Dynamic service node management method based on user connection rule analysis

Abstract

The invention discloses a dynamic service node management method based on user connection rule analysis. S1, determining a connection peak period; s2, dividing node resources; s3, carrying out routing selection; s4, analyzing the connection time of the user side; s5, dynamic node expansion; s6, dynamic node reduction; and S7, regularly monitoring and adjusting. The node resources of the server are divided into the persistent service node cluster and the temporary extension node cluster, the persistent service node cluster is used for long-time user connection, and the temporary extension node cluster is used for large-probability user connection only used in the peak period. The node resources can fully meet the requirements of different time periods, and the user experience is improved.

Description

Technical Field

[0001] The present invention relates to the field of remote connection technology, and in particular to a dynamic service node management method based on user connection rule analysis. Background Art

[0002] With the popularity of remote work, online education and cloud services, the demand for remote connection technology has increased significantly. In particular, it is becoming more common to see connection peaks during fixed time periods (such as 9 am to 11 am).

[0003] Server resources are usually expensive and limited. During peak hours, server nodes need to be added to meet a large number of connection requests, while during off-peak hours, nodes need to be reduced to save resources and reduce operating costs. Traditional load balancing methods are inefficient in handling dynamic load changes, especially when resources cannot be released in time after the peak period, resulting in resource waste.

[0004] Therefore, the prior art has defects and needs to be improved. Summary of the invention

[0005] The technical problem to be solved by the present invention is: to provide a dynamic service node management method based on user connection rule analysis, which can realize dynamic management of service nodes by analyzing user connection usage rules, and ensure efficient and stable operation of the server during connection peak and non-peak periods while saving server node resources.

[0006] The technical solution of the present invention is as follows: a dynamic service node management method based on user connection rule analysis is provided, comprising the following steps.

[0007] S1: Determine the peak period of connection; determine the peak time range by monitoring and statistically analyzing the number and time of connection requests, and then write it into the server node management script to achieve dynamic adjustment of the peak period.

[0008] S2: Division of node resources: The node resources of the server are divided into a persistent service node cluster and a temporary extension node cluster. The persistent service node cluster is used for user connections with long connections, and the temporary extension node is used for user connections that are likely to be used only during peak hours.

[0009] S3: Routing selection; when the user's client establishes a connection with the server, the previous user connection usage, that is, the time period range of the connection, is analyzed. If the user's client connection is likely to be used only during the peak time period, the user's connection is routed to the temporary node of the temporary extension node cluster, otherwise it is routed to the persistent node of the persistent service node cluster. The probability of the user's client connecting during the peak time period is calculated as follows: the number of times the user's client has previously connected during the peak time period divided by the total number of user connections. The probability that the user's client connection is only used during the peak time period is 70% or more.

[0010] S4: User connection time analysis: When the user initiates a connection request, the user connection time is recorded. After the user ends the connection, the duration of the user connection, the range of the connection time during the peak period, etc. are calculated. After the user connection information is collected, it is updated to the server user connection data storage so that the routing node can be dynamically adjusted the next time the user connects.

[0011] S5: Dynamic node expansion; during the connection peak period, if the number of connections exceeds the capacity of the persistent service node, the creation of a temporary expansion service node is triggered; the temporary expansion service node will be added to the service node cluster to meet the connection demand.

[0012] S6: Dynamic node reduction: After the connection peak period, if the number of connections on the temporary extension service node is less than a certain threshold, node reduction is triggered; the server node management script is called to automatically remove the temporary extension service node from the service node cluster to save server resources. In this step, the threshold is preferably 50-150.

[0013] S7: Regular monitoring and adjustment: Regularly monitor the connection requests and the load of the service nodes, adjust the number and capacity of nodes according to actual needs, and ensure efficient operation in different time periods.

[0014] The development of virtualization and cloud computing technologies has made it possible to dynamically expand and reduce computing resources. Through virtualization technology, the number and configuration of server nodes can be quickly adjusted to cope with different load requirements. By analyzing user connection time and behavior patterns, server resources can be allocated and managed more intelligently, thereby improving system efficiency and user experience. By dividing the server's node resources into persistent service node clusters and temporary extension node clusters, the persistent service node cluster is used for user connections that are connected for a long time, and the temporary extension node is used for user connections that are likely to be connected only during peak hours, so that node resources can fully meet the needs of different time periods and improve the user experience. The more previous data the user has on connecting to the server, the more accurate the analysis and prediction of connecting to the persistent service node cluster or the temporary extension node cluster will be.

[0015] Furthermore, the server dynamically expands the temporary nodes according to the start time of the peak period of writing.

