Edge computing load control method and related equipment

Abstract

The invention provides an edge computing load control method and related equipment, and relates to the technical field of edge computing. The method comprises the steps that a first network element sends a subscription request to a second network element, the subscription request is used for subscribing registration information of the edge computing device, and the registration information of the edge computing device is sent when the edge computing device registers to the second network element after being online; in response to the received 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 for indicating the edge computing device to measure the key index to be measured; and receiving a measurement result of the to-be-measured key index measured by the edge computing device, and performing load control on the edge computing device according to the measurement result of the to-be-measured key index. According to the invention, the mobile network can obtain the load condition of the edge computing equipment in real time, so that the load control strategy can be executed in time.

Description

Background Art

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

[0003] In the related art, the quality of service used by an application is applied for by an edge computing device. However, the mobile network cannot know the load condition of the edge computing device in real time, resulting in the quality of service of edge computing not being guaranteed and the effective integration of edge computing and the mobile network not being achieved.

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

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

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

[0007] According to one aspect of the present disclosure, there is provided an edge computing load control method applied to a first network element. The method includes: sending 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, 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, where the load control instruction is used to instruct the edge computing device to measure a key index to be measured; receiving the measurement result of the key index to be measured measured by the edge computing device, so as to perform load control on the edge computing device according to the measurement result of the key index to be measured.

[0008] In an embodiment of the present disclosure, the load control instruction includes: the key index to be measured; a threshold corresponding to the key index to be measured; a reporting method for the key index to be measured.

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

[0010] In an embodiment of the present disclosure, the reporting method for the key index 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 (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 result of the key index to be measured includes at least one of the following: a Quality of Service (QoS) control strategy, where the QoS control strategy is used to match the best or corresponding QoS for the applications deployed on the edge computing device; a load balancing strategy, where the load balancing strategy is used to perform load balancing on multiple edge computing devices based on the measurement results of the key indexes to be measured obtained from the multiple edge computing devices.

[0013] According to another aspect of the present disclosure, there is provided an edge computing load control method 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 the registration information of the 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 storage repository.

[0015] According to another aspect of the present disclosure, there is provided an edge computing load control method applied to an edge computing device. The method includes: after the edge computing device goes online, sending the 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, where the load control instruction is used to instruct the edge computing device to measure a key index to be measured; measuring the key index to be measured according to the load control instruction to obtain a measurement result of the key index to be measured, and sending the measurement result of the key index to be measured to the first network element.

[0016] In one embodiment of the present disclosure, the step of measuring the key index to be measured according to the load control instruction to obtain a measurement result of the key index to be measured, and sending the measurement result of the key index to be measured to the first network element includes: monitoring and sending the measurement result of the key index to be measured through the multi-access edge platform of the edge computing system.

[0017] In one embodiment of the present disclosure, receiving the load control instruction sent by the first network element includes: receiving the load control instruction through the multi-access edge orchestrator or multi-access edge platform of the edge computing system; wherein, according to the load control instruction, measuring the key index to be measured to obtain the measurement result of the key index to be measured, and sending the measurement result of the key index to be measured to the first network element includes: forwarding the load control instruction to the multi-access edge platform manager or multi-access edge platform of the edge computing system through the multi-access edge orchestrator; monitoring the key index to be measured according to the load control instruction by the multi-access edge platform manager or multi-access edge platform to obtain the measurement result of the key index to be measured and reporting it to the multi-access edge orchestrator; sending the measurement result of the key index to be measured to the first network element through the multi-access edge orchestrator.

[0018] In one embodiment of the present disclosure, the load control instruction includes: the key index to be measured; the threshold value corresponding to the key index to be measured; the reporting method of the key index to be measured.

[0019] In one embodiment of the present disclosure, the key index to be measured includes at least one of CPU usage rate, memory usage rate, network bandwidth occupancy rate, and current concurrent task number.

[0020] In one embodiment of the present disclosure, the reporting method of the key index to be measured includes event-triggered reporting and / or periodic reporting.

[0021] In one embodiment of the present disclosure, the method further includes: receiving and executing the 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, and the QoS control policy is used to match the best or corresponding QoS for the application configured on the edge computing device; a load balancing policy, and the load balancing policy is used to perform load balancing on the multiple edge computing devices based on the measurement results of the key indexes to be measured measured by the multiple edge computing devices.

[0022] According to another aspect of the present disclosure, there is also provided an edge computing load control device, which is applied to a first network element. The device includes: a subscription sending module, configured to send 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, 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; 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, where the load control instruction is used to instruct the edge computing device to measure a key index to be measured; and a result receiving module, configured to receive the measurement result of the key index to be measured measured by the edge computing device, so as to perform load control on the edge computing device according to the measurement result of the key index to be measured.

[0023] According to another aspect of the present disclosure, there is also provided an edge computing load control device, which is applied to a second network element. The device includes: a subscription receiving module, configured to receive a subscription request from a first network element, where the subscription request is used to subscribe to the 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 device, which is applied to an edge computing device. The device includes: a registration sending module, configured to send the registration information of the edge computing device to a second network element for registration after the edge computing device goes online; an instruction receiving module, configured to receive a load control instruction sent by a first network element; and a measurement execution module, configured to measure a key index to be measured according to the load control instruction to obtain a measurement result of the key index to be measured, and send the measurement result of the key index to be measured to the first network element.

