Node management method and apparatus based on scheduling analysis

Abstract

Embodiments of the present application provide a node management method and device based on scheduling analysis, the method comprising: obtaining push stream scheduling data corresponding to all nodes in an edge computing system, wherein the push stream scheduling data contains real-time push stream addresses; extracting a push stream destination address and a push stream protocol from the real-time push stream addresses; for each piece of push stream scheduling data, generating data of a scheduling failure of the push stream protocol and the push stream destination address once in the case that the real-time push stream address is different from the push stream destination address; determining a faulty node in the edge computing system according to all pieces of scheduling failure data, and controlling the faulty node to go offline. By analyzing the destination push stream address and the real-time push stream address in real time, some faulty nodes that have been scheduled but cannot successfully receive the stream are automatically discovered, and the automatic offline of these faulty nodes is controlled, which greatly reduces the risk of the system and improves the availability of the system.

Description

Technical Field

[0001] This application relates to the field of Internet technology, and in particular to a node management method, apparatus, computer device, and computer-readable storage medium based on scheduling analysis. Background Technology

[0002] In the current live streaming upstream system, live streaming platforms not only support the general RTMP streaming protocol based on TCP, but also provide the SRT protocol based on UDP to support low-latency streaming for broadcasters. Because the UDP protocol has advantages in terms of packet loss resistance and low latency, the business prioritizes scheduling the SRT streaming protocol to users via HttpDNS. If the SRT program fails, a large number of broadcasters will use the RTMP protocol for streaming via DNS, causing a sudden surge in traffic, which can overwhelm nodes and render them unusable.

[0003] In existing technologies, the industry standard for node availability detection is to perform real-time liveness probing of service ports. While this method can meet the needs of most business scenarios and ensure node availability, the inventors have found the following drawbacks in practice: 1. It cannot resolve issues when the service program port is healthy but the service process is already in a pending or unresolved state; 2. It cannot automatically take pending nodes offline in a timely manner, leading to a cascading failure effect. Summary of the Invention

[0004] The purpose of this application is to provide a node management method, apparatus, computer device, and computer-readable storage medium based on scheduling analysis to solve the following problem: existing service node activation methods cannot automatically take offline nodes that are in a pending state in a timely manner, thus causing an avalanche effect.

[0005] One aspect of this application provides a node management method based on scheduling analysis, applied to a scheduling analysis platform, the method comprising:

[0006] Obtain the push streaming scheduling data corresponding to all nodes in the edge computing system, wherein the push streaming scheduling data includes real-time push streaming addresses;

[0007] The streaming destination address and streaming protocol are extracted from the real-time streaming address;

[0008] For each push stream scheduling data, if the real-time push stream address is different from the push stream destination address, data indicating a scheduling failure of the push stream protocol and the push stream destination address is generated;

[0009] Based on all the scheduling failure data, identify the faulty nodes in the edge computing system and control the faulty nodes to go offline.

[0010] Optionally, determining the faulty node in the edge computing system based on all scheduling failure data includes:

[0011] The number of scheduling failures for each of the aforementioned streaming protocols and streaming destination addresses is counted based on all scheduling failure data.

[0012] If the number of scheduling failures reaches a preset threshold, the node corresponding to the push destination address is determined to be a faulty node.

[0013] Optionally, the step of counting the number of scheduling failures for each of the streaming protocols and the streaming destination address based on all scheduling failure data includes:

[0014] Iterate through each failed data entry sequentially, and accumulate the number of times data with the same push protocol and push destination address has failed to schedule.

[0015] The process continues until all scheduled data that failed to be scheduled is completed. Then, the number of times each data with the same push protocol and push destination address failed to be scheduled is output.

[0016] Optionally, controlling the faulty node to go offline includes:

[0017] A fault notification message is generated for the faulty node;

[0018] The fault notification message is transmitted to the node management platform so that the faulty node can be taken offline through the node management platform.

[0019] Optionally, the destination address and streaming protocol are extracted from the real-time streaming address, including:

[0020] The streaming destination address and streaming protocol are extracted from the private signature information of the real-time streaming address.

[0021] One aspect of this application provides a node management method based on scheduling analysis, applied to an uplink scheduling system, the method comprising:

[0022] Receive the request to obtain the live streaming address sent by the broadcaster;

[0023] The streaming protocol and streaming destination address corresponding to the broadcaster's terminal are determined based on the streaming address acquisition request.

