Network service orchestration and scheduling method and apparatus, device and storage medium

Abstract

Provided are a network service orchestration and scheduling method and apparatus, a device and a storage medium. The method comprises: acquiring computing power service node information and network quality information of a current in-cloud computing power service; obtaining a first orchestration result of a mobile terminal on the basis of the mobile terminal, the computing power service node information and the network quality information; scheduling service traffic of the mobile terminal to an optimal computing power service node and forwarding path comprised in the first orchestration result; obtaining a second orchestration result of the mobile terminal on the basis of an updated position of the mobile terminal, updated computing power service node information or network quality information; and on the basis of evaluation values of different types of services preset, determining whether to schedule the service traffic of the mobile terminal to an optimal computing power service node and forwarding path comprised in the second orchestration result.

Description

Network service orchestration and scheduling method, device, equipment and storage medium

[0001] This disclosure claims priority to Chinese patent application No. 202410101193.3, filed on January 24, 2024, the entire contents of which are incorporated herein by reference. Technical Field

[0002] The present disclosure relates to the field of computing power service technology, and in particular to a network service orchestration and scheduling method and apparatus, device, and storage medium. Background Art

[0003] With the rapid development of 5G and the cloud era, thousands of industries have more stringent requirements for computing resources and network services. The computing power network can realize on-demand scheduling of computing resources and provide intelligent network services. Summary of the Invention

[0004] In a first aspect, an embodiment of the present disclosure provides a method for orchestrating and scheduling network services. The method includes:

[0005] Obtain computing power service node information and network quality information of the current computing power service in the cloud;

[0006] Obtaining a first scheduling result for the mobile terminal based on the mobile terminal, computing power service node information, and network quality information. The first scheduling result is an optimal computing power service node and forwarding path for the mobile terminal at its current location.

[0007] Dispatching the service traffic of the mobile terminal to the optimal computing power service node and forwarding path included in the first orchestration result;

[0008] Obtaining a second scheduling result for the mobile terminal based on the updated location of the mobile terminal, the updated computing power service node information, or the network quality information, the second scheduling result including an optimal computing power service node and a forwarding path for the mobile terminal at the updated location;

[0009] According to preset evaluation values ​​of different types of services, it is determined whether to schedule the service traffic of the mobile terminal to the optimal computing power service node and forwarding path included in the second orchestration result.

[0010] In an embodiment of the present disclosure, before obtaining computing service node information and network quality information of the current computing service in the cloud, the method includes:

[0011] The current computing service node information and network quality information are obtained from the computing network management and orchestration system. The current computing service node information and network quality information are uploaded to the computing network management and orchestration system by the computing service in the cloud.

[0012] In the embodiment of the present disclosure, before obtaining the current computing power service node information and network quality information, the method further includes:

[0013] The current computing power service node information and network quality information are obtained from the network device. The current computing power service node information and network quality information are sent to the network device by the cloud computing power service through the border gateway protocol or the internal gateway protocol.

[0014] In an embodiment of the present disclosure, before obtaining the second orchestration result of the mobile terminal based on the updated location of the mobile terminal, the updated computing service node information, and the network quality information, the method further includes:

[0015] Determining a predicted location of the mobile terminal based on the planned route of the mobile terminal;

[0016] Determine the optimal service node and forwarding path for the predicted location based on the predicted location and the computing service node information and network quality information of the current computing service in the cloud.

[0017] Perform resource pre-configuration and pre-start operations on the optimal service node at the predicted location.

[0018] In an embodiment of the present disclosure, obtaining a second scheduling result of the mobile terminal according to the updated location of the mobile terminal, the updated computing service node information, or the network quality information includes:

[0019] Determine whether the updated position is consistent with the predicted position;

[0020] Determine whether the optimal computing power service node corresponding to the second arrangement result of the mobile terminal is consistent with the optimal service node of the predicted position.

[0021] In an embodiment of the present disclosure, after determining whether the optimal computing service node corresponding to the second scheduling result of the mobile terminal is consistent with the optimal service node of the predicted location, the method includes:

[0022] When the determination result shows that the updated location is consistent with the predicted location, and the optimal computing service node corresponding to the second orchestration result is consistent with the optimal service node of the predicted location, determining the optimal service node and forwarding path of the predicted location as the second orchestration result for the mobile terminal;

[0023] When the judgment result is that the updated location is consistent with the predicted location, and the optimal computing power service node corresponding to the second orchestration result is inconsistent with the optimal service node of the predicted location, the optimal computing power service node and forwarding path of the updated location are determined to be the second orchestration result of the mobile terminal.

[0024] In an embodiment of the present disclosure, after determining whether the optimal computing power service node corresponding to the second scheduling result of the mobile terminal is consistent with the optimal service node of the predicted location, the method further includes:

[0025] When the judgment result is that the updated location is inconsistent with the predicted location, and the optimal computing service node corresponding to the second orchestration result is consistent with the optimal service node of the predicted location, determining the optimal service node and forwarding path of the predicted location as the second orchestration result of the mobile terminal;

[0026] When the judgment result is that the updated location is inconsistent with the predicted location, and the optimal computing power service node corresponding to the second orchestration result is inconsistent with the optimal service node of the predicted location, the optimal computing power service node and forwarding path of the updated location are determined to be the second orchestration result of the mobile terminal.

[0027] In an embodiment of the present disclosure, determining whether to schedule service traffic of a mobile terminal to the optimal computing power service node and forwarding path included in the second orchestration result based on pre-set evaluation values ​​of different types of services includes:

[0028] Determine the evaluation parameters for the optimal computing service node and forwarding path, including CPU utilization, GPU utilization, TPU utilization, storage utilization, latency, available bandwidth, bandwidth utilization, packet loss rate, and available backup paths;

[0029] According to the evaluation parameter calculation formula, the value of the evaluation parameter is obtained. The evaluation parameter calculation formula is:

[0030] y is the value of the evaluation parameter, Xia is the evaluation parameter of the optimal computing service node and forwarding path of the first orchestration result, Xib is the evaluation parameter of the optimal computing service node and forwarding path of the second orchestration result, N is the number of evaluation parameters, i∈(1,N);

[0031] Comparing the value of the evaluation parameter with the evaluation value of the business to obtain a comparison result;

[0032] Based on the comparison result, it is determined whether to schedule the service traffic of the mobile terminal to the optimal computing power service node and forwarding path included in the second orchestration result.

