud node and each single-lamp edge node corresponding to the area identifier based on the data volume level and the dependency corresponding to the edge application to be deployed and the resource utilization rate of each single-lamp edge node.
The application deployment module 604 is configured to, for each target edge node, determine a target resource type of the target edge node based on the resource type of each edge cloud node corresponding to the area identifier and the resource type of each single-lamp edge node, acquire an edge application installation package to be deployed that is matched with the target resource type, determine a target number of edge applications to be deployed that need to be installed by the target edge node, and then issue the target number of edge application installation packages to be deployed to the target edge node, so as to complete edge application deployment at the target edge node.
According to the method and the device for deploying the edge application, the edge cloud nodes and the single lamp edge nodes of the area needing to be deployed are determined through the received area identification and the edge application identification to be deployed in the edge application deployment instruction, the subordination between each edge cloud node and each single lamp edge node, the resource type of each edge cloud node and the resource type of each single lamp edge node, then at least one target edge node is determined from each edge cloud node and each single lamp edge node corresponding to the area identification according to the data volume level and the subordination corresponding to the edge application to be deployed and the resource utilization rate of each single lamp edge node, an edge application installation package to be deployed corresponding to the resource type is installed on each target edge node, and therefore deployment of the edge application of the intelligent street lamp system is achieved. On one hand, in the scheme, the data volume level corresponding to the edge application to be deployed and the resource utilization rate of each single-lamp edge node are considered in the process of determining the target edge node for deploying the edge application to be deployed, so that the target edge node can provide enough computing capacity and computing resources after the edge application to be deployed is deployed, and the performance of the edge application to be deployed is further ensured; on the other hand, the scheme can issue the matched edge application installation package to be deployed for the target edge node according to the resource type of the target edge node, so that the application deployment of the target edge node with different resource types can be realized. To sum up, this application embodiment can realize that high efficiency, large-scale edge application in wisdom street lamp system deploy.
In an alternative embodiment of the present application, as shown in fig. 7, the target edge node determining module 603 is further configured to:
if the data volume level corresponding to the edge application to be deployed is not less than the preset level, determining each edge cloud node corresponding to the area identifier as a target edge node;
and if the data volume level corresponding to the edge application to be deployed is smaller than the preset level, determining at least one target edge node from each edge cloud node and each single-lamp edge node corresponding to the area identifier based on the dependency relationship and the resource utilization rate of each single-lamp edge node.
In an optional embodiment of the present application, the target edge node determining module 603 is further configured to:
acquiring the resource utilization condition of each single-lamp edge node corresponding to the area identifier through each edge cloud node corresponding to the area identifier;
for any edge cloud node, acquiring each single-lamp edge node subordinate to the edge cloud node based on the subordination relation, and if the resource utilization rate of the single-lamp edge nodes which are not less than a first preset number in the single-lamp edge nodes subordinate to the edge cloud node is not less than a first preset value, determining the edge cloud node as a target edge node;
and if the resource utilization rate of only the single lamp edge nodes with the number less than the first preset number in the single lamp edge nodes subordinate to the edge cloud node is not less than the first preset value, determining the single lamp edge nodes subordinate to the edge cloud node as target edge nodes.
In an optional embodiment of the present application, the application deployment module 604 is further configured to:
if the target edge nodes are edge cloud nodes, determining the number of single lamp edge nodes corresponding to the edge cloud nodes based on the membership relationship, and determining the number of targets based on the number of the single lamp edge nodes, wherein the number of the targets is in a direct proportion relationship with the number of the single lamp edge nodes corresponding to the edge cloud nodes;
and if the target edge nodes are single-lamp edge nodes, determining that the target number is 1.
In an alternative embodiment of the present application, as shown in fig. 7, the apparatus may further include an installation package library building module 701 configured to:
before receiving an edge application deployment instruction, obtaining edge application installation packages of different resource types corresponding to each edge application identifier, and storing each edge application installation package after marking each edge application identifier and each resource type corresponding to each edge application identifier to obtain a preset edge application installation package library.
Accordingly, the application deployment module 604 is further configured to:
and acquiring the edge application installation package to be deployed from a preset edge application installation package library based on the edge application identifier to be deployed and the target resource type.