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

[0026] According to still another aspect of the present disclosure, there is provided an electronic device, including: 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 yet another aspect of the present disclosure, there is provided a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the above-mentioned edge computing load control method is implemented.

[0028] According to yet another aspect of the present disclosure, there is provided a computer program product, including a computer program or computer instructions, and the computer program or the computer instructions are loaded and executed by a processor to enable a computer to implement the edge computing load control method described in any one of the above.

[0029] In an embodiment of the present disclosure, 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 an edge computing device. 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. The load control instruction is used to instruct the edge computing device to measure a key metric to be measured. The measurement result of the key metric to be measured obtained by the edge computing device is received, so as to perform load control on the edge computing device according to the measurement result of the key metric to be measured. By subscribing to the online notification of the edge computing device, the present disclosure can instruct the edge computing device to perform key metric measurement, so that the first network element can accurately grasp the load condition of the edge computing device, and then perform load control on the edge computing device according to the key metric measurement result, and timely adjust control strategies such as QoS and load balancing to ensure the user experience.

[0030] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The accompanying drawings herein are incorporated into the specification and constitute a part of this specification, showing embodiments consistent with the present disclosure, and are used together with the specification to explain the principles of the present disclosure. Obviously, the accompanying drawings in the following description are only some embodiments of the present disclosure, and those of ordinary skill in the art can obtain other drawings according to these drawings without creative efforts.

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

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

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

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

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

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

[0038] Figure 7 The flowchart showing another edge computing load control method executed by an edge computing device provided by an embodiment of the present disclosure.

[0039] Figure 8 The flowchart showing an example of an edge computing load control method provided by an embodiment of the present disclosure.

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

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

[0042] Figure 11 The schematic structural diagram showing yet another edge computing load control device provided by an embodiment of the present disclosure.

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

[0044] Figure 13 The structural block diagram showing an electronic device provided by an embodiment of the present disclosure. Detailed implementation manners

[0045] Example embodiments will now be described more fully with reference to the accompanying drawings. However, the example embodiments can be implemented in various 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 more complete and comprehensive, and will fully convey the concept of the example embodiments to those skilled in the art. The features, structures, or characteristics described may be combined in any suitable manner in one or more embodiments.

[0046] In addition, the drawings are only schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus repeated descriptions thereof will be omitted. Some of the block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0047] The following will describe in detail the specific implementation manners of the embodiments of the present disclosure with reference to the accompanying drawings.

[0048] Figure 1 The schematic diagram showing an exemplary system architecture to which the edge computing load control method according to the embodiments of the present disclosure can be applied.

[0049] As shown Figure 1 in the figure, 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 the core network, including but not limited to an Access and Mobility Management Function (AMF) network element, a Network Exposure Function (NEF) network element, and a Policy Control Function (PCF) network element. In addition, it may also include a Session Management Function (SMF) network element, a Unified Data Management (UDM) network element, a 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] As shown Figure 1 in the figure, the AMF network element supports edge computing devices 101 with different mobility management requirements. The PCF network element interacts with the access and mobility policy implementation in the AMF network element through service-based interfaces (SBIs); the NEF network element is responsible for opening the capabilities of the 5G network to external edge computing devices 101, and the edge computing device 101 can send registration information to the NEF network element through the AMF network element for registration; the SMF network element is used for session establishment and configuration of traffic control of the UPF network element, and routes the traffic to the correct destination. The UPF network element, as the user plane network element of the 5G network, mainly supports routing and forwarding of service data, data and service identification, action and policy execution, etc. The UPF network element interacts with the SMF network element through the N4 interface, is controlled and managed by the SMF network element, and processes the service flow according to various policies issued by the SMF network element. In other words, after the SMF network element receives the session policy control creation response from the PCF network element, it controls the UPF network element to process the service flow.

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

[0053] In the embodiments of the present disclosure, the edge computing device 101 serves as the device layer of the edge computing system. The edge computing device 101 can be a computing device physically located in the edge network, such as an intelligent 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, an MEC application, multi-access edge host-level management, and multi-access edge system-level management.

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

[0056] The MEC application is a virtual machine running on the virtualization infrastructure of the MEC host, supporting interaction with the MEP to build and provide MEC services.

[0057] The multi-access edge host-level management includes a Multi-access Edge Platform Manager (MEPM) and a Virtualisation Infrastructure Manager (VIM), which manage the MEC host and the MEC applications running thereon. Among them, the VIM mainly provides virtualization resource management functions, and the MEPM is used to implement application lifecycle management, MEP network element management, application rule and requirement management, etc.

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

[0059] In the related art, the current mobile network and edge computing belong to different standard organizations. In the non-trusted case, the mutual communication between the mobile network and edge computing requires a long request-response process through the NEF network element. Even in the trusted case, edge computing cannot be integrated with the mobile network as seamlessly as the network elements inside the mobile network. However, edge computing is an inseparable part of the mobile network and is a necessary guarantee for high bandwidth and low latency.

[0060] With the development of communication technology, the relationship between edge computing and mobile networks will become closer. In a mobile network, for internal services, a predetermined Quality of Service (QoS) is configured, and at the same time, the load situation of the network itself can be obtained in real time, and the QoS of the predetermined services can be adaptively adjusted according to the load situation of the current mobile network.

