Business scheduling path planning method, device and equipment based on digital twinning

Abstract

The application provides a business scheduling path planning method, device and equipment based on digital twinning, and belongs to the technical field of computers. The method comprises the following steps: acquiring user business data; inputting the user business data into a business twin model of a digital twinning application system, so that the business twin model simulates the user business data and generates business runtime sequence prediction data of the user business data; inputting the business runtime sequence prediction data into a digital twinning calculation network of the digital twinning application system, and calculating the running path of the business runtime sequence prediction data in the digital twinning calculation network by using a path planning model to obtain a target scheduling path. By establishing a digital twinning application system suitable for general business, the application realizes business operation prediction of different user business models, reasonably allocates computing power resources based on the business operation prediction, can maximize the effective utilization of limited computing power networks, and guarantees normal operation of the business.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of computer, in particular to a business scheduling path planning method, device and equipment based on digital twinning. BACKGROUND

[0002] With the in-depth development of digital transformation, the computing power network (referred to as algorithm network) has become an important infrastructure in the era of wisdom connection of all things. The computing power can be understood as the ability of the cloud computing center to process data. Due to the high development of informatization, the demand for computing power in various industries is increasing, such as autonomous driving, cloud gaming, machine vision, information security, home Internet of Things and other fields that require real-time computing.

[0003] The computing power network can provide computing power resources according to the needs of different businesses, including various computing, storage and connection services. Users do not need to purchase equipment and build their own computing power network platform, which can save costs and meet their business needs, and can play a role in reducing costs and increasing efficiency.

[0004] However, since the computing power network is a limited resource, it needs to be reasonably utilized, such as implementing on-demand allocation according to the needs of different users, so that the computing power resources can meet the needs of more users and ensure the quality of user services. At present, digital twinning technology can be used to simulate user business models and computing power resources to realize monitoring and scheduling of computing power resources.

[0005] However, in this algorithm network scheduling scheme, only the actual business situation of each user can be modeled, and it cannot be applied to all user businesses, that is, it cannot effectively restore the state and resource scheduling process of general businesses. In addition, the existing scheme can only monitor and allocate resources in real time, and cannot predictively deduce and judge the scheduling path of general businesses. The utilization rate of computing power resources needs to be further optimized. SUMMARY

[0006] The present application provides a business scheduling path planning method, device and equipment based on digital twinning, which solves the defect that the computing power resource demand of user business cannot be predicted in the prior art, resulting in low utilization rate of computing power resources, realizes unified modeling of different businesses, and deduces and predicts the computing power resource demand of the business, thereby unified planning the scheduling path of computing power resources, reasonably allocating computing power resources, and improving the utilization rate of computing power resources.

[0007] The present application provides a business scheduling path planning method based on digital twinning, comprising:

[0008] Obtaining user business data;

[0009] input the user service data into a service twin model of a digital twin application system, so that the service twin model simulates the user service data, and generates service running time sequence prediction data of the user service data;

[0010] input the service running time sequence prediction data into a digital twin calculation network of the digital twin application system, calculate a running path of the service running time sequence prediction data in the digital twin calculation network by using a path planning model, and obtain a target scheduling path.

[0011] According to the method provided by the application, before the user service data is obtained, the method comprises:

[0012] Three-dimensional modeling is performed on the entity network, the logical network and the topological relationship of the current calculation power network, and an initial calculation network model is obtained.

[0013] Real-time environment running data of the current calculation power network is obtained by using a network telemetry method.

[0014] The real-time environment running data is simulated in the initial calculation network model by using a digital twin method, and a digital twin calculation network is obtained.

[0015] According to the method provided by the application, the real-time environment running data comprises real-time performance data, real-time fault data, real-time configuration data and real-time resource data of the current calculation power network.

[0016] According to the method provided by the application, before the user service data is obtained, the method further comprises:

[0017] A general service parameter is obtained.

[0018] The general service parameter is processed in real time by using a digital thread technology, and the service twin model is generated.

[0019] According to the method provided by the application, the path planning model is generated based on a dynamic weight and an ant colony algorithm.

[0020] According to the method provided by the application, the user service data comprises a service type, a service amount, a service calculation power demand, a service network demand, a service index and a service performance demand.

[0021] According to the method provided by the application, before the user service data is obtained, the method further comprises:

[0022] The business twin model and the digital twin algorithm network are initialized by using a 3D visualization engine, and the initialized business twin model and the initialized digital twin algorithm network are displayed.