In an optional embodiment of the present application, the application deployment module 604 is further configured to:
if the resource type of the target edge node is a container type, installing a target number of edge application installation packages to be deployed on the target edge node through a container cluster interface;
and if the resource type of the target edge node is the virtual machine type, installing the target number of edge application installation packages to be deployed on the target edge node through the corresponding proxy server.
In an optional embodiment of the present application, the apparatus may further include a node relation table building module 702 configured to:
before receiving an edge application deployment instruction, acquiring edge cloud nodes and single lamp edge nodes corresponding to each area identifier, a subordinate relationship between each edge cloud node and each single lamp edge node, a resource type of each edge cloud node and a resource type of each single lamp edge node, and correspondingly storing the edge cloud nodes and the single lamp edge nodes corresponding to each area identifier, the subordinate relationship between each edge cloud node and each single lamp edge node, the resource types of each edge cloud node and the resource types of each single lamp edge node to obtain a preset edge node relationship table;
updating a preset edge node relation table every a first preset period;
accordingly, the resource type determination module 602 is further configured to:
based on the area identification, the edge cloud nodes and the single-lamp edge nodes corresponding to the area identification, the affiliation between each edge cloud node and each single-lamp edge node, the resource types of each edge cloud node and the resource types of each single-lamp edge node are obtained from a preset edge node relation table.
In an optional embodiment of the present application, the apparatus further includes a data volume level table building module 703 configured to:
before receiving an edge application deployment instruction, acquiring a data volume level corresponding to an edge application corresponding to each edge application identifier, and correspondingly storing each edge application identifier and the data volume level corresponding to each edge application to obtain a preset edge application data volume level table;
and updating the preset edge application data volume level table every second preset period.
Accordingly, the resource type determination module 602 is further configured to:
and acquiring the data volume level corresponding to the edge application to be deployed and corresponding to the edge application to be deployed from a preset edge application data volume level table based on the edge application identification to be deployed.
The electronic device in the embodiments of the present application may include, but is not limited to, a mobile terminal such as a mobile phone, a notebook computer, a digital broadcast receiver, a PDA (personal digital assistant), a PAD (tablet), a PMP (portable multimedia player), a vehicle terminal (e.g., a car navigation terminal), a wearable device, and the like, and a stationary terminal such as a digital TV, a desktop computer, and the like. Such electronic devices may generally include: a memory for storing a program for executing the method of the above-mentioned method embodiments and a processor; the processor is configured to execute programs stored in the memory. The processor may be referred to herein as a processing device, and the memory may include at least one of a Read Only Memory (ROM), a Random Access Memory (RAM), and a storage device.
In particular, according to embodiments of the application, the processes described above with reference to the flow diagrams may be implemented as computer software programs. For example, embodiments of the present application include a computer program product comprising a computer program carried on a non-transitory computer readable medium, the computer program containing program code for performing the method illustrated by the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network, or installed from a storage device, or installed from a ROM or the like. The computer program, when executed by a processing device, performs the above-described functions defined in the method of the embodiments of the present application.
It should be noted that the embodiment of the present application may also include a computer-readable storage medium. A computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium may be included in the electronic device or may exist separately without being incorporated in the electronic device.
The computer readable storage medium carries one or more programs which, when executed by the electronic device, cause the electronic device to perform the method steps of any of the embodiments described above. It is clear to those skilled in the art that, for convenience and brevity of description, the specific method implemented by the computer-readable storage medium described above when executed by the electronic device may refer to the corresponding process in the foregoing method embodiments, and will not be described herein again.
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 application. Each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified 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/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. The modules or units described in the embodiments of the present application may be implemented by software or hardware.
The foregoing is only a partial embodiment of the present application, and it should be noted that modifications can be made by those skilled in the art without departing from the principle of the present application, and these modifications should also be considered as the protection scope of the present application.

