Service access gateway dynamic intelligent selection method and system based on cloud network convergence

Abstract

The invention discloses a dynamic intelligent selection method and system for a service access gateway based on cloud network convergence, and the method comprises the steps: S1, carrying out the performance evaluation of a gateway according to the basic characteristics of the access gateway under a business demand and the real-time performance data of the gateway; s2, based on the performance evaluation result of the gateway, distributing service requirements; and S3, gateway faults are detected, and gateway switching is realized based on a cloud network fusion technology, so that dynamic intelligent selection of the access gateways is realized. According to the invention, the optimal gateway can be selected according to the real-time network condition and gateway performance, so that the reliability of the whole system is improved; dynamic selection can ensure that the flow is distributed to the gateway with the optimal performance, and the overall network performance and response speed can be improved.

Description

Technical Field

[0001] The present invention relates to the field of cloud-network integration technology, and in particular to a method and system for dynamically selecting a service access gateway based on cloud-network integration. Background Art

[0002] Cloud-network integration refers to the combination of cloud computing and network technology to achieve seamless integration of cloud computing and the network. It integrates cloud computing and network resources to achieve resource sharing and unified management. Through cloud computing technology, computing, storage, network and other resources can be virtualized so that they can be flexibly allocated and scheduled.

[0003] However, as cloud computing and network operators merge, the huge user base of operators also leads to high maintenance overhead and poor dynamic adaptability in gateway routing after entering cloud computing. Summary of the invention

[0004] In order to solve the above technical problems, the present invention provides a method for dynamically selecting a service access gateway based on cloud-network integration, the method comprising:

[0005] Step S1: Perform a performance evaluation on the gateway according to the basic characteristics of the access gateway under business requirements and the real-time performance data of the gateway;

[0006] Step S2: Allocate service requirements based on the performance evaluation results of the gateway;

[0007] Step S3: Detect gateway failures and implement gateway switching based on cloud-network integration technology, thereby achieving dynamic intelligent selection of access gateways.

[0008] Optionally, in step S1, the basic characteristics of the access gateway include processing power, latency and cost, and the real-time performance data of the gateway includes response time, throughput, reliability, security, scalability, compatibility and error rate.

[0009] Optionally, in step S1, the process of performing performance evaluation on the gateway specifically includes:

[0010] Step S11: Use several edge devices of cloud-network integration to collect business demand data and real-time performance data of the gateway, and package them into a data packet to be processed, wherein the data packet to be processed includes performance evaluation data, record information and device information;

[0011] Step S12: based on the gateway capacity information, the gateway is expanded or reduced in capacity, the gateway weight is updated according to the gateway capacity information after expansion or reduction, and the performance of the gateway is evaluated based on the gateway weight.

[0012] Optionally, in step S2, the process of allocating service requirements based on the performance evaluation result of the gateway specifically includes:

[0013] Step S21: Based on the performance evaluation of the gateway, a clustered routing algorithm is used to select a gateway;

[0014] Step S22: Based on the selected gateway, the service demand is allocated according to the number of service requests and the gateway throughput.

[0015] Optionally, in step S21, based on the performance evaluation of the gateway, the process of selecting the gateway using the clustering routing algorithm specifically includes:

[0016] Select edge gateway nodes to build a candidate list, and soft-select a node from the candidate list as the cluster head if the distance between the cluster member and the selected cluster head satisfies D(N α ,N β )≥D th ·D th , then add the cluster members of this operation to the candidate list;

[0017] A gateway utility function is constructed based on the candidate list, and a gateway is selected using the gateway utility function.

[0018] The present invention also provides a service access gateway dynamic intelligent selection system based on cloud-network integration, the system comprising: a performance evaluation module, a service allocation module and a gateway intelligent selection module;

[0019] The performance evaluation module is used to evaluate the performance of the gateway according to the basic characteristics of the access gateway under business requirements and the real-time performance data of the gateway;

[0020] The service allocation module is used to allocate service requirements based on the performance evaluation results of the gateway;

[0021] The gateway intelligent selection module is used to detect gateway failures and implement gateway switching based on cloud-network integration technology, thereby achieving dynamic intelligent selection of access gateways.

