A method, device, equipment and medium for determining a QoS scheduling scheme

Abstract

The present invention discloses a method, apparatus, device, and medium for determining a QoS scheduling scheme. The method comprises: obtaining QoS reference description information of each communication device in a current industrial scenario under multiple alternative QoS scheduling schemes; calculating the performance description information of multiple QoS flows in the current industrial scenario under each alternative QoS scheduling scheme based on each QoS reference description information and the service flow information of each communication device; calculating the scheduling scheme score corresponding to each alternative QoS scheduling scheme based on the performance description information of multiple QoS flows under each alternative QoS scheduling scheme; determining a target alternative QoS scheduling scheme in each alternative QoS scheduling scheme based on the scoring value of each scheduling scheme, and using the target alternative QoS scheduling scheme to perform network configuration for the current industrial scenario. By adopting the above technical solution, the optimal QoS scheduling scheme in the industrial scenario can be obtained.

Description

Technical Field

[0001] The present invention relates to the field of 5G communication technology, and in particular to a method, device, equipment and medium for determining a QoS scheduling scheme. Background Art

[0002] QoS (Quality of Service) is a technology used to address issues such as network latency and congestion. In industrial scenarios, optimizing the quality of service within a given scenario can be achieved by configuring a scheduling scheme for each QoS flow within each PDU (Protocol Data Unit) session on the 5G network. This is known as configuring a QoS scheduling scheme within that industrial scenario.

[0003] Most of the existing QoS scheduling schemes are formulated by operators based on the working requirements of various communication devices in the current industrial scenario, and are repeatedly tested after formulation to obtain the final QoS scheduling scheme.

[0004] However, the QoS scheduling solution obtained by the above method is not necessarily the optimal QoS scheduling solution in the current industrial scenario. It may cause the network performance in the current industrial scenario to not reach the optimal state and fail to guarantee the security of each communication device. Summary of the Invention

[0005] The present invention provides a method, apparatus, device and medium for determining a QoS scheduling scheme, which can obtain the optimal QoS scheduling scheme in an industrial scenario.

[0006] According to one aspect of the present invention, a method for determining a QoS scheduling scheme is provided, the method comprising:

[0007] Obtain QoS reference description information for each communication device in the current industrial scenario under multiple alternative QoS scheduling schemes;

[0008] Based on each QoS reference description information and the service flow information of each communication device, the performance description information of multiple QoS flows under each alternative QoS scheduling scheme in the current industrial scenario is calculated;

[0009] Calculate the scheduling scheme score corresponding to each alternative QoS scheduling scheme based on the performance description information of multiple QoS flows under each alternative QoS scheduling scheme;

[0010] According to the score values ​​of each scheduling scheme, a target alternative QoS scheduling scheme is determined among the alternative QoS scheduling schemes, and the target alternative QoS scheduling scheme is used to configure the network for the current industrial scenario.

[0011] According to another aspect of the present invention, a device for determining a QoS scheduling scheme is provided, characterized by comprising:

[0012] A reference description information acquisition module is used to obtain QoS reference description information of each communication device in the current industrial scenario under multiple alternative QoS scheduling schemes;

[0013] A performance description information acquisition module is used to calculate the performance description information of multiple QoS flows under each alternative QoS scheduling scheme in the current industrial scenario based on each QoS reference description information and the service flow information of each communication device;

[0014] A scheduling scheme scoring module is used to calculate a scheduling scheme scoring value corresponding to each alternative QoS scheduling scheme based on the performance description information of multiple QoS flows under each alternative QoS scheduling scheme;

[0015] The scheduling scheme selection module is used to determine the target alternative QoS scheduling scheme from among the alternative QoS scheduling schemes according to the scoring values ​​of each scheduling scheme, and use the target alternative QoS scheduling scheme to configure the network for the current industrial scenario.

