Cloud rendering management method and device

Abstract

The invention relates to the technical field of digital twinning, and particularly provides a cloud rendering management method and device, based on digital twinning application, comprising the following steps: S1, calling a cloud rendering service; s2, cloud rendering service logic; and S3, performing automatic operation and maintenance management on the digital twin application program. Compared with the prior art, the method has the advantages that the operation efficiency of the park can be improved, potential risks can be effectively reduced, and powerful data support is provided for scientific decision making.

Description

Technical Field

[0001] The present invention relates to the field of digital twin technology, and specifically provides a cloud rendering management method and device. Background Art

[0002] Digital twin technology is data-driven at its core. By fully simulating the entire life cycle of physical entities, it has become a key technology that connects the real and virtual worlds, greatly promoting the deep integration of the digital economy with real economy fields such as industrial manufacturing and urban management. Using the Internet of Things technology, digital twins can collect real-time data and process and analyze it with the help of advanced technologies such as cloud computing, big data and artificial intelligence, thereby achieving highly accurate digital mapping of physical entities. This technology has shown broad application prospects in many fields such as smart parks, smart cities, and smart factories. Especially in the field of smart parks, digital twins can not only help improve the operational efficiency of the park, but also effectively reduce potential risks and provide strong data support for scientific decision-making.

[0003] Cloud rendering technology is based on interactive multimedia technology. It generally uses the WebRTC protocol to transmit the images and sounds of applications. It also supports input devices such as mouse and keyboard. Compared with traditional media transmission technology, it can achieve two-way real-time interaction and feedback. It is mostly used in remote desktop, video conferencing, remote collaboration and other businesses. Cloud rendering technology uses the software and hardware resources of the cloud-based rendering server to perform real-time or offline rendering of applications, solving the resource limitations of local hardware and meeting the business scenario requirements of multi-terminal cross-platform and real-time access. However, the cloud rendering technology currently used in the field of digital twins still has the following problems:

[0004] 1. Resource exclusivity limitation: Under the existing technical route, the same instance can only serve one user at the same time, which means that when multiple users try to use the digital twin application in a "shared" manner, they can only wait for the previous user to complete the operation before continuing to use it. As the number of users grows, in order to support multi-user concurrent access, a complete application environment needs to be deployed for each user separately, which not only increases the deployment time and labor costs, but also leads to a huge waste of server resources.

[0005] Second, it is difficult to control resource usage in real time: For running digital twin applications, the specific amount of system resources consumed often requires remote logging into the rendering server and using tools such as resource managers to view it. If multiple digital twin applications share the same resources, it is even more difficult to distinguish the resources used by each. The lack of a real-time monitoring mechanism makes it impossible to discover and solve resource overload problems caused by instances not releasing resources in a timely manner, thus affecting the stability and efficiency of the overall system.

[0006] 3. Lack of full life cycle management: The existing cloud rendering architecture of digital twin applications does not support comprehensive life cycle management of applications, and lacks effective control measures in all links from establishing connections, starting programs to program destruction. This makes it difficult for maintenance personnel to efficiently monitor and manage the operating status of the entire application.

[0007] 4. Lack of resource scheduling strategy: The existing cloud rendering architecture of digital twin applications does not provide the ability to intelligently select the optimal rendering node based on resource utilization (such as CPU and GPU load) or network performance indicators (such as latency). Therefore, it is impossible to achieve flexible and efficient resource allocation and optimization in the face of different demand scenarios. Summary of the invention

[0008] The present invention aims to overcome the deficiencies of the above-mentioned prior art and provides a cloud rendering management method with strong practicality.

[0009] A further technical task of the present invention is to provide a cloud rendering management device that is rationally designed, safe and applicable.

[0010] The technical solution adopted by the present invention to solve its technical problem is:

[0011] A cloud rendering management method, based on a digital twin application, has the following steps:

[0012] S1, cloud rendering service call;

[0013] S2, cloud rendering service logic;

[0014] S3. Automated operation and maintenance management of digital twin applications.