[0024] Generate a push address carrying the push protocol and the push destination address, and return the push address to the broadcaster.

[0025] Optionally, generating the push address carrying the push protocol and the push destination address includes:

[0026] The streaming protocol and the streaming destination address are signed into the streaming address in the form of private signature information.

[0027] Optionally, the broadcaster terminal is used to push the live stream according to the push address, and if the live stream push fails, it will try to push the live stream again via DNS.

[0028] One aspect of this application provides a node management device based on scheduling analysis, applied to a scheduling analysis platform, the device comprising:

[0029] The push streaming scheduling data acquisition module is used to acquire push streaming scheduling data corresponding to all nodes in the edge computing system, wherein the push streaming scheduling data includes real-time push streaming addresses;

[0030] The streaming destination address extraction module is used to extract the streaming destination address and streaming protocol from the real-time streaming address;

[0031] The scheduling failure data generation module is used to generate data indicating a scheduling failure of the streaming protocol and the streaming destination address for each streaming scheduling data, in the case where the real-time streaming address is different from the streaming destination address.

[0032] The fault node control module is used to identify faulty nodes in the edge computing system based on all scheduling failure data and to control the faulty nodes to go offline.

[0033] One aspect of this application provides a node management device based on scheduling analysis, applied to an uplink scheduling system, the device comprising:

[0034] The streaming address acquisition request receiving module is used to receive the streaming address acquisition request sent by the broadcaster.

[0035] The push stream destination address determination module is used to determine the push stream protocol and push stream destination address corresponding to the broadcaster's terminal based on the live stream address acquisition request.

[0036] The push stream address return module is used to generate a push stream address carrying the push stream protocol and the push stream destination address, and return the push stream address to the broadcaster.

[0037] One aspect of this application provides a computer device, the computer device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the node management method based on scheduling analysis as described above.

[0038] One aspect of this application provides a computer-readable storage medium storing a computer program that can be executed by at least one processor to implement the steps of the node management method based on scheduling analysis as described above when the at least one processor executes the computer program.

[0039] The node management method, apparatus, device, and computer-readable storage medium based on scheduling analysis provided in this application, by issuing a push stream destination address and a push stream protocol in the push stream address, wherein the push stream destination address is the address of the node that the broadcaster should push the stream to, the scheduling analysis platform can automatically discover some faulty nodes that have been scheduled but cannot successfully connect to the stream by analyzing the destination push stream address and the real-time push stream address in real time, and control the automatic offline of these faulty nodes, thereby realizing the automatic discovery of some node failures that cannot provide services due to unknown program reasons and automatically taking them offline, which greatly reduces the risk of the system and improves the availability of the system. Attached Figure Description

[0040] Figure 1 This diagram illustrates an application environment of a node management method based on scheduling analysis according to an embodiment of this application.

[0041] Figure 2 A flowchart illustrating a node management method based on scheduling analysis according to Embodiment 1 of this application is shown schematically.

[0042] Figure 3 A flowchart illustrating a node management method based on scheduling analysis according to Embodiment 2 of this application is shown in the schematic diagram.

[0043] Figure 4 The diagram illustrates a block diagram of a node management method based on scheduling analysis.

[0044] Figure 5 A block diagram of a node management device based on scheduling analysis according to Embodiment 3 of this application is shown schematically;

[0045] Figure 6 A block diagram of a node management device based on scheduling analysis according to Embodiment 4 of this application is schematically shown; and

[0046] Figure 7The illustration shows a schematic diagram of the hardware architecture of a computer device suitable for implementing a node management method based on scheduling analysis, according to Embodiment 5 of this application. Detailed Implementation

[0047] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application. All other embodiments obtained by those skilled in the art based on the embodiments in this application without inventive effort are within the scope of protection of this application.

[0048] It should be noted that the descriptions involving "first," "second," etc., in the embodiments of this application are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of that feature. Furthermore, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed in this application.

[0049] In the current live streaming upstream system, live streaming platforms not only support the general RTMP streaming protocol based on TCP, but also provide the SRT protocol based on UDP to support low-latency streaming for broadcasters. Because the UDP protocol has advantages in terms of packet loss resistance and low latency, the business prioritizes scheduling the SRT streaming protocol to users via HttpDNS. If the SRT program fails, a large number of broadcasters will use the RTMP protocol for streaming via DNS, causing a sudden surge in traffic, which can overwhelm nodes and render them unusable.