[0061] Currently, edge computing mainly undertakes the near-offloading of traffic. However, the QoS used by the applications of edge computing devices needs to be applied by the edge computing devices as Application Functions (AFs), and the mobile network cannot know the load situation of edge computing devices in real time, resulting in low utilization of edge computing and inability to achieve effective integration of edge computing and mobile networks.

[0062] To at least solve some of the above technical problems, the present disclosure provides an edge computing load control method. 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 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, 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 key index to be measured; the measurement result of the key index to be measured measured by the edge computing device is received, so as to perform load control on the edge computing device according to the measurement result of the key index to be measured. By subscribing to the online notification of the edge computing device, the present disclosure can instruct the edge computing device to perform key index measurement, so that the first network element can accurately master the load situation of the edge computing device, and then perform load control on the edge computing device according to the key index measurement result, and timely adjust control strategies such as QoS and load balancing to ensure the user experience.

[0063] The following will describe this exemplary embodiment in detail with reference to the accompanying drawings and embodiments.

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

[0065] Figure 2 The flowchart of an edge computing load control method executed by a first network element provided in an embodiment of the present disclosure is shown. As Figure 2 shown, the edge computing load control method provided in an embodiment of the present disclosure is applied to a first network element, and this method mainly includes the following steps: S202. Send a subscription request to the second network element, where the subscription request is used to subscribe to the registration information of the edge computing device. The registration information of the edge computing device is sent when the edge computing device registers with the second network element after going online.

[0066] In one embodiment, the first network element may be a PCF network element, and the second network element is a NEF network element.

[0067] The subscription request is used to subscribe to the online notification of the edge computing device from the NEF network element. After the edge computing device goes online, the edge computing device sends a registration request to the NEF network element. The registration request may carry the registration information of the edge computing device. The registration information of the edge computing device includes a serial number (Serial Number, SN), device name, etc. Among them, the SN is the unique identity identifier of the edge computing device, and 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.

[0068] After receiving the registration information of the edge computing device, the NEF network element stores the registration information in the Unified Data Repository (UDR). At the same time, the NEF network element sends the registration information of the edge computing device to the PCF network element. The UDR is a common database that can store various standardized data structures. For example, the registration information of the edge computing device in this disclosure.

[0069] In one embodiment, the PCF network element can initiate a subscription to the UDR of the NEF network element by invoking the Nudr_DataRepository_Subscribe service operation of the UDR to subscribe to the UDR update of the NEF network element, so as to obtain the registration information of the newly online edge computing device in a timely manner.

[0070] S204. 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 metrics to be measured.

[0071] After receiving the registration information of the edge computing device, the PCF network element triggers the load control instruction and sends the load control instruction to the edge computing device. The edge computing device can measure the key metrics to be measured according to the load control instruction, so that the PCF network element can obtain the load situation of the edge computing device in a timely manner.

[0072] In one embodiment, the load control instruction includes: the key metrics to be measured; the threshold corresponding to the key metrics to be measured; the reporting method of the key metrics to be measured.

[0073] The key metrics to be measured are used to measure the metrics that have a relatively high impact on the load during the operation of the edge computing device. The above key metrics to be measured may include at least one of the Central Processing Unit (CPU) utilization rate, memory utilization rate, network bandwidth occupancy rate, and current number of concurrent tasks. In addition, the key metrics to be measured may also include the Graphics Processing Unit (GPU) utilization rate, GPU video memory utilization rate, hard disk utilization rate, etc.

[0074] It should be noted that the above key metrics to be measured may also be equivalent measurement methods. For example, the memory utilization rate may also be the used memory capacity or the remaining memory capacity, and the network bandwidth occupancy rate may also be the used network bandwidth amount or the remaining network bandwidth amount, etc.

[0075] The thresholds corresponding to the above key metrics to be measured are used to represent the upper limit value or the lower limit value corresponding to when the threshold is triggered. For example, the threshold corresponding to the CPU utilization rate is 95%, indicating that when the CPU utilization rate of the edge computing device reaches 95%, an event-triggered report is initiated.

[0076] The reporting methods of the key metrics to be measured include event-triggered reporting or periodic reporting.

[0077] Among them, event-triggered reporting is initiated when the measurement result of the key metric to be measured meets the corresponding threshold.

[0078] Periodic reporting refers to the edge computing device regularly sending measurement reports at the time interval configured in the load control instruction.

[0079] It should be noted that the thresholds corresponding to the above key metrics to be measured and the time interval configured for periodic reporting can be determined according to the actual situation, and the present disclosure does not make specific limitations thereto.

[0080] S206. Receive the measurement results of the key metrics 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 metrics to be measured.

[0081] After the PCF network element sends the load control instruction to the edge computing device, the edge computing device measures the key metrics to be measured according to the indication of the load control instruction, obtains the measurement results of the key metrics to be measured, and reports the measurement results of the key metrics to be measured to the PCF network element. The measurement results of the key metrics to be measured may include the values of each key metric to be measured at different times, the change trend curve, etc.

[0082] In one embodiment, the load control strategy for performing load control on the edge computing device according to the measurement results of the key metrics to be measured in S206 above includes at least one of the following: Quality of Service (QoS) control policy, which is used to match the best or corresponding QoS for the applications configured on the edge computing device; Load balancing policy, which is used to perform load balancing on multiple edge computing devices based on the measurement results of the key metrics to be measured obtained from the multiple edge computing devices.

[0083] The QoS control policy can allocate different bandwidth, latency, and priorities to the applications of the edge computing device through pre-configured QoS rules, so as to ensure that the critical applications of the edge computing device can still provide good quality of service during network congestion.