[0016] According to another aspect of the present invention, an electronic device is provided, comprising:

[0017] at least one processor; and

[0018] a memory communicatively connected to the at least one processor; wherein,

[0019] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to perform the method for determining the QoS scheduling scheme described in any embodiment of the present invention.

[0020] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for determining the QoS scheduling scheme described in any embodiment of the present invention when executed.

[0021] The technical solution of the embodiment of the present invention obtains various types of information related to QoS scheduling in the current industrial scenario, and combines the machine learning model to obtain the performance description information of multiple QoS flows under each alternative QoS scheduling scheme, thereby calculating the score value of each QoS scheduling scheme, and finally obtaining the target alternative QoS scheduling scheme with the highest score value. This realizes the fair selection of the optimal QoS scheduling scheme among multiple alternative QoS scheduling schemes in the current industrial scenario.

[0022] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0024] Figure 1 is a flowchart of a method for determining a QoS scheduling solution provided according to embodiment 1 of the present invention;

[0025] Figure 2 is a flowchart of a method for determining a QoS scheduling solution provided according to embodiment 2 of the present invention;

[0026] Figure 3 1 is a schematic structural diagram of a device for determining a QoS scheduling solution according to a third embodiment of the present invention;

[0027] Figure 4 The present invention is a schematic diagram of the structure of an electronic device for implementing the method for determining a QoS scheduling solution according to an embodiment of the present invention. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0029] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0030] Example 1

[0031] Figure 1 This is a flowchart of a method for determining a QoS scheduling scheme provided in Example 1 of the present invention. This embodiment can be applied to obtaining the optimal QoS scheduling scheme in the current industrial scenario based on various types of information in the current industrial scenario. The method can be executed by a QoS scheduling scheme determination device. The QoS scheduling scheme determination device can be implemented in the form of hardware and / or software. The QoS scheduling scheme determination device can be configured in a computer or server with data processing capabilities.

[0032] To facilitate understanding of the present invention, the relationship between communication devices, QoS scheduling schemes, and QoS flows is explained here. An industrial scenario may include multiple communication devices, each of which can establish multiple PDU sessions with a base station based on workload allocation. Consequently, each communication device can generate multiple different QoS flows. Each QoS scheduling scheme includes a configuration scheme for the multiple QoS flows within the industrial scenario. By selecting an appropriate QoS scheduling scheme, network configuration can be performed for each communication device, ensuring optimal network performance within the industrial scenario.

[0033] The existing method of manually configuring QoS scheduling schemes may obtain relatively safe QoS scheduling schemes, but they are not necessarily the optimal QoS scheduling schemes in the current industrial scenario. This may result in the network performance in the industrial scenario not being able to reach the optimal state when using the manually configured QoS scheduling scheme, and when the network is congested, the security of each communication device cannot be guaranteed.

[0034] like Figure 1 As shown, the method includes:

[0035] S110: Obtain QoS reference description information of each communication device in the current industrial scenario under multiple alternative QoS scheduling schemes.

[0036] The QoS reference description information may include at least one of the following:

[0037] QoS throughput indicators, ARP (Allocation and Retention Priority) information, GBR (Guaranteed Bit Rate) information, and required bandwidth.

[0038] Specifically, the QoS reference description information can generally be pre-configured when generating a QoS scheduling solution.

[0039] A QoS flow is a data flow with the same QoS requirements within a PDU session. Since QoS flows are the finest granularity of QoS differentiation within a PDU session, the QoS scheduling solution can be used to configure each QoS flow within each PDU session in current industrial scenarios.

[0040] The difference between QoS technology in 5G and 4G communications is that in 5G communications, QoS flow is the finest QoS differentiation granularity, but in 4G communications, bearer is the basic QoS differentiation granularity.

[0041] Industrial scenarios may include base stations and various communication devices used to execute work instructions. The base stations and various communication devices can be connected through a 5G network, and each communication device can conduct multiple PDU sessions.