Claims (10)

1. An edge application deployment method in an intelligent street lamp system is characterized by comprising the following steps:
receiving an edge application deployment instruction, wherein the edge application deployment instruction comprises an area identifier and an edge application identifier to be deployed;
acquiring edge cloud nodes and single-lamp edge nodes corresponding to the area identification, the subordination relation between each edge cloud node and each single-lamp edge node, the resource type of each edge cloud node and the resource type of each single-lamp edge node, and acquiring the data volume level corresponding to the edge application to be deployed corresponding to the edge application identification to be deployed;
acquiring resource utilization rates of the single lamp edge nodes corresponding to the area identification, and determining at least one target edge node from each edge cloud node and each single lamp edge node corresponding to the area identification based on the data volume level corresponding to the edge application to be deployed, the dependency relationship and the resource utilization rate of each single lamp edge node;
for each target edge node, determining the target resource type of the target edge node based on the resource type of each edge cloud node corresponding to the area identifier and the resource type of each single-lamp edge node, acquiring an edge application installation package to be deployed matched with the target resource type, determining the target number of the edge applications to be deployed, which need to be installed by the target edge node, and then issuing the target number of the edge application installation packages to be deployed to the target edge node, so as to complete edge application deployment at the target edge node.
2. The method according to claim 1, wherein the determining at least one target edge node from each edge cloud node and each single-light edge node corresponding to the area identifier based on the data volume level corresponding to the edge application to be deployed, the dependency relationship, and a resource utilization rate of each single-light edge node comprises:
if the data volume level corresponding to the edge application to be deployed is not less than a preset level, determining each edge cloud node corresponding to the area identifier as a target edge node;
and if the data volume level corresponding to the edge application to be deployed is smaller than a preset level, determining at least one target edge node from each edge cloud node and each single-lamp edge node corresponding to the area identifier based on the dependency relationship and the resource utilization rate of each single-lamp edge node.
3. The method according to claim 2, wherein if the data volume level corresponding to the edge application to be deployed is smaller than a preset level, determining at least one target edge node from each edge cloud node and each single-light edge node corresponding to the area identifier based on the dependency relationship and the resource utilization rate of each single-light edge node includes:
acquiring the resource utilization condition of each single-lamp edge node corresponding to the area identifier through each edge cloud node corresponding to the area identifier;
for any edge cloud node, acquiring each single-lamp edge node subordinate to the edge cloud node based on the subordination relation, and if the resource utilization rate of the single-lamp edge nodes which are not less than a first preset number in the single-lamp edge nodes subordinate to the edge cloud node is not less than a first preset value, determining the edge cloud node as a target edge node;
and if the resource utilization rate of only the single lamp edge nodes with the number less than the first preset number in the single lamp edge nodes subordinate to the edge cloud node is not less than the first preset value, determining the single lamp edge nodes subordinate to the edge cloud node as target edge nodes.
4. The method of claim 1, wherein determining the target number of the edge applications to be deployed that the target edge node needs to install comprises:
if the target edge nodes are edge cloud nodes, determining the number of single lamp edge nodes corresponding to the edge cloud nodes based on the subordination relation, and determining the target number based on the number of the single lamp edge nodes, wherein the target number is in direct proportion to the number of the single lamp edge nodes corresponding to the edge cloud nodes;
and if the target edge nodes are single-lamp edge nodes, determining that the target number is 1.
5. The method of claim 1, further comprising:
before receiving an edge application deployment instruction, acquiring edge application installation packages of different resource types corresponding to each edge application identifier, marking each edge application installation package with the corresponding edge application identifier and the corresponding resource type, and storing the edge application installation packages to obtain a preset edge application installation package library;
correspondingly, the obtaining the to-be-deployed edge application installation package matched with the target resource type includes:
and acquiring the application installation package to be deployed from the preset edge application installation package library based on the edge application identifier to be deployed and the target resource type.