[0084] In one embodiment, the PCF network element can manage the computing tasks of multiple edge computing devices simultaneously. When the PCF network element receives the measurement results of the key metrics to be measured obtained from the multiple edge computing devices, it can perform load balancing according to the load conditions of the multiple edge computing devices. The specific manner of load balancing is not specifically limited in this disclosure.

[0085] In the embodiment of the present disclosure, the first network element sends a subscription request to the 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 metrics to be measured; the measurement results of the key metrics 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 metrics to be measured. By subscribing to the online notification of the edge computing device, the present disclosure can instruct the edge computing device to perform key metric measurements, so that the first network element can accurately grasp the load conditions of the edge computing device, and then perform load control on the edge computing device according to the key metric measurement results, and timely adjust control policies such as QoS and load balancing to ensure the user experience.

[0086] Figure 3 Shows a flowchart of another edge computing load control method executed by the first network element provided in the embodiment of the present disclosure. On the basis of Figure 2 the embodiment, after S204, S205 is added to limit the registration information of the edge computing system stored by the first network element. As Figure 3 shown, in one embodiment, the edge computing load control method of the present disclosure includes S202 to S206, where: 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.

[0087] It should be noted that the specific implementation manners of S202, S204, and S206 in this embodiment are the same as those of S202, S204, and S206 in the foregoing embodiment, and will not be elaborated here.

[0088] In one embodiment, after receiving the registration information of the edge computing device, the PCF network element stores the above registration information, as well as the IP address, port, and active status of the edge computing device. For example, a list can be used to record multiple edge computing devices and their corresponding status information, so as to formulate policies based on multiple edge computing devices.

[0089] In the implementation manner of the present disclosure, by storing the registration information of the edge computing device and the corresponding online status, the computing tasks can be dynamically allocated to appropriate edge computing devices based on the registration information, shortening the data transmission path, reducing the latency, and by monitoring the online status of the edge computing device, adjusting the task distribution policy in real time to avoid overloading of a single edge computing node and improve the overall resource utilization rate.

[0090] Figure 4 The flowchart of an edge computing load control method executed by a second network element provided by an embodiment of the present disclosure is shown. As Figure 4 shown, in one embodiment, an edge computing load control method of an embodiment of the present disclosure is applied to a second network element, and the method includes the following: S402: Receive a subscription request from a first network element, where the subscription request is used to subscribe to the registration information of the edge computing device; S404: Receive the registration information of the edge computing device; S406: Send the registration information of the edge computing device to the first network element.

[0091] In one embodiment, the method further includes: storing the registration information of the edge computing device in a unified data storage repository.

[0092] In one embodiment, the NEF network element receives a subscription request from the PFC network element to subscribe to the online notification of the edge computing device. After the edge computing device goes online, it registers with the NEF network element. The NEF network element stores the registration information of the edge computing device in a unified data storage repository and pushes it to the PCF network element. Thus, after receiving the registration information of the edge computing device, the PCF network element can send a load balancing instruction to the online edge computing device. After receiving the load balancing instruction, the edge computing device starts to measure the key metrics to be measured and reports the measurement results according to the load balancing instruction.

[0093] In the embodiments of the present disclosure, a second network element receives a subscription request from a first network element. When an edge computing device initiates registration with the second network element after going online, the second network element sends the registration information of the edge computing device to the first network element, enabling the mobile network to promptly know the load information of the edge computing device, and further matching the optimal QoS for the applications of the edge computing device and achieving load balancing based on the load conditions of different edge computing devices, realizing on-demand offloading of traffic and optimizing resource utilization.

[0094] Figure 5 The flowchart of an edge computing load control method executed by an edge computing device provided by an embodiment of the present disclosure is shown. As Figure 5 shown, in one embodiment, an edge computing load control method of an embodiment of the present disclosure is applied to an edge computing device, and the method includes: S502. After the edge computing device goes online, send the registration information of the edge computing device to a second network element for registration.

[0095] The registration information of the edge computing device includes, but is not limited to, a serial number (Serial Number, SN), a device name, etc. Among them, the SN is the unique identity identification code of the edge computing device, and the device name can be defined according to the device type and can be represented by text, letters, numbers, symbols, etc. For example, Camera 1, Camera 2, etc.

[0096] S504. 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 to-be-detected key index.

[0097] It should be noted that the load control instruction includes: a to-be-detected key index; a threshold corresponding to the to-be-detected key index; a reporting method for the to-be-detected key index.

[0098] The to-be-detected key index is used to measure an index that has a relatively high impact on the load of the edge computing device during its operation. The above to-be-detected key index may 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.

[0099] In addition, the to-be-detected key index may further include a graphics processing unit (GPU) usage rate, a GPU video memory usage rate, a hard disk usage rate, etc.

[0100] It should be noted that the above to-be-detected key index may also be an equivalent measurement method. For example, the memory usage rate may also be the used memory capacity or the remaining memory capacity, and the network bandwidth occupancy rate may also be the used network bandwidth amount or the remaining network bandwidth amount, etc.

[0101] The threshold value corresponding to the above-mentioned key index to be measured is used to represent the upper limit value or the lower limit value corresponding to the threshold trigger.

[0102] The reporting methods of the key index to be measured include event-triggered reporting or periodic reporting. Among them, event-triggered reporting is initiated when the measurement result of the key index to be measured meets the corresponding threshold value. Periodic reporting means that the edge computing device regularly sends a measurement report according to the time interval configured in the load control instruction.