[0022] Optionally, the performance evaluation module includes a data packet collection submodule and a weight evaluation submodule;

[0023] The data packet collection submodule is used to collect business demand data and real-time performance data of the gateway using several edge devices of cloud-network integration, and pack them into data packets to be processed, wherein the data packets to be processed include performance evaluation data, record information and device information;

[0024] The weight evaluation submodule is used to expand or reduce the capacity of the gateway based on the gateway capacity information, update the weight of the gateway according to the capacity information of the gateway after expansion or reduction, and evaluate the performance of the gateway based on the weight of the gateway.

[0025] Optionally, the service allocation module includes a gateway selection submodule and a demand allocation submodule;

[0026] The gateway selection submodule is used to select a gateway based on the performance evaluation of the gateway using a clustered routing algorithm;

[0027] The demand allocation submodule is used to allocate service demands based on the selected gateway, the number of service requests and the gateway throughput.

[0028] Compared with the prior art, the present invention has the following beneficial effects:

[0029] The present invention can select the best gateway according to the real-time network status and gateway performance, thereby improving the reliability of the entire system; dynamic selection can ensure that traffic is distributed to the gateway with the best performance, which can improve the overall network performance and response speed. The dynamic selection mechanism of the present invention can achieve more intelligent load balancing and avoid the situation where some gateways are overloaded while other gateways are idle. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solution of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0031] Figure 1 This is a method step diagram of a method for dynamically selecting an access gateway according to an embodiment of the present invention. DETAILED DESCRIPTION

[0032] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0033] Embodiment 1

[0034] A method for dynamically selecting a service access gateway based on cloud-network integration, such as Figure 1 As shown, the method includes:

[0035] Step S1: Perform a performance evaluation on the gateway according to the basic characteristics of the access gateway under business requirements and the real-time performance data of the gateway.

[0036] The basic characteristics of the access gateway include processing power, latency and cost, and the real-time performance data of the gateway includes response time, throughput, reliability, security, scalability, compatibility and error rate.

[0037] The process of evaluating the performance of a gateway includes:

[0038] Step S11, using several edge devices of cloud-network integration to collect business demand data and real-time performance data of the gateway, and packing them into data packets to be processed, wherein the data packets to be processed include performance evaluation data, record information and device information; in this embodiment, the record information includes edge device location information, collection time and collection data type, as well as the size of the collected data and the size of the packaged data packet. Device information router information, sensor information, etc. The edge devices used may include routers, routing switches, hubs, smart sensors, programmable logic controllers, edge smart routers, ICT fusion gateways, etc.

[0039] In order to prevent the increase of edge devices from increasing the amount of calculation and affecting the data processing effect, the data packets to be processed are analyzed before evaluation to determine the preferred values ​​in the data packets to be processed.

[0040] In the process of prioritizing the data to be sent, several delicate steps are required to ensure an efficient and secure data transmission strategy. First, through in-depth analysis of the recorded information, we can accurately assign priority weights to each data type. The specific operations are as follows: 1. Type frequency calculation: According to the data type label, count each of the collected records one by one to quantify the frequency of each type of data being collected, so as to obtain the activity level of each type of data, that is, the type frequency. 2. Data type total volume evaluation: For each category of data, the size of all its instances is summarized to form the total volume of the type of data, providing a quantitative basis for data importance evaluation. 3. Logical relationship combing: Deeply explore the data association identifiers in the records to reveal the interaction patterns between different types of data. Whether it is a dependent chain or a mutually exclusive constraint, it can be clearly identified and recorded at this stage. 4. Priority value calculation: Taking into account the above-mentioned type frequency, total data volume and logical relationship, an advanced algorithm model is used to quantify the priority of each data type as the basis for data packet scheduling. This calculation is not only scientific, but also highly adaptable to different task requirements. 5. Data packet correlation analysis: In view of the complexity of the data sending task, it is also necessary to examine the internal connection between the data packets to be sent. With the help of interactive information or task identification between edge devices, data packets are reasonably classified and split to enhance the pertinence and efficiency of data processing. 6. Density analysis and security considerations: In order to prevent the potential security risks caused by the concentrated transmission of data from adjacent edge devices in a single period of time, we introduce a density analysis mechanism. By setting multiple concentric circles and dividing lines, the monitoring area is divided and the density of its data transmission is calculated. The data sending plan is adjusted accordingly to strive for a uniform and secure distribution of data flows. The implementation of this series of strategies not only improves the accuracy of data processing priority sorting, but also strengthens the security and efficiency of data transmission, providing solid support for complex edge computing environments.

