Multi-node service scheduling method, system and server
By sorting the status and network delay scores of edge nodes and dynamic up-and-down operations, the problem of insufficient dynamic management of edge nodes in the existing technology is solved, real-time monitoring and efficient service scheduling are realized, and service quality and efficiency are ensured.
Patent Information
- Application Number
- CN202411344978.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-25
- Publication Date
- 2025-01-10
AI Technical Summary
The existing multi-node service scheduling technology cannot be effective and dynamically moved up and down according to the load and health status of edge nodes in real time, resulting in invalid client requests or unavailable nodes being unable to invest in services in time, increasing interaction complexity.
By performing multi-dimensional comprehensive evaluation of state collection and network delay on edge node servers, select nodes with high scores as primary and secondary dual-node servers, and periodically monitor node status to perform up- and offline operations in real time.
Real-time load and health status monitoring of edge nodes is realized, ensuring the availability and service quality of nodes, reducing invalid requests, and improving service efficiency.
Smart Images
Figure CN119299293A_ABST
Abstract
Description
Technical Field
[0001] The present application belongs to the field of computer networks, and in particular, relates to a multi-node service scheduling method, system and server. Background Art
[0002] In a distributed computing environment, multiple nodes jointly provide services to meet client requests. It is necessary to effectively schedule client requests to appropriate service nodes to improve system performance and reliability. This scheduling strategy can be based on a variety of factors, such as node load, network latency, data locality, etc., to ensure that each request can be processed quickly and accurately. Through reasonable task allocation and resource management, the system throughput can be maximized, response time can be reduced, and overall efficiency can be improved.
[0003] In traditional multi-node service scheduling, a central node is usually responsible for receiving all task requests and then allocating tasks to edge nodes according to a certain strategy.
[0004] However, the existing methods have the following technical disadvantages: they cannot effectively and in real time dynamically bring edge nodes online and offline according to the load and health status of edge nodes. If edge nodes cannot be brought online and offline dynamically in a timely manner, a large number of clients will initiate invalid requests or available edge nodes will not be able to be put into service in a timely manner.
[0005] The central node only responds to the client's single available edge node information. When the responded edge node is unavailable, the client needs to request the central node server again to obtain a new available edge node, which increases the complexity of the interaction.
[0006] Therefore, there is an urgent need for a technical solution for multi-node service scheduling that can solve the above problems. Summary of the invention
[0007] In order to address the deficiencies of the prior art, the present application provides a multi-node service scheduling method, system and server, which collects the status of edge node servers and conducts a multi-dimensional comprehensive evaluation of network delays, and selects servers with high scores as primary and backup dual-node servers.
[0008] The technical effects to be achieved by this application are achieved through the following solutions: According to a first aspect of the present application, a multi-node service scheduling method is provided, comprising the following steps: Step 1: The client sends a request to the central node server to obtain the list information of all available edge node servers; Step 2: According to the list information, a network delay test request is initiated to each edge node server, and the obtained network delay data is sent to the central node server; Step 3: The central node server scores and sorts the edge node servers according to the network delay data and the edge node server status data; Step 4: The client selects the two edge node servers with the highest scores as the primary node server and the backup node server.
[0009] Preferably, the edge node server periodically reports the edge node server status data to the central node server, and the edge node server status data includes: current CPU usage and memory usage.
[0010] Preferably, the specific method for scoring and ranking edge node servers is: Scoring the edge node server status data and the network delay data respectively; Adding the edge node server status data score, network delay data score and manual weighted score to obtain a final node score; Compare and sort the scores of each node.
[0011] Preferably, the edge node server status data is scored according to the following formula: Score_A= A1*(1-CPU usage%)*(1-memory usage%); A1 is the impact factor, which defaults to 40.
[0012] Preferably, network latency data is scored according to: Divide the network delay data into grades and set the grade score rate LP for each grade; The network latency score is calculated according to the following formula: Score_B=A2*LP; A2 affects the shadow and the default value is 40.