[0042] The alternative QoS scheduling schemes can be formulated by the operator based on the working requirements and historical experience of each communication device. In order to ensure that the QoS scheduling scheme finally obtained is the optimal scheduling scheme, the alternative QoS scheduling schemes can include all QoS scheduling schemes that the operator can provide.

[0043] The purpose of obtaining QoS reference description information of each communication device in the current industrial scenario under multiple alternative QoS scheduling schemes is to facilitate further use of the QoS reference description information to calculate performance description information of each QoS flow in the current industrial scenario.

[0044] S120 . Calculate performance description information of multiple QoS flows under each alternative QoS scheduling scheme in the current industrial scenario based on each QoS reference description information and service flow information of each communication device.

[0045] The performance description information includes required bandwidth, throughput, and transmission control protocol TCP delay; the service flow information of each communication device may include GBR information of each service flow processed by each communication device.

[0046] The purpose of calculating the performance description information of multiple QoS flows under each alternative QoS scheduling scheme in the current industrial scenario is to obtain the performance description information for further scoring each QoS flow.

[0047] Furthermore, the performance description information of multiple QoS flows under each alternative QoS scheduling scheme in the current industrial scenario can be calculated through a machine learning model. The machine learning model can include at least one sub-model, and the machine learning model can be trained using historical data related to the machine learning model.

[0048] In a specific embodiment, the machine learning model may include an access network QoS allocation submodel, a channel propagation submodel, and a transport layer / application layer QoS submodel. The access network QoS allocation submodel can be used to calculate the required bandwidth of each QoS flow, the channel propagation submodel can be used to calculate the throughput of each QoS flow, and the transport layer / application layer QoS submodel can be used to calculate the TCP delay.

[0049] The QoS reference description information and service flow information mentioned in the technical solution of the present invention can also increase or decrease adaptability according to the selection of different machine learning models. The QoS reference description information and service flow information required by different machine learning models may be different. The purpose of this step is only to obtain the performance description information of the QoS flow for further calculation of the score of the QoS scheduling scheme. Therefore, it is only necessary to ensure that the performance description information of the QoS flow can be obtained through the selected machine learning model.

[0050] S130: Calculate a scheduling scheme score corresponding to each candidate QoS scheduling scheme according to the performance description information of multiple QoS flows under each candidate QoS scheduling scheme.

[0051] Since a QoS scheduling scheme can include multiple QoS flows, and the performance description information of multiple QoS flows under each alternative QoS scheduling scheme in the current industrial scenario is obtained through the above method, the score value of each QoS flow can be calculated first, and then the score values ​​of all QoS flows under each alternative QoS scheduling scheme can be integrated to obtain the score value of each alternative QoS scheduling scheme.

[0052] In an embodiment of the present invention, the pros and cons of the scheduling scheme can be evaluated by the size of the score value. The larger the score value, the better the scheduling scheme is and the more it meets the QoS requirements in the current industrial scenario. The smaller the score value, the less the scheduling scheme meets the QoS requirements in the current industrial scenario.

[0053] Furthermore, since each QoS flow has a different priority, if the score of each QoS flow in the QoS scheduling scheme is added together to calculate the score of the QoS scheduling scheme, QoS flows with higher scores but lower priorities may affect the score of the overall QoS scheduling scheme. To ensure that the final QoS scheduling scheme is the optimal one, the QoS flow priority parameters can be set so that the optimal QoS scheduling scheme can first consider the needs of all high-priority access devices.

[0054] The advantage of this setting is that it takes into account the different priorities of various QoS flows and ensures the fairness of selecting the optimal QoS scheduling solution by setting priority parameters.

[0055] S140 . Determine a target alternative QoS scheduling scheme from among the alternative QoS scheduling schemes according to the score values ​​of each scheduling scheme, and use the target alternative QoS scheduling scheme to perform network configuration for the current industrial scenario.

[0056] After obtaining the score values ​​of each alternative QoS scheduling scheme, the score values ​​of each alternative QoS scheduling scheme can be compared, and the QoS scheduling scheme with the highest score value can be selected as the target alternative QoS scheduling scheme for network configuration in the current industrial scenario.