[0103] It should be noted that the threshold value corresponding to the above-mentioned key index to be measured and the time interval configured for periodic reporting can be determined according to the actual situation, and the present disclosure does not make specific limitations thereto.

[0104] S506. Measure the key index to be measured according to the load control instruction, obtain the measurement result of the key index to be measured, and send the measurement result of the key index to be measured to the first network element.

[0105] The edge computing device measures the key index to be measured according to the indication of the load control instruction, obtains the measurement result of the key index to be measured, and reports the measurement result of the key index to be measured to the PCF network element. The measurement result of the key index to be measured may include the values of each key index to be measured at different times, the change trend curve, etc.

[0106] In the embodiment of the present disclosure, after the edge computing device is powered on, 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 the load control instruction. After receiving the load control instruction, the edge computing device measures the key index to be measured according to the load control instruction, obtains the corresponding measurement result, and sends it to the first network element, thereby realizing the effective integration of edge computing and the mobile network, synchronizing the load situation of edge computing to the mobile network in a timely manner, and further matching the timely execution of optimal QoS, load balancing and other strategies to improve the user experience.

[0107] Figure 6 Show a flowchart of another edge computing load control method executed by an edge computing device provided in an embodiment of the present disclosure. In Figure 5 On the basis of the embodiment, S506 is refined into S5062 to limit the method of monitoring the load situation through the MEP. As Figure 6 shown, in one embodiment, the above-mentioned S506 measures the key index to be measured according to the load control instruction, obtains the measurement result of the key index to be measured, and sends the measurement result of the key index to be measured to the first network element, including: S5062. Monitor and send the measurement result of the key index to be measured through the multi-access edge platform MEP of the edge computing system.

[0108] In one embodiment, the MEP obtains key metrics to be measured, such as the CPU usage rate, memory occupancy rate, and storage capacity of the edge computing device, in real time through the underlying interface.

[0109] In the embodiment of the present disclosure, the MEP monitors the test results of the key metrics to be measured 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 metrics to be measured, 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, avoiding local congestion.

[0110] Figure 7 The flowchart of another edge computing load control method executed by an edge computing device provided in the embodiment of the present disclosure is shown. Based on Figure 5 the embodiment, S504 is refined to S5042, and S506 is refined to S5064 to S5068 to define the case of receiving and sending load information through the MEO. As Figure 7 shown, in one embodiment, the above S504 receiving the load control instruction sent by the first network element includes: S5042: Receiving the load control instruction through the Multi-Access Edge Orchestrator (MEO) or the Multi-Access Edge Platform (MEP) of the edge computing system; Among them, S506 measuring the key metrics to be measured according to the load control instruction, obtaining the measurement results of the key metrics to be measured, and sending the measurement results of the key metrics to be measured to the first network element includes: S5064: Forwarding 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); S5066: Monitoring the key metrics to be measured according to the load control instruction by the Multi-Access Edge Platform Manager (MEPM) or the Multi-Access Edge Platform (MEP), obtaining the measurement results of the key metrics to be measured and reporting them to the Multi-Access Edge Orchestrator (MEO); S5068: Sending the measurement results of the key metrics to be measured to the first network element through the Multi-Access Edge Orchestrator (MEO).

[0111] In S5042, the MEO can be connected to the PCF network element through the Npcf interface and communicate using the HTTP / 2 protocol, which can ensure the security of the transmission of the load control instruction.

[0112] In S5068, the MEO can report the measurement results of the key metrics to be measured to the PCF network element through the MP2 interface, so that the PCF network element issues a dynamic adjustment instruction according to the measurement results of the key metrics to be measured.

[0113] In an embodiment of the present disclosure, the MEO receives a load control instruction and forwards it to the MEPM or MEP, so that the MEPM or MEP measures the key metrics to be measured to obtain corresponding measurement results. The 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 metrics to be measured, giving priority to ensuring the resource requirements of high-priority services, and realizing the joint load balancing of multiple edge computing devices to avoid local congestion.

[0114] In one embodiment, the edge computing load control method of the embodiments of the present disclosure further includes: receiving and executing 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, and the QoS control policy is used to match the best or corresponding QoS for an application configured on an edge computing device; a load balancing policy, and the load balancing policy is used to perform load balancing on multiple edge computing devices based on the measurement results of the key metrics to be measured obtained by the multiple edge computing devices.

[0115] The QoS control policy can allocate different bandwidths, latencies, and priorities to the applications of the edge computing device through pre-configured QoS rules, so as to ensure that the critical applications of the edge computing device can still provide good quality of service during network congestion.

[0116] In one embodiment, the PCF network element can simultaneously manage the computing tasks of multiple edge computing devices. When the PCF network element receives the measurement results of the key metrics to be measured obtained by the multiple edge computing devices, it can perform load balancing according to the load conditions of the multiple edge computing devices, and the specific manner of load balancing is not specifically limited in the present disclosure.

[0117] In an 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, according to the dynamically adjusted QoS policy formulated by the first network element, gives priority to ensuring the resource requirements of high-priority services, and realizes the joint load balancing of multiple edge computing devices to avoid local congestion.