[0033] In an embodiment of the present disclosure, determining whether to schedule service traffic of a mobile terminal to the optimal computing power service node and forwarding path included in the second orchestration result based on pre-set evaluation values ​​of different types of services includes:

[0034] If the comparison result shows that the value of the evaluation parameter is greater than the evaluation value of the service, the service traffic of the mobile terminal is dispatched to the optimal computing power service node and forwarding path included in the second orchestration result;

[0035] When the comparison result shows that the value of the evaluation parameter is less than or equal to the evaluation value of the service, the service traffic of the mobile terminal is reserved on the optimal computing power service node and forwarding path included in the first orchestration result.

[0036] In a second aspect, an embodiment of the present disclosure provides a network service orchestration and scheduling device. The device includes: an acquisition module, a first orchestration module, a scheduling module, a second orchestration module, and a judgment module;

[0037] The acquisition module is used to obtain the computing service node information and network quality information of the current computing service in the cloud;

[0038] A first orchestration module is configured to obtain a first orchestration result for the mobile terminal based on the mobile terminal, computing power service node information, and network quality information, where the first orchestration result is an optimal computing power service node and forwarding path for the mobile terminal at its current location;

[0039] A scheduling module, configured to schedule the service traffic of the mobile terminal to the optimal computing power service node and forwarding path included in the first orchestration result;

[0040] A second orchestration module is configured to obtain a second orchestration result for the mobile terminal based on the updated location of the mobile terminal, the updated computing power service node information, or the network quality information, where the second orchestration result includes an optimal computing power service node and forwarding path for the mobile terminal at the updated location;

[0041] The judgment module is used to determine whether to dispatch the service traffic of the mobile terminal to the optimal computing power service node and forwarding path included in the second orchestration result according to the preset evaluation values ​​of different types of services.

[0042] In a third aspect, an embodiment of the present disclosure provides an electronic device, comprising: a processor, and a memory communicatively connected to the processor;

[0043] Memory stores computer-executable instructions;

[0044] The processor executes the computer-executable instructions stored in the memory to perform the network service orchestration and scheduling method described in the first aspect of the embodiment of the present disclosure.

[0045] In a fourth aspect, an embodiment of the present disclosure provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the network service orchestration and scheduling method described in the first aspect of the embodiment of the present disclosure.

[0046] In a fifth aspect, an embodiment of the present disclosure provides a computer program product, comprising computer program instructions, which, when executed by a processor, implement the network service orchestration and scheduling method described in the first aspect of the embodiment of the present disclosure.

[0047] In a sixth aspect, an embodiment of the present disclosure provides a computer program, comprising computer program instructions, which, when executed by a processor, implement the network service orchestration and scheduling method described in the first aspect of the embodiment of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0049] FIG1 is a schematic diagram of a scenario of a network service orchestration and scheduling method according to some embodiments.

[0050] FIG2A is a flowchart illustrating a method for orchestrating and scheduling network services according to some embodiments.

[0051] FIG2B is a system diagram of computing network management, control, and orchestration according to some embodiments.

[0052] FIG3 is a flowchart of a method for obtaining a second arrangement result of a mobile terminal according to some embodiments.

[0053] FIG4 is a flowchart of a method for scheduling service traffic of a mobile terminal according to some embodiments.

[0054] FIG5 is a schematic structural diagram of a network service orchestration and scheduling device according to some embodiments.

[0055] FIG6 is a structural block diagram of a device for executing the network service orchestration and scheduling method according to some embodiments of the present disclosure.

[0056] The above drawings illustrate specific embodiments of the present disclosure, which will be described in more detail below. These drawings and textual descriptions are not intended to limit the scope of the present disclosure in any way, but rather to illustrate the concepts of the present disclosure to those skilled in the art by reference to specific embodiments. DETAILED DESCRIPTION

[0057] Exemplary embodiments will be described in detail herein, examples of which are illustrated in the accompanying drawings. In the following description, when referring to the drawings, like numbers in different figures represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all possible embodiments consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.

[0058] The following will clearly and completely describe the technical solutions of this disclosure in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of this disclosure, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of this disclosure without inventive effort are within the scope of protection of this disclosure.

[0059] It should be noted that in this disclosure, expressions such as "exemplarily" or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design described in this disclosure as "exemplary" or "for example" should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of expressions such as "exemplarily" or "for example" is intended to present the relevant concepts in a detailed manner.

[0060] In the following, the terms "first," "second," etc. are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the quantity of the technical features indicated. Therefore, a feature specified as "first," "second," etc. may explicitly or implicitly include one or more of the features.

[0061] In the description of this disclosure, unless otherwise specified, " / " means "or." For example, A / B can mean A or B. "And / or" herein is simply a way to describe an association relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can mean: only A, A and B, and only B. Furthermore, "at least one" means one or more, and "a plurality" means two or more.

[0062] With the rapid development of 5G and the cloud era, numerous industries are placing ever-more stringent demands on computing resources and network services. Computing networks enable on-demand scheduling of computing resources and provide intelligent network services. Many application scenarios of the Internet of Vehicles (IoV) have very high latency requirements. For example, in remote driving scenarios, basic road condition information collected by the vehicle's cameras, radar, and other equipment must be uploaded to a cloud computing service. After computation and processing, the cloud computing service sends the generated road condition status to the remote cockpit. The remote cockpit then issues driving instructions based on real-time road condition information, and the vehicle executes the instructions. Throughout this process, the collected information must be uploaded to the cloud computing service for processing as quickly as possible and quickly sent to the remote cockpit. This ensures real-time transmission of road condition status and ensures that the vehicle's status when executing the instructions is consistent with the status of the cockpit when the instructions were issued.