[0057] The technical solution of the embodiment of the present invention obtains various types of information related to QoS scheduling in the current industrial scenario, and combines the machine learning model to obtain the performance description information of multiple QoS flows under each alternative QoS scheduling scheme, thereby calculating the score value of each QoS scheduling scheme, and finally obtaining the target alternative QoS scheduling scheme with the highest score value. This realizes the fair selection of the optimal QoS scheduling scheme among multiple alternative QoS scheduling schemes in the current industrial scenario.

[0058] Example 2

[0059] Figure 2 This is a flowchart of a method for determining a QoS scheduling solution provided by the second embodiment of the present invention. Based on the above embodiment, this embodiment further specifies the process of obtaining the performance description information of the QoS flow and the process of scoring the QoS scheduling solution. Figure 2 As shown, the method includes:

[0060] S210: Obtain QoS reference description information of each communication device in the current industrial scenario under multiple alternative QoS scheduling schemes.

[0061] S220: Obtain scene description information of the current industrial scene.

[0062] The scene description information may include at least one of the following:

[0063] Base station transmission power, network bandwidth, network latency, base station location coordinates, and background noise interference in current industrial scenarios.

[0064] Scene description information can be obtained by measuring the current industrial scene using relevant equipment.

[0065] S230 , combining the QoS reference description information of each communication device under each alternative QoS scheduling scheme with the scenario description information and the device location information, respectively, to obtain comprehensive description information of each communication device under each alternative QoS scheduling scheme.

[0066] S240. Calculate performance description information of at least one QoS flow of each communication device under each alternative QoS scheduling scheme based on the comprehensive description information and service flow information of each communication device under each alternative QoS scheduling scheme.

[0067] Calculating the performance description information of at least one QoS flow of each communication device under each alternative QoS scheduling scheme based on the comprehensive description information and service flow information of each communication device under each alternative QoS scheduling scheme may specifically include:

[0068] The comprehensive description information and service flow information of each communication device under each alternative QoS scheduling scheme are respectively input into the pre-trained machine learning model to obtain the performance description information of at least one QoS flow of each communication device under each alternative QoS scheduling scheme.

[0069] S250: Summarize the performance description information of multiple QoS flows of each communication device under each alternative QoS scheduling solution.

[0070] S260: Calculate score information of multiple QoS flows under each candidate QoS scheduling scheme based on the performance description information of multiple QoS flows under each candidate QoS scheduling scheme.

[0071] Calculating the score information of the multiple QoS flows under each alternative QoS scheduling scheme according to the performance description information of the multiple QoS flows under each alternative QoS scheduling scheme may specifically include:

[0072] Get the jth candidate QoS scheduling solution pro currently being processed j Performance description information of N target QoS flows under

[0073] According to the formula:

[0074]

[0075] Calculate the target QoS flow of item i separately i The flow score of , i∈[1,N]; j∈[1,M], M is the total number of alternative QoS scheduling schemes;

[0076] w1 and w2 are normalization parameters, delay target The network delay in the current production scenario, delay is flow i TCP latency, throughput is flow i Throughput, demand is flow i Required bandwidth.

[0077] The reason for setting the normalization parameters w1 and w2 is that, considering that different indicators have different magnitudes in the QoS scheduling scheme, the scores of different indicators can be normalized by setting the two parameters w1 and w2.

[0078] The reason for choosing the logarithmic function is: to prevent and If the value of is too large, which affects the fairness of QoS flow scoring, the logarithmic function is used to and Controlling the value of within a reasonable range is also a means to achieve score normalization.

[0079] S270: Calculate the scheduling scheme score value corresponding to each candidate QoS scheduling scheme according to the multiple QoS flow score information under each candidate QoS scheduling scheme.