[0013] Preferably, the manual weighted score is calculated according to the following formula: Score_C=A3*weighted data / 100; A3 is the impact factor, which defaults to 20; the weighted data defaults to 50 and can be adjusted within the range of 0-100 as needed.
[0014] Preferably, in step 4, the client attempts to connect to the primary node server. If the connection is normal, the primary node server is used for subsequent business access; if the primary node server connection is abnormal, the backup node server is used for business access, and the primary node server unavailability event is reported to the central node server.
[0015] Preferably, the following steps are also included: the central node server monitors the survival of the edge node servers according to periodic edge node server status data, takes unavailable edge node servers offline, monitors the offline edge node servers, and brings them back online when available.
[0016] According to a second aspect of the present application, a multi-node service scheduling system using the multi-node service scheduling method is provided, including a central node server and several edge node servers, wherein the central node server includes an edge node status monitoring module and an edge node service orchestration module, wherein: The edge node status monitoring module is used to monitor the status of the edge node server; The edge node service orchestration module is used to perform scoring and sorting as well as online and offline operations on edge node servers.
[0017] According to a third aspect of the present application, there is provided a server, comprising: a memory and at least one processor; The memory stores a computer program, and the at least one processor executes the computer program stored in the memory to implement the above-mentioned multi-node service scheduling method.
[0018] According to one embodiment of the present application, the beneficial effect of adopting this multi-node service scheduling method is that it can monitor the load and health status of the edge node server in real time, and dynamically go online and offline according to the health status, so as to maximize the availability of each node during interaction; adapt the appropriate edge node server according to the request initiated by the client, so as to ensure service quality and service efficiency. BRIEF DESCRIPTION OF THE DRAWINGS
[0019] In order to more clearly illustrate the embodiments of the present application or the existing technical solutions, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.
[0020] Figure 1 This is a flowchart of a multi-node service scheduling method in one embodiment of the present application; Figure 2 This is a flow chart of a multi-node service scheduling system in one embodiment of the present application; Figure 3 This is a structural block diagram of a server in an embodiment of the present application. DETAILED DESCRIPTION
[0021] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.
[0022] like Figure 1 As shown, the multi-node service scheduling method in one embodiment of the present application includes the following steps: Step 1: The client sends a request to the central node server to obtain the list information of all available edge node servers; In this step, the edge node server periodically reports the current edge node server status data to the central node server through heartbeat, including but not limited to the following information: the server's current CPU usage, memory usage, etc.
[0023] The central service node monitors the survival of the edge node servers according to the above periodic heartbeat, takes unavailable edge node servers offline, monitors the offline edge node servers, and brings them back online when they are available, thereby maintaining the edge node server list information.
[0024] The client accesses the central node server and requests to obtain the above-mentioned currently available edge node server list information.
[0025] Step 2: According to the list information, a network delay test request is initiated to each edge node server, and the obtained network delay data is sent to the central node server; In this step, the client initiates a network delay test request to each edge node server based on the acquired edge node server list information, obtains the network delay data between the client and each edge node; and reports the data to the central node server.
[0026] The method for testing network delay is: the client executes the ping command to obtain the delay time from the current client to each edge node server.
[0027] Step 3: The central node server scores and sorts the edge node servers according to the network delay data and the edge node server status data; In this step, the edge node orchestration module of the central node server performs a multi-dimensional comprehensive evaluation and ranking of each edge node based on the client reported data, node reported data, and manually weighted data. The specific method is as follows: The edge node server status data and the network delay data are scored respectively: The edge node server status data is scored according to the following formula: Score_A= A1*(1-CPU usage%)*(1-memory usage%); A1 is the impact factor, which defaults to 40.