[0016] Furthermore, the user terminal establishes a network connection with the server, and the connection request first goes to the gateway service, which obtains the user's previous connection analysis data from the data cache (such as redis); based on the obtained user connection data, it decides whether to route to a persistent node or a temporary node.

[0017] Furthermore, the connection analysis data is updated after the user terminal is disconnected.

[0018] By adopting the above scheme, the present invention provides a dynamic service node management method based on user connection rule analysis, which has the following technical effects:

[0019] 1. Efficiently cope with connection peaks; during connection peaks, the present invention can rapidly expand service nodes to meet the connection needs of a large number of users and avoid connection failures or performance degradation due to insufficient resources.

[0020] 2. Significantly save server resources; after the connection peak period, the present invention can timely reduce unnecessary service nodes, avoid resource waste, and reduce operating costs.

[0021] 3. Improve system flexibility and response speed; by analyzing user connection time, assign long-term connected users to persistent service nodes, and short-term connected users to temporary extension service nodes, to ensure that the system can flexibly respond to different types of connection requirements and improve response speed.

[0022] 4. Ensure the continuity and stability of services; ensure that there are sufficient server resources to support existing connections at any time period, avoid reducing nodes when the connection is not fully released, and thus ensure the continuity and stability of user experience.

[0023] 5. Intelligent resource management: Analyze the user's connection time through algorithms, perform intelligent node allocation and management, optimize resource allocation strategies, and improve the overall efficiency of the system.

[0024] 6. Reduce operating costs by dynamically adjusting the number of service nodes, reasonably expanding nodes during peak periods, and timely reducing nodes during non-peak periods, thereby significantly reducing the cost of using server resources.

[0025] 7. Improve user experience; provide sufficient resources to ensure stable connection during peak connection periods, release resources during non-peak periods, ensure stable system performance, and improve user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0027] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0028] See also Figure 1 The present invention provides a dynamic service node management method based on user connection rule analysis, comprising the following steps.

[0029] S1: Determine the peak period of connection; determine the peak time range by monitoring and statistically analyzing the number and time of connection requests, and then write it into the server node management script to achieve dynamic adjustment of the peak period.

[0030] S2: Division of node resources: The node resources of the server are divided into a persistent service node cluster and a temporary extension node cluster. The persistent service node cluster is used for user connections with long connections, and the temporary extension node is used for user connections that are likely to be used only during peak hours.

[0031] S3: Routing selection; when the user's client establishes a connection with the server, the previous user connection usage, that is, the time period range of the connection, is analyzed. If the user's client connection is likely to be used only during the peak time period, the user's connection is routed to the temporary node of the temporary extension node cluster, otherwise it is routed to the persistent node of the persistent service node cluster. The probability of the user's client connecting during the peak time period is calculated as follows: the number of times the user's client has previously connected during the peak time period divided by the total number of user connections. The probability that the user's client connection is only used during the peak time period is 70% or more.

[0032] S4: User connection time analysis: When the user initiates a connection request, the user connection time is recorded. After the user ends the connection, the duration of the user connection, the range of the connection time during the peak period, etc. are calculated. After the user connection information is collected, it is updated to the server user connection data storage so that the routing node can be dynamically adjusted the next time the user connects.

[0033] S5: Dynamic node expansion; during the connection peak period, if the number of connections exceeds the capacity of the persistent service node, the creation of a temporary expansion service node is triggered; the temporary expansion service node will be added to the service node cluster to meet the connection demand.

[0034] S6: Dynamic node reduction: After the connection peak period, if the number of connections on the temporary extension service node is less than a certain threshold, node reduction is triggered; the server node management script is called to automatically remove the temporary extension service node from the service node cluster to save server resources. In this step, the threshold is preferably 50-150.

[0035] S7: Regular monitoring and adjustment: Regularly monitor the connection requests and the load of the service nodes, adjust the number and capacity of nodes according to actual needs, and ensure efficient operation in different time periods.

[0036] The development of virtualization and cloud computing technologies has made it possible to dynamically expand and reduce computing resources. Through virtualization technology, the number and configuration of server nodes can be quickly adjusted to cope with different load requirements. By analyzing user connection time and behavior patterns, server resources can be allocated and managed more intelligently, thereby improving system efficiency and user experience. By dividing the server's node resources into persistent service node clusters and temporary extension node clusters, the persistent service node cluster is used for user connections that are connected for a long time, and the temporary extension node is used for user connections that are likely to be connected only during peak hours, so that node resources can fully meet the needs of different time periods and improve the user experience. The more previous data the user has on connecting to the server, the more accurate the analysis and prediction of connecting to the persistent service node cluster or the temporary extension node cluster will be.

[0037] In this embodiment, the server dynamically expands the temporary nodes according to the start time of the peak period of writing.