[0118] It can be understood that for the edge computing device executing the above method, it can also be a chip or a chip system disposed in the edge computing device; for the first network element executing the above method, it can also be a chip or a chip system disposed in the first network element; for the second network element executing the above method, it can also be a chip or a chip system disposed in the second network element, and the present application does not make specific limitations thereto.

[0119] For the edge computing device, the first network element, and the second network element in the above method, the edge computing device can be an MEC device, the first network element can be a PCF network element, and the second network element is a NEF network element.

[0120] To deepen the understanding of the embodiments of the present disclosure, the following is a detailed description in conjunction with Figure 8 This is described in detail by taking the edge computing device as the MEC device, the first network element as the PCF network element, and the second network element as the NEF network element as an example.

[0121] As Figure 8 shown, the edge computing load control method provided by the present disclosure includes the following steps: 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; S802. After the MEC device goes online, it performs online registration with the NEF network element and sends the registration information of the MEC device to the NEF network element; S803. The NEF network element sends the online information of the MEC device to the PCF network element to complete the registration; S804. After receiving the registration information of the MEC device, the PCF network element triggers a load control instruction, and the load control instruction is used to instruct the MEC device to measure the key metrics to be measured; S805. The PCF network element sends the load control instruction to the MEC device; S806. The MEC device monitors the key metrics to be measured according to the load control instruction and obtains the measurement results of the key metrics to be measured; S807. The MEC device reports the measurement results of the key metrics to be measured according to the load control instruction.

[0122] In some embodiments, the PCF network element may also generate a load control strategy according to the measurement results of the key metrics to be measured, and send the load control strategy to the MEC device, and the MEC device executes the load control strategy.

[0123] Through the above method, the present disclosure can enable the mobile network to obtain the load situation of the edge computing device in real time, and execute corresponding load control strategies according to the load situation, so as to improve the effectiveness and reliability of the system, and make the integration degree of the mobile network and the edge computing device higher.

[0124] The present disclosure can be applied to the application scenarios of mobile communication and edge computing. There is no need to modify the hardware, only the software function needs to be enhanced. The edge computing device adds functions such as a registration process, load monitoring, and load situation reporting; a load control module is added on the network side. Through the linkage between the above modules, the mobile network can master the load of the edge computing device to prepare for the timely execution of strategies such as QoS dynamic adjustment and load balancing.

[0125] Based on the same inventive concept, embodiments of the present disclosure also provide an edge computing load control device and system, as described in the following embodiments. Since the principle of solving problems by the device and system embodiments is similar to that of the above method embodiments, the implementation of these embodiments can refer to the implementation of the above method embodiments, and repeated parts will not be elaborated.

[0126] Figure 9 A schematic diagram showing an edge computing load control device provided by an embodiment of the present disclosure. As Figure 9 shown, an edge computing load control device in 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, where: The subscription sending module 910 is configured to send 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, 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; The instruction sending module 920 is configured to send a load control instruction to the edge computing device in response to receiving the registration information of the edge computing device, and the load control instruction is used to instruct the edge computing device to measure a key index to be measured; The result receiving module 930 is configured to receive the measurement result of the key index to be measured measured by the edge computing device, so as to perform load control on the edge computing device according to the measurement result of the key index to be measured.

[0127] It should be noted that the load control instruction includes: the key index to be measured; the threshold corresponding to the key index to be measured; the reporting method of the key index to be measured.

[0128] It should be noted that the key index to be measured includes at least one of CPU usage rate, memory usage rate, network bandwidth occupancy rate, and current concurrent task number.

[0129] It should be noted that the reporting method of the key index to be measured includes event-triggered reporting and / or periodic reporting.

[0130] In one embodiment, the device further includes a first storage module not shown in the drawings. The first storage module is configured 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.

[0131] It should be noted that the load control strategy for controlling the load of the edge computing device according to the measurement result of the key index to be measured includes at least one of the following: the quality of service (QoS) control strategy, which is used to match the best or corresponding QoS for the applications configured on the edge computing device; the load balancing strategy, which is used to perform load balancing on multiple edge computing devices based on the measurement results of the key indexes to be measured obtained from the multiple edge computing devices.

[0132] In the embodiment of the present disclosure, the first network element sends a subscription request to the 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 index to be measured; the measurement result of the key index to be measured obtained by the edge computing device is received, so as to perform load control on the edge computing device according to the measurement result of the key index to be measured. By subscribing to the online notification of the edge computing device, the present disclosure can instruct the edge computing device to perform key index measurement, so that the first network element can accurately grasp the load condition of the edge computing device, and then perform load control on the edge computing device according to the key index measurement result, and timely adjust control strategies such as QoS and load balancing to ensure the user experience.

[0133] Figure 10 The schematic diagram of another edge computing load control device provided by the embodiment of the present disclosure is shown. As Figure 10 shown, an edge computing load control device according to an embodiment of the present disclosure is applied to the second network element. The device includes: A subscription receiving module 1010, configured to receive the subscription request of the first network element, where the subscription request is used to subscribe to the registration information of the edge computing device; An information receiving module 1020, configured to receive the registration information of the edge computing device; An information sending module 1030, configured to send the registration information of the edge computing device to the first network element.

[0134] In one embodiment, the device further includes a second storage module not shown in the drawings. The second storage module is configured to store the registration information of the edge computing device in a unified data storage repository.