[0063] However, some technologies have delays when mobile terminals access cloud computing services, resulting in poor user experience.

[0064] In some technologies, in the Internet of Vehicles scenario, when vehicle terminals access services in the cloud pool, the network forwarding path is selected only based on the network status. In addition, the impact of changes in computing power status and network status during the movement of the vehicle, as well as changes in vehicle location on the computing power service orchestration, are not considered. Secondly, although some solutions for vehicle terminals to access services in the cloud pool take computing power status and network status into consideration, the overall user experience of the Internet of Vehicles service is not high.

[0065] Based on this, a network service orchestration and scheduling method provided by an embodiment of the present disclosure proposes a computing network for computing network perception when a mobile terminal is driving, and makes computing routing decisions based on the perception information. At the same time, in the process of orchestration and scheduling, cloud computing services are pre-prepared according to the route that the mobile terminal may travel, so as to achieve the effect of rapid switching of computing service nodes without user perception. Finally, resources are prepared or released according to the driving conditions of the mobile terminal and the changes in the computing network status, further improving the overall user experience of the Internet of Vehicles business.

[0066] The network service orchestration and scheduling method provided in this disclosure is intended to solve the above technical problems of some technologies.

[0067] The following detailed embodiments describe the technical solution of the present disclosure and how the technical solution of the present disclosure solves the above-mentioned technical problems. The following detailed embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The following embodiments of the present disclosure are described in conjunction with the accompanying drawings.

[0068] Figure 1 is a schematic diagram of a scenario for a network service orchestration and scheduling method according to some embodiments. As shown in Figure 1, the network service orchestration and scheduling provided by the embodiments of the present disclosure is performed by a cloud server, which implements cloud computing services and orchestrates and schedules network services for mobile terminals, including vehicles and other types.

[0069] Figure 2A is a flow chart of a method for orchestrating and scheduling network services according to some embodiments. As shown in Figure 2A , the method includes: S201 to S205 .

[0070] S201. Obtain computing power service node information and network quality information of the current computing power service in the cloud.

[0071] Computing power refers to the ability of computer equipment or data centers to process information. Commonly used computing power service node information includes CPU utilization, GPU utilization, storage utilization, number of connections, etc.

[0072] Network quality information refers to network performance information. Network performance refers to the quality of service provided by the network system. Common network quality information includes latency, bandwidth, packet loss rate, etc.

[0073] It should be noted that before obtaining the computing service node information and network quality information of the current computing service in the cloud, the method includes:

[0074] The current computing service node information and network quality information are obtained from the computing network management and orchestration system. The current computing service node information and network quality information are uploaded to the computing network management and orchestration system by the computing service in the cloud.

[0075] Cloud computing power services refer to computing power services provided for network service orchestration and scheduling of mobile terminals; the computing network management and orchestration system includes multiple system modules such as network controllers, cloud controllers, and service orchestration platforms, which are used to orchestrate and notify computing power service node information and network quality information.

[0076] By using cameras or radars on mobile terminals, the collected road condition information is uploaded to the cloud computing service. After processing by the cloud computing service, the computing service node information and network quality information are obtained, which are then reported to the computing network control and orchestration system for orchestration, thereby obtaining the optimal computing service and forwarding path.

[0077] It should be noted that before obtaining the current computing power service node information and network quality information, the method also includes:

[0078] The current computing power service node information and network quality information are obtained from the network device. The current computing power service node information and network quality information are sent to the network device by the cloud computing power service through the border gateway protocol or the internal gateway protocol.

[0079] Network nodes can realize three major functions: storage, routing, and forwarding data. Network devices are devices that transmit data in the network, usually referring to routers or switches connected to the Internet.

[0080] After obtaining computing power service node information and network quality information through processing through the computing power service in the cloud, the computing power service node information and network quality information can also be sent to the network equipment for orchestration, and the optimal computing power service and forwarding path can also be obtained; the computing power service node information and network quality information can also be sent to the network equipment, and then the network equipment reports it to the computing network control and orchestration system for orchestration, and the obtained optimal computing power service and forwarding path are then sent to the network equipment.

[0081] S202. Obtain a first scheduling result for the mobile terminal based on the mobile terminal, computing power service node information, and network quality information. The first scheduling result is an optimal computing power service node and forwarding path for the mobile terminal at its current location.

[0082] The first orchestration result refers to the optimal computing service node and forwarding path of the current mobile terminal calculated by the computing network control and orchestration system or network equipment. For example, as shown in Figure 2B, if the current mobile terminal is at position A, the calculated optimal computing service node is located at the computing service 1-1 of MEC1, and the optimal forwarding path is R1-R4-R7-R10-R13.

[0083] Computing service refers to a model that uses a computing network as a connection, unifies the output of heterogeneous computing power through cloud computing technology, and uniformly encapsulates computing power, storage, network and other resources, and delivers them in the form of services; the computing service node refers to the MEC node serving the current mobile terminal, and the forwarding path refers to the communication path to the computing service node reaching the current mobile terminal. MEC (Multi-access Edge Computing) refers to a network architecture that allows cloud computing platforms to migrate from within the mobile core network to the edge of the mobile access network, thereby achieving better performance, latency and security.

[0084] A mobile terminal refers to a computer device that can be used on the move, including a vehicle's onboard computer.

[0085] S203: Schedule the service traffic of the mobile terminal to the optimal computing power service node and forwarding path included in the first orchestration result.

[0086] Mobile terminal traffic refers to the network traffic used to implement connected vehicle (IoV) business scenarios such as navigation, remote control, and intelligent driving. IoV business scenarios are primarily categorized as assisted driving and entertainment. High-priority traffic, such as vehicle warning information, needs to be dispatched to the optimal computing service node for computation. Non-real-time traffic, such as in-vehicle entertainment, is dispatched to remote nodes or the cloud for processing. This prioritizes low-latency services, ensuring user safety and a positive travel experience.

