Edge computing load control method and related devices

Abstract

The present disclosure provides an edge computing load control method and related equipment, and relates to the technical field of edge computing. The method comprises the following steps: a first network element sends a subscription request to a second network element, the subscription request is used to subscribe to registration information of an edge computing device, and the registration information of the edge computing device is sent when the edge computing device is registered to the second network element after being online; in response to receiving the registration information of the edge computing device, a load control instruction is sent to the edge computing device, the load control instruction is used to instruct the edge computing device to measure a to-be-measured key indicator; and the measurement result of the to-be-measured key indicator measured by the edge computing device is received, so as to control the load of the edge computing device according to the measurement result of the to-be-measured key indicator. The present disclosure can enable the mobile network to instantly know the load condition of the edge computing device, so as to prepare for timely execution of the load control strategy.

Description

Technical Field

[0001] The present disclosure relates to the field of edge computing technology, and in particular to an edge computing load control method, an edge computing load control device, an edge computing system, an electronic device, a computer-readable storage medium, and a computer program product. Background Art

[0002] With the rapid development of communication technology, edge computing has become an integral part of mobile networks and a necessary guarantee for high bandwidth and low latency.

[0003] In related technologies, edge computing devices apply for quality of service (QoS) for applications. However, mobile networks cannot monitor the load of edge computing devices in real time, resulting in unreliable QoS guarantees and the inability to effectively integrate edge computing with mobile networks.

[0004] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure, and therefore may include information that does not constitute prior art known to ordinary technicians in the field. Summary of the Invention

[0005] The present disclosure provides an edge computing load control method and related equipment, which at least to a certain extent overcome the problems of existing edge computing that the service quality cannot be guaranteed and the user experience is poor.

[0006] Other features and advantages of the present disclosure will become apparent from the following detailed description, or may be learned in part by practice of the present disclosure.

[0007] According to one aspect of the present disclosure, there is provided an edge computing load control method, which is applied to a first network element, and the method includes: sending a subscription request to a second network element, wherein the subscription request is used to subscribe to registration information of an edge computing device, and the registration information of the edge computing device is sent when the edge computing device registers with the second network element after going online; in response to receiving the registration information of the edge computing device, sending a load control instruction to the edge computing device, and the load control instruction is used to instruct the edge computing device to measure a key indicator to be measured; and receiving a measurement result of the key indicator to be measured obtained by the edge computing device, so as to perform load control on the edge computing device according to the measurement result of the key indicator to be measured.

[0008] In one embodiment of the present disclosure, the load control instruction includes: the key indicator to be measured; a threshold value corresponding to the key indicator to be measured; and a reporting method of the key indicator to be measured.

[0009] In one embodiment of the present disclosure, the key indicator to be measured includes at least one of CPU usage, memory usage, network bandwidth occupancy, and the current number of concurrent tasks.

[0010] In one embodiment of the present disclosure, the reporting method of the key indicator to be measured includes event-triggered reporting and / or periodic reporting.

[0011] In one embodiment of the present disclosure, the method further includes: after receiving the registration information of the edge computing device, storing the registration information, Internet Protocol address (IP address), port, and active status of the edge computing device.

[0012] In one embodiment of the present disclosure, the load control strategy for performing load control on the edge computing device according to the measurement results of the key indicators to be measured includes at least one of the following: a quality of service QoS control strategy, wherein the QoS control strategy is used to match the best or corresponding QoS for the application deployed on the edge computing device; and a load balancing strategy, wherein the load balancing strategy is used to perform load balancing on the multiple edge computing devices based on the measurement results of the key indicators to be measured obtained by measuring the multiple edge computing devices.

[0013] According to another aspect of the present disclosure, an edge computing load control method is provided, which is applied to a second network element. The method includes: receiving a subscription request from a first network element, where the subscription request is used to subscribe to registration information of an edge computing device; receiving the registration information of the edge computing device; and sending the registration information of the edge computing device to the first network element.

[0014] In one embodiment of the present disclosure, the method further includes: storing the registration information of the edge computing device in a unified data repository.

[0015] According to another aspect of the present disclosure, an edge computing load control method is provided, which is applied to an edge computing device. The method includes: after the edge computing device is online, sending registration information of the edge computing device to a second network element for registration; receiving a load control instruction sent by a first network element, wherein the load control instruction is used to instruct the edge computing device to measure a key indicator to be measured; measuring the key indicator to be measured according to the load control instruction, obtaining a measurement result of the key indicator to be measured, and sending the measurement result of the key indicator to be measured to the first network element.

[0016] In an embodiment of the present disclosure, the measuring the to-be-measured key indicator according to the load control instruction, obtaining a measurement result of the to-be-measured key indicator, and sending the measurement result of the to-be-measured key indicator to the first network element comprises monitoring and sending the measurement result of the to-be-measured key indicator by a multi-access edge platform of the edge computing system.

[0017] In an embodiment of the present disclosure, the receiving the load control instruction sent by the first network element comprises receiving the load control instruction by a multi-access edge orchestrator or a multi-access edge platform of the edge computing system; and the measuring the to-be-measured key indicator according to the load control instruction, obtaining a measurement result of the to-be-measured key indicator, and sending the measurement result of the to-be-measured key indicator to the first network element comprises forwarding the load control instruction to a multi-access edge platform manager or a multi-access edge platform of the edge computing system by the multi-access edge orchestrator; monitoring the to-be-measured key indicator according to the load control instruction, obtaining a measurement result of the to-be-measured key indicator, and reporting the measurement result to the multi-access edge orchestrator by the multi-access edge platform manager or the multi-access edge platform; and sending the measurement result of the to-be-measured key indicator to the first network element by the multi-access edge orchestrator.

[0018] In an embodiment of the present disclosure, the load control instruction comprises the to-be-measured key indicator, a threshold corresponding to the to-be-measured key indicator, and a reporting mode of the to-be-measured key indicator.

[0019] In an embodiment of the present disclosure, the to-be-measured key indicator comprises at least one of a CPU usage, a memory usage, a network bandwidth occupancy, and a current number of concurrent tasks.

[0020] In an embodiment of the present disclosure, the reporting mode of the to-be-measured key indicator comprises event-triggered reporting and / or periodic reporting.

[0021] In an embodiment of the present disclosure, the method further comprises receiving and executing a load control policy sent by the first network element, the load control policy comprising at least one of a quality of service (QoS) control policy for matching an optimal or corresponding QoS for an application configured on the edge computing device, and a load balancing policy for performing load balancing on a plurality of edge computing devices based on measurement results of to-be-measured key indicators measured by the plurality of edge computing devices.

[0022] According to another aspect of the present disclosure, there is also provided an edge computing load control apparatus applied to a first network element, the apparatus comprising: a subscription sending module configured to send a subscription request to a second network element, wherein the subscription request is used to subscribe to registration information of an edge computing device, and the registration information of the edge computing device is sent when the edge computing device registers with the second network element after being online; an instruction sending module configured to send a load control instruction to the edge computing device in response to receiving the registration information of the edge computing device, wherein the load control instruction is used to instruct the edge computing device to measure a to-be-measured key indicator; and a result receiving module configured to receive a measurement result of the to-be-measured key indicator measured by the edge computing device, and to perform load control on the edge computing device according to the measurement result of the to-be-measured key indicator.

[0023] According to another aspect of the present disclosure, there is also provided an edge computing load control apparatus applied to a second network element, the apparatus comprising: a subscription receiving module configured to receive a subscription request from a first network element, wherein the subscription request is used to subscribe to registration information of an edge computing device; an information receiving module configured to receive the registration information of the edge computing device; and an information sending module configured to send the registration information of the edge computing device to the first network element.

