A cloud computing-based intelligent gateway management platform

Abstract

The application relates to the gateway management field and discloses an intelligent gateway management platform based on cloud computing, which comprises an interface module, the interface module is connected with multiple gateways, and the data of multiple groups of the gateways is transmitted to a gateway management and control module through the interface module; a security protection module is connected to the interface module; a load balancing and flow management module is connected to the interface module; the load balancing and flow management module monitors and manages the flow in the gateway transmission process; and the load balancing and flow management module is connected with the gateway management and control module. Through the load balancing and flow management module, the flow in the gateway transmission process can be monitored and managed in real time, so that the flow can be reasonably distributed when multiple groups of gateway information are transmitted during the peak period, transmission channels are prevented from being blocked, and the stability and use performance of the system are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of gateway management, in particular to an intelligent gateway management platform based on cloud computing. BACKGROUND

[0002] In today's digital age, S domain as a continuous time (ana l og) representation of signal and system domain, plays a vital role in many fields. The continuous time signal characteristics of S domain makes it irreplaceable in the scene with high real-time and stability requirements. For example, in the field of industrial automation control and intelligent traffic signal control.

[0003] And the existing gateway management platform, usually support multiple network connection mode to realize equipment access, such as through the Ethernet interface to connect various terminal equipment, and establish management platform, at the same time can carry out certain monitoring and management to data flow.

[0004] And considering in the process of peak use, gateway management platform due to receiving multiple different gateway information, and gateway information flow is too large, easy to cause transmission channel to appear the situation of congestion, and lead to gateway management system to appear stop or congestion, serious even lead to system paralysis and collapse, seriously affect the system use performance and user experience. SUMMARY

[0005] In view of the deficiencies of the prior art, the present application provides an intelligent gateway management platform based on cloud computing, which solves the problem that the existing gateway management platform is prone to transmission channel congestion when receiving multiple gateway information and large flow during peak period, and even leads to system stop, congestion, paralysis and collapse, seriously affecting the system use performance and user experience.

[0006] In order to achieve the above object, the present application is realized by the following technical scheme: a kind of intelligent gateway management platform based on cloud computing, including interface module, the interface module is connected with multiple gateways, and the data of multiple groups of gateways is transmitted to gateway management and control module by interface module, security protection module is connected on the interface module, the security protection module is encrypted and protected in the process of gateway information transmission, load balancing and traffic management module are connected on the interface module, the load balancing and traffic management module monitor and manage the traffic in the process of gateway transmission, gateway management and control module are connected on the load balancing and traffic management module, the parameter data from each gateway is received by the gateway management and control module, and management is concentrated by staff, and specific management content includes: gateway device registration and authentication, gateway device state monitoring, gateway device remote control, display control module is connected on the gateway management and control module, the specific value of each gateway is displayed by the display control module, staff is facilitated to watch, simultaneously provides operating platform for staff, intelligent optimization module is connected on the load balancing and traffic management module, the intelligent optimization module reads historical management scheme data in load balancing and traffic management module, and data conclusion is analyzed and optimized according to data.

[0007] Preferably, the load balancing and traffic management module includes a traffic parameter acquisition module, which monitors multiple groups of traffic received and transmitted by the interface module and acquires specific traffic size data, which is transmitted to the scheduling algorithm module, the scheduling algorithm module receives data collected from the traffic parameter acquisition module and calculates according to the data, so as to select a suitable scheduling scheme, the load balancing strategy module is connected on the scheduling algorithm module, the load balancing strategy module records multiple different scheduling and distribution schemes, which are used for the scheduling algorithm module to substitute the conclusion and select the corresponding scheme for execution, the traffic distribution module is connected on the load balancing strategy module, the traffic distribution module reads the finally selected scheme and distributes the traffic according to the contents of the scheme.

[0008] Preferably, the specific calculation formula in the scheduling algorithm module includes: weighted round robin algorithm traffic calculation formula and minimum connection number algorithm traffic calculation formula.