[0087] The business traffic of the mobile terminal is dispatched to the calculated optimal computing service node and forwarding path to facilitate the pre-preparation of cloud computing services along the routes that the mobile terminal may travel.

[0088] S204. Obtain a second scheduling result for the mobile terminal based on the updated location of the mobile terminal, the updated computing power service node information, or the network quality information. The second scheduling result includes an optimal computing power service node and forwarding path for the mobile terminal at the updated location.

[0089] When the user access location changes, or the computing power service status or network quality status changes, it is necessary to calculate the optimal computing power service node and forwarding path for the mobile terminal after the change.

[0090] It should be noted that before obtaining the second arrangement result of the mobile terminal based on the updated location of the mobile terminal, the updated computing service node information, or the network quality information, the following steps are also included:

[0091] Determining a predicted location of the mobile terminal based on the planned route of the mobile terminal;

[0092] Determine the optimal service node for the predicted location based on the predicted location and the computing service node information and network quality information of the current computing service in the cloud;

[0093] Perform resource pre-configuration and pre-start operations on the optimal service node at the predicted location.

[0094] The updated location of the mobile terminal refers to the geographical location that the mobile terminal will reach at the next moment, and the updated computing power service node information and network quality information refer to the computing power service node information and network quality information collected when the mobile terminal is at the geographical location at the next moment.

[0095] The second orchestration result refers to the optimal computing service node and forwarding path calculated based on the mobile terminal's next moment's geographic location, computing service node information, and network quality information. For example, as shown in Figure 2B, if the mobile terminal follows the pre-planned route and arrives at location B at the next moment, the optimal computing service node calculated based on this location is located at computing service 2-1 in MEC2, and the optimal forwarding path is R2-R5-R8-R11-R14.

[0096] The optimal computing service node is predicted based on the planned route when the mobile terminal is at the next geographical location. Resource pre-configuration and pre-start operations are prepared in advance at the computing service node. If the mobile terminal arrives at the predicted location at the next moment, the advance preparation of resources can effectively save the preparation time for service resource activation, pre-setting, etc.

[0097] For example, as shown in Figure 2B, if the planned route of the mobile terminal is to move from position A to position B, the optimal computing service node is calculated based on the predicted position B, which is the computing service 2-1 of MEC2. The computing network management and orchestration system issues instructions to open the computing service 2-1 in MEC2 in advance, and prepare resources in advance based on the needs of the mobile terminal.

[0098] S205: Determine whether to schedule the service traffic of the mobile terminal to the optimal computing power service node and forwarding path included in the second scheduling result based on preset evaluation values ​​of different types of services.

[0099] The evaluation value of the service is used to describe whether the user service meets the service retention or service stability requirements based on different types of user services. For example, in the embodiment of the present disclosure, a constant set according to historical evaluation parameter data is used as the threshold of the evaluation parameter that meets the service requirements, that is, the evaluation value of the service is set to the threshold value of 0.1. Alternatively, instructions that meet the service requirements can also be set according to the characteristics of different types of user services. For example, a certain type of user service needs to maintain 0.01S on the original computing power service node and forwarding path, that is, the evaluation value of the service is set to the corresponding instruction.

[0100] In the embodiment of the present disclosure, the evaluation value of the service is set to the threshold value of the evaluation parameter of 0.1. According to the first orchestration result and the second orchestration result, it is necessary to calculate the evaluation parameters of the computing power service node and the evaluation parameters of the forwarding path. The evaluation parameters of the computing power service node include CPU utilization, GPU utilization, TPU utilization, storage utilization, etc.; the evaluation parameters of the forwarding path include latency, available bandwidth, bandwidth utilization, packet loss rate, available backup path, etc.

[0101] When multiple evaluation parameters of the computing power service node in the second orchestration result are improved by more than a threshold compared to the multiple evaluation parameters of the computing power service node in the first orchestration result, it is determined that switching the computing power service node is meaningful. Otherwise, since the improvement in the evaluation parameters is not significant and the experience improvement brought by the switch is not enough to offset the service interruption or instability caused by the switch, the original computing power service node is maintained and the forwarding path is not switched.

[0102] In summary, the network service orchestration and scheduling method provided by the embodiments of the present disclosure obtains the optimal computing service node and optimal forwarding path for a mobile terminal based on computing service node information and network quality information. Furthermore, based on the possible travel routes of the mobile terminal, a predicted computing service node is obtained, and resources are pre-prepared for computing services within the cloud, achieving the effect of rapid switching of computing service nodes without user perception. At the same time, by recalculating the optimal computing service node and optimal forwarding path, evaluation parameters are calculated to determine whether to switch the computing service node and forwarding path, thereby achieving node load balancing and improving the overall user experience in the Internet of Vehicles service.

[0103] Based on the above embodiment, the following embodiment further illustrates the implementation of the method for obtaining the second arrangement result of the mobile terminal.

[0104] Fig. 3 is a flow chart of a method for obtaining a second arrangement result of a mobile terminal according to some embodiments. As shown in Fig. 3 , the method includes: S301 to S302.

[0105] S301: Determine whether the updated position is consistent with the predicted position.

[0106] As the network and services are constantly changing, the status of computing service node information and network quality information will also change accordingly. Therefore, an update notification is required. Different treatments are required for situations where the updated location and the corresponding computing service node deviate from the predicted location and the corresponding optimal service node. For example, as shown in Figure 2B, the predicted location of the mobile terminal is B. The optimal computing service node calculated based on this location is computing service 2-1 in MEC2, and the optimal forwarding path is R2-R5-R8-R11-R14. It is necessary to determine whether the actual updated location of the mobile terminal reaches location B and whether the corresponding optimal computing service node is computing service 2-1 in MEC2.

[0107] S302: Determine whether the optimal computing power service node corresponding to the second arrangement result of the mobile terminal is consistent with the optimal service node of the predicted position.