[0024] According to another aspect of the present disclosure, there is also provided an edge computing load control apparatus applied to an edge computing device, the apparatus comprising: a registration sending module configured to send registration information of the edge computing device to a second network element to register after the edge computing device is online; an instruction receiving module configured to receive a load control instruction sent by a first network element; and a measurement performing module configured to measure a to-be-measured key indicator according to the load control instruction, to obtain a measurement result of the to-be-measured key indicator, and to send the measurement result of the to-be-measured key indicator to the first network element.

[0025] According to another aspect of the present disclosure, an edge computing system is provided, including an edge computing device, a first network element, and a second network element, wherein: the first network element is configured to send a subscription request to the second network element, wherein the subscription request is used to subscribe to the registration information of the edge computing device; in response to receiving the registration information of the edge computing device, send a load control instruction to the edge computing device, the load control instruction is used to instruct the edge computing device to measure the key indicator to be measured; receive the measurement result of the key indicator to be measured obtained by the edge computing device, so as to perform load control on the edge computing device according to the measurement result of the key indicator to be measured; the second network element is configured to receive the subscription request of the first network element; receive the registration information of the edge computing device; send the registration information of the edge computing device to the first network element; the edge computing device is configured to send the registration information of the edge computing device to the second network element for registration after going online; receive the load control instruction sent by the first network element; measure the key indicator to be measured according to the load control instruction, obtain the measurement result of the key indicator to be measured, and send the measurement result of the key indicator to be measured to the first network element.

[0026] According to another aspect of the present disclosure, an electronic device is provided, comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute the above-mentioned edge computing load control method by executing the executable instructions.

[0027] According to another aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the above-mentioned edge computing load control method is implemented.

[0028] According to another aspect of the present disclosure, a computer program product is provided, including a computer program or computer instructions, which are loaded and executed by a processor to enable a computer to implement any of the above-mentioned edge computing load control methods.

[0029] In an implementation of the present disclosure, the first network element sends a subscription request to the second network element, the subscription request being used to subscribe to registration information of the edge computing device, the registration information of the edge computing device being sent when the edge computing device registers with the second network element after going online; in response to receiving the registration information of the edge computing device, a load control instruction is sent to the edge computing device, the load control instruction being used to instruct the edge computing device to measure a to-be-measured key indicator; a measurement result of the to-be-measured key indicator measured by the edge computing device is received, so as to control the load of the edge computing device according to the measurement result of the to-be-measured key indicator. By subscribing to the online notification of the edge computing device, the present disclosure can instruct the edge computing device to measure a key indicator, so that the first network element can accurately grasp the load condition of the edge computing device, and then control the load of the edge computing device according to the measurement result of the key indicator, timely adjust the control strategies such as QoS and load balancing, and ensure user experience.

[0030] It should be understood that the foregoing general description and the following detailed description are only exemplary and explanatory, and are not limiting to the present disclosure. BRIEF DESCRIPTION OF DRAWINGS

[0031] The accompanying drawings, which are incorporated into and form a part of the specification, illustrate an embodiment consistent with the present disclosure and, together with the description, serve to explain the principles of the disclosure. Obviously, the drawings in the following description are only some embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0032] Figure 1 A schematic diagram showing a system architecture provided by an embodiment of the present disclosure.

[0033] Figure 2 A flowchart showing an edge computing load control method performed by a first network element provided by an embodiment of the present disclosure.

[0034] Figure 3 A flowchart showing another edge computing load control method performed by a first network element provided by an embodiment of the present disclosure.

[0035] Figure 4 A flowchart showing an edge computing load control method performed by a second network element provided by an embodiment of the present disclosure.

[0036] Figure 5 A flowchart showing an edge computing load control method performed by an edge computing device provided by an embodiment of the present disclosure.

[0037] Figure 6 A flowchart showing another edge computing load control method performed by an edge computing device provided by an embodiment of the present disclosure.

[0038] Figure 7 A flowchart of an edge computing load control method performed by another edge computing device provided by an embodiment of the present disclosure is shown.

[0039] Figure 8 A flowchart illustrating an example of an edge computing load control method provided by an embodiment of the present disclosure is shown.

[0040] Figure 9 A schematic structural diagram of an edge computing load control device provided by an embodiment of the present disclosure is shown.

[0041] Figure 10 A structural schematic diagram of another edge computing load control device provided by an embodiment of the present disclosure is shown.

[0042] Figure 11 A structural schematic diagram of another edge computing load control device provided by an embodiment of the present disclosure is shown.

[0043] Figure 12 A schematic structural diagram of an edge computing system provided by an embodiment of the present disclosure is shown.

[0044] Figure 13 A structural block diagram of an electronic device provided by an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0045] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be embodied in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete and will fully convey the concepts of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0046] In addition, the accompanying drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. Identical reference numerals in the figures denote identical or similar parts, and thus repetitive descriptions thereof will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities that do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0047] The specific implementation of the embodiment of the present disclosure is described in detail below with reference to the accompanying drawings.

[0048] Figure 1 A schematic diagram shows an exemplary system architecture that can be applied to the edge computing load control method of the embodiment of the present disclosure.

[0049] like Figure 1 As shown, the system architecture includes an edge computing device 101 and a core network 102.

[0050] The core network 102 includes various network entities of the access network or core network, including but not limited to the Access and Mobility Management Function (AMF) network element, the Network Exposure Function (NEF) network element, and the Policy Control Function (PCF) network element. In addition, it may also include the Session Management Function (SMF) network element, the Unified Data Management (UDM) network element, the User Plane Function (UPF) network element, etc. It should be noted that the specific type of the core network 102 is not limited in the embodiments of the present disclosure.

[0051] like Figure 1 As shown, the AMF network element supports edge computing devices 101 with different mobility management requirements. The PCF network element interacts with the AMF network element for access and mobility policy implementation via service-based interfaces (SBIs). The NEF network element is responsible for exposing 5G network capabilities to external edge computing devices 101. Edge computing devices 101 can register by sending registration information to the NEF network element through the AMF network element. The SMF network element is used to establish sessions and configure traffic control for the UPF network element, routing traffic to the correct destination. As a 5G network user plane network element, the UPF network element primarily supports service data routing and forwarding, data and service identification, and action and policy execution. The UPF network element interacts with the SMF network element via the N4 interface and is controlled and managed by the SMF network element. It executes service flow processing based on various policies issued by the SMF network element. In other words, after receiving the session policy control creation response from the PCF network element, the SMF network element controls the UPF network element to execute service flow processing.

[0052] like Figure 1 As shown, Nnssf, Nnef, Nnrf, Npcf, Nudm, Naf, Nausf, Namf, and Nsmf are the communication interfaces or service interfaces of the corresponding network elements respectively. Each network element provides services to the outside world through the corresponding service interface and allows other authorized network elements to access or call the network element corresponding to the service interface.

[0053] In the embodiment of the present disclosure, the edge computing device 101 serves as the device layer of the edge computing system. The edge computing device 101 may be a computing device physically located in the edge network, such as a smart camera, a sensor, a smart phone, a drone, etc.

[0054] In one embodiment, the edge computing system may further include a multi-access edge computing (MEC) host, a MEC application, multi-access edge host-level management, and multi-access edge system-level management.

[0055] Among them, the MEC host is composed of virtualized infrastructure and multi-access edge platform MEC platform (Multi-access Edge Platform, MEP). The virtualized infrastructure data plane is responsible for executing the traffic rules received by the mobile edge platform and realizing traffic forwarding. MEP provides a series of functions to enable MEC applications to run on specific virtual infrastructure and provide mobile edge services.