[0015] Furthermore, in step S1, it includes:

[0016] S1-1. The user requests the cloud rendering service through the client application or web page to obtain the real-time rendering results of the digital twin application;

[0017] S1-2. After obtaining the signaling address, the user terminal forwards the connection establishment request with the cloud rendering instance through the obtained signaling address.

[0018] Furthermore, in step S1-1, after receiving the user's request, the cloud rendering service platform will check the available resource status in the token bucket. If there are free resources in the token bucket, an available token will be allocated to the request, and a signaling address will be generated and returned to the user;

[0019] If there are no idle resources, the platform will return a notification to the user, informing him that there are currently no idle instances available and suggesting that the user try again later.

[0020] Furthermore, in step S1-2, when establishing a request, available communication channels supported by each other are obtained from each other, and when the user end and the cloud rendering instance negotiate and determine an available communication channel, a WebRTC point-to-point communication connection is established.

[0021] Furthermore, in step S2, it includes:

[0022] S2-1. In the cloud rendering service, according to the preset configuration items in the database, automatically create and manage rendering instances of certain data;

[0023] S2-2, when a new service request arrives, first, determine whether there are enough available resources to satisfy the new request;

[0024] S2-3. The newly started rendering instance needs to carry basic information to the registration center to complete the registration process;

[0025] S2-4, the administrator watches the current rendering screen of the activity instance in real time;

[0026] S2-5, the configuration center, as an independent service component, maintains the configuration information and change events subscribed by all instances;

[0027] S2-6, users access rendering resources in a preemptive exclusive mode;

[0028] S2-7. All computing nodes and rendering nodes report node status regularly;

[0029] S2-8, computing nodes and rendering nodes are assigned permissions based on users;

[0030] S2-9, computing nodes and rendering nodes are deployed online with one click through automated scripts.

[0031] Further, in step S2-1, the rendering instances are assigned a specific number of tokens, representing the maximum number of users they serve simultaneously, and added to a token bucket;

[0032] In step S2-2, it is determined whether there are sufficient available resources to satisfy the new request. If so, resources are allocated based on the current host load and the optimal strategy, and the corresponding rendering instance is started asynchronously.

[0033] Furthermore, in step S2-5, when there is a new configuration update event, the configuration center will actively push it to the relevant rendering instance, and the rendering instance will perform configuration updates, so that the instance can dynamically adjust its own settings without restarting;

[0034] In step S2-6, the preemptive exclusive mode means that once a user starts using a rendering instance, other users cannot share the same instance until the user's task is completed; however, once it is detected that a user has been inactive for a long time or actively closes the instance, the resources occupied by the user will be released for use by subsequent users waiting in line.

[0035] Furthermore, in step S2-7, the cloud rendering service management terminal can list and view the parameters of all current computing nodes and rendering nodes, and for a certain computing node or rendering node, can view the running instances on it in the list;

[0036] In step S2-8, users can exclusively use designated computing nodes and rendering nodes, giving priority to the current user's resource usage. Different users can also have their own digital twin application libraries, realizing permission management from two dimensions: application and resource.

[0037] In step S3, it includes:

[0038] S3-1. When a user wants to add or update a digital twin application, he or she first needs to upload the program package to the repository, and then execute the release program instruction. First, the program package will be searched from the repository according to the storage path of the digital twin application package configured by the user in the repository and the startup program path in the program package, and the startup program path will be checked to see if it is correct. The package size will be returned for comparison by the user, and then the package pull request will be sent to all rendering nodes to which the user has access rights according to the permission group of the launching user.

[0039] S3-2, after receiving the package pull request, the rendering node first checks whether there are users still using the digital twin application. If there are users, it waits for all instances to exit before pulling the package;

[0040] If it is an update operation, you need to delete the previous version of the package first, then pull the package from the repository to the local computer according to the configured digital twin application unique identification ID and decompress it;

[0041] S3-3. Monitor the overall update process. Every time a user performs an update operation, the version number of the maintained package is upgraded. The administrator can view the real-time update status of each rendering node in the synchronization list of the digital twin application, including four states: waiting, downloading, download completed and waiting for decompression, and completed.