[0080] Calculating the scheduling scheme score value corresponding to each candidate QoS scheduling scheme based on the multiple QoS flow score information under each candidate QoS scheduling scheme may specifically include:

[0081] According to the formula:

[0082]

[0083] Calculated and pro j The corresponding scheduling scheme score value Score(pro j ), priority i For the preset flow i The priority parameter.

[0084] It is understandable that in the same industrial scenario, when the services allocated to each communication device remain unchanged, the number of QoS flows under each QoS scheduling scheme should be the same, but the reason why the sum of all QoS flow scoring information under the target QoS scheduling scheme is not used as the scoring value of the QoS scheduling scheme is that: in order to obtain the optimal QoS scheduling scheme, the needs of communication devices with higher priority should be considered first, and the proportion of scores for QoS flows with higher priority and QoS flows with lower priority in the same QoS scheduling scheme should be different.

[0085] Based on the above perspective, embodiments of the present invention also incorporate a priority parameter when calculating the QoS scheduling scheme score. Optionally, a larger priority parameter represents a lower priority. By setting the inverse of the priority, the score of a higher-priority QoS flow can have a greater impact on the QoS scheduling scheme score, making the ultimately selected optimal QoS scheduling scheme more in line with actual needs.

[0086] S280. Compare the scheduling scheme scores of the alternative QoS scheduling schemes, select the alternative QoS scheduling scheme with the highest scheduling scheme score as the target alternative QoS scheduling scheme, and use the target alternative QoS scheduling scheme to configure the network for the current industrial scenario.

[0087] The technical solution of the embodiment of the present invention fully takes into account the problem that different indicators have different magnitudes in the QoS scheduling scheme by adding normalization parameters and priority parameters when calculating the score of the QoS scheduling scheme. At the same time, it takes into account the problem that QoS flows with different priorities should not have the same impact on the score of the QoS scheduling scheme, thereby ensuring that the target alternative QoS scheduling scheme finally obtained is fair and can achieve communication optimization of each communication device.

[0088] Example 3

[0089] Figure 3 This is a structural diagram of a device for determining a QoS scheduling solution provided in the third embodiment of the present invention. Figure 3 As shown, the device includes: a reference description information acquisition module 310, a performance description information acquisition module 320, a scheduling scheme scoring module 330 and a scheduling scheme selection module 340.

[0090] The reference description information acquisition module 310 is used to obtain QoS reference description information of each communication device in the current industrial scenario under multiple alternative QoS scheduling schemes.

[0091] The performance description information acquisition module 320 is used to calculate the performance description information of multiple QoS flows under each alternative QoS scheduling scheme in the current industrial scenario based on each QoS reference description information and the service flow information of each communication device.

[0092] The scheduling scheme scoring module 330 is configured to calculate a scheduling scheme scoring value corresponding to each candidate QoS scheduling scheme based on the performance description information of multiple QoS flows under each candidate QoS scheduling scheme.

[0093] The scheduling scheme selection module 340 is used to determine a target alternative QoS scheduling scheme from among the alternative QoS scheduling schemes according to the score values ​​of each scheduling scheme, and use the target alternative QoS scheduling scheme to perform network configuration for the current industrial scenario.

[0094] The technical solution of the embodiment of the present invention obtains various types of information related to QoS scheduling in the current industrial scenario, and combines the machine learning model to obtain the performance description information of multiple QoS flows under each alternative QoS scheduling scheme, thereby calculating the score value of each QoS scheduling scheme, and finally obtaining the target alternative QoS scheduling scheme with the highest score value. This realizes the fair selection of the optimal QoS scheduling scheme among multiple alternative QoS scheduling schemes in the current industrial scenario.

[0095] Based on the above embodiments, the QoS reference description information may include at least one of the following:

[0096] QoS throughput indicators, allocation and reservation priority ARP information, guaranteed bit rate GBR information and required bandwidth.