[0056] MEC applications are virtual machines running on the MEC host virtualization infrastructure and support interaction with MEPs to build and provide MEC services.

[0057] Multi-access edge host-level management includes the Multi-access Edge Platform Manager (MEPM) and the Virtualization Infrastructure Manager (VIM), which manage the MEC host and the MEC applications running on it. Among them, VIM mainly provides virtualization resource management functions, and MEPM is used to implement application lifecycle management, MEP network element management, application rules and demand management, etc.

[0058] Multi-access edge system-level management includes the Multi-access Edge Orchestrator (MEO), which is responsible for maintaining the overall view of the edge computing system, activating application packages, selecting appropriate MEC hosts based on constraints to implement application instantiation, etc.

[0059] In related technologies, mobile networks and edge computing currently belong to different standards organizations. In untrusted environments, communication between the mobile network and edge computing requires a lengthy request-response process through NEF network elements. Even in trusted environments, edge computing cannot be integrated into the mobile network like network elements within the mobile network. However, edge computing is an integral part of the mobile network and is essential for ensuring high bandwidth and low latency.

[0060] With the development of communication technology, the relationship between edge computing and mobile networks will become closer. In mobile networks, for internal services, a predetermined Quality of Service (QoS) can be configured. At the same time, the network's own load status can be obtained in real time, and the QoS of the predetermined services can be adaptively adjusted based on the current mobile network load.

[0061] Currently, edge computing primarily offloads traffic locally. However, the QoS used by edge computing devices is determined by the edge computing devices themselves, acting as application functions (AFs). Mobile networks lack real-time visibility into the load on edge computing devices, resulting in low edge computing utilization and the inability to effectively integrate edge computing with mobile networks.

[0062] In order to solve at least some of the above technical problems, the present disclosure provides an edge computing load control method, wherein a first network element sends a subscription request to a second network element, the subscription request is used to subscribe to the registration information of the edge computing device, and the registration information of the edge computing device is sent when the edge computing device registers with the second network element after going online; in response to receiving the registration information of the edge computing device, a load control instruction is sent to the edge computing device, and the load control instruction is used to instruct the edge computing device to measure the key indicators to be measured; and the measurement results of the key indicators to be measured obtained by the edge computing device are received, so as to load control the edge computing device according to the measurement results of the key indicators to be measured. The present disclosure can instruct the edge computing device to measure the key indicators by subscribing to the online notification of the edge computing device, so that the first network element can accurately grasp the load situation of the edge computing device, and then load control the edge computing device according to the key indicator measurement results, and timely adjust QoS, load balancing and other control strategies to ensure user experience.

[0063] This exemplary implementation is described in detail below with reference to the accompanying drawings and examples.

[0064] First, the embodiments of the present disclosure provide an edge computing load control method executed by a terminal device. This method can be executed by any electronic device with computing processing capabilities. For example, the method can be executed by an edge computing device, a first network element, a second network element, or implemented through interaction between the edge computing device, the first network element, and the second network element.

[0065] Figure 2 FIG. 1 shows a flow chart of an edge computing load control method performed by a first network element according to an embodiment of the present disclosure. Figure 2 As shown, the edge computing load control method provided in the embodiment of the present disclosure is applied to the first network element, and the method mainly includes the following steps:

[0066] S202, sending a subscription request to the second network element, wherein the subscription request is used to subscribe to the registration information of the edge computing device, and the registration information of the edge computing device is sent when the edge computing device is registered to the second network element after being online.

[0067] In one embodiment, the first network element can be a PCF network element, and the second network element can be an NEF network element.

[0068] The subscription request is used to subscribe to the online notification of the edge computing device to the NEF network element. After the edge computing device is online, the edge computing device sends a registration request to the NEF network element, and the registration request can carry the registration information of the edge computing device, which includes a serial number (SN), a device name, etc. The SN is a unique identity code of the edge computing device, and the device name can be defined according to the device type. The device name can be represented by characters, letters, numbers, symbols, etc. For example, camera 1, camera 2, etc.

[0069] After the NEF network element receives the registration information of the edge computing device, the registration information is stored in a unified data repository (UDR), and the NEF network element sends the registration information of the edge computing device to the PCF network element. The UDR is a public database that can store various standardized data structures, such as the registration information of the edge computing device of the present disclosure.

[0070] In one embodiment, the PCF network element can initiate a subscription to the UDR by calling the Nudr_DataRepository_Subscribe service operation of the UDR of the NEF network element, to subscribe to the UDR update of the NEF network element, so as to timely obtain the registration information of the newly online edge computing device.

[0071] S204, in response to receiving the registration information of the edge computing device, sending a load control instruction to the edge computing device, the load control instruction being used to instruct the edge computing device to measure the to-be-measured key indicator.

[0072] After the PCF network element receives the registration information of the edge computing device, the load control instruction is triggered and sent to the edge computing device. The edge computing device can measure the to-be-measured key indicator according to the load control instruction, so that the PCF network element can timely obtain the load condition of the edge computing device.

[0073] In one embodiment, the load control instruction includes: the to-be-measured key indicator; a threshold corresponding to the to-be-measured key indicator; and a reporting mode of the to-be-measured key indicator.

[0074] Key metrics to be measured are used to measure the indicators that significantly impact the load of edge computing devices during operation. These metrics may include at least one of the following: central processing unit (CPU) utilization, memory utilization, network bandwidth utilization, and the number of concurrent tasks. Other key metrics to be measured may include graphics processing unit (GPU) utilization, GPU memory utilization, and hard disk utilization.

[0075] It should be noted that the above key indicators to be measured can also be equivalent measurement methods. For example, memory usage can also be memory used capacity or memory remaining capacity, and network bandwidth occupancy can also be network bandwidth used or network bandwidth remaining.

[0076] The thresholds for the key metrics above represent the upper or lower limits at which the thresholds are triggered. For example, a threshold of 95% for CPU usage indicates that when the CPU usage of an edge computing device reaches 95%, an event trigger is triggered.

[0077] The reporting methods of key indicators to be measured include event-triggered reporting or periodic reporting.

[0078] Among them, event-triggered reporting is initiated when the measurement result of the key indicator to be measured meets the corresponding threshold.

[0079] Periodic reporting means that the edge computing device sends measurement reports regularly according to the time interval configured in the load control instruction.

[0080] It should be noted that the thresholds corresponding to the above-mentioned key indicators to be measured and the time intervals for periodic reporting configurations can be determined according to actual conditions, and this disclosure does not make specific limitations on this.

[0081] S206: Receive measurement results of the key indicators to be measured obtained by the edge computing device, and perform load control on the edge computing device according to the measurement results of the key indicators to be measured.

[0082] After the PCF network element sends the load control command to the edge computing device, the edge computing device measures the key indicators to be measured according to the load control command, obtains the measurement results of the key indicators to be measured, and reports the measurement results of the key indicators to be measured to the PCF network element. The measurement results of the key indicators to be measured can include the values ​​of each key indicator to be measured at different times and the change trend curve.

[0083] In one embodiment, the load control strategy for performing load control on the edge computing device according to the measurement result of the key indicator to be measured in S206 includes at least one of the following:

[0084] Quality of Service (QoS) control policy: The QoS control policy is used to match the best or corresponding QoS for applications configured on edge computing devices.

[0085] Load balancing strategy,The load balancing strategy is used to perform load balancing on multiple edge computing devices based on the measurement results of the key indicators to be measured obtained by multiple edge computing devices.

[0086] QoS control policies can allocate different bandwidths, delays, and priorities to applications on edge computing devices through pre-configured QoS rules, thereby ensuring that key applications on edge computing devices can still provide good service quality when the network is congested.