[0050] In existing technologies, the industry standard for node availability detection is to perform real-time liveness probing of service ports. While this method can meet the needs of most business scenarios and ensure node availability, the inventors have found the following drawbacks in practice: 1. It cannot resolve issues when the service program port is healthy but the service process is already in a pending or unresolved state; 2. It cannot automatically take pending nodes offline in a timely manner, leading to a cascading failure effect.

[0051] In view of this, this application aims to propose a node management method based on scheduling analysis. This method acquires streaming scheduling data corresponding to all nodes in an edge computing system, wherein the streaming scheduling data includes real-time streaming addresses. The streaming destination address and streaming protocol are extracted from the real-time streaming address. For each streaming scheduling data, if the real-time streaming address and the streaming destination address are different, data indicating a scheduling failure for the streaming protocol and the streaming destination address is generated. Based on all the scheduling failure data, faulty nodes in the edge computing system are identified, and these faulty nodes are taken offline. By issuing the streaming destination address and streaming protocol in the streaming address (the streaming destination address being the address of the node that the broadcaster should be streaming to), the scheduling analysis platform can automatically discover faulty nodes that are constantly being scheduled but cannot successfully connect to the stream by analyzing the destination streaming address and the real-time streaming address in real time. This allows for the automatic offline detection and removal of nodes that cannot provide service due to unknown program reasons, greatly reducing system risk and improving system availability.

[0052] This application provides several embodiments to further illustrate a node management scheme based on scheduling analysis, as detailed below.

[0053] In the description of this application, it should be understood that the numerical labels before the steps do not indicate the order of the steps, but are only used to facilitate the description of this application and to distinguish each step, and therefore should not be construed as a limitation of this application.

[0054] The following is a definition of the terminology used in this application:

[0055] Edge computing refers to migrating IT resources (computing, storage, networking, and other internet-related resources) from traditional cloud data centers to the user side, bringing users and IT resources closer together, achieving lower data interaction latency, saving network traffic, and thus providing users with low-latency and highly stable IT solutions.

[0056] RTMP: Real-Time Messaging Protocol, is a streaming media transmission protocol.

[0057] SRT: Secure Reliable Transport is an open-source, low-latency video transmission protocol based on the UDT protocol.

[0058] DNS: Domain Name System, is a system for resolving the naming of machines on the Internet.

[0059] HttpDNS: This uses the HTTP protocol to request DNS servers from port 80, instead of the traditional DNS protocol which requests from port 53. In other words, it uses the HTTP protocol to make DNS resolution requests and directly sends the resolution result (the server IP address corresponding to the domain name) returned by the server to that IP address to make the corresponding API service request, instead of using the domain name.

[0060] Figure 1 A schematic diagram illustrating an environmental application according to an embodiment of this application is provided. Figure 1 As shown:

[0061] Computer device 10000 can connect to client 30000 via network 20000.

[0062] Computer device 10000 can provide services such as network debugging or returning node management results data based on scheduling analysis to client 30000.

[0063] Computer equipment 10000 may be located in a data center, such as a single site, or distributed across different geographical locations (e.g., multiple sites). Computer equipment 10000 may provide services via one or more networks 20000. Network 20000 includes various network devices, such as routers, switches, multiplexers, hubs, modems, bridges, repeaters, firewalls, agent devices, and / or similar devices. Network 20000 may include physical links, such as coaxial cable links, twisted-pair cable links, fiber optic links, combinations thereof, etc. Network 20000 may include wireless links, such as cellular links, satellite links, Wi-Fi links, etc.

[0064] Computer device 10000 can be implemented by one or more compute nodes. One or more compute nodes can include virtualized compute instances. Virtualized compute instances can include virtual machines, such as emulations of computer systems, operating systems, servers, etc. Compute nodes can load virtual machines based on virtual images and / or other data defining specific software used for emulation (e.g., operating systems, dedicated applications, servers). As the demand for different types of processing services changes, different virtual machines can be loaded and / or terminated on one or more compute nodes. A hypervisor can be implemented to manage the use of different virtual machines on the same compute node.

[0065] Client 30000 can be configured to access the content and services of computer device 10000. Client 30000 can include any type of electronic device, such as mobile devices, tablets, laptops, workstations, virtual reality devices, gaming devices, set-top boxes, digital streaming media devices, vehicle terminals, smart TVs, etc.