[0009] Preferably, the specific weighted round robin algorithm traffic calculation formula is: Wherein: W i represents the weight value of each device or path, which can be determined according to device performance, bandwidth capacity, historical load factors; T represents total traffic; F i represents the current allocated traffic of device or path; n represents the total number of devices or paths.

[0010] Preferably, the minimum connection number algorithm flow calculation formula is: Wherein: C i Represents the current connection number of each device or path, and represents a very small positive number to prevent the denominator from being 0.

[0011] Preferably, the specific scheduling and allocation scheme in the load balancing strategy module includes a service priority-based allocation scheme and a dynamic adjustment allocation scheme.

[0012] Preferably, the service priority-based allocation scheme is specifically: different services are divided into high, medium and low priority; high-priority services are preferentially provided with sufficient flow guarantee, and 50% of the total flow needs to be allocated, then medium-priority services are allocated 30% of the total flow, and low-priority services are allocated 20% of the total flow; in the same priority service, further flow allocation can be performed according to weighted round robin or other algorithms.

[0013] Preferably, the dynamic adjustment allocation scheme is: continuously monitoring the load condition of the device and the network flow change; when the load of a certain device exceeds a certain threshold (more than 80%), part of the flow of the device is transferred to a device with lower load, and an adjustment coefficient can be set to dynamically adjust the flow allocation according to the load condition.

[0014] Preferably, the intelligent optimization module includes a historical data reading module, the historical data reading module extracts and correspondingly arranges the historical adjustment scheme content and adjustment result, an AI simulation module is connected to the historical data reading module, the AI simulation module simulates the current environment according to the adjustment content, and appropriately changes the scheme content, and tests whether the effect of the optimized adjustment scheme is better than that of the historical scheme, when the optimized scheme content is greater than the historical scheme content, it is determined that the optimized scheme content is effective, and is executed, when the historical scheme content is greater than the optimized scheme content, it is determined that the optimized scheme content is invalid, and the optimized scheme content is adjusted again for secondary AI simulation, an optimization result module is connected to the AI simulation module, the optimization result module transmits the adjusted scheme to the load balancing strategy module to replace the original historical scheme, and the optimization result module is connected with the load balancing strategy module.

[0015] An application of an intelligent gateway management platform based on cloud computing, the intelligent gateway management platform based on cloud computing as claimed in claims 1-9 is applied to the field of gateway management, in particular to the fields of industrial automation control and intelligent traffic management.

[0016] The application provides an intelligent gateway management platform based on cloud computing.

[0017] 1、The present application can monitor and manage the traffic in the gateway transmission process in real time through the load balancing and traffic management module, wherein the traffic parameter acquisition module accurately collects traffic size data, the scheduling algorithm module selects a suitable scheduling scheme according to the weighted round robin algorithm traffic calculation formula and the minimum connection number algorithm traffic calculation formula, the load balancing strategy module provides a distribution scheme and a dynamic adjustment distribution scheme based on service priority, and the traffic distribution module implements specific traffic distribution. This series of measures ensures that the traffic can be reasonably distributed when multiple groups of gateway information are transmitted during peak hours, avoids transmission channel congestion, and improves the stability and use performance of the system.

[0018] 2、The present application extracts historical adjustment scheme content and results for sorting through the historical data reading module, the AI simulation module simulates the current environment and optimizes the scheme, and the optimization result module transmits the optimized scheme to the load balancing strategy module to replace the original historical scheme. This function enables the system to continuously learn and improve, and continuously improve the efficiency and effect of traffic management.

[0019] 3、The present application provides a scientific basis for the reasonable distribution of traffic by setting calculation formulas. The weighted round robin algorithm traffic calculation formula and the minimum connection number algorithm traffic calculation formula can accurately calculate the traffic distribution of each device or path according to different situations, making the traffic distribution more fair and efficient, and combining the distribution scheme and the dynamic adjustment distribution scheme based on service priority, further optimizing the traffic distribution strategy. BRIEF DESCRIPTION OF DRAWINGS

[0020] Figure 1 The system flowchart of the present application;

[0021] Figure 2 The load balancing and traffic management module flowchart of the present application;

[0022] Figure 3 The intelligent optimization module flowchart of the present application. DETAILED DESCRIPTION

[0023] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the specification of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of the present application.