[0087] In one embodiment, the PCF network element can manage and control the computing tasks of multiple edge computing devices at the same time. When the PCF network element receives the measurement results of the key indicators to be measured obtained by multiple edge computing devices, it can perform load balancing according to the load conditions of the multiple edge computing devices. The load balancing method is not specifically limited in this disclosure.

[0088] In an embodiment of the present disclosure, a first network element sends a subscription request to a second network element, where the subscription request is used to subscribe to the registration information of an edge computing device, where the registration information of the edge computing device is sent when the edge computing device registers with the second network element after going online; in response to receiving the registration information of the edge computing device, a load control instruction is sent to the edge computing device, where the load control instruction is used to instruct the edge computing device to measure the key indicators to be measured; and the measurement results of the key indicators to be measured obtained by the edge computing device are received, so as to load control the edge computing device according to the measurement results of the key indicators to be measured. The present disclosure can instruct the edge computing device to measure the key indicators by subscribing to the online notification of the edge computing device, so that the first network element can accurately grasp the load situation of the edge computing device, and then load control the edge computing device according to the key indicator measurement results, and timely adjust the control strategies such as QoS and load balancing to ensure user experience.

[0089] Figure 3 A flow chart of another edge computing load control method performed by a first network element according to an embodiment of the present disclosure is shown. Figure 2 On the basis of the embodiment, after S204, S205 is added to limit the registration information of the edge computing system stored by the first network element. Figure 3 As shown, in one embodiment, the edge computing load control method disclosed herein includes S202 to S206, wherein:

[0090] S205: After receiving the registration information of the edge computing device, store the registration information, Internet Protocol Address (IP address), port, and active status of the edge computing device.

[0091] It should be noted that the specific implementation of S202, S204, and S206 in this embodiment is the same as the specific implementation of S202, S204, and S206 in the aforementioned embodiment, and will not be repeated here.

[0092] In one embodiment, after receiving the registration information of the edge computing device, the PCF network element stores the above registration information and the IP address, port and active status of the edge computing device. For example, multiple edge computing devices and corresponding status information can be recorded in a list format, so as to formulate strategies based on multiple edge computing devices.

[0093] In the embodiment of the present disclosure, by storing the registration information and corresponding online status of the edge computing device, computing tasks can be dynamically allocated to the appropriate edge computing device based on the registration information, shortening the data transmission path and reducing latency. By monitoring the online status of the edge computing device, the task distribution strategy can be adjusted to avoid overloading of a single edge computing node and improve overall resource utilization.

[0094] Figure 4 FIG. 1 shows a flow chart of an edge computing load control method performed by a second network element according to an embodiment of the present disclosure. Figure 4 As shown, in one embodiment, an edge computing load control method according to an embodiment of the present disclosure is applied to a second network element, and the method includes the following:

[0095] S402: Receive a subscription request from a first network element, where the subscription request is used to subscribe to registration information of an edge computing device;

[0096] S404: Receive registration information of the edge computing device;

[0097] S406: Send the registration information of the edge computing device to the first network element.

[0098] In one embodiment, the method further includes: storing registration information of the edge computing device in a unified data repository.

[0099] In one embodiment, the NEF network element receives a subscription request from the PFC network element to subscribe to online notifications of edge computing devices. After the edge computing device comes online, it registers with the NEF network element. The NEF network element stores the edge computing device's registration information in a unified data repository and pushes it to the PCF network element. After receiving the edge computing device's registration information, the PCF network element can issue a load balancing instruction to the online edge computing device. After receiving the load balancing instruction, the edge computing device starts measuring the key indicators to be measured and reports the measurement results according to the load balancing instruction.

[0100] In an embodiment of the present disclosure, the second network element receives a subscription request from the first network element. When the edge computing device goes online and initiates registration with the second network element, the second network element sends the registration information of the edge computing device to the first network element, so that the mobile network can know the load information of the edge computing device in a timely manner, and then match the optimal QoS for the application of the edge computing device and achieve load balancing based on the load conditions of different edge computing devices, thereby realizing on-demand unloading of traffic and optimizing resource utilization.

[0101] Figure 5 The following is a flow chart of an edge computing load control method performed by an edge computing device according to an embodiment of the present disclosure. Figure 5 As shown, in one embodiment, an edge computing load control method according to an embodiment of the present disclosure is applied to an edge computing device, and the method includes:

[0102] S502: After the edge computing device goes online, the registration information of the edge computing device is sent to the second network element for registration.

[0103] The registration information of the edge computing device includes but is not limited to the serial number (SN), device name, etc., where SN is the unique identification code of the edge computing device. The device name can be defined according to the device type. The device name can be represented by text, letters, numbers, symbols, etc., for example, Camera 1, Camera 2, etc.

[0104] S504: Receive a load control instruction sent by the first network element, where the load control instruction is used to instruct the edge computing device to measure the key indicator to be measured.

[0105] It should be noted that the load control instruction includes: the key indicator to be measured; the threshold value corresponding to the key indicator to be measured; and the reporting method of the key indicator to be measured.

[0106] The to-be-measured key indicators are used to measure indicators that have a high degree of influence on the load of the edge computing device during operation. The to-be-measured key indicators can include at least one of a central processing unit (CPU) usage rate, a memory usage rate, a network bandwidth occupancy rate, and a current number of concurrent tasks.

[0107] In addition, the to-be-measured key indicators can also include a graphics processing unit (GPU) usage rate, a GPU video memory usage rate, and a hard disk usage rate.

[0108] It should be noted that the to-be-measured key indicators can also be equivalent measurement methods. For example, the memory usage rate can also be a used memory capacity or a remaining memory capacity, and the network bandwidth occupancy rate can also be a used network bandwidth or a remaining network bandwidth.

[0109] The threshold value corresponding to the to-be-measured key indicators is used to represent an upper limit value or a lower limit value when the threshold value is triggered.

[0110] The reporting method of the to-be-measured key indicators includes event-triggered reporting or periodic reporting. The event-triggered reporting is started when the measurement result of the to-be-measured key indicators meets the corresponding threshold value. The periodic reporting refers to that the edge computing device sends a measurement report at regular intervals according to the time interval configured in the load control instruction.

[0111] It should be noted that the threshold value corresponding to the to-be-measured key indicators and the time interval configured for periodic reporting can be determined according to actual conditions, and the present disclosure does not make specific limitations thereto.

[0112] S506, measuring the to-be-measured key indicators according to the load control instruction to obtain a measurement result of the to-be-measured key indicators, and sending the measurement result of the to-be-measured key indicators to the first network element.

[0113] The edge computing device measures the to-be-measured key indicators according to the indication of the load control instruction, obtains a measurement result of the to-be-measured key indicators, and reports the measurement result of the to-be-measured key indicators to the PCF network element. The measurement result of the to-be-measured key indicators can include the values of the to-be-measured key indicators at different times, a change trend curve, and the like.

[0114] In an embodiment of the present disclosure, after the edge computing device goes online, the edge computing device sends the registration information of the edge computing device to the second network element for registration. The second network element sends the registration information to the first network element and triggers a load control instruction. After receiving the load control instruction, the edge computing device measures the key indicators to be measured according to the load control instruction, obtains the corresponding measurement results, and sends them to the first network element, thereby realizing the effective integration of edge computing and mobile networks, and timely synchronizing the load status of edge computing to the mobile network, thereby matching the timely execution of optimal QoS, load balancing and other strategies to improve user experience.