[0135] In an embodiment of the present disclosure, a second network element receives a subscription request from a first network element. When an edge computing device initiates registration with the second network element after going online, the second network element sends the registration information of the edge computing device to the first network element, enabling the mobile network to promptly learn about the load information of the edge computing device. Furthermore, the optimal QoS can be matched for the applications of the edge computing device, and load balancing can be achieved based on the load conditions of different edge computing devices, realizing on-demand offloading of traffic and optimizing resource utilization.

[0136] Figure 11 A schematic diagram showing another edge computing load control device provided by an embodiment of the present disclosure. As Figure 11 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: A registration sending module 1110, configured to send the registration information of the edge computing device to a second network element for registration after the edge computing device goes online; An instruction receiving module 1120, configured to receive a load control instruction sent by a first network element; A measurement execution module 1130, configured to measure a to-be-measured key index according to the load control instruction to obtain a measurement result of the to-be-measured key index, and send the measurement result of the to-be-measured key index to the first network element.

[0137] In one embodiment, the measurement execution module 1130 is configured to monitor and send the measurement result of the to-be-measured key index through a multi-access edge platform of the edge computing system.

[0138] In one embodiment, the instruction receiving module 1120 is configured to receive the load control instruction through a multi-access edge orchestrator or a multi-access edge platform of the edge computing system; The measurement execution module 1130 is configured to forward the load control instruction to a multi-access edge platform manager or a multi-access edge platform of the edge computing system through a multi-access edge orchestrator; monitor the to-be-measured key index according to the load control instruction through the multi-access edge platform manager or the multi-access edge platform to obtain a measurement result of the to-be-measured key index and report it to the multi-access edge orchestrator; send the measurement result of the to-be-measured key index to the first network element through the multi-access edge orchestrator.

[0139] It should be noted that the load control instruction includes: the to-be-measured key index; the threshold corresponding to the to-be-measured key index; the reporting method of the to-be-measured key index.

[0140] It should be noted that the to-be-measured key index includes at least one of CPU usage rate, memory usage rate, network bandwidth occupancy rate, and current concurrent task number.

[0141] It should be noted that the reporting method of the to-be-measured key index includes event-triggered reporting and / or periodic reporting.

[0142] In one embodiment, the device further includes a load control execution module not shown in the drawings. The load control execution module is configured 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: a quality of service (QoS) control policy, which is used to match the best or corresponding QoS for the applications configured on the edge computing device; and a load balancing policy, which is used to perform load balancing on multiple edge computing devices based on the measurement results of the key metrics to be measured obtained from the multiple edge computing devices.

[0143] In the 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 metrics 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 the mobile network, synchronizing the load situation of edge computing to the mobile network in a timely manner, and further matching the timely execution of strategies such as optimal QoS and load balancing, and improving the user experience.

[0144] Figure 12 The structure diagram of an edge computing system provided by an embodiment of the present disclosure is shown. As Figure 12 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, where: the first network element 1210 is configured to send a subscription request to the second network element 1220, where 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, send a load control instruction to the edge computing device 101, where the load control instruction is used to instruct the edge computing device 101 to measure the key metrics to be measured; receive the measurement results of the key metrics to be measured obtained by the edge computing device 101, so as to perform load control on the edge computing device 101 according to the measurement results of the key metrics to be measured; the second network element 1220 is configured 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 configured to, after going online, send the registration information of the edge computing device 101 to the second network element 1220 for registration; receive the load control instruction sent by the first network element 1210; measure the key metrics to be measured according to the load control instruction, obtain the measurement results of the key metrics to be measured, and send the measurement results of the key metrics to be measured to the first network element 1210.

[0145] Those skilled in the art can understand that various aspects of the present disclosure can be implemented as a system, a method, or a program product. Therefore, various aspects of the present disclosure can be specifically implemented in the following forms, namely: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or an implementation combining hardware and software aspects, which can be collectively referred to as "circuit", "module", or "system" here.

[0146] Reference is made below Figure 13 to describe the electronic device 1300 according to such an embodiment of the present disclosure. Figure 13 The shown electronic device 1300 is only an example and should not impose any limitation on the functions and usage scope of the embodiments of the present disclosure.

[0147] As Figure 13 shown, the electronic device 1300 is presented in the form of a general-purpose computing device. The components of the electronic device 1300 may include, but are not limited to: at least one of the above-mentioned processing units 1310, at least one of the above-mentioned storage units 1320, and a bus 1330 connecting different system components (including the storage unit 1320 and the processing unit 1310).

[0148] Among them, the storage unit stores program code, and the program code can be executed by the processing unit 1310, so that the processing unit 1310 executes the steps according to various exemplary embodiments of the present disclosure described in the above "Exemplary Method" section of this specification. For example, the processing unit 1310 may execute the following steps of the above method embodiment: 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, 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 metrics to be measured; the measurement result of the key metrics to be measured obtained by the edge computing device is received, so as to perform load control on the edge computing device according to the measurement result of the key metrics to be measured.

[0149] For example, the processing unit 1310 may perform the following steps of the above method embodiment by itself: the second network element receives the subscription request of the first network element, and the subscription request is used to subscribe to the registration information of the edge computing device; the registration information of the edge computing device is received; the registration information of the edge computing device is sent to the first network element.

[0150] For example, the processing unit 1310 may perform the following steps of the above method embodiments: after the edge computing device is powered on, the edge computing device sends registration information of the edge computing device to a second network element for registration; receives 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 metric to be measured; measures the key metric to be measured according to the load control instruction to obtain a measurement result of the key metric to be measured, and sends the measurement result of the key metric to be measured to the first network element.