[0042] A cloud rendering management device, comprising: at least one memory and at least one processor;

[0043] The at least one memory is used to store a machine-readable program;

[0044] The at least one processor is used to call the machine-readable program to execute a cloud rendering management method.

[0045] Compared with the prior art, the cloud rendering management method and device of the present invention have the following outstanding beneficial effects:

[0046] The present invention realizes unified authorization and unified management of multiple users and multiple terminals, monitors and tracks the overall service link of the digital twin application, quickly locates the occurrence of problems and takes corresponding measures to repair and optimize them in time, ensuring the stable operation and efficient performance of the application.

[0047] It provides configuration hot update and instance health monitoring capabilities in the running state of digital twin applications, effectively controls and manages various configurations in the system, ensures its security, increases the availability and stability of digital twin applications, and reduces the workload of debugging and system operation and maintenance.

[0048] Monitoring and management of rendering resources, including real-time monitoring and analysis of the host's performance, resource utilization, and operating status, can promptly identify problems and load conditions of rendering resources, and take appropriate measures to adjust and optimize them, ensuring stable operation of the host and rational utilization of rendering resources, improving performance and reliability.

[0049] For the package management of digital twin applications, one-click automatic update and deployment of multiple rendering nodes can be achieved based on user permissions. The overall update and deployment process of digital twin applications can be monitored in real time, effectively improving the operation and maintenance efficiency of digital twin applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0051] Attached Figure 1 It is a schematic diagram of a cloud rendering service calling process in a cloud rendering management method;

[0052] Attached Figure 2 The invention is a schematic diagram of a logical flow of a cloud rendering service in a cloud rendering management method. DETAILED DESCRIPTION

[0053] In order to enable those skilled in the art to better understand the solution of the present invention, the present invention is further described in detail below in conjunction with specific implementation methods. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0054] A best embodiment is given below:

[0055] A cloud rendering management method in this embodiment has the following steps:

[0056] S1, cloud rendering service call;

[0057] like Figure 1 As shown, including:

[0058] S1-1. The user requests the cloud rendering service through the client application or web page to obtain the real-time rendering results of the digital twin application. After receiving the user's request, the cloud rendering service platform will check the status of the available resources in the token bucket. If there are free resources in the token bucket, an available token will be allocated for the request, and a signaling address will be generated and returned to the user.

[0059] If there are no idle resources, the platform will return a notification to the user, informing him that there are currently no idle instances available and suggesting that the user try again later.

[0060] S1-2, after obtaining the signaling address, the user end forwards the connection establishment request with the cloud rendering instance through it;

[0061] The two parties obtain available communication channels supported by each other. When the user terminal and the cloud rendering instance negotiate and determine an available communication channel, a WebRTC point-to-point communication connection is established, which allows users to efficiently transmit audio, video and data streams with the remote rendering server, achieving a low-latency interactive experience.

[0062] S2, cloud rendering service logic;

[0063] like Figure 2 As shown, including:

[0064] S2-1. In the cloud rendering service, a certain number of rendering instances are automatically created and managed according to the preset configuration items in the database. These instances are given a specific number of tokens, representing the maximum number of users they can serve simultaneously, and are added to the token bucket.

[0065] S2-2, when a new service request arrives, the system first determines whether there are enough available resources to meet the new request. If so, it allocates resources based on the current host load and the optimal strategy, and asynchronously starts the corresponding rendering instance.

[0066] S2-3. The newly started rendering instance needs to carry its basic information (such as instance name, IP address, listening port, etc.) to the registration center to complete the registration process. The registration center is responsible for maintaining the status information of all active instances and performing health checks regularly to ensure service quality.