[0115] Figure 6 A flow chart of an edge computing load control method performed by another edge computing device provided by an embodiment of the present disclosure is shown. Figure 5 Based on the embodiment, S506 is refined into S5062 to define the way of monitoring the load condition through MEP. Figure 6 As shown, in one embodiment, the above S506 measures the key indicator to be measured according to the load control instruction, obtains the measurement result of the key indicator to be measured, and sends the measurement result of the key indicator to be measured to the first network element, including:

[0116] S5062. Monitor and send measurement results of key indicators to be measured through the multi-access edge platform MEP of the edge computing system.

[0117] In one embodiment, the MEP obtains key indicators such as CPU usage, memory occupancy, storage capacity, etc. of the edge computing device in real time through the underlying interface.

[0118] In the disclosed embodiment, the MEP monitors the test results of the key indicators to be tested and feeds the data back to the first network element, so that the first network element dynamically adjusts the QoS policy according to the test results of the key indicators to be tested, giving priority to ensuring the resource requirements of high-priority services; through the collaboration between the MEP and the first network element, joint load balancing of multiple edge computing devices can be achieved to avoid local congestion.

[0119] Figure 7 A flow chart of an edge computing load control method performed by an edge computing device according to an embodiment of the present disclosure is shown. Figure 5 Based on the embodiment, S504 is refined into S5042, and S506 is refined into S5064~S5068, so as to limit the situation of receiving and sending load information through MEO. Figure 7 As shown, in one embodiment, the above S504 receives the load control instruction sent by the first network element, including:

[0120] S5042. Receive a load control instruction through the multi-access edge orchestrator MEO or the multi-access edge platform MEP of the edge computing system;

[0121] S506 measures the key indicator to be measured according to the load control instruction, obtains a measurement result of the key indicator to be measured, and sends the measurement result of the key indicator to be measured to the first network element, including:

[0122] S5064. Forward the load control instruction to the multi-access edge platform manager MEPM or the multi-access edge platform MEP of the edge computing system through the multi-access edge orchestrator MEO;

[0123] S5066. The multi-access edge platform manager MEPM or the multi-access edge platform MEP monitors the key indicator to be measured according to the load control instruction, obtains the measurement result of the key indicator to be measured, and reports it to the multi-access edge orchestrator MEO.

[0124] S5068. Send the measurement results of the key indicators to be measured to the first network element through the multi-access edge orchestrator MEO.

[0125] In S5042, MEO can connect to the PCF network element through the Npcf interface and communicate using the HTTP / 2 protocol, which can ensure the security of load control instruction transmission.

[0126] In S5068, the MEO may report the measurement results of the key indicators to be measured to the PCF network element through the MP2 interface, so that the PCF network element issues dynamic adjustment instructions according to the measurement results of the key indicators to be measured.

[0127] In the embodiment of the present disclosure, the load control instruction is received by MEO and forwarded to MEPM or MEP, so that MEPM or MEP measures the key indicators to be measured and obtains corresponding measurement results. MEO reports the measurement results to the first network element, so that the first network element dynamically adjusts the QoS policy according to the test results of the key indicators to be measured, gives priority to the resource requirements of high-priority services, and realizes joint load balancing of multiple edge computing devices to avoid local congestion.

[0128] In one embodiment, the edge computing load control method of the embodiment of the present disclosure also includes: receiving and executing the load control policy sent by the first network element, the load control policy includes at least one of the following: quality of service QoS control policy, the QoS control policy is used to match the best or corresponding QoS for the application configured on the edge computing device; load balancing policy, the load balancing policy is used to perform load balancing on multiple edge computing devices based on the measurement results of the key indicators to be measured obtained by multiple edge computing devices.

[0129] QoS control policies can allocate different bandwidths, delays, and priorities to applications on edge computing devices through pre-configured QoS rules, thereby ensuring that key applications on edge computing devices can still provide good service quality when the network is congested.

[0130] In one embodiment, the PCF network element can manage and control the computing tasks of multiple edge computing devices at the same time. When the PCF network element receives the measurement results of the key indicators to be measured obtained by multiple edge computing devices, it can perform load balancing according to the load conditions of the multiple edge computing devices. The load balancing method is not specifically limited in this disclosure.

[0131] In the embodiment of the present disclosure, the edge computing device receives and executes the load control policy sent by the first network element, so that the edge computing device dynamically adjusts the QoS policy formulated by the first network element, prioritizes the resource requirements of high-priority services, and can achieve joint load balancing of multiple edge computing devices to avoid local congestion.

[0132] It can be understood that the edge computing device for executing the above method can also be a chip or chip system set in the edge computing device; the first network element for executing the above method can also be a chip or chip system set in the first network element; the second network element for executing the above method can also be a chip or chip system set in the second network element. This application does not make specific limitations on this.

[0133] For the edge computing device, the first network element, and the second network element in the above method, the edge computing device may be an MEC device, the first network element may be a PCF network element, and the second network element may be an NEF network element.

[0134] In order to deepen the understanding of the embodiments of the present disclosure, Figure 8 For detailed explanation, take the edge computing device as MEC device, the first network element as PCF network element, and the second network element as NEF network element as an example.

[0135] like Figure 8 As shown, the edge computing load control method provided by the present disclosure includes the following steps:

[0136] S801. The PCF network element subscribes to the UDR update of the NEF network element to subscribe to the registration information of the edge computing device;

[0137] S802. After the MEC device goes online, it registers with the NEF network element and sends the registration information of the MEC device to the NEF network element.

[0138] S803. The NEF network element sends the online information of the MEC device to the PCF network element to complete the registration.

[0139] S804: After receiving the registration information of the MEC device, the PCF network element triggers a load control instruction, which is used to instruct the MEC device to measure the key indicators to be measured;

[0140] S805. The PCF network element sends a load control instruction to the MEC device.

[0141] S806. The MEC device monitors the key indicator to be measured according to the load control instruction and obtains the measurement result of the key indicator to be measured;

[0142] S807. The MEC device reports the measurement results of the key indicators to be measured according to the load control instruction.

[0143] In some embodiments, the PCF network element may also generate a load control strategy based on the measurement results of the key indicators to be measured, and send the load control strategy to the MEC device, and the MEC device executes the load control strategy.

[0144] Through the above-mentioned method, the present disclosure can enable the mobile network to obtain the load status of the edge computing device in real time, and execute the corresponding load control strategy according to the load status, so as to improve the effectiveness and reliability of the system and make the integration of the mobile network and the edge computing device higher.

[0145] The present disclosure is applicable to application scenarios of mobile communications and edge computing. No hardware changes are required, only software function enhancements are required. Edge computing devices are equipped with registration process, load monitoring, and load status reporting functions. A load control module is added on the network side. Through the linkage between the above modules, the mobile network can grasp the load of edge computing devices, so as to prepare for the timely execution of QoS dynamic adjustment, load balancing and other strategies.

[0146] Based on the same inventive concept, the present disclosure also provides an edge computing load control device and system, as described in the following embodiments. Since the principles of the device and system embodiments are similar to those of the above-mentioned method embodiments, the implementation of this embodiment can refer to the implementation of the above-mentioned method embodiments, and the repeated parts will not be repeated.

[0147] Figure 9 A schematic diagram of an edge computing load control device provided by an embodiment of the present disclosure is shown. Figure 9 As shown, an edge computing load control device of this embodiment is applied to a first network element. The device includes a subscription sending module 910, an instruction sending module 920, and a result receiving module 930, wherein:

[0148] A subscription sending module 910 is configured to send a subscription request to the second network element, wherein the subscription request is used to subscribe to the registration information of the edge computing device, and the registration information of the edge computing device is sent when the edge computing device registers with the second network element after going online;

[0149] An instruction sending module 920 is configured to send a load control instruction to the edge computing device in response to receiving registration information of the edge computing device, where the load control instruction is used to instruct the edge computing device to measure the key indicator to be measured;

[0150] The result receiving module 930 is used to receive the measurement results of the key indicators to be measured obtained by the edge computing device, so as to perform load control on the edge computing device according to the measurement results of the key indicators to be measured.