[0023] The application further provides a business scheduling path planning device based on digital twinning, comprising:

[0024] A business data acquisition module is configured to acquire user business data.

[0025] A business operation prediction module is configured to input the user business data into a business twin model of a digital twin application system, so that the business twin model simulates the user business data and generates business operation timing prediction data of the user business data.

[0026] A target scheduling path calculation module is configured to input the business operation timing prediction data into a digital twin algorithm network of the digital twin application system, calculate a running path of the business operation timing prediction data in the digital twin algorithm network by using a path planning model, and obtain a target scheduling path.

[0027] The application further provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the business scheduling path planning method based on digital twinning as described above.

[0028] The application further provides a non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program is executable by a processor to implement the business scheduling path planning method based on digital twinning as described above.

[0029] The application further provides a computer program product comprising a computer program, wherein the computer program is executable by a processor to implement the business scheduling path planning method based on digital twinning as described above.

[0030] The application provides a business scheduling path planning method, device and equipment based on digital twinning, which comprises the following steps: acquiring user business data; inputting the user business data into a business twin model of a digital twinning application system, so that the business twin model simulates the user business data and generates business runtime sequence prediction data of the user business data; inputting the business runtime sequence prediction data into a digital twinning calculation network of the digital twinning application system, and calculating the running path of the business runtime sequence prediction data in the digital twinning calculation network by using a path planning model to obtain a target scheduling path. The application can realize business running prediction of different user business models by establishing a digital twinning application system suitable for general business, obtain the computing resource demand of a user in a future period of time, combine the computing resource demand with the current digital twinning calculation network to obtain the optimal computing resource scheduling path matching the current user demand, not only meet the computing resource demand of the user, but also globally plan and reasonably allocate the computing resources in the current region, so that the limited computing resource network can be maximally and effectively utilized, and the purpose of reducing cost and increasing efficiency is achieved. BRIEF DESCRIPTION OF DRAWINGS

[0031] In order to more clearly illustrate the technical solutions in the application or prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are some embodiments of the application, and other drawings can be obtained by those skilled in the art without creative effort on the basis of these drawings.

[0032] Figure 1 FIG. 1 is an application environment schematic diagram of the business scheduling path planning method based on digital twinning provided by the application;

[0033] Figure 2 FIG. 2 is a flow schematic diagram of the business scheduling path planning method based on digital twinning provided by the application;

[0034] Figure 3 FIG. 3 is a structure schematic diagram of the business scheduling path planning device based on digital twinning provided by the application;

[0035] Figure 4 FIG. 4 is a structure schematic diagram of the electronic device provided by the application. DETAILED DESCRIPTION

[0036] In order to make the objects, technical solutions and advantages of the present application clearer, the following will clearly and completely describe the technical solutions in the present application with reference to the drawings in the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work belong to the protection scope of the present application.

[0037] It should be noted that in the description of the embodiments of the present application, the terms "comprising", "containing" or any other variants thereof are intended to cover the non-exclusive inclusion, so that the process, method, article or equipment including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or equipment. Without more limitations, the element defined by the sentence "including a" does not exclude the presence of other identical elements in the process, method, article or equipment including the element. The terms "upper", "lower" and the like indicate the orientation or positional relationship shown in the drawings, and are only used to facilitate the description of the present application and simplify the description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the present application. Unless otherwise specified and limited, the terms "mounting", "connecting", "connecting" should be understood broadly, for example, it can be fixedly connected, or it can be detachably connected, or integrally connected; it can be mechanically connected, or it can be electrically connected; it can be directly connected, or it can be indirectly connected through an intermediate medium, or it can be connected inside two elements. For those of ordinary skill in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0038] The terms "first", "second", and the like in the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second", etc. are usually a class, and do not limit the number of objects, for example, the first object can be one or more. In addition, "and / or" means at least one of the connected objects, and the character " / ", generally means that the front and rear associated objects are in a "or" relationship.