[0151] The storage unit 1320 may include a readable medium in the form of a volatile storage unit, such as a random access storage unit (RAM) 13201 and / or a cache 13202, and may further include a read-only storage unit (ROM) 13203.

[0152] The storage unit 1320 may further include a program / utilities 13204 having a set (at least one) of program modules 13205. Such program modules 13205 include, but are not limited to: an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment.

[0153] The bus 1330 may represent one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of a variety of bus structures.

[0154] The electronic device 1300 may also communicate with one or more external devices 1340 (such as a keyboard, a pointing device, a Bluetooth device, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 1300, and / or may communicate with any device that enables the electronic device 1300 to communicate with one or more other computing devices (such as a router, a modem, etc.). Such communication may be performed through an input / output (I / O) interface 1350. And, the electronic device 1300 may also communicate with one or more networks (such as a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through a network adapter 1360. As Figure 13 shown, the network adapter 1360 communicates with other modules of the electronic device 1300 through the bus 1330. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 1300, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0155] From the description of the above embodiments, those skilled in the art can easily understand that the exemplary embodiments described herein can be implemented by software, or by 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, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (such as a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.

[0156] In an exemplary embodiment of the present disclosure, there is also provided a computer-readable storage medium, which may be a readable signal medium or a readable storage medium. A program product capable of implementing the above method of the present disclosure is stored on the computer-readable storage medium. In an exemplary embodiment of the present disclosure, there is also provided a computer program product, which includes a computer program or computer instructions. The computer program or computer instructions are loaded and executed by a processor to enable the computer to implement any of the above edge computing load control methods.

[0157] More specific examples of the computer-readable storage medium in the present disclosure may include, but are not limited to: an electrical connection having one or more wires, 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), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0158] In the present disclosure, the computer-readable storage medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries readable program code. Such a propagated data signal may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The readable signal medium may also be any readable medium other than the readable storage medium, and the readable medium may send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device.

[0159] Optionally, the program code contained on the computer-readable storage medium may be transmitted by any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination of the above.

[0160] It should be noted that although several modules or units of the device for action execution are mentioned in the above detailed description, 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 embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0161] In addition, although the steps of the methods in the present disclosure are described in a specific order in the drawings, this does not require or imply that these steps must be executed in that specific order, or that all the steps shown must be executed to achieve the desired result. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step for execution, and / or one step may be decomposed into multiple steps for execution, etc.

[0162] Through the description of the above embodiments, those skilled in the art can easily understand that the exemplary embodiments described herein can be implemented by software, or by 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, mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (such as a personal computer, server, mobile terminal, or network device, etc.) to execute the methods according to the embodiments of the present disclosure.

[0163] After considering the specification and practicing the invention disclosed herein, those skilled in the art will readily conceive of other embodiments of the present disclosure. The present disclosure is intended to cover any variations, uses, or adaptations of the present disclosure, which follow the general principles of the present disclosure and include known common knowledge or conventional technical means in the technical field not disclosed by the present disclosure. The specification and examples are only regarded as exemplary, and the true scope of the present disclosure is pointed out by the appended claims.

Claims

1. An edge computing load control method, characterized in that: Applied to a first network element, the method includes: Sending a subscription request to the second network element, wherein the subscription request is used to subscribe to 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, 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 tested; The threshold value corresponding to the key indicator to be measured; The reporting method of the key indicator to be tested.

3. The edge computing load control method according to claim 2, characterized in that: 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.

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: According to the measurement result of the key indicator to be measured, the load control strategy for load controlling the edge computing device includes at least one of the following: A quality of service (QoS) control strategy, wherein the QoS control strategy is used to match an optimal or corresponding QoS for an application deployed on the edge computing device; A load balancing strategy, wherein the 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. An edge computing load control method, characterized in that: Applied to a second network element, the method comprises: 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 registration information of the edge computing device; Send the registration information of the edge computing device to the first network element.

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. An edge computing load control method, characterized in that: Applied to edge computing devices, the method includes: After the edge computing device is online, sending registration information of the edge computing device to the second network element for registration; Receiving 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 a key indicator to be measured; 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 step of measuring the key indicator to be measured according to the load control instruction to obtain 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 to obtain 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 a 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 the 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 tested; The threshold value corresponding to the key indicator to be measured; The reporting method of the key indicator to be tested.

13. The edge computing load control method according to claim 12, characterized in that: 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.

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: receiving and executing a load control strategy sent by the first network element, where the load control strategy includes at least one of the following: A quality of service (QoS) control strategy, wherein the QoS control strategy is used to match an optimal or corresponding QoS for an application configured on the edge computing device; A load balancing strategy, wherein the 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, the device includes: A subscription sending module, used 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; 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, the device comprises: A subscription receiving module, used 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; An information receiving module, used 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.

18. An edge computing load control device, characterized in that: Applied to edge computing equipment, the device comprises: A registration sending module, configured to send registration information of the edge computing device to the second network element for registration after the edge computing device is online; An instruction receiving module, used for receiving a load control instruction sent by the first 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 method 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; 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; 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; 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 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.

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 a computer instruction, which is loaded and executed by a processor so that the computer implements the edge computing load control method as described in any one of claims 1 to 6, or implements the edge computing load control method as described in any one of claims 7 to 8, or implements the edge computing load control method as described in any one of claims 9 to 15.

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