6. The method according to claim 1, wherein said issuing the target number of the edge application installation packages to be deployed to the target edge node to complete edge application deployment at the target edge node comprises:
if the resource type of the target edge node is a container type, installing the target number of the edge application installation packages to be deployed on the target edge node through a container cluster interface;
and if the resource type of the target edge node is the virtual machine type, installing the target number of the edge application installation packages to be deployed on the target edge node through the corresponding proxy server.
7. The method of claim 1, further comprising:
before receiving an edge application deployment instruction, acquiring edge cloud nodes and single lamp edge nodes corresponding to each area identifier, a subordinate relationship between each edge cloud node and each single lamp edge node, a resource type of each edge cloud node and a resource type of each single lamp edge node, and correspondingly storing the edge cloud nodes and the single lamp edge nodes corresponding to each area identifier, the subordinate relationship between each edge cloud node and each single lamp edge node, the resource types of each edge cloud node and the resource types of each single lamp edge node to obtain a preset edge node relationship table;
updating the preset edge node relation table every interval of a first preset period;
correspondingly, the obtaining of the edge cloud nodes and the single-lamp edge nodes corresponding to the area identifier, the membership between each edge cloud node and each single-lamp edge node, the resource types of each edge cloud node, and the resource types of each single-lamp edge node includes:
based on the area identification, obtaining the edge cloud nodes and the single lamp edge nodes corresponding to the area identification, the affiliation between each edge cloud node and each single lamp edge node, the resource types of each edge cloud node and the resource types of each single lamp edge node from the preset edge node relation table.
8. The method of claim 1, further comprising:
before receiving an edge application deployment instruction, acquiring a data volume level corresponding to an edge application corresponding to each edge application identifier, and correspondingly storing each edge application identifier and the data volume level corresponding to each edge application to obtain a preset edge application data volume level table;
updating the preset edge application data volume level table every second preset period;
correspondingly, the obtaining of the data volume level corresponding to the edge application to be deployed identifier includes:
and acquiring the data volume level corresponding to the edge application to be deployed from the preset edge application data volume level table on the basis of the edge application identification to be deployed.
9. The utility model provides an edge application deploys device among wisdom street lamp system which characterized in that includes:
the deployment instruction receiving module is used for receiving an edge application deployment instruction, and the edge application deployment instruction comprises an area identifier and an edge application identifier to be deployed;
the resource type determining module is used for acquiring the edge cloud nodes and the single-lamp edge nodes corresponding to the area identifiers, the subordination relation between each edge cloud node and each single-lamp edge node, the resource type of each edge cloud node and the resource type of each single-lamp edge node, and acquiring the data volume level corresponding to the edge application to be deployed corresponding to the edge application identifier to be deployed;
a target edge node determining module, configured to obtain a resource utilization rate of each single-lamp edge node corresponding to the area identifier, and determine at least one target edge node from each edge cloud node and each single-lamp edge node corresponding to the area identifier based on the data volume level corresponding to the edge application to be deployed, the dependency relationship, and the resource utilization rate of each single-lamp edge node;
and the application deployment module is used for determining the target resource type of each target edge node based on the resource type of each edge cloud node corresponding to the area identifier and the resource type of each single-lamp edge node, acquiring an edge application installation package to be deployed matched with the target resource type, determining the target quantity of the edge applications to be deployed, which are required to be installed by the target edge node, and issuing the target quantity of the edge application installation packages to be deployed to the target edge node so as to complete edge application deployment at the target edge node.
10. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, which computer program, when being executed by a processor, carries out the method of any one of claims 1 to 8.
CN202210386954.5A 2022-04-14 2022-04-14 Edge application deployment method and device in intelligent street lamp system and readable storage medium Active CN114500539B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202210386954.5A CN114500539B (en) 2022-04-14 2022-04-14 Edge application deployment method and device in intelligent street lamp system and readable storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202210386954.5A CN114500539B (en) 2022-04-14 2022-04-14 Edge application deployment method and device in intelligent street lamp system and readable storage medium