[0024] Embodiment:

[0025] Please refer to the drawings in the specification of the present application Figure 1 - the drawings in the specification of the present application Figure 3The embodiment of the application provides a cloud computing-based intelligent gateway management platform, which comprises an interface module, the interface module is connected with multiple gateways, and data of multiple groups of the gateways is transmitted to a gateway management and control module through the interface module, a security protection module is connected to the interface module, the security protection module encrypts and protects in the process of gateway information transmission, prevents information from being attacked or stolen, guarantees the integrity and safety of data transmission, a load balancing and traffic management module is connected to the interface module, the load balancing and traffic management module monitors and manages the traffic in the gateway transmission process, prevents the system from being paralyzed due to overload or overloading in the peak use stage;

[0026] The load balancing and traffic management module comprises a traffic parameter acquisition module, the traffic parameter acquisition module monitors multiple groups of traffic received and transmitted by the interface module, acquires specific traffic size data, and transmits the specific traffic size data to a scheduling algorithm module, the scheduling algorithm module is connected to the traffic parameter acquisition module, the scheduling algorithm module receives data collected from the traffic parameter acquisition module, and calculates according to the data, so that a suitable scheduling scheme is selected, the reasonable allocation of resources is guaranteed, and the system is prevented from being paralyzed due to overload, the scheduling algorithm module is connected to a load balancing strategy module, the load balancing strategy module records multiple different scheduling and allocation schemes, the scheduling algorithm module substitutes the conclusion into the load balancing strategy module, and a corresponding scheme is selected and executed, the load balancing strategy module is connected to a traffic distribution module, the traffic distribution module reads the finally selected scheme, and distributes the traffic according to the content of the scheme;

[0027] The specific calculation formula in the scheduling algorithm module is as follows:

[0028] I. Weighted round robin algorithm traffic calculation formula:

[0029]

[0030] Wherein: W i represents the weight value of each device or path, the weight can be determined according to the device performance, bandwidth capacity, historical load condition and the like; T represents total traffic; F i represents the current allocated traffic of the device or path; n represents the total number of devices or paths.

[0031] II. Minimum connection number algorithm traffic calculation formula:

[0032]

[0033] Wherein: C i represents the current connection number of each device or path; ∈ represents a very small positive number, preventing the denominator from being 0.

[0034] The above formula is demonstrated by the following embodiment:

[0035] Device performance-based allocation scheme:

[0036] According to the performance indicators such as processing power, memory capacity, network bandwidth of the device, a performance score is set for each device.

[0037] The traffic allocation is proportional to the performance score. For example, the performance score of device A is 80, and the performance score of device B is 60, and the total traffic is 100 Mbps. Then the traffic allocated to device A is The traffic allocated to device B is 100-57.14=42.86 Mbps.

[0038] The specific scheduling and allocation scheme in the load balancing strategy module is:

[0039] I. Allocation scheme based on service priority:

[0040] Different services are divided into high, medium and low priority; high priority services are given priority to obtain sufficient traffic guarantee, which requires 50% of the total traffic, then medium priority services are allocated 30% of the total traffic, and low priority services are allocated 20% of the total traffic; in the same priority service, further traffic allocation can be carried out according to weighted round robin or other algorithms;

[0041] II. Dynamic adjustment allocation scheme:

[0042] The load condition of the device and the change of network traffic are continuously monitored; when the load of a certain device exceeds a certain threshold (more than 80%), part of the traffic of the device is transferred to a device with lower load, and an adjustment coefficient can be set to dynamically adjust the traffic allocation according to the load condition;

[0043] Suppose: the load of device A is 90%, the load of device B is 40%, and the adjustment coefficient is 0.5, then part of the traffic of device A is transferred to device B, and the size of the transferred traffic is