[0108] It should be noted that when the judgment result is that the updated location is consistent with the predicted location, and the optimal computing service node corresponding to the second orchestration result is consistent with the optimal service node of the predicted location, the optimal service node and forwarding path of the predicted location are determined as the second orchestration result of the mobile terminal;

[0109] When the judgment result is that the updated location is consistent with the predicted location, and the optimal computing service node corresponding to the second orchestration result is inconsistent with the optimal service node of the predicted location, determining the optimal computing service node and forwarding path of the updated location as the second orchestration result of the mobile terminal;

[0110] When the judgment result is that the updated location is inconsistent with the predicted location, and the optimal computing service node corresponding to the second orchestration result is consistent with the optimal service node of the predicted location, determining the optimal service node and forwarding path of the predicted location as the second orchestration result of the mobile terminal;

[0111] When the judgment result is that the updated location is inconsistent with the predicted location, and the optimal computing power service node corresponding to the second orchestration result is inconsistent with the optimal service node of the predicted location, the optimal computing power service node and forwarding path of the updated location are determined to be the second orchestration result of the mobile terminal.

[0112] As shown in Figure 2B, when the mobile terminal actually drives to the predicted location B, the optimal computing service node is the computing service 2-1 in MEC2, which means that the advance preparation work of resource pre-configuration and pre-start operation is effective, and it can be switched directly and quickly, effectively improving the switching rate; when the mobile terminal actually drives to the predicted location B, and the optimal computing service node is the computing service 3-1 in MEC3, it means that the advance preparation work of resource pre-configuration and pre-start operation is invalid, and the computing network control and orchestration system issues instructions to release resources, and quickly starts the service and prepares resources in 3-1 to realize the switching of computing service; when the mobile terminal actually drives to the location C. If the mobile terminal does not drive according to the pre-planned route, the optimal computing service node recalculated based on location C will still be computing service 3-1 in MEC3. At this time, the advance preparation work of resource pre-configuration and pre-start operation is still valid, and can be switched directly and quickly; when the mobile terminal actually drives to location C, the optimal computing service node recalculated based on location C becomes computing service 2-1 in MEC2, then the advance preparation work of resource pre-configuration and pre-start operation is invalid, and the computing network control and orchestration system issues instructions to release resources, and performs service startup and resource preparation of 3-1 to switch computing service.

[0113] In summary, the embodiments of the present disclosure obtain predicted computing power service nodes based on the possible travel routes of the mobile terminal, prepare resources for the computing power service in the cloud in advance, and then judge whether the prepared resources are valid based on the actual updated location traveled to, and then determine whether to switch the computing power service, which can reduce the delay in switching the computing power service nodes.

[0114] Based on the above embodiment, the following embodiment will describe in detail the implementation of the method for scheduling the service traffic of a mobile terminal according to a preset threshold.

[0115] Figure 4 is a flow chart of a method for scheduling service traffic of a mobile terminal according to some embodiments. As shown in Figure 4 , the method includes: S401 to S404.

[0116] S401. Determine evaluation parameters for the optimal computing service node and forwarding path, where the evaluation parameters include CPU utilization, GPU utilization, TPU utilization, storage utilization, latency, available bandwidth, bandwidth utilization, packet loss rate, and available backup paths.

[0117] S402. Obtain the value of the evaluation parameter according to the evaluation parameter calculation formula. The evaluation parameter calculation formula is:

[0118] y is the value of the evaluation parameter, Xia is the evaluation parameter of the optimal computing service node and forwarding path of the first orchestration result, Xib is the evaluation parameter of the optimal computing service node and forwarding path of the second orchestration result, N is the number of evaluation parameters, i∈(1,N);

[0119] S403: Compare the value of the evaluation parameter with the evaluation value of the service to obtain a comparison result;

[0120] S404: Determine, based on the comparison result, whether to schedule the service traffic of the mobile terminal to the optimal computing power service node and forwarding path included in the second orchestration result.

[0121] Based on the optimal computing power service node and forwarding path obtained in the second orchestration result, it is also necessary to calculate the values ​​of the evaluation parameters of the optimal computing power service node and forwarding path, and determine whether to schedule the service traffic to the optimal computing power service node and forwarding path included in the second orchestration result based on the evaluation value of the service.

[0122] The selection of evaluation parameters is based on actual conditions. One or more evaluation parameters can be selected, and the obtained evaluation parameter value is compared with a preset threshold. For example, when the CPU utilization is selected as an evaluation parameter and the threshold of the evaluation parameter is set to 0.1, it only makes sense to switch the computing power service when the CPU utilization of the optimal computing power service node and forwarding path of the second orchestration result is greater than 0.1 higher than the CPU utilization of the optimal computing power service node and forwarding path of the first orchestration result. Otherwise, since the CPU utilization is not increased much, and the user experience improvement brought about by the switching is not enough to match the business interruption or instability caused by the switching, it makes no sense to switch the computing power service.

[0123] For example, when multiple evaluation parameters are selected, if the first orchestration result includes the optimal computing service node a and the optimal forwarding path m, and the second orchestration result includes the optimal computing service node b and the optimal forwarding path n, the evaluation parameters for the optimal computing service node and forwarding path are:

[0124] The CPU utilization of the computing power service node is X1. In the first orchestration result, this value is X1a = 50%, and in the second orchestration result, this value is X1b = 40%;

[0125] Storage utilization of the computing power service node: X2. In the first arrangement result, this value is X2a = 70%, and in the second arrangement result, this value is X2b = 65%;

[0126] Forwarding path delay value: X3, in the first arrangement result, this value is X3a = 25ms, and in the second arrangement result, this value is X3b = 15ms;

[0127] The available bandwidth value of the forwarding path is X4. In the first arrangement result, this value is X4a = 50M, and in the second arrangement result, this value is X4b = 60M. The evaluation parameter calculation formula is: Get the value of the evaluation parameter:

[0128] Finally, the calculated value of the evaluation parameter is compared with the threshold to obtain a comparison result, and then determine whether to switch the computing power service node and forwarding path.