[0039] The specific embodiments of the present application will be described below in conjunction with Figures 1-4 The specific embodiments of the present application will be described below in conjunction with

[0040] The business scheduling path planning method based on digital twinning provided by the embodiments of the present application can be applied to, for example Figure 1The application environment shown. Among them, the user node cluster 101 communicates with the server cluster 103 through the network. The data storage system can store the data that the server cluster 103 needs to process. The server 102 is used to monitor various running data of the user node cluster 101 and the server cluster 103, run the business twin model corresponding to the user node cluster 101 and the digital twin algorithm network corresponding to the server cluster 103; The data storage system can be integrated on the server cluster 103, or it can be placed on the cloud or other network servers. Among them, each node in the user node cluster 101 can be, but is not limited to, various personal computers, notebook computers, smart phones, tablet computers, Internet of Things devices and portable wearable devices. The Internet of Things device can be a smart speaker, a smart TV, a smart air conditioner, a smart vehicle device, etc. The portable wearable device can be a smart watch, a smart bracelet, a head-mounted device, etc. The server cluster 104 can be realized by an independent server or a server cluster composed of multiple servers. It is worth noting that, Figure 1 The application environment in the above is only a schematic diagram of the logical connection relationship of each node, and does not one by one correspond to the position relationship of each node in the actual environment. In fact, each node in the user node cluster 101 and the server cluster 103 is scattered and distributed within a certain area range.

[0041] In one embodiment, as Figure 2 shown, a business scheduling path planning method based on digital twinning is provided. Taking the server 102 in Figure 1 as an example for illustration, the method comprises the following steps:

[0042] Step 201, obtaining user service data;

[0043] Among them, the user service data refers to the user service data that needs to be calculated for resource path planning at present, for example, if the current user service is the service of a certain e-commerce APP, then the corresponding user service data is the service plan data including the use of the current APP and the service required by the e-commerce APP in the coming service peak.

[0044] Preferably, the user service data includes the service type, service volume, service computing power demand, service network demand, service index and service performance demand of the current user service.

[0045] Specifically, the server 102 can obtain the user service data related to the current user through network monitoring, and also can be the user service data submitted by the current user to the server 102 according to the actual situation, reporting his own demand plan in the future.

[0046] Step 202, input the user service data into the service twin model of the digital twin system, so that the service twin model simulates the user service data, and generates service runtime sequence prediction data of the user service data;

[0047] The digital twin system is a model pre-built by a digital twin technology, including a service twin model and a digital twin algorithm network. The digital twin technology refers to a simulation process integrating multiple disciplines and multiple scales by fully utilizing a physical model, a sensor, current algorithm network operation history data, local various user service history data and other information. As a mirror of an entity product in a virtual space, the digital twin technology reflects a full life cycle process of a corresponding physical entity product. The digital twin system in the present application is obtained by simulating user services and algorithm network resources in a certain region, for example, a model built by digital twinning all user services in A city and existing algorithm network resources in A city.

[0048] The service twin model refers to a virtual model obtained by digital twinning all user services in a region, which can abstract common parameters of all user services in the region, such as network traffic, service type classification, maximum traffic in a data peak period, etc.

[0049] The digital twin algorithm network refers to a mapping model obtained by virtually simulating the structure, quantity, performance parameters, etc. of the local algorithm network.

[0050] Specifically, the user service data to be planned for resource scheduling path is input into the service twin model of the digital twin application system. The service twin model can predict the service runtime sequence prediction data of the user service in a future preset time period according to the type of the current user service and the past operation law of the current user service.

[0051] Step 203, input the above service runtime sequence prediction data into the digital twin algorithm network of the digital twin application system, and calculate the running path of the service runtime sequence prediction data in the digital twin algorithm network by using the path planning model, to obtain a target scheduling path.

[0052] Specifically, the service running time sequence prediction data is input into the digital twin computing network. Since the digital twin computing network is a virtual mapping of the distribution locations and running states of the computing resources in the current region, the service running time sequence prediction data is simulated and calculated in the digital twin computing network through a certain path planning algorithm, and the target scheduling path can be obtained in combination with the service data distribution law of other users in the region in the future preset time period. The target scheduling path can be an optimal path that meets the user demand. For example, if the user service has a high requirement on time delay, the target scheduling path can allocate the computing resources that are close to the user and idle to the user according to the high time delay requirement of the user.

[0053] The above embodiment can realize service running prediction of different user service models by establishing a digital twin application system suitable for general services, obtain the computing resource demand of the user in a future period of time, and obtain the optimal computing resource scheduling path that matches the current user demand by combining the computing resource demand with the current digital twin computing network. The optimal computing resource scheduling path not only meets the computing demand of the user, but also globally plans the computing resources in the current region, reasonably allocates the computing resources, maximally and effectively uses the limited computing network, and achieves the purpose of reducing cost and increasing efficiency.

[0054] In an embodiment, before the step 201, the method further includes: modeling the entity network, the logical network, and the topological relationship of the current computing network in three dimensions to obtain an initial computing network model; obtaining real-time environment running data of the current computing network by a network telemetry method; and simulating the real-time environment running data in the initial computing network model by a digital twin method to obtain the digital twin computing network.