[0097] Based on the above embodiments, the performance description information acquisition module 320 may include:

[0098] A scene description information acquisition unit, used to acquire scene description information of the current industrial scene;

[0099] a comprehensive description information acquisition unit, configured to combine the QoS reference description information of each communication device under each alternative QoS scheduling scheme with the scenario description information and the device location information, respectively, to obtain comprehensive description information of each communication device under each alternative QoS scheduling scheme;

[0100] a performance description information calculation unit, configured to calculate performance description information of at least one QoS flow of each communication device under each alternative QoS scheduling scheme based on the comprehensive description information and service flow information of each communication device under each alternative QoS scheduling scheme;

[0101] The performance description information aggregation unit is used to aggregate the performance description information of multiple QoS flows of each communication device under each alternative QoS scheduling solution.

[0102] Based on the above embodiments, the scene description information may include at least one of the following:

[0103] Base station transmission power, network bandwidth, network latency, base station location coordinates, and background noise interference in current industrial scenarios.

[0104] Based on the above embodiments, the performance description information includes required bandwidth, throughput and Transmission Control Protocol TCP delay.

[0105] Based on the above embodiments, the performance description information calculation unit can be specifically used to: input the comprehensive description information and service flow information of each communication device under each alternative QoS scheduling scheme into a pre-trained machine learning model, and obtain the performance description information of at least one QoS flow of each communication device under each alternative QoS scheduling scheme.

[0106] Based on the above embodiments, the scheduling scheme scoring module 330 can be specifically used to:

[0107] Get the jth candidate QoS scheduling solution pro currently being processed j Performance description information of N target QoS flows under

[0108] According to the formula:

[0109]

[0110] Calculate the target QoS flow of item i separately i The flow score of , i∈[1,N]; j∈[1,M], M is the total number of alternative QoS scheduling schemes;

[0111] w1 and w2 are normalization parameters, delay target The network delay in the current production scenario, delay is flow i TCP latency, throughput is flow i Throughput, demand is flow i Required bandwidth;

[0112] According to the formula:

[0113]

[0114] Calculated and pro j The corresponding scheduling scheme score value Score(pro j ), priority i For the preset flow i The priority parameter.

[0115] Based on the above embodiments, the scheduling scheme selection module 340 can be specifically used to:

[0116] The scheduling scheme scores of the alternative QoS scheduling schemes are compared, and the alternative QoS scheduling scheme with the highest scheduling scheme score is selected as the target alternative QoS scheduling scheme.

[0117] The QoS scheduling scheme determination device provided in the embodiment of the present invention can execute the QoS scheduling scheme determination method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0118] Example 4

[0119] Figure 4 A schematic diagram of the structure of an electronic device 40 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0120] like Figure 4 As shown, the electronic device 40 includes at least one processor 41 and a memory, such as a read-only memory (ROM) 42, a random access memory (RAM) 43, etc., which is communicatively connected to the at least one processor 41. The memory stores a computer program that can be executed by the at least one processor, and the processor 41 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 42 or the computer program loaded from the storage unit 48 into the random access memory (RAM) 43. Various programs and data required for the operation of the electronic device 40 can also be stored in the RAM 43. The processor 41, ROM 42, and RAM 43 are connected to each other via a bus 44. An input / output (I / O) interface 45 is also connected to the bus 44.

[0121] Multiple components in the electronic device 40 are connected to the I / O interface 45, including an input unit 46, such as a keyboard, a mouse, etc.; an output unit 47, such as various types of displays, speakers, etc.; a storage unit 48, such as a magnetic disk, an optical disk, etc.; and a communication unit 49, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 49 allows the electronic device 40 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0122] The processor 41 may be a variety of general and / or specialized processing components with processing and computing capabilities. Some examples of the processor 41 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The processor 41 executes the various methods and processes described above, such as the method for determining the QoS scheduling scheme described in the embodiment of the present invention. That is:

[0123] Obtain QoS reference description information for each communication device in the current industrial scenario under multiple alternative QoS scheduling schemes;

[0124] Based on each QoS reference description information and the service flow information of each communication device, the performance description information of multiple QoS flows under each alternative QoS scheduling scheme in the current industrial scenario is calculated;

[0125] Calculate the scheduling scheme score corresponding to each alternative QoS scheduling scheme based on the performance description information of multiple QoS flows under each alternative QoS scheduling scheme;

[0126] According to the score values ​​of each scheduling scheme, a target alternative QoS scheduling scheme is determined among the alternative QoS scheduling schemes, and the target alternative QoS scheduling scheme is used to configure the network for the current industrial scenario.