[0066] Client 30000 can output (e.g., display, render, present) node management results data based on scheduling analysis to the user.

[0067] The following will describe a network debugging solution through several embodiments. This solution can be implemented using computer equipment 10000.

[0068] Example 1

[0069] Figure 2 A flowchart illustrating a node management method based on scheduling analysis according to Embodiment 1 of this application is shown. Applied to a scheduling analysis platform, the method includes steps S202-S208, wherein...

[0070] Step S202: Obtain the push streaming scheduling data corresponding to all nodes in the edge computing system, wherein the push streaming scheduling data includes real-time push streaming addresses;

[0071] In this embodiment, the real-time streaming address is the address of the uplink node that is streaming the content to the broadcaster. The scheduling and analysis platform acquires real-time streaming scheduling data for all nodes in the edge computing system to identify faulty nodes by analyzing the streaming scheduling data.

[0072] Step S204: Extract the streaming destination address and streaming protocol from the real-time streaming address;

[0073] In this embodiment, the real-time streaming address can carry the streaming destination address and streaming protocol to identify potentially faulty nodes by comparing and analyzing the streaming destination address and the real-time streaming address. Specifically, the streaming destination address and streaming protocol can be signed into the real-time streaming address using a private signature. Therefore, the streaming destination address and streaming protocol can be extracted from the private signature information of the real-time streaming address.

[0074] Step S206: For each push stream scheduling data, if the real-time push stream address is different from the push stream destination address, generate data indicating that the push stream protocol and the push stream destination address have experienced a scheduling failure.

[0075] In this embodiment, for each push stream scheduling data, it is determined whether the real-time push stream address and the push stream destination address are the same. If the real-time push stream address and the push stream destination address are the same, it indicates that the push stream scheduling is normal; if the real-time push stream address and the push stream destination address are different, it indicates that the push stream scheduling is abnormal. By generating data indicating a scheduling failure in the case where the real-time push stream address and the push stream destination address are different, this scheduling failure data can be used for subsequent analysis to identify faulty nodes.

[0076] Step S208: Based on all the scheduling failure data, determine the faulty nodes in the edge computing system and control the faulty nodes to go offline.

[0077] Specifically, by analyzing all scheduling failure data, nodes that consistently fail to connect can be identified as faulty nodes in the edge computing system, and these faulty nodes can be taken offline. Thus, the scheduling analysis platform can automatically identify faulty nodes that are constantly being scheduled but cannot successfully connect by analyzing the destination streaming address and the real-time streaming address, and automatically take these faulty nodes offline, greatly reducing system risk and improving system availability.

[0078] The following are several optional embodiments for optimizing the node management method based on scheduling analysis, as follows:

[0079] In a preferred embodiment of this application, step S208 may include the following steps:

[0080] Based on all the scheduling failure data, the number of times each streaming protocol and streaming destination address experienced scheduling failure is counted; if the number of scheduling failures reaches a preset threshold, the node corresponding to the streaming destination address is determined to be a faulty node.

[0081] In this embodiment, by analyzing all scheduling failure data, the number of scheduling failures for each streaming protocol and the streaming destination address is counted. Then, the number of scheduling failures is checked against a preset threshold. If the number of scheduling failures reaches the preset threshold, the node corresponding to the streaming destination address is determined to be a faulty node. The preset threshold is a pre-set minimum threshold value, which can be set according to actual needs. This embodiment does not impose specific restrictions on it. For example, if the preset threshold is 300, then a node is considered faulty if the number of scheduling failures reaches 300.

[0082] In a preferred embodiment of this application, the step of counting the number of scheduling failures for each streaming protocol and the streaming destination address based on all scheduling failure data includes:

[0083] Iterate through each data entry that failed to schedule, and accumulate the number of times that data with the same streaming protocol and streaming destination address failed to schedule; until all data with failed scheduling has been traversed, output the number of times that data with the same streaming protocol and streaming destination address failed to schedule.