[0028] Network latency data is scored according to: The network delay data is divided into grades, and a grade score rate LP is set for each grade. The specific network delay data grade rules are as follows: 0ms<=network delay<=10ms, then: LP=100% 10ms<network delay<=20ms, then: LP=80% 20ms<network delay<=30ms, then: LP=60% 30ms<network delay<=40ms, then: LP=40% 40ms<network delay<=60ms, then: LP=20% 60ms<network delay, then: LP=0% The network latency score is calculated according to the following formula: Score_B=A2*LP; A2 affects the shadow and the default value is 40.
[0029] The manually weighted score is calculated according to the following formula: Score_C=A3*weighted data / 100; A3 is the impact factor, which defaults to 20; the weighted data defaults to 50 and can be adjusted within the range of 0-100 as needed.
[0030] The edge node server status data score, network delay data score and manual weighted score are added together to obtain the final node score Score: Score = Score_A + Score_B + Score_C.
[0031] Step 4: The client selects the two edge node servers with the highest scores as the primary node server and the backup node server.
[0032] In this step, all edge node servers are sorted in reverse order according to the Score, and the first two nodes with the highest scores are taken as the optimal active and standby dual-node server information suitable for the client, and the active and standby edge node server information is returned to the client.
[0033] After selecting the primary and backup dual-node servers, the client will give priority to selecting the primary node server returned by the central node server for connection attempts. If the connection is normal, the primary edge node will be used for subsequent business access; if the primary edge node connection is abnormal, the backup node server will be enabled for business access. At the same time, the primary edge node unavailability event will be reported to the central node server, which will take the edge node server offline and notify relevant personnel for maintenance.
[0034] like Figure 2 As shown, a multi-node service scheduling system using the multi-node service scheduling method includes a central node server and several edge node servers. The client first initiates an application to the central node server, wherein: Client refers to a terminal that has the ability to initiate HTTPS requests, which can be a smartphone, tablet computer, etc. The central node server should be located on the public network and have the ability to receive public network access from clients and edge nodes; The edge node server should be located on the public network and have the ability to communicate with the central node and the client. The edge node server should be reasonably distributed according to the geographical distribution of the client.
[0035] In this embodiment, the central node server includes an edge node status monitoring module and an edge node service orchestration module, wherein: The edge node status monitoring module is used to monitor the status of the edge node server according to the periodic heartbeat of the edge node server. If no heartbeat is received within a certain period, the edge node server is considered abnormal, and it is judged as an unavailable node and reported to the edge node service orchestration module; at the same time, all unavailable edge node servers are monitored in real time, and when they resend heartbeats, they are reported to the edge node service orchestration module in time for re-online operation; The edge node service orchestration module is used to score and rank edge node servers and perform online and offline operations. Specifically, it receives the status of edge node servers collected by the edge node status monitoring module in real time, scores and ranks them according to the status and network delay data, and performs online and offline operations according to the status to avoid invalid requests caused by clients applying to unavailable servers.
[0036] The edge node service orchestration module monitors the offline edge node servers in real time. When the following conditions are met at the same time, the server is determined to be available and the online operation is performed again: 1. The heartbeat request is sent to the offline server to determine that the network is normal; 2. The heartbeat request is sent to the offline server service test interface to determine that the service is normal.
[0037] like Figure 3 As shown, an embodiment of the present application discloses a server, including: a memory and at least one processor; The memory stores a computer program, and the at least one processor executes the computer program stored in the memory to implement the above-mentioned multi-node service scheduling method.
[0038] According to one embodiment of the present application, the beneficial effect of adopting this multi-node service scheduling method is that it can monitor the load and health status of the edge node server in real time, and dynamically go online and offline according to the health status to ensure that all nodes are available during interaction; adapt the appropriate edge node server according to the request initiated by the client to ensure service quality and service efficiency.
[0039] It should be noted that the above detailed descriptions are exemplary and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the art to which the present application belongs.
[0040] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should also be understood that when the terms "comprise" and / or "include" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.
[0041] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the terms used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein.
[0042] In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units that are not explicitly listed or inherent to these processes, methods, products, or apparatuses.