[0151] It should be noted that the load control instruction includes: the key indicator to be measured; the threshold value corresponding to the key indicator to be measured; and the reporting method of the key indicator to be measured.

[0152] It should be noted that the key indicators to be measured include at least one of CPU usage, memory usage, network bandwidth occupancy, and the current number of concurrent tasks.

[0153] It should be noted that the reporting methods of the key indicators to be measured include event-triggered reporting and / or periodic reporting.

[0154] In one embodiment, the device also includes a first storage module not shown in the accompanying drawings, and the first storage module is used to store the registration information, IP address, port and active status of the edge computing device after receiving the registration information of the edge computing device.

[0155] It should be noted that the load control strategy for load control of edge computing devices based on the measurement results of the key indicators to be measured includes at least one of the following: quality of service QoS control strategy, the QoS control strategy is used to match the best or corresponding QoS for the application configured on the edge computing device; load balancing strategy, the load balancing strategy is used to perform load balancing on multiple edge computing devices based on the measurement results of the key indicators to be measured obtained by multiple edge computing devices.

[0156] In an embodiment of the present disclosure, a first network element sends a subscription request to a second network element, where the subscription request is used to subscribe to the registration information of an edge computing device, where the registration information of the edge computing device is sent when the edge computing device registers with the second network element after going online; in response to receiving the registration information of the edge computing device, a load control instruction is sent to the edge computing device, where the load control instruction is used to instruct the edge computing device to measure the key indicators to be measured; and the measurement results of the key indicators to be measured obtained by the edge computing device are received, so as to load control the edge computing device according to the measurement results of the key indicators to be measured. The present disclosure can instruct the edge computing device to measure the key indicators by subscribing to the online notification of the edge computing device, so that the first network element can accurately grasp the load situation of the edge computing device, and then load control the edge computing device according to the key indicator measurement results, and timely adjust the control strategies such as QoS and load balancing to ensure user experience.

[0157] Figure 10 A schematic diagram of another edge computing load control device provided by an embodiment of the present disclosure is shown. Figure 10 As shown, an edge computing load control device according to an embodiment of the present disclosure is applied to a second network element, and the device includes:

[0158] A subscription receiving module 1010 is configured to receive a subscription request from a first network element, where the subscription request is used to subscribe to registration information of an edge computing device;

[0159] An information receiving module 1020 is configured to receive registration information of an edge computing device;

[0160] The information sending module 1030 is used to send the registration information of the edge computing device to the first network element.

[0161] In one embodiment, the apparatus further includes a second storage module not shown in the accompanying drawings, and the second storage module is used to store registration information of the edge computing device in a unified data repository.

[0162] In an embodiment of the present disclosure, the second network element receives a subscription request from the first network element. When the edge computing device goes online and initiates registration with the second network element, the second network element sends the registration information of the edge computing device to the first network element, so that the mobile network can know the load information of the edge computing device in a timely manner, and then match the optimal QoS for the application of the edge computing device and achieve load balancing based on the load conditions of different edge computing devices, thereby realizing on-demand unloading of traffic and optimizing resource utilization.

[0163] Figure 11 A schematic diagram of another edge computing load control device provided by an embodiment of the present disclosure is shown. Figure 11As shown, an edge computing load control device according to an embodiment of the present disclosure is applied to an edge computing device, and the device includes:

[0164] The registration sending module 1110 is used to send the registration information of the edge computing device to the second network element for registration after the edge computing device goes online;

[0165] The instruction receiving module 1120 is configured to receive a load control instruction sent by the first network element;

[0166] The measurement execution module 1130 is configured to measure the key indicator to be measured according to the load control instruction, obtain a measurement result of the key indicator to be measured, and send the measurement result of the key indicator to be measured to the first network element.

[0167] In one embodiment, the measurement execution module 1130 is configured to monitor and send measurement results of key indicators to be measured through a multi-access edge platform of an edge computing system.

[0168] In one embodiment, the instruction receiving module 1120 is configured to receive a load control instruction through a multi-access edge orchestrator or a multi-access edge platform of an edge computing system;

[0169] The measurement execution module 1130 is configured to forward the load control instruction to the multi-access edge platform manager or the multi-access edge platform of the edge computing system through the multi-access edge orchestrator; monitor the key indicators to be measured according to the load control instruction through the multi-access edge platform manager or the multi-access edge platform, obtain measurement results of the key indicators to be measured, and report them to the multi-access edge orchestrator; and send the measurement results of the key indicators to be measured to the first network element through the multi-access edge orchestrator.

[0170] It should be noted that the load control instruction includes: the key indicator to be measured; the threshold value corresponding to the key indicator to be measured; and the reporting method of the key indicator to be measured.

[0171] It should be noted that the key indicators to be measured include at least one of CPU usage, memory usage, network bandwidth occupancy, and the current number of concurrent tasks.

[0172] It should be noted that the reporting methods of the key indicators to be measured include event-triggered reporting and / or periodic reporting.

[0173] In one embodiment, the device also includes a load control execution module not shown in the accompanying drawings, and the load control execution module is used to receive and execute the load control policy sent by the first network element. The load control policy includes at least one of the following: quality of service QoS control policy, the QoS control policy is used to match the best or corresponding QoS for the application configured on the edge computing device; the load balancing policy, the load balancing policy is used to perform load balancing on multiple edge computing devices based on the measurement results of the key indicators to be measured obtained by multiple edge computing devices.

[0174] In an embodiment of the present disclosure, after the edge computing device goes online, the edge computing device sends the registration information of the edge computing device to the second network element for registration. The second network element sends the registration information to the first network element and triggers a load control instruction. After receiving the load control instruction, the edge computing device measures the key indicators to be measured according to the load control instruction, obtains the corresponding measurement results, and sends them to the first network element, thereby realizing the effective integration of edge computing and mobile networks, and timely synchronizing the load status of edge computing to the mobile network, thereby matching the timely execution of optimal QoS, load balancing and other strategies to improve user experience.

[0175] Figure 12 FIG. 1 shows a schematic diagram of the structure of an edge computing system provided by an embodiment of the present disclosure. Figure 12 As shown, in one embodiment, an edge computing system provided by an embodiment of the present disclosure includes a first network element 1210, a second network element 1220 and an edge computing device 101, wherein: the first network element 1210 is used to send a subscription request to the second network element 1220, wherein the subscription request is used to subscribe to the registration information of the edge computing device 101; in response to receiving the registration information of the edge computing device 101, a load control instruction is sent to the edge computing device 101, and the load control instruction is used to instruct the edge computing device 101 to measure the key indicator to be measured; the measurement result of the key indicator to be measured obtained by the edge computing device 101 is received, and the load control instruction is used to instruct the edge computing device 101 to measure the key indicator to be measured according to the key indicator to be measured. The second network element 1220 is used to receive the subscription request of the first network element 1210; receive the registration information of the edge computing device 101; send the registration information of the edge computing device 101 to the first network element 1210; the edge computing device 101 is used to send the registration information of the edge computing device 101 to the second network element 1220 for registration after going online; receive the load control instruction sent by the first network element 1210; measure the key indicator to be measured according to the load control instruction, obtain the measurement result of the key indicator to be measured, and send the measurement result of the key indicator to be measured to the first network element 1210.