[0041] Step S12: Based on the gateway capacity information, the gateway is expanded or reduced, the gateway weight is updated according to the gateway capacity information after expansion or reduction, and the gateway performance is evaluated based on the gateway weight. Combining the time window graph model and the penalty local structure entropy improved algorithm model, the gateway node activity weight and degree contribution weight are introduced to determine the comprehensive weight of the gateway node, and finally the importance of each gateway node is obtained. The gateway performance is evaluated according to the importance result of the gateway node.

[0042] Step S2, allocating service requirements based on the performance evaluation results of the gateway, specifically including: step S21, selecting a gateway based on the performance evaluation of the gateway using a clustering routing algorithm; step S22, allocating service requirements based on the selected gateway according to the number of service requests and gateway throughput.

[0043] Step S21 specifically includes: selecting edge gateway nodes to construct a candidate list, softly selecting a node from the candidate list as a cluster head, and if the distance between the cluster member and the selected cluster head satisfies D(N α ,N β )≥D th ·D th , then add the cluster members of this operation to the candidate list; construct a gateway utility function based on the candidate list, and use the gateway utility function to select a gateway:

[0044]

[0045] in,

[0046] Step S3: Detect gateway failures and implement gateway switching based on cloud-network integration technology, thereby achieving dynamic intelligent selection of access gateways.

[0047] To ensure the high availability and stability of the virtual gateway service, monitor the status of the current virtual gateway node. This process involves the following key steps: 1. Comprehensively detect the health of the virtual gateway node, which covers the integrity check at the hardware level to eliminate physical problems such as hard disk failure and memory damage; at the software level, monitor whether the program runs normally and whether there are abnormal exits or crashes; at the system level, pay attention to the overall operation status to ensure that there are no abnormal log records to avoid system-level errors. 2. Pay close attention to the bandwidth usage of the node. Once the bandwidth load exceeds the preset safety threshold, trigger an alarm immediately. At the same time, monitor resource usage, including CPU and memory usage. If any indicator exceeds the set upper limit, the node is considered to be in a state of pressure overload. 3. Once any of the above-mentioned unhealthy states is detected, the system will respond quickly and remove the faulty node from the virtual gateway cluster to isolate potential risks. This measure can effectively prevent the spread of problems in individual nodes, ensure that the remaining nodes in the cluster can seamlessly take over business traffic, and maintain service continuity. 4. After the node is removed, the load balancing mechanism in the cluster will automatically adjust and redistribute business flows to healthy nodes to ensure that data transmission is not affected and users do not perceive any interruption.

[0048] The platform sends the network configuration of the primary link to the primary edge computing gateway. After confirming that the primary gateway has successfully received and applied the configuration, the platform further sends the configuration of the network quality monitoring of the primary link. Based on these monitoring configurations, the primary edge computing gateway collects the link network quality information in real time and reports the data to the cloud through the MQTT protocol. Subsequently, after receiving the feedback that the backup link configuration is successful, the cloud edge computing gateway management platform sends the backup link network quality monitoring configuration to the backup gateway. The backup edge computing gateway receives and applies these configurations, and also monitors and reports the link network quality information in real time. When the cloud edge computing gateway management platform detects that the backup link has been successfully created and is running stably, it sends the configuration information of the primary and backup link switching to the primary edge computing gateway. The primary edge computing gateway receives and applies these switching configurations to ensure that it can seamlessly switch to the backup link when necessary, and successfully feeds back the switching results to the cloud edge computing gateway management platform. The entire process reflects the efficiency and automation capabilities of the cloud edge computing gateway management platform, ensuring the high availability and stability of the network. In this way, users can easily monitor and manage edge computing gateways while ensuring business continuity and data transmission reliability.