[0038] In this embodiment, the user terminal establishes a network connection with the server, and the connection request first goes to the gateway service. The gateway service obtains the user's previous connection analysis data from the data cache (such as redis); based on the obtained user connection data, it decides whether to route to a persistent node or a temporary node.

[0039] In this embodiment, the connection analysis data is updated after the user terminal is disconnected.

[0040] In summary, the present invention provides a dynamic service node management method based on user connection rule analysis, which has the following technical effects:

[0041] 1. Efficiently cope with connection peaks; during connection peaks, the present invention can rapidly expand service nodes to meet the connection needs of a large number of users and avoid connection failures or performance degradation due to insufficient resources.

[0042] 2. Significantly save server resources; after the connection peak period, the present invention can timely reduce unnecessary service nodes, avoid resource waste, and reduce operating costs.

[0043] 3. Improve system flexibility and response speed; by analyzing user connection time, assign long-term connected users to persistent service nodes, and short-term connected users to temporary extension service nodes, to ensure that the system can flexibly respond to different types of connection requirements and improve response speed.

[0044] 4. Ensure the continuity and stability of services; ensure that there are sufficient server resources to support existing connections at any time period, avoid reducing nodes when the connection is not fully released, and thus ensure the continuity and stability of user experience.

[0045] 5. Intelligent resource management: Analyze the user's connection time through algorithms, perform intelligent node allocation and management, optimize resource allocation strategies, and improve the overall efficiency of the system.

[0046] 6. Reduce operating costs by dynamically adjusting the number of service nodes, reasonably expanding nodes during peak periods, and timely reducing nodes during non-peak periods, thereby significantly reducing the cost of using server resources.

[0047] 7. Improve user experience; provide sufficient resources to ensure stable connection during peak connection periods, release resources during non-peak periods, ensure stable system performance, and improve user experience.

[0048] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A dynamic service node management method based on user connection rule analysis, characterized in that: The following steps are involved: S1: Determine the peak period of connection; determine the peak period time range by monitoring and statistically analyzing the number and time of connection requests, and then write it into the server node management script to achieve dynamic adjustment of the peak period; S2: Division of node resources: The node resources of the server are divided into a persistent service node cluster and a temporary extension node cluster. The persistent service node cluster is used for user connections that are connected for a long time, and the temporary extension node is used for user connections that are likely to be used only during peak hours. S3: Routing selection: When the user's client establishes a connection with the server, the previous user connection usage, that is, the time period range of the connection, is analyzed. If the user's client connection is likely to be used only during peak time periods, the user's connection is routed to a temporary node in the temporary expansion node cluster, otherwise it is routed to a persistent node in the persistent service node cluster; S4: User connection time analysis: When the user initiates a connection request, the user connection time is recorded. After the user ends the connection, the duration of the user connection is calculated, and the range of the connection time during the peak period is calculated. After the user connection information is collected, it is updated to the server user connection data storage so that the routing node can be dynamically adjusted when the user connects next time. S5: Dynamic node expansion: During the peak period of connections, if the number of connections exceeds the capacity of the persistent service node, the creation of a temporary expansion service node is triggered; the temporary expansion service node will be added to the service node cluster to meet the connection demand; S6: Dynamic node reduction: After the connection peak period, if the number of connections on the temporary extension service node is less than a certain threshold, node reduction is triggered; the server node management script will be called to automatically remove the temporary extension service node from the service node cluster to save server resources; S7: Regular monitoring and adjustment: Regularly monitor the connection requests and the load of the service nodes, adjust the number and capacity of nodes according to actual needs, and ensure efficient operation in different time periods.

2. A dynamic service node management method based on user connection rule analysis according to claim 1, characterized in that: The server dynamically scales the temporary nodes based on the start time of the write peak.

3. A method for dynamic service node management based on user connection rule analysis according to claim 1, characterized in that: The user end establishes a network connection with the server. The connection request first goes to the gateway service. The gateway service obtains the user's previous connection analysis data from the data cache; based on the obtained user connection data, it decides whether to route to a persistent node or a temporary node.

4. A method for dynamic service node management based on user connection rule analysis according to claim 1, characterized in that: Update connection analysis data after the client disconnects.

5. A method for dynamic service node management based on user connection rule analysis according to claim 1, characterized in that: The probability of the user terminal connecting during the peak time period is calculated as follows: the number of times the user terminal has connected during the peak time period in the past divided by the total number of times the user terminal has connected.

6. A method for dynamic service node management based on user connection rule analysis according to claim 1, characterized in that: The user's connection is most likely only used during peak hours with a probability of 70% or more.

7. A method for dynamic service node management based on user connection rule analysis according to claim 1, characterized in that: In step S6, the threshold value is 50-150.

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