[0127] In some embodiments, the method for determining a QoS scheduling scheme may be implemented as a computer program that is tangibly contained in a computer-readable storage medium, such as a storage unit 48. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 40 via the ROM 42 and / or the communication unit 49. When the computer program is loaded into the RAM 43 and executed by the processor 41, one or more steps of the method for determining a QoS scheduling scheme described above may be performed. Alternatively, in other embodiments, the processor 41 may be configured to perform the method for determining a QoS scheduling scheme in any other appropriate manner (e.g., by means of firmware).

[0128] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0129] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer program is executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0130] In the context of the present invention, computer-readable storage media can be tangible media that can contain or store a computer program for use with an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. Computer-readable storage media can include but are not limited to electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, computer-readable storage media can be machine-readable signal media. More specific examples of machine-readable storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0131] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0132] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0133] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0134] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.

[0135] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A method for determining a quality of service (QoS) scheduling scheme, characterized in that: include: Obtain QoS reference description information for each communication device in the current industrial scenario under multiple alternative QoS scheduling schemes; Based on each QoS reference description information and the service flow information of each communication device, the performance description information of multiple QoS flows under each alternative QoS scheduling scheme in the current industrial scenario is calculated; Calculate the scheduling scheme score corresponding to each alternative QoS scheduling scheme based on the performance description information of multiple QoS flows under each alternative QoS scheduling scheme; According to the scoring values ​​of each scheduling scheme, a target alternative QoS scheduling scheme is determined among the alternative QoS scheduling schemes, and the target alternative QoS scheduling scheme is used to configure the network for the current industrial scenario; The QoS reference description information includes at least one of the following: QoS throughput indicators, allocation and reservation priority ARP information, guaranteed bit rate GBR information and required bandwidth; The calculation of the performance description information of multiple QoS flows in each alternative QoS scheduling scheme in the current industrial scenario includes: Calculate the performance description information of multiple QoS flows under each alternative QoS scheduling scheme in the current industrial scenario through a machine learning model trained with relevant historical data; The machine learning model includes an access network QoS allocation sub-model, a channel propagation sub-model, and a transport layer / application layer QoS sub-model; the performance description information includes required bandwidth, throughput, and transmission control protocol TCP delay; The machine learning model calculates the performance description information of multiple QoS flows under each alternative QoS scheduling scheme in the current industrial scenario, including: Calculate the required bandwidth of each QoS flow through the access network QoS allocation sub-model; Calculating the throughput of each QoS flow through the channel propagation sub-model; The transmission control protocol TCP delay of each QoS flow is calculated through the transport layer / application layer QoS sub-model.

2. The method according to claim 1, characterized in that Based on each QoS reference description information and the service flow information of each communication device, the performance description information of multiple QoS flows under each alternative QoS scheduling scheme in the current industrial scenario is calculated, including: Get the scene description information of the current industrial scene; Combine the QoS reference description information of each communication device under each alternative QoS scheduling scheme with the scenario description information and the device location information to obtain comprehensive description information of each communication device under each alternative QoS scheduling scheme; Calculate performance description information of at least one QoS flow of each communication device under each alternative QoS scheduling scheme based on the comprehensive description information and service flow information of each communication device under each alternative QoS scheduling scheme; The performance description information of multiple QoS flows of each communication device under each alternative QoS scheduling scheme is summarized.