[0067] S2-4. Support system administrators to view the current rendering screen of the activity instance in real time, but do not provide operation permissions, so that system administrators can confirm the current service status of a certain activity instance.

[0068] S2-5. As an independent service component, the configuration center maintains the configuration information and change events subscribed by all instances of the system. When there is a new configuration update event, the configuration center will actively push it to the relevant rendering instance, and the rendering instance will update the configuration, so that the instance can dynamically adjust its own settings without restarting.

[0069] S2-6. To maximize resource utilization, users use a preemptive exclusive mode to access rendering resources. This means that once a user starts using a rendering instance, other users cannot share the same instance until the user's task is completed; however, once it is detected that a user has been inactive for a long time or actively closes the instance, the resources occupied by the user will be released for subsequent users waiting in line.

[0070] S2-7. All computing nodes and rendering nodes report node status regularly. The cloud rendering service management terminal can list and view the memory, storage, computing load, rendering load and other parameters of all computing nodes and rendering nodes in the current system. For a computing node or rendering node, the running instances on it can be listed and supported to carry out operations such as online and offline for the running instances.

[0071] S2-8. Compute nodes and rendering nodes can be assigned permissions based on users. Users can exclusively use designated compute nodes and rendering nodes, giving priority to the current user's resource usage. Different users can also have their own digital twin application libraries, realizing permission management from two dimensions: application and resource.

[0072] S2-9, computing nodes and rendering nodes can be deployed online with one click through automated scripts, supporting node resource scaling and expansion to improve system scalability.

[0073] S3, automated operation and maintenance management of digital twin applications;

[0074] include:

[0075] S3-1. When a user wants to add or update a digital twin application, he or she first needs to upload the program package to the repository, and then execute the release program instruction. First, the program package will be searched from the repository according to the storage path of the digital twin application package configured by the user in the repository and the startup program path in the program package, and the startup program path will be checked to see if it is correct. The package size will be returned for comparison by the user, and then the package pull request will be sent to all rendering nodes to which the user has access rights according to the permission group of the launching user.

[0076] S3-2, after receiving the package pull request, the rendering node first checks whether there are users still using the digital twin application. If there are users, it waits for all instances to exit before pulling the package;

[0077] If it is an update operation, you need to delete the previous version of the package first, then pull the package from the repository to the local computer according to the configured digital twin application unique identification ID and decompress it;

[0078] S3-3. Monitor the overall update process. Every time a user performs an update operation, the version number of the maintained package is upgraded. The administrator can view the real-time update status of each rendering node in the synchronization list of the digital twin application, including four states: waiting, downloading, download completed and waiting for decompression, and completed.

[0079] Based on the above method, a cloud rendering management device in this embodiment includes: at least one memory and at least one processor;

[0080] The at least one memory is used to store a machine-readable program;

[0081] The at least one processor is used to call the machine-readable program to execute a cloud rendering management method.

[0082] The above-mentioned specific implementations are only specific cases of the present invention. The patent protection scope of the present invention includes but is not limited to the above-mentioned specific implementations. Any technical solutions that conform to the above-mentioned specific implementations of the present invention and any appropriate changes or substitutions made by ordinary technicians in the relevant technical field shall fall within the patent protection scope of the present invention.

[0083] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A cloud rendering management method, characterized in that: Based on the digital twin application, there are the following steps: S1, cloud rendering service call; S2, cloud rendering service logic; S3. Automated operation and maintenance management of digital twin applications.

2. A cloud rendering management method according to claim 1, characterized in that: In step S1, it includes: S1-1. The user requests the cloud rendering service through the client application or web page to obtain the real-time rendering results of the digital twin application; S1-2. After obtaining the signaling address, the user terminal forwards the connection establishment request with the cloud rendering instance through the obtained signaling address.