[0129] It should be noted that, based on the comparison result, determining whether to schedule the service traffic of the mobile terminal to the optimal computing power service node and forwarding path included in the second orchestration result includes:

[0130] If the comparison result shows that the value of the evaluation parameter is greater than the evaluation value of the service, the service traffic of the mobile terminal is dispatched to the optimal computing power service node and forwarding path included in the second orchestration result;

[0131] When the comparison result shows that the value of the evaluation parameter is less than or equal to the evaluation value of the service, the service traffic of the mobile terminal is reserved on the optimal computing power service node and forwarding path included in the first orchestration result.

[0132] The evaluation value of the service is set to the threshold value r=0.1 of the evaluation parameter. It can be determined that the value of the evaluation parameter is greater than the threshold value, and it is meaningful to switch the computing power service. Then, the service traffic of the mobile terminal is scheduled to the optimal computing power service node and forwarding path included in the second orchestration result.

[0133] In summary, the embodiment of the present disclosure calculates the optimal computing power service node and the optimal forwarding path included in the second orchestration result, calculates the value of the evaluation parameter according to the evaluation parameter formula, and then determines whether to switch the computing power service node and the forwarding path, thereby achieving load balancing of the computing power service node and improving the user's overall usage experience.

[0134] FIG5 is a schematic diagram of the structure of a network service orchestration and scheduling device according to some embodiments. As shown in FIG5 , the network service orchestration and scheduling device 500 includes: an acquisition module 501 , a first orchestration module 502 , a scheduling module 503 , a second orchestration module 504 , and a determination module 505 .

[0135] The acquisition module 501 is used to obtain the computing power service node information and network quality information of the current computing power service in the cloud.

[0136] The first orchestration module 502 is configured to obtain a first orchestration result for the mobile terminal based on the mobile terminal, computing power service node information, and network quality information. The first orchestration result is the optimal computing power service node and forwarding path for the mobile terminal at its current location.

[0137] The scheduling module 503 is configured to schedule the service traffic of the mobile terminal to the optimal computing power service node and forwarding path included in the first orchestration result.

[0138] The second orchestration module 504 is configured to obtain a second orchestration result for the mobile terminal based on the updated location of the mobile terminal, the updated computing service node information, or the network quality information. The second orchestration result includes an optimal computing service node and forwarding path for the mobile terminal at the updated location.

[0139] The judgment module 505 is used to determine whether to schedule the service traffic of the mobile terminal to the optimal computing power service node and forwarding path included in the second scheduling result according to the preset evaluation values ​​of different types of services.

[0140] In the embodiment of the present disclosure, the acquisition module 501 is further configured to:

[0141] The current computing service node information and network quality information are obtained from the computing network management and orchestration system. The current computing service node information and network quality information are uploaded to the computing network management and orchestration system by the computing service in the cloud.

[0142] In the embodiment of the present disclosure, the acquisition module 501 is further configured to:

[0143] The current computing power service node information and network quality information are obtained from the network device. The current computing power service node information and network quality information are sent to the network device by the cloud computing power service through the border gateway protocol or the internal gateway protocol.

[0144] In the embodiment of the present disclosure, the first orchestration module 502 is further configured to:

[0145] Determining a predicted location of the mobile terminal based on the planned route of the mobile terminal;

[0146] Determine the optimal service node for the predicted location based on the predicted location and the computing service node information and network quality information of the current computing service in the cloud;

[0147] Perform resource pre-configuration and pre-start operations on the optimal service node at the predicted location.

[0148] In the embodiment of the present disclosure, the second arrangement module 504 is further configured to:

[0149] Determine whether the updated position is consistent with the predicted position;

[0150] Determine whether the computing power service node corresponding to the second arrangement result of the mobile terminal is consistent with the optimal service node of the predicted position.

[0151] In the embodiment of the present disclosure, the second arrangement module 504 is further configured to:

[0152] When the judgment result is that the updated location is consistent with the predicted location, and the computing power service node corresponding to the second orchestration result is consistent with the optimal service node of the predicted location, determining the optimal service node and forwarding path of the predicted location as the second orchestration result of the mobile terminal;

[0153] When the judgment result is that the updated location is consistent with the predicted location, and the computing power service node corresponding to the second orchestration result is inconsistent with the optimal service node of the predicted location, the optimal computing power service node and forwarding path of the updated location are determined to be the second orchestration result of the mobile terminal.

[0154] In the embodiment of the present disclosure, the second arrangement module 504 is further configured to:

[0155] When the judgment result is that the updated location is inconsistent with the predicted location, and the computing power service node corresponding to the second orchestration result is consistent with the optimal service node of the predicted location, determining the optimal service node and forwarding path of the predicted location as the second orchestration result of the mobile terminal;

[0156] When the judgment result is that the updated position is inconsistent with the predicted position, and the computing power service node corresponding to the second orchestration result is inconsistent with the optimal service node of the predicted position, the optimal computing power service node and forwarding path of the updated position are determined to be the second orchestration result of the mobile terminal.

[0157] In the embodiment of the present disclosure, the determination module 505 is further configured to:

[0158] Determine the evaluation parameters for the optimal computing service node and forwarding path, including CPU utilization, GPU utilization, TPU utilization, storage utilization, latency, available bandwidth, bandwidth utilization, packet loss rate, and available backup paths;

[0159] According to the evaluation parameter calculation formula, the value of the evaluation parameter is obtained. The evaluation parameter calculation formula is:

[0160] y is the value of the evaluation parameter, Xia is the evaluation parameter of the optimal computing service node and forwarding path of the first orchestration result, Xib is the evaluation parameter of the optimal computing service node and forwarding path of the second orchestration result, N is the number of evaluation parameters, i∈(1,N);

[0161] Comparing the value of the evaluation parameter with the evaluation value of the business to obtain a comparison result;

[0162] Based on the comparison result, it is determined whether to schedule the service traffic of the mobile terminal to the optimal computing power service node and forwarding path included in the second orchestration result.