[0176] Those skilled in the art will appreciate that various aspects of the present disclosure may be implemented as systems, methods, or program products. Therefore, various aspects of the present disclosure may be implemented in the following forms: entirely in hardware, entirely in software (including firmware, microcode, etc.), or in a combination of hardware and software, collectively referred to herein as "circuits," "modules," or "systems."

[0177] Refer to the following Figure 13 1300 according to this embodiment of the present disclosure will be described. Figure 13 The electronic device 1300 shown is merely an example and should not limit the functions and scope of use of the embodiments of the present disclosure.

[0178] like Figure 13 As shown, electronic device 1300 is implemented as a general-purpose computing device. Components of electronic device 1300 may include, but are not limited to, the aforementioned at least one processing unit 1310, the aforementioned at least one storage unit 1320, and a bus 1330 connecting various system components (including storage unit 1320 and processing unit 1310).

[0179] Wherein, the storage unit stores a program code, and the program code can be executed by the processing unit 1310, so that the processing unit 1310 executes the steps described in the above "Exemplary Method" section of this specification according to various exemplary embodiments of the present disclosure. For example, the processing unit 1310 can execute the following steps of the above method embodiment: the first network element sends a subscription request to the second network element, wherein the subscription request is used to subscribe to the registration information of the edge computing device, and the registration information of the edge computing device is sent when the edge computing device registers with the second network element after going online; in response to receiving the registration information of the edge computing device, a load control instruction is sent to the edge computing device, and the load control instruction is used to instruct the edge computing device to measure the key indicator to be measured; and the measurement results of the key indicator to be measured obtained by the edge computing device are received, so as to perform load control on the edge computing device according to the measurement results of the key indicator to be measured.

[0180] For example, the processing unit 1310 can independently perform the following steps of the above method embodiment: the second network element receives the subscription request of the first network element, the subscription request is used to subscribe to the registration information of the edge computing device; receives the registration information of the edge computing device; and sends the registration information of the edge computing device to the first network element.

[0181] For example, the processing unit 1310 can implement the following steps of the above method embodiments by itself: after the edge computing device is online, the edge computing device sends registration information of the edge computing device to a second network element for registration; receiving a load control instruction sent by the first network element, the load control instruction being used to instruct the edge computing device to measure a to-be-measured key indicator; measuring the to-be-measured key indicator according to the load control instruction to obtain a measurement result of the to-be-measured key indicator, and sending the measurement result of the to-be-measured key indicator to the first network element.

[0182] The storage unit 1320 can include a readable medium in the form of a volatile storage unit, such as a random access memory (RAM) 13201 and / or a cache 13202, and can further include a read-only memory (ROM) 13203.

[0183] The storage unit 1320 can also include a program / utility 13204 having a set (at least one) of program modules 13205, such as an operating system, one or more application programs, other program modules, and program data, each of which can give implementation to the network environment in one or a combination of the examples.

[0184] The bus 1330 can represent one or more of several types of bus structures, including a storage unit bus or bus controller, a peripheral bus, a graphics acceleration port, a processing unit bus, or a local bus using any of a variety of bus architectures.

[0185] The electronic device 1300 can also communicate with one or more external devices 1340, such as a keyboard or pointing device, a Bluetooth device, etc.; other devices that enable a user to interact with the electronic device 1300; and / or one or more devices that enable the electronic device 1300 to communicate with one or more other computing devices. Such communication can occur via an input / output (I / O) interface 1350. Still yet, the electronic device 1300 can communicate with one or more networks, such as a local area network (LAN), a wide area network (WAN), and / or the Internet, through a network adapter 1360. As Figure 13 illustrated, the network adapter 1360 can communicate with the other components of the electronic device 1300 via the bus 1330. It should be understood that, although not shown explicitly, other hardware and / or software components could be used in conjunction with the electronic device 1300. These include, but are not limited to, microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data archival storage systems, etc.

[0186] Through the description of the above embodiments, it will be readily understood by those skilled in the art that the example embodiments described herein can be implemented via software or via a combination of software and necessary hardware. Therefore, the technical solutions according to the embodiments of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, or mobile hard drive) or on a network and includes several instructions for enabling a computing device (such as a personal computer, server, terminal device, or network device) to execute the methods according to the embodiments of the present disclosure.

[0187] In an exemplary embodiment of the present disclosure, a computer-readable storage medium is further provided, which may be a readable signal medium or a readable storage medium. The computer-readable storage medium stores a program product capable of implementing the above-mentioned method of the present disclosure. In an exemplary embodiment of the present disclosure, a computer program product is further provided, which includes a computer program or computer instructions, which are loaded and executed by a processor to enable a computer to implement any of the above-mentioned edge computing load control methods.

[0188] More specific examples of computer-readable storage media in the present disclosure may include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), optical fibers, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0189] In the present disclosure, a computer-readable storage medium may include a data signal propagated in baseband or as part of a carrier wave, which carries readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium that can transmit, propagate, or transfer a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0190] Alternatively, the program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination thereof.

[0191] It should be noted that although several modules or units of the device for action execution are mentioned in the detailed description above, this division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules or units described above can be concretized in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided into multiple modules or units to be concretized.

[0192] Furthermore, although the steps of the method of the present disclosure are described in a particular order in the accompanying drawings, this does not require or imply that the steps must be performed in this particular order, or that all steps shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps.

[0193] Through the description of the above embodiments, it will be readily understood by those skilled in the art that the example embodiments described herein can be implemented via software or via a combination of software and necessary hardware. Therefore, the technical solutions according to the embodiments of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, or mobile hard drive) or on a network and includes several instructions for enabling a computing device (such as a personal computer, server, mobile terminal, or network device) to execute the methods according to the embodiments of the present disclosure.

[0194] 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 of the present disclosure being indicated by the appended claims.

Claims

1. A method for edge computing load control, characterized in that: Applied to a first network element, where the first network element is a policy control function network element, the method includes: Sending a subscription request to a second network element, wherein the subscription request is used to subscribe to registration information of an edge computing device, the registration information of the edge computing device being sent when the edge computing device registers with the second network element after going online, the second network element being a network capability exposure function network element, and the subscription request being initiated by calling a service operation of a unified data repository of the second network element; In response to receiving the registration information of the edge computing device, sending a load control instruction to the edge computing device, wherein the load control instruction is used to instruct the edge computing device to measure the key indicator to be measured; Receive a measurement result of the key indicator to be measured obtained by the edge computing device, so as to perform load control on the edge computing device according to the measurement result of the key indicator to be measured.

2. The edge computing load control method according to claim 1, characterized in that: The load control instruction includes: The key indicators to be measured; The threshold corresponding to the key indicator to be measured; The reporting method of the key indicators to be measured.

3. The edge computing load control method according to claim 2, characterized in that: The key indicators to be measured include at least one of CPU usage, memory usage, network bandwidth occupancy, and the current number of concurrent tasks.

4. The edge computing load control method according to claim 2, characterized in that: The reporting method of the key indicator to be measured includes event-triggered reporting and / or periodic reporting.

5. The edge computing load control method according to claim 1, characterized in that: The method further comprises: After receiving the registration information of the edge computing device, the registration information, Internet Protocol address (IP address), port, and active status of the edge computing device are stored.

6. The edge computing load control method according to any one of claims 1 to 5, characterized in that: The load control strategy for performing load control on the edge computing device according to the measurement result of the key indicator to be measured includes at least one of the following: A quality of service (QoS) control policy, wherein the QoS control policy is used to match the best or corresponding QoS for the application deployed on the edge computing device; A load balancing strategy is used to perform load balancing on multiple edge computing devices based on measurement results of key indicators to be measured obtained by multiple edge computing devices.