3. A cloud rendering management method according to claim 2, characterized in that: In step S1-1, after receiving the user's request, the cloud rendering service platform will check the available resource status in the token bucket. If there are free resources in the token bucket, an available token will be allocated to the request, and a signaling address will be generated and returned to the user; If there are no idle resources, the platform will return a notification to the user, informing him that there are currently no idle instances available and suggesting that the user try again later.

4. A cloud rendering management method according to claim 3, characterized in that: In step S1-2, when establishing a request, the two parties obtain available communication channels supported by each other. When the user end and the cloud rendering instance negotiate and determine an available communication channel, a WebRTC point-to-point communication connection is established.

5. A cloud rendering management method according to claim 4, characterized in that: In step S2, it includes: S2-1. In the cloud rendering service, according to the preset configuration items in the database, automatically create and manage rendering instances of certain data; S2-2, when a new service request arrives, first, determine whether there are enough available resources to satisfy the new request; S2-3. The newly started rendering instance needs to carry basic information to the registration center to complete the registration process; S2-4, the administrator watches the current rendering screen of the activity instance in real time; S2-5, the configuration center, as an independent service component, maintains the configuration information and change events subscribed by all instances; S2-6, users access rendering resources in a preemptive exclusive mode; S2-7. All computing nodes and rendering nodes report node status regularly; S2-8, computing nodes and rendering nodes are assigned permissions based on users; S2-9, computing nodes and rendering nodes are deployed online with one click through automated scripts.

6. A cloud rendering management method according to claim 5, characterized in that: In step S2-1, the rendering instances are assigned a specific number of tokens, representing the maximum number of users they can serve simultaneously, and added to a token bucket; In step S2-2, it is determined whether there are sufficient available resources to satisfy the new request. If so, resources are allocated based on the current host load and the optimal strategy, and the corresponding rendering instance is started asynchronously.

7. A cloud rendering management method according to claim 6, characterized in that: In step S2-5, when there is a new configuration update event, the configuration center will actively push it to the relevant rendering instance, and the rendering instance will perform configuration updates, so that the instance can dynamically adjust its own settings without restarting; In step S2-6, the preemptive exclusive mode means that once a user starts using a rendering instance, other users cannot share the same instance until the user's task is completed; however, once it is detected that a user has been inactive for a long time or actively closes the instance, the resources occupied by the user will be released for use by subsequent users waiting in line.

8. A cloud rendering management method according to claim 7, characterized in that: In step S2-7, the cloud rendering service management terminal can list and view the parameters of all current computing nodes and rendering nodes. For a computing node or rendering node, the running instances on it can be viewed in the list; In step S2-8, users can exclusively use designated computing nodes and rendering nodes, giving priority to the current user's resource usage. Different users can also have their own digital twin application libraries, realizing permission management from two dimensions: application and resource.

9. A cloud rendering management method according to claim 8, characterized in that: In step S3, it includes: S3-1. When a user wants to add or update a digital twin application, he or she first needs to upload the program package to the repository, and then execute the release program instruction. First, the program package will be searched from the repository according to the storage path of the digital twin application package configured by the user in the repository and the startup program path in the program package, and the startup program path will be checked to see if it is correct. The package size will be returned for comparison by the user, and then the package pull request will be sent to all rendering nodes to which the user has access rights according to the permission group of the launching user. S3-2, after receiving the package pull request, the rendering node first checks whether there are users still using the digital twin application. If there are users, it waits for all instances to exit before pulling the package; If it is an update operation, you need to delete the previous version of the package first, then pull the package from the repository to the local computer according to the configured digital twin application unique identification ID and decompress it; S3-3. Monitor the overall update process. Every time a user performs an update operation, the version number of the maintained package is upgraded. The administrator can view the real-time update status of each rendering node in the synchronization list of the digital twin application, including four states: waiting, downloading, download completed and waiting for decompression, and completed.

10. A cloud rendering management device, characterized in that: include: at least one memory and at least one processor; The at least one memory is used to store a machine-readable program; The at least one processor is configured to call the machine-readable program to execute the method according to any one of claims 1 to 9.

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