[0163] In the embodiment of the present disclosure, the determination module 505 is further configured to:

[0164] If the comparison result shows that the value of the evaluation parameter is greater than the evaluation value of the service, the service traffic of the mobile terminal is dispatched to the optimal computing power service node and forwarding path included in the second orchestration result;

[0165] When the comparison result shows that the value of the evaluation parameter is less than or equal to the evaluation value of the service, the service traffic of the mobile terminal is reserved on the optimal computing power service node and forwarding path included in the first orchestration result.

[0166] It should be noted that for the aforementioned method embodiments, for simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present disclosure is not limited by the order of the actions described, because according to the present disclosure, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required by the present disclosure.

[0167] It should be further noted that, although the various steps in the flowchart are shown in sequence as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps may be performed in other orders. Moreover, at least a portion of the steps in the flowchart may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily performed at the same time, but may be performed at different times. The execution order of these sub-steps or stages is not necessarily to be performed in sequence, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0168] It should be understood that the above-described device embodiments are merely illustrative, and the devices of the present disclosure may also be implemented in other ways. For example, the division of units / modules in the above-described embodiments is merely a logical functional division, and actual implementations may employ other division methods. For example, multiple units, modules, or components may be combined or integrated into another system, or some features may be omitted or not implemented.

[0169] In addition, unless otherwise specified, the functional units / modules in the various embodiments of the present disclosure may be integrated into a single unit / module, each unit / module may exist physically separately, or two or more units / modules may be integrated together. The aforementioned integrated units / modules may be implemented in the form of hardware or software program modules.

[0170] If the integrated unit / module is implemented in hardware, the hardware may be digital circuits, analog circuits, etc. The physical implementation of the hardware structure includes, but is not limited to, transistors, memristors, etc. Unless otherwise specified, the processor may be any appropriate hardware processor, such as a CPU, GPU, FPGA, DSP, and ASIC. Unless otherwise specified, the storage unit may be any appropriate magnetic storage medium or magneto-optical storage medium, such as resistive random access memory (RRAM), dynamic random access memory (DRAM), static random access memory (SRAM), enhanced dynamic random access memory (EDRAM), high-bandwidth memory (HBM), hybrid memory cube (HMC), etc.

[0171] If the integrated unit / module is implemented in the form of a software program module and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present disclosure is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a memory, including a number of instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various embodiments of the present disclosure. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program code.

[0172] Figure 6 is a schematic diagram of the structure of a device for executing the network service orchestration and scheduling method according to some embodiments of the present disclosure. As shown in Figure 6, the device 600 includes: a processor 601 with one or more processing cores, one or more memories 602 storing computer-readable storage media, a communication component 603, and other components. The processor 601, memory 602, and communication component 603 are connected via a bus 604.

[0173] In a detailed implementation process, at least one processor 601 executes computer-executable instructions stored in the memory 602 , so that at least one processor 601 executes the above network service orchestration and scheduling method.

[0174] The detailed implementation process of the processor 601 can be found in the above method embodiment. Its implementation principle and technical effects are similar and will not be repeated here in this embodiment.

[0175] In the embodiment shown in FIG6 above, it should be understood that the processor may be a central processing unit (CPU), or may be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the present disclosure may be directly implemented as being executed by a hardware processor, or may be executed by a combination of hardware and software modules in the processor.

[0176] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage.

[0177] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. Buses can be categorized as address buses, data buses, and control buses. For ease of illustration, the buses in the figures of this disclosure are not limited to just one bus or just one type of bus.

[0178] In the above embodiments, the description of each embodiment has its own emphasis. For parts not described in detail in a particular embodiment, please refer to the relevant description of other embodiments. The technical features of the above embodiments can be combined in any way. To keep the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0179] Furthermore, this embodiment provides an electronic device, including a memory and a memory communicatively connected to a processor, wherein the memory stores computer-executable instructions, and the processor executes the computer-executable instructions stored in the memory to implement the method in the embodiment of the present disclosure.

[0180] In some embodiments, the embodiments of the present disclosure further provide a computer program product, including a computer program or instructions, which implement any of the above-mentioned network service orchestration and scheduling methods when executed by a processor.

[0181] The detailed implementation of each of the above operations can be found in the previous embodiments and will not be repeated here.

[0182] Those skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be accomplished by instructions, or by controlling related hardware through instructions. The instructions may be stored in a computer-readable storage medium and loaded and executed by a processor.

[0183] To this end, embodiments of the present disclosure provide a computer-readable storage medium storing a plurality of computer-executable instructions that can be loaded by a processor to execute any of the network service orchestration and scheduling methods provided in embodiments of the present disclosure. The computer-readable storage medium includes a non-transitory computer-readable storage medium.

[0184] The storage medium may include: a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0185] According to one aspect of the present disclosure, an embodiment of the present disclosure also provides a computer program product or a computer program, which includes computer instructions. When the computer instructions are run on a computer, the computer executes any one of the network service orchestration and scheduling methods provided in the above embodiments.

[0186] Other embodiments of the present disclosure will readily occur to those skilled in the art after considering the specification and practicing the invention disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, with the true scope and spirit of the present disclosure being indicated by the following claims.

[0187] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes can be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A network service orchestration and scheduling method, comprising: Obtaining the computing power service node information and network quality information of the current in-cloud computing power service; Based on the mobile terminal, as well as the computing power service node information and network quality information, obtaining a first orchestration result of the mobile terminal, where the first orchestration result is the optimal computing power service node and forwarding path of the mobile terminal at the current location; Scheduling the service traffic of the mobile terminal to the optimal computing power service node and forwarding path included in the first orchestration result; Based on the updated location of the mobile terminal, updated computing power service node information, or network quality information, obtaining a second orchestration result of the mobile terminal, where the second orchestration result includes the optimal computing power service node and forwarding path of the mobile terminal at the updated location; Determining whether to schedule the service traffic of the mobile terminal to the optimal computing power service node and forwarding path included in the second orchestration result according to the evaluation values of different types of services set in advance.

2. The method according to claim 1, wherein, Before the step of obtaining the computing power service node information and network quality information of the current in-cloud computing power service, the method includes: Obtaining the current computing power service node information and network quality information from the computing network management and orchestration system, where the current computing power service node information and network quality information are uploaded by the in-cloud computing power service to the computing network management and orchestration system.