[0084] In this embodiment, by sequentially traversing each data entry that failed to schedule, the number of scheduling failures for data entries with the same streaming protocol and destination address is accumulated until all data entries with failed scheduling are traversed. The output then shows the number of scheduling failures for each data entry with the same streaming protocol and destination address. As an example, the data entries with failed scheduling include: RTMP protocol + streaming destination address A, RTMP protocol + streaming destination address B, RTMP protocol + streaming destination address A, RTMP protocol + streaming destination address B, SRT protocol + streaming destination address A, and SRT protocol + streaming destination address B. Therefore, the statistics show that: the number of scheduling failures for RTMP protocol and streaming destination address A is 2; the number of scheduling failures for RTMP protocol and streaming destination address B is 2; the number of scheduling failures for SRT protocol and streaming destination address A is 1; and the number of scheduling failures for SRT protocol and streaming destination address B is 1.

[0085] In a preferred embodiment of this application, controlling the faulty node to go offline includes:

[0086] A fault notification message is generated for the faulty node; the fault notification message is transmitted to the node management platform so that the faulty node can be taken offline through the node management platform.

[0087] In this embodiment, a node management and control platform is deployed. After the scheduling and analysis platform discovers a faulty node, it generates a fault notification message for the faulty node and transmits the fault notification message to the node management and control platform. The node management and control platform controls the faulty node to go offline, thereby realizing the automatic discovery of some nodes that cannot provide services due to unknown program reasons and automatically taking them offline, which greatly reduces the risk of the system and improves the availability of the system.

[0088] In a preferred embodiment of this application, extracting the streaming destination address and streaming protocol from the real-time streaming address includes:

[0089] The streaming destination address and streaming protocol are extracted from the private signature information of the real-time streaming address.

[0090] In this embodiment, the real-time streaming address can carry private signature information. The streaming destination address and streaming protocol can be extracted from the private signature information of the real-time streaming address. In addition, the real-time streaming address can also carry streaming platform information for analyzing the streaming platform of the broadcaster.

[0091] Example 2

[0092] Figure 3The flowchart illustrating a node management method based on scheduling analysis according to Embodiment 2 of this application is shown schematically. Applied to an uplink scheduling system, the method includes steps S302-S306, wherein...

[0093] Step S302: Receive a request from the broadcaster to obtain the live streaming address;

[0094] In this embodiment, when the broadcaster starts broadcasting, it can send a request to the uplink scheduling system to obtain the broadcast push address in order to obtain the push address for broadcasting.

[0095] Step S302: Determine the streaming protocol and streaming destination address corresponding to the broadcaster based on the streaming address acquisition request;

[0096] In this embodiment, the uplink scheduling system determines the streaming protocol and destination address corresponding to the broadcaster by responding to the request to obtain the streaming address. Specifically, the uplink scheduling system can first determine the inference platform corresponding to the broadcaster, and then determine the streaming protocol and destination address corresponding to the broadcaster based on the streaming platform.

[0097] Step S302: Generate a push address carrying the push protocol and the push destination address, and return the push address to the broadcaster.

[0098] In this embodiment, after determining the streaming protocol and streaming destination address corresponding to the broadcaster, the uplink scheduling system can generate a streaming address carrying the streaming protocol and streaming destination address, and return the streaming address to the broadcaster.

[0099] The following are several optional embodiments for optimizing the node management method based on scheduling analysis, as follows:

[0100] In a preferred embodiment of this application, generating a push address carrying the push protocol and the push destination address includes:

[0101] The streaming protocol and the streaming destination address are signed into the streaming address in the form of private signature information.

[0102] In this embodiment, the uplink scheduling system can sign the streaming protocol and the streaming destination address into the streaming address in the form of private signature information. In addition, when signing the private signature, the streaming platform corresponding to the broadcaster can also be signed into the streaming address.

[0103] In a preferred embodiment of this application, the broadcaster is used to perform live streaming according to the streaming address, and if the live streaming fails, it will try to stream again via DNS.

[0104] In this embodiment, after receiving the push address returned by the uplink scheduling system, the broadcaster can directly push the live stream according to the push address. If the live stream fails to push the live stream according to the push address returned by the uplink scheduling system, the live stream can be pushed again through DNS.

[0105] To further describe the node management method based on scheduling analysis according to the embodiments of this application, such as Figure 4 A block diagram of a node management method based on scheduling analysis is shown, including an uplink scheduling system, an edge computing system, a scheduling analysis platform, and a node control platform.