7. A method for edge computing load control, characterized in that: Applied to a second network element, where the second network element is a network capability exposure function network element, the method includes: Receive a subscription request from a first network element, the subscription request being used to subscribe to registration information of an edge computing device, the first network element being a policy control function network element, and the subscription request being initiated by calling a service operation of a unified data repository of the second network element; Receiving registration information of the edge computing device; The registration information of the edge computing device is sent to the first network element so that the first network element receives the registration information of the edge computing device and sends a load control instruction to the edge computing device, wherein the load control instruction is used to instruct the edge computing device to measure the key indicators to be measured; and the measurement results of the key indicators to be measured obtained by the edge computing device are received to perform load control on the edge computing device according to the measurement results of the key indicators to be measured.

8. The edge computing load control method according to claim 7, characterized in that: The method further comprises: The registration information of the edge computing device is stored in a unified data repository.

9. A method for edge computing load control, characterized in that: Applied to an edge computing device, the method includes: After the edge computing device goes online, the registration information of the edge computing device is sent to a second network element for registration, where the second network element is a network capability exposure function network element; Receive a load control instruction sent by a first network element, where the load control instruction is used to instruct the edge computing device to measure a key indicator to be measured, where the first network element is a policy control function network element; The key indicator to be measured is measured according to the load control instruction to obtain a measurement result of the key indicator to be measured, and the measurement result of the key indicator to be measured is sent to the first network element.

10. The edge computing load control method according to claim 9, characterized in that: The measuring the key indicator to be measured according to the load control instruction, obtaining a measurement result of the key indicator to be measured, and sending the measurement result of the key indicator to be measured to the first network element includes: The measurement results of the key indicators to be measured are monitored and sent through the multi-access edge platform of the edge computing system.

11. The edge computing load control method according to claim 9, characterized in that: The receiving a load control instruction sent by the first network element includes: Receiving the load control instruction through a multi-access edge orchestrator or a multi-access edge platform of an edge computing system; The step of measuring the key indicator to be measured according to the load control instruction, obtaining a measurement result of the key indicator to be measured, and sending the measurement result of the key indicator to be measured to the first network element includes: forwarding the load control instruction to the multi-access edge platform manager or the multi-access edge platform of the edge computing system through the multi-access edge orchestrator; Monitoring the key indicator to be measured according to the load control instruction by the multi-access edge platform manager or the multi-access edge platform, obtaining a measurement result of the key indicator to be measured and reporting it to the multi-access edge orchestrator; The measurement result of the key indicator to be measured is sent to the first network element through the multi-access edge orchestrator.

12. The edge computing load control method according to claim 9, characterized in that: The load control instruction includes: The key indicators to be measured; The threshold corresponding to the key indicator to be measured; The reporting method of the key indicators to be measured.

13. The edge computing load control method according to claim 12, characterized in that: The key indicators to be measured include at least one of CPU usage, memory usage, network bandwidth occupancy, and the current number of concurrent tasks.

14. The edge computing load control method according to claim 12, characterized in that: The reporting method of the key indicator to be measured includes event-triggered reporting and / or periodic reporting.

15. The edge computing load control method according to claim 9, characterized in that: The method further comprises: Receive and execute a load control policy sent by the first network element, where the load control policy includes at least one of the following: A quality of service (QoS) control policy, wherein the QoS control policy is used to match an optimal or corresponding QoS for an application configured on the edge computing device; A load balancing strategy is used to perform load balancing on multiple edge computing devices based on measurement results of key indicators to be measured obtained by multiple edge computing devices.

16. An edge computing load control device, characterized in that: Applied to a first network element, where the first network element is a policy control function network element, the device includes: A subscription sending module is configured to send a subscription request to a second network element, wherein the subscription request is used to subscribe to registration information of an edge computing device, the registration information of the edge computing device being sent when the edge computing device registers with the second network element after going online, the second network element being a network capability exposure function network element, and the subscription request being initiated by calling a service operation of a unified data repository of the second network element; an instruction sending module, configured to send a load control instruction to the edge computing device in response to receiving registration information of the edge computing device, wherein the load control instruction is used to instruct the edge computing device to measure a key indicator to be measured; The result receiving module is used to receive the measurement results of the key indicators to be measured obtained by the edge computing device, so as to perform load control on the edge computing device according to the measurement results of the key indicators to be measured.

17. An edge computing load control device, characterized in that: Applied to a second network element, where the second network element is a network capability exposure function network element, the device includes: A subscription receiving module, configured to receive a subscription request from a first network element, the subscription request being used to subscribe to registration information of an edge computing device, the first network element being a policy control function network element, and the subscription request being initiated by calling a service operation of a unified data repository of the second network element; An information receiving module, configured to receive registration information of the edge computing device; An information sending module is used to send the registration information of the edge computing device to the first network element, so that the first network element receives the registration information of the edge computing device and sends a load control instruction to the edge computing device, wherein the load control instruction is used to instruct the edge computing device to measure the key indicators to be measured; receive the measurement results of the key indicators to be measured obtained by the edge computing device, so as to perform load control on the edge computing device according to the measurement results of the key indicators to be measured.

18. An edge computing load control device, characterized in that: Applied to edge computing equipment, the apparatus includes: A registration sending module, configured to send registration information of the edge computing device to a second network element for registration after the edge computing device is online, where the second network element is a network capability exposure function network element; An instruction receiving module, configured to receive a load control instruction sent by a first network element, where the first network element is a policy control function network element; The measurement execution module is used to measure the key indicator to be measured according to the load control instruction, obtain the measurement result of the key indicator to be measured, and send the measurement result of the key indicator to be measured to the first network element.

19. An edge computing system, characterized in that: The system comprises an edge computing device, a first network element and a second network element, wherein: The first network element is configured to send a subscription request to the second network element, wherein the subscription request is used to subscribe to the registration information of the edge computing device, and the subscription request is initiated by calling a service operation of a unified data repository of the second network element; in response to receiving the registration information of the edge computing device, send a load control instruction to the edge computing device, wherein the load control instruction is used to instruct the edge computing device to measure the key indicator to be measured; receive a measurement result of the key indicator to be measured obtained by the edge computing device, so as to perform load control on the edge computing device according to the measurement result of the key indicator to be measured, wherein the first network element is a policy control function network element; The second network element is configured to receive a subscription request from the first network element; receive registration information of the edge computing device; and send the registration information of the edge computing device to the first network element, wherein the second network element is a network capability exposure function network element; The edge computing device is used to send the registration information of the edge computing device to the second network element for registration after going online; receive the load control instruction sent by the first network element; measure the key indicators to be measured according to the load control instruction, obtain the measurement results of the key indicators to be measured, and send the measurement results of the key indicators to be measured to the first network element.

20. An electronic device, characterized in that: It includes a processor and a memory, the memory is used to store executable instructions of the processor; wherein the processor is configured to execute the edge computing load control method described in any one of claims 1-6, or execute the edge computing load control method described in any one of claims 7-8, or execute the edge computing load control method described in any one of claims 9-15 by executing the executable instructions.

21. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, it implements the edge computing load control method described in any one of claims 1-6, or implements the edge computing load control method described in any one of claims 7-8, or implements the edge computing load control method described in any one of claims 9-15.

22. A computer program product, characterized in that It includes a computer program or computer instructions, which are loaded and executed by a processor to enable the computer to implement the edge computing load control method as described in any one of claims 1 to 6, or the edge computing load control method as described in any one of claims 7 to 8, or the edge computing load control method as described in any one of claims 9 to 15.

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