[0055] The current computing network refers to the actual situation of the computing resources in the region, including the number of devices, the distribution locations of nodes, the current states of nodes, performance parameters of nodes, and the like. The real-time environment running data includes real-time performance data, real-time fault data, real-time configuration data, and real-time resource data of the current computing network.

[0056] Specifically, the entity network, the logical network, and the topological relationship of the current computing network are modeled in three dimensions in the current region (i.e., in the current scheduling range) to obtain an initial computing network model. Real-time environment running data of the current computing network is obtained by a network telemetry method, that is, real-time performance data, real-time fault data, real-time configuration data, and real-time resource data of the current computing network are obtained by sensors distributed in the network. The real-time environment running data is simulated in the initial computing network model by a digital twin method to obtain the digital twin computing network.

[0057] In this embodiment, the real-time running model of the local computing power network is obtained by simulating the local computing power network distribution and the real-time running state of the current computing power network using the digital twin method, thereby providing an effective calculation model for subsequent allocation of computing power resources according to user demand.

[0058] In an embodiment, before step 201, the method further includes: obtaining general service parameters; and generating the service twin model by performing real-time processing on the general service parameters using the digital thread technology.

[0059] The digital thread technology is one of the key technologies in the digital twin technology. The digital thread is a communication framework that can show the interconnected data flow and integrated view of asset data throughout the entire life cycle (from raw materials to final products), and can shield different types of data and model formats to support rapid flow and seamless integration of all types of data and models.

[0060] Specifically, the general service parameters are obtained using the digital thread. The general service parameters are common parameters of user services in the region, which are set in advance, such as network traffic data, traffic peak time of each service, etc. The service twin model corresponding to all user services in the region is obtained by simulating and flowing the general service parameters using the digital thread technology.

[0061] The above embodiment generates the general service twin model corresponding to all services in the region using the digital thread technology, thereby providing a data basis for subsequent allocation of operator resources and path planning for a specific user service.

[0062] In an embodiment, the path planning model in step 203 is generated based on a dynamic weight and an ant colony algorithm.

[0063] The ant colony algorithm is a probabilistic algorithm used to find an optimal path and is applied to solve optimization problems. The basic idea is to use the walking path of an ant to represent a feasible solution to the optimization problem, and all paths of the entire ant colony constitute the solution space of the optimization problem. Ants that take shorter paths release more pheromone, and as time progresses, the concentration of pheromone accumulated on shorter paths gradually increases, and the number of ants choosing that path also increases. Eventually, the entire ant colony will concentrate on the best path under the action of positive feedback, which corresponds to the optimal solution to the optimization problem.

[0064] Specifically, based on the dynamic weight and the optimized ant colony algorithm, the scheduling path planning in the computing network resource region is completed through AI intelligent decision-making, and the scheduling result is simulated and continuously optimized in the digital twin computing network to find the optimal scheduling path (i.e., the target scheduling path).

[0065] In the embodiment, the walking path of each ant represents a resource allocation scheme, which includes the number of server nodes and node identification in the resource allocation scheme.

[0066] First, the decision criteria are determined by dynamic weight, and then the optimal path is determined based on the optimized ant colony algorithm.

[0067] The dynamic weight is used to build a multi-path selection model based on dynamic weight by effectively analyzing the variable network environment in the region. The bandwidth, delay, jitter, and packet loss rate of the network path in the specific region of the network are used as the decision criteria for network path selection. The fitness function in the ant colony algorithm is determined based on the decision criteria.

[0068] The idea of the optimized ant colony algorithm is to divide all ants into k ant colonies, each including m ants. In one iteration, there are k x m ants participating in path search. The pheromone released by the ants during the search process only affects the same ant colony and does not interfere with each other. A resource occupation table is set to record the network resource occupation information of all ants during the search process. If two or more ants arrive at the same network node at the same time along different paths and request the use of the same network resource, a comprehensive measurement-based key network resource scheduling strategy is used to determine the allocation scheme or the priority of the resource. If the ant arrives at the target node within the constraint range, it indicates that there is a network path to complete the corresponding task. When all k ants complete the search, the network path set is recorded, the task completion rate is calculated, and the network pheromone is locally updated. If k x m ants complete one search, it indicates that one iteration is completed, the path planning scheme with the highest task completion rate is recorded, and the pheromone of each path in the path planning scheme is updated.