Publications (2)

Publication Number Publication Date
CN114500539A true CN114500539A (en) 2022-05-13
CN114500539B CN114500539B (en) 2022-08-16

Family

ID=81489159

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202210386954.5A Active CN114500539B (en) 2022-04-14 2022-04-14 Edge application deployment method and device in intelligent street lamp system and readable storage medium

Country Status (1)

Country Link
CN (1) CN114500539B (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114743382A (en) * 2022-06-13 2022-07-12 浙江大云物联科技有限公司 Vehicle violation behavior identification method and device based on intelligent lamp pole system

Citations (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2020192598A1 (en) * 2019-03-22 2020-10-01 华为技术有限公司 Method and device for deploying virtual machine and container
WO2020207264A1 (en) * 2019-04-08 2020-10-15 阿里巴巴集团控股有限公司 Network system, service provision and resource scheduling method, device, and storage medium
CN112035121A (en) * 2019-06-03 2020-12-04 大唐移动通信设备有限公司 Edge application deployment method and system
WO2020253266A1 (en) * 2019-06-15 2020-12-24 华为技术有限公司 Method for providing edge service, apparatus and device
CN112583861A (en) * 2019-09-27 2021-03-30 阿里巴巴集团控股有限公司 Service deployment method, resource configuration method, system, device and server
CN112764920A (en) * 2021-01-08 2021-05-07 世纪龙信息网络有限责任公司 Edge application deployment method, device, equipment and storage medium
CN113055478A (en) * 2021-03-16 2021-06-29 海尔数字科技(青岛)有限公司 Method, device, equipment and medium for processing equipment data
CN113301078A (en) * 2020-05-22 2021-08-24 阿里巴巴集团控股有限公司 Network system, service deployment and network division method, device and storage medium
CN113515514A (en) * 2021-07-02 2021-10-19 国网辽宁省电力有限公司大连供电公司 Multi-level edge computing system architecture based on cloud edge cooperation and implementation method thereof
CN113867933A (en) * 2021-08-10 2021-12-31 中标慧安信息技术股份有限公司 Edge computing application deployment method and device
CN113986521A (en) * 2020-07-23 2022-01-28 中国联合网络通信集团有限公司 Deployment method and device of edge computing nodes
CN114138453A (en) * 2021-10-18 2022-03-04 中标慧安信息技术股份有限公司 Resource optimization allocation method and system suitable for edge computing environment
CN114138450A (en) * 2022-02-07 2022-03-04 浙江大云物联科技有限公司 Composite task scheduling method and device in intelligent street lamp system and readable storage medium
CN114265664A (en) * 2021-11-26 2022-04-01 中国联合网络通信集团有限公司 Edge application deployment method, device, equipment and storage medium

Patent Citations (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2020192598A1 (en) * 2019-03-22 2020-10-01 华为技术有限公司 Method and device for deploying virtual machine and container
WO2020207264A1 (en) * 2019-04-08 2020-10-15 阿里巴巴集团控股有限公司 Network system, service provision and resource scheduling method, device, and storage medium
CN112035121A (en) * 2019-06-03 2020-12-04 大唐移动通信设备有限公司 Edge application deployment method and system
WO2020253266A1 (en) * 2019-06-15 2020-12-24 华为技术有限公司 Method for providing edge service, apparatus and device
CN112583861A (en) * 2019-09-27 2021-03-30 阿里巴巴集团控股有限公司 Service deployment method, resource configuration method, system, device and server
CN113301078A (en) * 2020-05-22 2021-08-24 阿里巴巴集团控股有限公司 Network system, service deployment and network division method, device and storage medium
CN113986521A (en) * 2020-07-23 2022-01-28 中国联合网络通信集团有限公司 Deployment method and device of edge computing nodes
CN112764920A (en) * 2021-01-08 2021-05-07 世纪龙信息网络有限责任公司 Edge application deployment method, device, equipment and storage medium
CN113055478A (en) * 2021-03-16 2021-06-29 海尔数字科技(青岛)有限公司 Method, device, equipment and medium for processing equipment data
CN113515514A (en) * 2021-07-02 2021-10-19 国网辽宁省电力有限公司大连供电公司 Multi-level edge computing system architecture based on cloud edge cooperation and implementation method thereof
CN113867933A (en) * 2021-08-10 2021-12-31 中标慧安信息技术股份有限公司 Edge computing application deployment method and device
CN114138453A (en) * 2021-10-18 2022-03-04 中标慧安信息技术股份有限公司 Resource optimization allocation method and system suitable for edge computing environment
CN114265664A (en) * 2021-11-26 2022-04-01 中国联合网络通信集团有限公司 Edge application deployment method, device, equipment and storage medium
CN114138450A (en) * 2022-02-07 2022-03-04 浙江大云物联科技有限公司 Composite task scheduling method and device in intelligent street lamp system and readable storage medium