[0049] Embodiment 2

[0050] A service access gateway dynamic intelligent selection system based on cloud-network integration, the system comprising: a performance evaluation module, a service allocation module and a gateway intelligent selection module;

[0051] The performance evaluation module is used to evaluate the performance of the gateway according to the basic characteristics of the access gateway under business requirements and the real-time performance data of the gateway. The performance evaluation module includes a data packet collection submodule and a weight evaluation submodule; the data packet collection submodule is used to use several edge devices of cloud network integration to collect business demand data and real-time performance data of the gateway, and package them into data packets to be processed, and the data packets to be processed include performance evaluation data, record information and device information; the weight evaluation submodule is used to expand or reduce the capacity of the gateway based on the gateway capacity information, update the weight of the gateway according to the gateway capacity information after expansion or reduction, and evaluate the performance of the gateway based on the gateway weight.

[0052] In this embodiment, the recorded information includes edge device location information, the time of collection, the type of data collected, the size of the collected data, and the size of the packaged data packet. Device information router information, sensor information, etc. The edge devices used may include routers, routing switches, hubs, smart sensors, programmable logic controllers, edge smart routers, ICT fusion gateways, etc.

[0053] In order to prevent the increase of edge devices from increasing the amount of calculation and affecting the data processing effect, the data packets to be processed are analyzed before evaluation to determine the preferred values ​​in the data packets to be processed. Combining the time window graph model and the penalty local structure entropy improved algorithm model, the gateway node activity weight and degree contribution weight are introduced to determine the comprehensive weight of the gateway node, and finally the importance of each gateway node is obtained. The gateway performance is evaluated according to the importance results of the gateway node.

[0054] The service allocation module is used to allocate service requirements based on the performance evaluation results of the gateway. The service allocation module includes a gateway selection submodule and a demand allocation submodule; the gateway selection submodule is used to select a gateway based on the performance evaluation of the gateway using a clustered routing algorithm; the demand allocation submodule is used to allocate service requirements based on the selected gateway according to the number of service requests and gateway throughput.

[0055] The gateway intelligent selection module is used to detect gateway failures and implement gateway switching based on cloud-network integration technology, thereby achieving dynamic intelligent selection of access gateways.

[0056] To ensure the high availability and stability of the virtual gateway service, monitor the status of the current virtual gateway node. This process involves the following key steps: 1. Comprehensively detect the health of the virtual gateway node, which covers the integrity check at the hardware level to eliminate physical problems such as hard disk failure and memory damage; at the software level, monitor whether the program runs normally and whether there are abnormal exits or crashes; at the system level, pay attention to the overall operation status to ensure that there are no abnormal log records to avoid system-level errors. 2. Pay close attention to the bandwidth usage of the node. Once the bandwidth load exceeds the preset safety threshold, trigger an alarm immediately. At the same time, monitor resource usage, including CPU and memory usage. If any indicator exceeds the set upper limit, the node is considered to be in a state of pressure overload. 3. Once any of the above-mentioned unhealthy states is detected, the system will respond quickly and remove the faulty node from the virtual gateway cluster to isolate potential risks. This measure can effectively prevent the spread of problems in individual nodes, ensure that the remaining nodes in the cluster can seamlessly take over business traffic, and maintain service continuity. 4. After the node is removed, the load balancing mechanism in the cluster will automatically adjust and redistribute business flows to healthy nodes to ensure that data transmission is not affected and users do not perceive any interruption.

[0057] The platform sends the network configuration of the primary link to the primary edge computing gateway. After confirming that the primary gateway has successfully received and applied the configuration, the platform further sends the configuration of the network quality monitoring of the primary link. Based on these monitoring configurations, the primary edge computing gateway collects the link network quality information in real time and reports the data to the cloud through the MQTT protocol. Subsequently, after receiving the feedback that the backup link configuration is successful, the cloud edge computing gateway management platform sends the backup link network quality monitoring configuration to the backup gateway. The backup edge computing gateway receives and applies these configurations, and also monitors and reports the link network quality information in real time. When the cloud edge computing gateway management platform detects that the backup link has been successfully created and is running stably, it sends the configuration information of the primary and backup link switching to the primary edge computing gateway. The primary edge computing gateway receives and applies these switching configurations to ensure that it can seamlessly switch to the backup link when necessary, and successfully feeds back the switching results to the cloud edge computing gateway management platform. The entire process reflects the efficiency and automation capabilities of the cloud edge computing gateway management platform, ensuring the high availability and stability of the network. In this way, users can easily monitor and manage edge computing gateways while ensuring business continuity and data transmission reliability.