[0106] The uplink scheduling system is the first step in the entire invention. When the uplink scheduling system sends the streaming address to the broadcaster, it signs the broadcaster's streaming platform, streaming protocol, and destination address into the streaming address using a private signature. The broadcaster then starts using the streaming address to stream. If the broadcaster successfully streams, the streaming server address (i.e., the real-time streaming address) should be consistent with the sent destination streaming address. If the broadcaster fails to stream, it will try to stream again using DNS. In this case, the streaming server address (i.e., the real-time streaming address) will be inconsistent with the destination streaming address in the private signature.

[0107] Edge computing system: responsible for receiving streaming data from the broadcaster, including RTMP server and SRT server.

[0108] The scheduling and analysis platform collects real-time push address data from all nodes in the edge computing system. It continuously analyzes and compares the real-time push address of each push with the destination push address in the signature, filtering out address conflicts. It records the push protocol and destination push address of this information as a scheduling failure. After one round of analysis, based on the push protocol and the push platform aggregation, nodes with the same protocol and the same destination push address whose number of scheduling failures exceeds a preset threshold (e.g., 300) are considered faulty. At this point, the information of this faulty node is sent to the node management platform.

[0109] Node management platform: This is the management system responsible for managing the online and offline status of nodes in the entire edge computing system. By receiving fault notification messages from the scheduling analysis platform, it controls the automatic offline status of faulty nodes, thus realizing a device that automatically removes faulty nodes based on the analysis of scheduling results.

[0110] Example 3

[0111] Figure 5The diagram illustrates a block diagram of a node management device based on scheduling analysis according to Embodiment 3 of this application. This node management device can be divided into one or more program modules. One or more program modules are stored in a storage medium and executed by one or more processors to complete the embodiments of this application. The program modules referred to in the embodiments of this application are a series of computer program instruction segments capable of performing specific functions. The following description will specifically introduce the functions of each program module in the embodiments of this application.

[0112] like Figure 5 As shown, the node management device 500 based on scheduling analysis is applied to a scheduling analysis platform and may include the following modules:

[0113] The streaming scheduling data acquisition module 510 is used to acquire streaming scheduling data corresponding to all nodes in the edge computing system, wherein the streaming scheduling data includes real-time streaming addresses.

[0114] The push stream destination address extraction module 520 is used to extract the push stream destination address and the push stream protocol from the real-time push stream address;

[0115] The scheduling failure data generation module 530 is used to generate data indicating that the streaming protocol and the streaming destination address have failed once for each streaming scheduling data when the real-time streaming address is different from the streaming destination address.

[0116] The fault node control module 540 is used to determine the fault nodes in the edge computing system based on all scheduling failure data and to control the fault nodes to go offline.

[0117] In a preferred embodiment of this application, the fault node control module 540 includes:

[0118] The scheduling failure count submodule is used to count the number of scheduling failures for each of the streaming protocols and the streaming destination address based on all the scheduling failure data.

[0119] The fault node determination submodule is used to determine the node corresponding to the push destination address as a fault node when the number of scheduling failures reaches a preset threshold.

[0120] In a preferred embodiment of this application, the scheduling failure count statistics submodule includes:

[0121] The count accumulation unit is used to sequentially traverse each data that failed to be scheduled and accumulate the count of data that failed to be scheduled when the push protocol and the push destination address are the same.

[0122] The count output unit is used to output the number of times each data with the same push protocol and push destination address has failed to schedule until all the scheduled failure data has been traversed.

[0123] In a preferred embodiment of this application, the fault node control module 540 further includes:

[0124] The fault notification message determination module is used to generate a fault notification message for the faulty node.

[0125] The fault notification message transmission module is used to transmit the fault notification message to the node management platform so that the faulty node can be taken offline through the node management platform.

[0126] In a preferred embodiment of this application, the push stream destination address extraction module 520 includes:

[0127] The push stream destination address extraction submodule is used to extract the push stream destination address and push stream protocol from the private signature information of the real-time push stream address.

[0128] Example 4

[0129] Figure 6 The diagram illustrates a block diagram of a node management device based on scheduling analysis according to Embodiment 4 of this application. This node management device can be divided into one or more program modules. One or more program modules are stored in a storage medium and executed by one or more processors to complete the embodiments of this application. The program module referred to in the embodiments of this application refers to a series of computer program instruction segments capable of performing a specific function. The following description will specifically introduce the functions of each program module in the embodiments of this application.

[0130] like Figure 6 As shown, the node management device 600 based on scheduling analysis is applied to the uplink scheduling system and may include the following modules:

[0131] The streaming address acquisition request receiving module 610 is used to receive the streaming address acquisition request sent by the broadcaster.