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
张展等: "面向边缘计算的目标追踪应用部署策略研究", 《软件学报》 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114743382A (en) * 2022-06-13 2022-07-12 浙江大云物联科技有限公司 Vehicle violation behavior identification method and device based on intelligent lamp pole system
CN114743382B (en) * 2022-06-13 2022-10-28 浙江大云物联科技有限公司 Vehicle violation behavior identification method and device based on intelligent lamp pole system

Also Published As

Publication number Publication date
CN114500539B (en) 2022-08-16

Similar Documents

Publication Publication Date Title
CN108055264B (en) Scheduling apparatus and method for push streaming server, and computer-readable storage medium
CN109213600B (en) GPU resource scheduling method and device based on AI cloud
CN111818136B (en) Data processing method, device, electronic equipment and computer readable medium
CN105049268A (en) Distributed computing resource allocation system and task processing method
CN101741912A (en) Method, network apparatus and distributed network system for processing computation task
CN107977254B (en) Method for responding to request in cloud data system and computer-readable storage medium
CN114500539B (en) Edge application deployment method and device in intelligent street lamp system and readable storage medium
CN112560724A (en) Vehicle monitoring method and device and cloud control platform
CN103873534A (en) Method and device for application cluster migration
CN103067486B (en) Based on the large data processing method of PaaS platform
CN105321346A (en) Method for utilizing cloud computing basic resource pool to control urban intelligent traffic
CN103414767A (en) Method and device for deploying application software on cloud computing platform
CN104410821A (en) Large-scale intelligent video analysis operating system and method
CN103685540A (en) Task decomposition and composition method based on cloud computing
CN111124640A (en) Task allocation method and system, storage medium and electronic device
CN104580194A (en) Virtual resource management method and device oriented to video applications
CN112181542A (en) Function calling method and device, electronic equipment and storage medium
CN204650755U (en) A kind of material flow tracking supervisory system based on cloud computing
CN104598266A (en) Client application service logic updating method and device and equipment
CN104090746A (en) Android system based application management method and device
CN110807050A (en) Performance analysis method and device, computer equipment and storage medium
CN112799908B (en) Intelligent terminal safety monitoring method, equipment and medium based on edge calculation
CN111459510A (en) Cross-network operating system installation method and device, electronic equipment and medium
CN114138450B (en) Composite task scheduling method and device in intelligent street lamp system and readable storage medium
CN116032614A (en) Container network micro-isolation method, device, equipment and medium

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant
TR01 Transfer of patent right
TR01 Transfer of patent right

Effective date of registration: 20230330

Address after: 310000 room 501-3, Longhe international building, No. 1961, Jianghui Road, Changhe street, Binjiang District, Hangzhou City, Zhejiang Province

Patentee after: HANGZHOU REQE INFORMATION TECHNOLOGY CO.,LTD.

Address before: 310000 room 501-2, Longhe international building, No. 1961, Jianghui Road, Changhe street, Binjiang District, Hangzhou City, Zhejiang Province

Patentee before: ZHEJIANG DAYUN IOT TECHNOLOGY Co.,Ltd.