[0069] Preferably, the user service data includes service status data and user perception data. The current state of the service is diagnosed based on the service status data and user perception data, and the AI intelligent judgment is used to determine whether the general service can be normally completed. If yes, the general service is guaranteed to run normally based on the pre-planned network resource scheduling path. Otherwise, the state of the production service in the future is predicted based on the data trend through digital twin simulation technology, the network resource state in the region is searched from the digital twin network, and the optimal scheduling path is found through AI intelligent decision based on dynamic weight and optimized ant colony algorithm, and the scheduling result is simulated and continuously optimized in the digital twin network to ensure the normal operation of the general service.

[0070] The above embodiment can predict the optimal computing resource scheduling path based on the current user's service characteristics by using the ant colony algorithm combined with dynamic weight.

[0071] In an embodiment, before step 201, the method further comprises: initializing the business twin model and the digital twin computing network by using a 3D visualization engine, and displaying the initialized business twin model and the initialized digital twin computing network.

[0072] Specifically, the digital twin computing network and the business twin model are initialized by using the 3D visualization engine, so as to realize the visualization of the digital twin computing network and the business twin model.

[0073] In the embodiment, the visualization of the digital twin computing network and the business twin model is realized by using the 3D visualization engine, so that the resource scheduling on the digital twin application system is more intuitive, and the monitoring of the computing resource usage in the region is more convenient.

[0074] The digital-twin-based business scheduling path planning device provided by the application is described below, and the digital-twin-based business scheduling path planning device described below can be correspondingly referred to the digital-twin-based business scheduling path planning method described above.

[0075] In one embodiment, as shown in Figure 3 A digital-twin-based business scheduling path planning device is provided, which comprises a business data acquisition module 301, a business running prediction module 302, and a target scheduling path calculation module 303, wherein

[0076] The business data acquisition module 301 is configured to acquire user business data.

[0077] The business running prediction module 302 is configured to input the user business data into a business twin model of a digital twin application system, so that the business twin model simulates the user business data to generate business running time sequence prediction data of the user business data.

[0078] The target scheduling path calculation module 303 is configured to input the business running time sequence prediction data into a digital twin computing network of the digital twin application system, and calculate a running path of the business running time sequence prediction data in the digital twin computing network by using a path planning model, to obtain a target scheduling path.

[0079] In an embodiment, the device further comprises a digital twin model generation unit configured to perform three-dimensional modeling on an entity network, a logical network, and a topological relationship of a current computing network to obtain an initial computing network model, acquire real-time environment running data of the current computing network by using a network telemetry method, and simulate the real-time environment running data in the initial computing network model by using a digital twin method to obtain the digital twin computing network.

[0080] In one embodiment, the real-time environment operation data includes the real-time performance data, real-time fault data, real-time configuration data, and real-time resource data of the current computing power network.

[0081] In one embodiment, the digital twin model generation unit is further configured to acquire general business parameters; and to process the general business parameters in real time using digital thread technology to generate the business twin model.

[0082] In one embodiment, the path planning model is generated based on dynamic weights and an ant colony algorithm.

[0083] In one embodiment, the user service data includes service type, service volume, service computing power requirements, service network requirements, service metrics, and service performance requirements.

[0084] In one embodiment, the aforementioned digital twin model generation unit is further configured to initialize the business twin model and the digital twin computing network using a 3D visualization engine, and display the initialized business twin model and the initialized digital twin computing network.

[0085] Figure 4 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 4 As shown, the electronic device may include a processor 410, a communications interface 420, a memory 430, and a communication bus 440. The processor 410, communications interface 420, and memory 430 communicate with each other via the communication bus 440. The processor 410 can call logical instructions in the memory 430 to execute a service scheduling path planning method based on digital twins. This method includes: acquiring user service data; inputting the user service data into a service twin model of the digital twin application system, so that the service twin model simulates the user service data and generates service runtime sequence prediction data for the user service data; inputting the service runtime sequence prediction data into the digital twin computing network of the digital twin application system, and using a path planning model to calculate the running path of the service runtime sequence prediction data in the digital twin computing network to obtain a target scheduling path.