[0132] The push stream destination address determination module 620 is used to determine the push stream protocol and push stream destination address corresponding to the broadcaster terminal based on the live stream address acquisition request.

[0133] The push stream address return module 630 is used to generate a push stream address carrying the push stream protocol and the push stream destination address, and return the push stream address to the broadcaster.

[0134] In a preferred embodiment of this application, the push address return module 630 includes:

[0135] The signature submodule is used to sign the push protocol and the push destination address into the push address in the form of private signature information.

[0136] In a preferred embodiment of this application, the broadcaster is used to perform live streaming according to the streaming address, and if the live streaming fails, it will try to stream again via DNS.

[0137] Example 5

[0138] Figure 7 This illustration schematically shows a hardware architecture diagram of a computer device 10000 suitable for implementing a node management method based on scheduling analysis according to Embodiment 3 of this application. In this embodiment, the computer device 10000 is a device capable of automatically performing numerical calculations and / or information processing according to pre-set or stored instructions. For example, it can be a smartphone, tablet computer, laptop computer, desktop computer, rack server, blade server, tower server, or cabinet server (including independent FEN servers, or server clusters composed of multiple servers), etc. Figure 7 As shown, the computer device 10000 includes, but is not limited to, at least the following: a memory 10010, a processor 10020, and a network interface 10030 that can communicate and be linked to each other via a system bus. Wherein:

[0139] The memory 10010 includes at least one type of computer-readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 10010 may be an internal storage module of the computer device 10000, such as the hard disk or memory of the computer device 10000. In other embodiments, the memory 10010 may also be an external storage device of the computer device 10000, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the computer device 10000. Of course, the memory 10010 may also include both the internal storage module and the external storage device of the computer device 10000. In this embodiment, the memory 10010 is typically used to store the operating system and various application software installed on the computer device 10000, such as program code for a node management method based on scheduling analysis. In addition, the memory 10010 can also be used to temporarily store various types of data that have been output or will be output.

[0140] In some embodiments, processor 10020 may be a central processing unit (CPU), controller, microcontroller, microprocessor, or other data processing chip. Processor 10020 is typically used to control the overall operation of computer device 10000, such as performing control and processing related to data interaction or communication with computer device 10000. In this embodiment, processor 10020 is used to run program code stored in memory 10010 or process data.

[0141] Network interface 10030 may include a wireless network interface or a wired network interface, which is typically used to establish a communication link between computer device 10000 and other computer devices. For example, network interface 10030 is used to connect computer device 10000 to an external terminal via a network, establishing a data transmission channel and communication link between computer device 10000 and the external terminal. The network may be an intranet, the Internet, Global System for Mobile Communication (GSM), Wideband Code Division Multiple Access (WCDMA), 4G network, 5G network, Bluetooth, Wi-Fi, or other wireless or wired networks.

[0142] It should be pointed out that, Figure 7 Only computer devices with components 10010-10030 are shown; however, it should be understood that it is not required to implement all of the shown components, and more or fewer components may be implemented instead.

[0143] In this embodiment, the node management method based on scheduling analysis stored in memory 10010 can be further divided into one or more program modules and executed by one or more processors (processor 10020 in this embodiment) to complete the embodiment of this application.

[0144] Example 6

[0145] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the node management method based on scheduling analysis in the embodiments.

[0146] In this embodiment, the computer-readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the computer-readable storage medium can be an internal storage unit of a computer device, such as the hard disk or memory of the computer device. In other embodiments, the computer-readable storage medium can also be an external storage device of the computer device, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the computer device. Of course, the computer-readable storage medium can also include both the internal storage unit and the external storage device of the computer device. In this embodiment, the computer-readable storage medium is typically used to store the operating system and various application software installed on the computer device, such as the program code of the node management method based on scheduling analysis in this embodiment. In addition, the computer-readable storage medium can also be used to temporarily store various types of data that have been output or will be output.

[0147] Obviously, those skilled in the art should understand that the modules or steps of the embodiments of this application described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those presented here, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the embodiments of this application are not limited to any particular combination of hardware and software.