[0043] For ease of description, spatially relative terms, such as "above", "above", "on the upper surface of", "above", etc., may be used herein to describe the spatial positional relationship between a device or feature and other devices or features as shown in the figure. It should be understood that spatially relative terms are intended to include different orientations of the device in use or operation in addition to the orientation described in the figure. For example, if the device in the accompanying drawings is inverted, the device described as "above other devices or structures" or "above other devices or structures" will be positioned as "below other devices or structures" or "below other devices or structures". Thus, the exemplary term "above" may include both "above" and "below". The device may also be positioned in other different ways, such as rotated 90 degrees or in other orientations, and the spatially relative descriptions used herein are interpreted accordingly.
[0044] In the above detailed description, reference is made to the accompanying drawings, which form a part of this document. In the accompanying drawings, similar symbols typically identify similar components unless the context indicates otherwise. The illustrated embodiments described in the detailed description, drawings, and claims are not meant to be limiting. Other embodiments may be used, and other changes may be made, without departing from the spirit or scope of the subject matter presented herein.
[0045] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.
Claims
1. A multi-node service scheduling method, characterized in that: The steps include: Step 1: The client sends a request to the central node server to obtain the list information of all available edge node servers; Step 2: According to the list information, a network delay test request is initiated to each edge node server, and the obtained network delay data is sent to the central node server; Step 3: The central node server scores and sorts the edge node servers according to the network delay data and the edge node server status data; Step 4: The client selects the two edge node servers with the highest scores as the primary node server and the backup node server.
2. The multi-node service scheduling method according to claim 1, characterized in that: The edge node server periodically reports the edge node server status data to the central node server, and the edge node server status data includes: current CPU usage and memory usage.
3. The multi-node service scheduling method according to claim 2, characterized in that: The specific method for scoring and ranking edge node servers is as follows: Scoring the edge node server status data and the network delay data respectively; Adding the edge node server status data score, network delay data score and manual weighted score to obtain a final node score; Compare and sort the scores of each node.
4. The multi-node service scheduling method according to claim 3, characterized in that: The edge node server status data is scored according to the following formula: Score_A= A1*(1-CPU usage%)*(1-memory usage%); A1 is the impact factor, which defaults to 40.
5. The multi-node service scheduling method according to claim 3, characterized in that: Network latency data is scored according to: Divide the network delay data into grades and set the grade score rate LP for each grade; The network latency score is calculated according to the following formula: Score_B=A2*LP; A2 affects the shadow and the default value is 40.
6. The multi-node service scheduling method according to claim 3, characterized in that: The manually weighted score is calculated according to the following formula: Score_C=A3*weighted data / 100; A3 is the impact factor, which defaults to 20; the weighted data defaults to 50 and can be adjusted within the range of 0-100 as needed.
7. The multi-node service scheduling method according to claim 1, characterized in that: In step 4, the client attempts to connect to the primary node server. If the connection is normal, the primary node server is used for subsequent business access; if the primary node server connection is abnormal, the backup node server is used for business access, and the primary node server unavailable event is reported to the central node server.
8. The multi-node service scheduling method according to claim 1, characterized in that: The method also includes the following steps: the central node server monitors the survival of the edge node servers according to the periodic edge node server status data, takes the unavailable edge node servers offline, monitors the offline edge node servers, and puts them back online when they are available.
9. A multi-node service scheduling system using the multi-node service scheduling method according to any one of claims 1 to 8, characterized in that: It includes a central node server and several edge node servers, wherein the central node server includes an edge node status monitoring module and an edge node service orchestration module, wherein: The edge node status monitoring module is used to monitor the status of the edge node server; The edge node service orchestration module is used to perform scoring and sorting as well as online and offline operations on edge node servers.
10. A server, characterized in that: include: memory and at least one processor; The memory stores a computer program, and the at least one processor executes the computer program stored in the memory to implement the multi-node service scheduling method according to any one of claims 1 to 8.