[0086] In addition, the logic instructions in the memory 430 described above can be implemented in the form of a software function unit and sold or used as an independent product, which can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application essentially or the parts that contribute to the prior art or parts of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0087] In another aspect, the present application also provides a computer program product, which comprises a computer program, the computer program can be stored on a non-transitory computer readable storage medium, and the computer program can be executed by a processor to enable a computer to execute the service scheduling path planning method based on digital twinning provided by the above-mentioned methods, the method comprising: obtaining user service data; inputting the user service data into a service twin model of a digital twinning application system, so that the service twin model simulates the user service data to generate service runtime sequence prediction data of the user service data; inputting the service runtime sequence prediction data into a digital twinning algorithm network of the digital twinning application system, and calculating the running path of the service runtime sequence prediction data in the digital twinning algorithm network by using a path planning model to obtain a target scheduling path.

[0088] In another aspect, the present application also provides a non-transitory computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the service scheduling path planning method based on digital twinning provided by the above-mentioned methods, the method comprising: obtaining user service data; inputting the user service data into a service twin model of a digital twinning application system, so that the service twin model simulates the user service data to generate service runtime sequence prediction data of the user service data; inputting the service runtime sequence prediction data into a digital twinning algorithm network of the digital twinning application system, and calculating the running path of the service runtime sequence prediction data in the digital twinning algorithm network by using a path planning model to obtain a target scheduling path.

[0089] The device embodiments described above are merely illustrative, wherein the units described as separate components can or can not be physically separate, and the components displayed as units can or can not be physical units, i.e., can be located in one place, or can be distributed to multiple network units. Part or all of the modules can be selected to achieve the purposes of the embodiments according to actual needs. Those skilled in the art can understand and implement without creative labor.

[0090] Through the description of the above embodiments, those skilled in the art can clearly understand that the embodiments can be realized by means of software and the necessary general hardware platform, and of course can also be realized by hardware. Based on such understanding, the above technical solutions can be embodied in the form of a software product, which can be stored in a computer readable storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute the methods described in each embodiment or some parts of the embodiments.

[0091] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement to part of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A service scheduling path planning method based on digital twins, characterized in that, include: Obtain user business data; The user business data is input into the business twin model of the digital twin application system, so that the business twin model can simulate the user business data and generate business runtime sequence prediction data of the user business data; wherein, the business runtime sequence prediction data represents the computing resource requirements of the user business data in a future preset time period; The business runtime sequence prediction data is input into the digital twin computing network of the digital twin application system. The path planning model is used to calculate the running path of the business runtime sequence prediction data in the digital twin computing network to obtain the target scheduling path. The path planning model is generated based on dynamic weights and ant colony algorithm.

2. The service scheduling path planning method based on digital twins according to claim 1, characterized in that, Before acquiring user business data, the method includes: A three-dimensional model of the physical network, logical network, and topological relationships of the current computing power network is performed to obtain the initial computing network model; Real-time environmental operation data of the current computing network is obtained through network telemetry methods; The digital twin computing network is obtained by simulating the real-time environment operation data in the initial computing network model using the digital twin method.

3. The service scheduling path planning method based on digital twins according to claim 2, characterized in that, The real-time environment operation data includes the real-time performance data, real-time fault data, real-time configuration data, and real-time resource data of the current computing power network.

4. The service scheduling path planning method based on digital twins according to claim 1, characterized in that, Before acquiring user business data, the method further includes: Obtain general business parameters; The general business parameters are processed in real time using digital thread technology to generate the business twin model.

5. The service scheduling path planning method based on digital twins according to claim 1, characterized in that, The user service data includes service type, service volume, service computing power requirements, service network requirements, service metrics, and service performance requirements.

6. The service scheduling path planning method based on digital twins according to any one of claims 1 to 5, characterized in that, Before acquiring user business data, the process also includes: The business twin model and the digital twin computing network are initialized using a 3D visualization engine, and the initialized business twin model and the initialized digital twin computing network are displayed.

7. A service scheduling path planning device based on digital twins, characterized in that, include: The business data acquisition module is used to acquire user business data; The business operation prediction module is used to input the user business data into the business twin model of the digital twin application system, so that the business twin model can simulate the user business data and generate business operation sequence prediction data of the user business data; wherein, the business operation sequence prediction data represents the computing power resource requirements of the user business data in a future preset time period; The target scheduling path calculation module is used to input the business runtime sequence prediction data into the digital twin computing network of the digital twin application system, and use the path planning model to calculate the running path of the business runtime sequence prediction data in the digital twin computing network to obtain the target scheduling path; wherein, the path planning model is generated based on dynamic weights and ant colony algorithm.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the service scheduling path planning method based on digital twins as described in any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the digital twin-based service scheduling path planning method as described in any one of claims 1 to 6.

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