3. The method according to any one of claims 1 to 2, wherein Before the step of obtaining the current computing power service node information and network quality information, the method further includes: Obtaining the current computing power service node information and network quality information from network devices, where the current computing power service node information and network quality information are sent by the in-cloud computing power service to the network devices through the Border Gateway Protocol or the Interior Gateway Protocol.

4. The method according to any one of claims 1 to 3, wherein, Before the step of obtaining the second orchestration result of the mobile terminal based on the updated location of the mobile terminal, updated computing power service node information, or network quality information, the method further includes: Determining the predicted location of the mobile terminal according to the planned route of the mobile terminal; Based on the predicted location, as well as the computing power service node information and network quality information of the current in-cloud computing power service, determining the optimal service node and forwarding path at the predicted location; Performing resource pre-configuration and pre-start operations on the optimal service node at the predicted location.

5. The method according to any one of claims 1 to 4, wherein [[ID=!14]]The step of obtaining the second orchestration result of the mobile terminal based on the updated location of the mobile terminal, updated computing power service node information, or network quality information includes: Judging whether the updated location is consistent with the predicted location; Determining whether the optimal computing power service node corresponding to the second orchestration result of the mobile terminal is consistent with the optimal service node at the predicted location.

6. The method according to claim 5, wherein After the step of determining whether the optimal computing power service node corresponding to the second orchestration result of the mobile terminal is consistent with the optimal service node at the predicted location, the method includes: When the judgment result is that the updated location is consistent with the predicted location, and the optimal computing power service node corresponding to the second orchestration result is consistent with the optimal service node at the predicted location, determining the optimal service node and forwarding path at the predicted location as the second orchestration result of the mobile terminal; When the judgment result is that the updated position is consistent with the predicted position, and the optimal computing power service node corresponding to the second orchestration result is inconsistent with the optimal service node at the predicted position, determine the optimal computing power service node and forwarding path at the updated position as the second orchestration result of the mobile terminal.

7. The method according to any one of claims 5 to 6, wherein After determining whether the optimal computing power service node corresponding to the second orchestration result of the mobile terminal is consistent with the optimal service node at the predicted position, the method further includes: When the judgment result is that the updated position is inconsistent with the predicted position, and the optimal computing power service node corresponding to the second orchestration result is consistent with the optimal service node at the predicted position, determine the optimal service node and forwarding path at the predicted position as the second orchestration result of the mobile terminal; When the judgment result is that the updated position is inconsistent with the predicted position, and the optimal computing power service node corresponding to the second orchestration result is inconsistent with the optimal service node at the predicted position, determine the optimal computing power service node and forwarding path at the updated position as the second orchestration result of the mobile terminal.

8. The method according to claim 1, wherein Determining whether to schedule the service traffic of the mobile terminal to the optimal computing power service node and forwarding path included in the second orchestration result according to the evaluation values of different types of services set in advance includes: Determine the evaluation parameters of the optimal computing power service node and forwarding path, where the evaluation parameters include CPU utilization rate, GPU utilization rate, TPU utilization rate, storage utilization rate, latency, available bandwidth, bandwidth utilization rate, packet loss rate, available backup path; According to the evaluation parameter calculation formula, the value of the evaluation parameter is obtained, and the evaluation parameter calculation formula is as follows: Where y is the value of the evaluation parameter, Xia is the evaluation parameter of the optimal computing power service node and forwarding path of the first orchestration result, Xib is the evaluation parameter of the optimal computing power service node and forwarding path of the second orchestration result, N is the number of evaluation parameters, and i ∈ (1, N); Compare the value of the evaluation parameter with the evaluation value of the service to obtain a comparison result; According to the comparison result, determine whether to schedule the service traffic of the mobile terminal to the optimal computing power service node and forwarding path included in the second orchestration result.

9. The method according to claim 8, wherein, Determining whether to schedule the service traffic of the mobile terminal to the optimal computing power service node and forwarding path included in the second orchestration result according to the evaluation values of different types of services set in advance includes: When the comparison result is that the value of the evaluation parameter is greater than the evaluation value of the service, schedule the service traffic of the mobile terminal to the optimal computing power service node and forwarding path included in the second orchestration result; When the comparison result is that the value of the evaluation parameter is less than or equal to the evaluation value of the service, retain the service traffic of the mobile terminal on the optimal computing power service node and forwarding path included in the first orchestration result.

10. A network service orchestration and scheduling device, including: An acquisition module, configured to acquire the computing power service node information and network quality information of the current in-cloud computing power service; A first orchestration module, configured to obtain a first orchestration result of the mobile terminal according to the mobile terminal, the computing power service node information, and the network quality information, where the first orchestration result is the optimal computing power service node and forwarding path of the mobile terminal at the current location; A scheduling module, configured to schedule the service traffic of the mobile terminal to the optimal computing power service node and forwarding path included in the first orchestration result; A second orchestration module, configured to obtain a second orchestration result of the mobile terminal according to the updated location of the mobile terminal, the updated computing power service node information, or the network quality information, where the second orchestration result includes the optimal computing power service node and forwarding path of the mobile terminal at the updated location; A judgment module, configured to determine whether to schedule the service traffic of the mobile terminal to the optimal computing power service node and forwarding path included in the second orchestration result according to the evaluation values of different types of services set in advance.

11. An electronic device, comprising: A processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; When the processor executes the computer-executable instructions stored in the memory, the method according to any one of claims 1 to 9 is implemented.

12. A computer-readable storage medium, wherein, Computer-executable instructions are stored in the computer-readable storage medium, and when the computer-executable instructions are executed by the processor, the method according to any one of claims 1 to 9 is implemented.

13. A computer program product, including computer program instructions, where the computer program instructions implement the method according to any one of claims 1 to 9 when executed by the processor.

14. A computer program, including computer program instructions, where the computer program instructions implement the method according to any one of claims 1 to 9 when executed by the processor.

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