3. The method according to claim 2, characterized in that The scene description information includes at least one of the following: Base station transmission power, network bandwidth, network latency, base station location coordinates, and background noise interference in current industrial scenarios.

4. The method according to claim 3, characterized in that The performance description information includes required bandwidth, throughput and transmission control protocol TCP delay; Calculating performance description information of at least one QoS flow of each communication device under each alternative QoS scheduling scheme based on the comprehensive description information and service flow information of each communication device under each alternative QoS scheduling scheme, including: The comprehensive description information and service flow information of each communication device under each alternative QoS scheduling scheme are respectively input into the pre-trained machine learning model to obtain the performance description information of at least one QoS flow of each communication device under each alternative QoS scheduling scheme.

5. The method according to claim 4, characterized in that Based on the performance description information of multiple QoS flows under each candidate QoS scheduling scheme, a scheduling scheme score corresponding to each candidate QoS scheduling scheme is calculated, including: Get the jth candidate QoS scheduling solution pro currently being processed j Performance description information of N target QoS flows under According to the formula: Calculate the target QoS flow of item i separately i The traffic score of , i∈[1, N]; j∈[1, M], M is the total number of alternative QoS scheduling schemes; w1 and w2 are normalization parameters, delay target The network delay in the current production scenario, delay is flow i TCP latency, throughput is flow i Throughput, demand is flow i Required bandwidth; According to the formula: Calculated and pro j The corresponding scheduling scheme score value Score(pro j ), priority i For the preset flow i The priority parameter.

6. The method according to any one of claims 1 to 5, characterized in that Based on the scores of each scheduling scheme, a target alternative QoS scheduling scheme is determined from among the alternative QoS scheduling schemes, including: The scheduling scheme scores of the alternative QoS scheduling schemes are compared, and the alternative QoS scheduling scheme with the highest scheduling scheme score is selected as the target alternative QoS scheduling scheme.

7. A device for determining a QoS scheduling scheme, characterized in that: include: A reference description information acquisition module is used to obtain QoS reference description information of each communication device in the current industrial scenario under multiple alternative QoS scheduling schemes; A performance description information acquisition module is used to calculate the performance description information of multiple QoS flows under each alternative QoS scheduling scheme in the current industrial scenario based on each QoS reference description information and the service flow information of each communication device; A scheduling scheme scoring module is used to calculate a scheduling scheme scoring value corresponding to each alternative QoS scheduling scheme based on the performance description information of multiple QoS flows under each alternative QoS scheduling scheme; The scheduling scheme selection module is used to determine the target alternative QoS scheduling scheme from the alternative QoS scheduling schemes based on the scoring values ​​of each scheduling scheme, and use the target alternative QoS scheduling scheme to configure the network for the current industrial scenario; The QoS reference description information includes at least one of the following: QoS throughput indicators, allocation and reservation priority ARP information, guaranteed bit rate GBR information and required bandwidth; The calculation of the performance description information of multiple QoS flows in each alternative QoS scheduling scheme in the current industrial scenario includes: Calculate the performance description information of multiple QoS flows under each alternative QoS scheduling scheme in the current industrial scenario through a machine learning model trained with relevant historical data; The machine learning model includes an access network QoS allocation sub-model, a channel propagation sub-model, and a transport layer / application layer QoS sub-model; the performance description information includes required bandwidth, throughput, and transmission control protocol TCP delay; The machine learning model calculates the performance description information of multiple QoS flows under each alternative QoS scheduling scheme in the current industrial scenario, including: Calculate the required bandwidth of each QoS flow through the access network QoS allocation sub-model; Calculating the throughput of each QoS flow through the channel propagation sub-model; The transmission control protocol TCP delay of each QoS flow is calculated through the transport layer / application layer QoS sub-model.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to perform the method for determining a quality of service (QoS) scheduling scheme according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for determining a quality of service (QoS) scheduling solution according to any one of claims 1 to 6 when executed.

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