[0058] The embodiments described above are only descriptions of the preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. A method for dynamic intelligent selection of service access gateways based on cloud-network integration. It is characterized in that The method comprises: Step S1: Perform a performance evaluation on the gateway according to the basic characteristics of the access gateway under business requirements and the real-time performance data of the gateway; Step S2: Allocate service requirements based on the performance evaluation results of the gateway; Step S3: Detect gateway failures and implement gateway switching based on cloud-network integration technology, thereby achieving dynamic intelligent selection of access gateways.

2. According to claim 1, the method for dynamically selecting a service access gateway based on cloud-network integration, It is characterized in that In step S1, the basic characteristics of the access gateway include processing capacity, delay and cost, and the real-time performance data of the gateway includes response time, throughput, reliability, security, scalability, compatibility and error rate.

3. According to claim 2, the method for dynamically selecting a service access gateway based on cloud-network integration, It is characterized in that In step S1, the process of performing performance evaluation on the gateway specifically includes: Step S11: Use several edge devices of cloud-network integration to collect business demand data and real-time performance data of the gateway, and package them into a data packet to be processed, wherein the data packet to be processed includes performance evaluation data, record information and device information; Step S12: based on the gateway capacity information, the gateway is expanded or reduced in capacity, the gateway weight is updated according to the gateway capacity information after expansion or reduction, and the performance of the gateway is evaluated based on the gateway weight.

4. According to claim 1, the method for dynamically selecting a service access gateway based on cloud-network integration, It is characterized in that In step S2, the process of allocating service requirements based on the performance evaluation result of the gateway specifically includes: Step S21: Based on the performance evaluation of the gateway, a clustered routing algorithm is used to select a gateway; Step S22: Based on the selected gateway, the service demand is allocated according to the number of service requests and the gateway throughput.

5. According to claim 4, the method for dynamically selecting a service access gateway based on cloud-network integration, It is characterized in that In step S21, based on the performance evaluation of the gateway, the process of selecting the gateway using the clustering routing algorithm specifically includes: Select edge gateway nodes to build a candidate list, and soft-select a node from the candidate list as the cluster head if the distance between the cluster member and the selected cluster head satisfies D(N α ,N β )≥D th ·D th , then add the cluster members of this operation to the candidate list; A gateway utility function is constructed based on the candidate list, and a gateway is selected using the gateway utility function.

6. A service access gateway dynamic intelligent selection system based on cloud-network integration, the gateway dynamic intelligent selection system is used to implement the data transmission method according to any one of claims 1 to 5, It is characterized in that The system includes: performance evaluation module, service allocation module and gateway intelligent selection module; The performance evaluation module is used to evaluate the performance of the gateway according to the basic characteristics of the access gateway under business requirements and the real-time performance data of the gateway; The service allocation module is used to allocate service requirements based on the performance evaluation results of the gateway; The gateway intelligent selection module is used to detect gateway failures and implement gateway switching based on cloud-network integration technology, thereby achieving dynamic intelligent selection of access gateways.

7. The service access gateway dynamic intelligent selection system based on cloud-network integration according to claim 6, It is characterized in that The performance evaluation module includes a data packet collection submodule and a weight evaluation submodule; The data packet collection submodule is used to collect business demand data and real-time performance data of the gateway using several edge devices of cloud-network integration, and pack them into data packets to be processed, wherein the data packets to be processed include performance evaluation data, record information and device information; The weight evaluation submodule is used to expand or reduce the capacity of the gateway based on the gateway capacity information, update the weight of the gateway according to the capacity information of the gateway after expansion or reduction, and evaluate the performance of the gateway based on the weight of the gateway.

8. The service access gateway dynamic intelligent selection system based on cloud-network integration according to claim 6, It is characterized in that The service allocation module includes a gateway selection submodule and a demand allocation submodule; The gateway selection submodule is used to select a gateway based on the performance evaluation of the gateway using a clustered routing algorithm; The demand allocation submodule is used to allocate service demands based on the selected gateway, the number of service requests and the gateway throughput.

Images