[0148] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A node management method based on scheduling analysis, characterized in that, Applied to a scheduling analysis platform, the method includes: Obtain the push streaming scheduling data corresponding to all nodes in the edge computing system, wherein the push streaming scheduling data includes real-time push streaming addresses; The streaming destination address and streaming protocol are extracted from the real-time streaming address; For each push stream scheduling data, if the real-time push stream address is different from the push stream destination address, data indicating a scheduling failure of the push stream protocol and the push stream destination address is generated; Based on all the scheduling failure data, identify the faulty nodes in the edge computing system and control the faulty nodes to go offline.

2. The node management method based on scheduling analysis according to claim 1, characterized in that, The step of determining the faulty node in the edge computing system based on all scheduling failure data includes: The number of scheduling failures for each of the aforementioned streaming protocols and streaming destination addresses is counted based on all scheduling failure data. If the number of scheduling failures reaches a preset threshold, the node corresponding to the push destination address is determined to be a faulty node.

3. The node management method based on scheduling analysis according to claim 2, characterized in that, The step of counting the number of scheduling failures for each streaming protocol and streaming destination address based on all scheduling failure data includes: Iterate through each failed data entry sequentially, and accumulate the number of times data with the same push protocol and push destination address has failed to schedule. The process continues until all scheduled data that failed to be scheduled is completed. Then, the number of times each data with the same push protocol and push destination address failed to be scheduled is output.

4. The node management method based on scheduling analysis according to claim 1, characterized in that, The process of controlling the faulty node to go offline includes: A fault notification message is generated for the faulty node; The fault notification message is transmitted to the node management platform so that the faulty node can be taken offline through the node management platform.

5. The node management method based on scheduling analysis according to claim 1, characterized in that, The step of extracting the streaming destination address and streaming protocol from the real-time streaming address includes: The streaming destination address and streaming protocol are extracted from the private signature information of the real-time streaming address.

6. A node management method based on scheduling analysis, characterized in that, Applied to an uplink scheduling system, the method includes: Receive the request to obtain the live streaming address sent by the broadcaster; The streaming protocol and streaming destination address corresponding to the broadcaster's terminal are determined based on the streaming address acquisition request. Generate a push address carrying the push protocol and the push destination address, and return the push address to the broadcaster. The step of generating a push address carrying the push protocol and the push destination address includes: The streaming protocol and the streaming destination address are signed into the streaming address in the form of private signature information. The private signature information is used by the scheduling and analysis platform to extract the streaming protocol and the streaming destination address from the real-time streaming address and compare them with the real-time streaming address to identify the faulty node and control the faulty node to go offline.

7. The node management method based on scheduling analysis according to claim 6, characterized in that, The broadcaster terminal is used to push live streams according to the push address, and if the live stream push fails, it will try to push live streams again via DNS.

8. A node management device based on scheduling analysis, characterized in that, The device, applied to a scheduling and analysis platform, includes: The push streaming scheduling data acquisition module is used to acquire push streaming scheduling data corresponding to all nodes in the edge computing system, wherein the push streaming scheduling data includes real-time push streaming addresses; The streaming destination address extraction module is used to extract the streaming destination address and streaming protocol from the real-time streaming address; The scheduling failure data generation module is used to generate data indicating a scheduling failure of the streaming protocol and the streaming destination address for each streaming scheduling data, in the case where the real-time streaming address is different from the streaming destination address. The fault node control module is used to identify faulty nodes in the edge computing system based on all scheduling failure data and to control the faulty nodes to go offline.

9. A node management device based on scheduling analysis, characterized in that, The device, applied to an uplink scheduling system, includes: The streaming address acquisition request receiving module is used to receive the streaming address acquisition request sent by the broadcaster. The push stream destination address determination module is used to determine the push stream protocol and push stream destination address corresponding to the broadcaster's terminal based on the live stream address acquisition request. The push stream address return module is used to generate a push stream address carrying the push stream protocol and the push stream destination address, and return the push stream address to the broadcaster. The push stream address return module is further used for: The streaming protocol and the streaming destination address are signed into the streaming address in the form of private signature information. The private signature information is used by the scheduling and analysis platform to extract the streaming protocol and the streaming destination address from the real-time streaming address and compare them with the real-time streaming address to identify the faulty node and control the faulty node to go offline.

10. A computer device, the computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the node management method based on scheduling analysis as described in any one of claims 1 to 5 or 6 to 7.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that can be executed by at least one processor to perform the steps of the node management method based on scheduling analysis as described in any one of claims 1 to 5 or 6 to 7.

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