[0044] The load balancing and traffic management module is connected with a gateway management and control module, the gateway management and control module receives parameter data from each gateway, and the parameter data is managed by the staff, the specific management content includes: gateway device registration and authentication, gateway device state monitoring, gateway device remote control, to ensure the normal operation and efficient work of the device, the gateway management and control module is connected with a display control module, the display control module displays the specific values of each gateway, which is convenient for the staff to watch, and provides an operation platform for the staff, which is convenient for the management and control of multiple gateway devices;

[0045] The load balancing and traffic management module is connected with an intelligent optimization module, the intelligent optimization module reads historical management scheme data in the load balancing and traffic management module, and analyzes and optimizes according to data conclusion, the intelligent optimization module comprises a historical data reading module, the historical data reading module extracts and correspondingly arranges historical adjustment scheme content and adjustment results, the historical data reading module is connected with an AI simulation module, the AI simulation module simulates the current environment according to the adjustment content, and appropriately changes the scheme content, tests whether the effect of the optimized adjustment scheme is better than that of the historical scheme, when the optimized scheme content is greater than the historical scheme content, it is determined that the optimized scheme content is effective, and is executed, when the historical scheme content is greater than the optimized scheme content, it is determined that the optimized scheme content is invalid, then the optimized scheme content is adjusted again for secondary AI simulation, the AI simulation module is connected with an optimization result module, the optimization result module transmits the adjusted scheme to the load balancing strategy module to replace the original historical scheme, and the optimization result module is connected with the load balancing strategy module.

[0046] Although embodiments of the present application have been shown and described, it is to be understood that various modifications, substitutions, alternatives and variations can be made to these embodiments without departing from the principles and spirit of the present application, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A cloud computing based intelligent gateway management platform comprising an interface module, characterized in that, The interface module is connected with multiple gateways, and the data of multiple groups of gateways is transmitted to the gateway management and control module through the interface module; the interface module is connected with a security protection module, which encrypts and protects the gateway information during transmission; the interface module is connected with a load balancing and traffic management module, which monitors and manages the traffic during gateway transmission; the load balancing and traffic management module is connected with a gateway management and control module, which receives parameter data from each gateway and manages them through staff; the specific management content includes: gateway device registration and authentication, gateway device state monitoring, and gateway device remote control; the gateway management and control module is connected with a display control module, which displays the specific values of each gateway for staff to view and provides an operation platform for staff; the load balancing and traffic management module is connected with an intelligent optimization module, which reads historical management scheme data in the load balancing and traffic management module and analyzes and optimizes the data conclusions. The load balancing and traffic management module includes a traffic parameter acquisition module, which monitors multiple groups of traffic received and transmitted by the interface module and acquires specific traffic size data, which is transmitted to a scheduling algorithm module; the traffic parameter acquisition module is connected with the scheduling algorithm module, which receives data collected by the traffic parameter acquisition module and calculates according to the data, so as to select appropriate scheduling and distribution schemes; the scheduling algorithm module is connected with a load balancing strategy module, which records multiple different scheduling and distribution schemes, which are used by the scheduling algorithm module to substitute conclusions and select corresponding scheduling and distribution schemes for execution; the load balancing strategy module is connected with a traffic distribution module, which reads the selected scheduling and distribution scheme and allocates traffic according to the content of the scheduling and distribution scheme. The specific calculation formulas in the scheduling algorithm module include: weighted round robin algorithm traffic calculation formula and minimum connection number algorithm traffic calculation formula. Wherein the specific weighted round robin algorithm flow calculation formula: Wherein: W i represents the weight value of each device or path; T represents the total flow; F i represents the current allocated flow of the device or path; n represents the total number of devices or paths; The minimum connection number algorithm flow calculation formula is: Wherein: C i represents the current connection number of each device or path; ∈ represents a very small positive number to prevent the denominator from being 0. 2.The cloud computing-based intelligent gateway management platform of claim 1, wherein, The specific scheduling and distribution schemes in the load balancing strategy module include: service priority-based distribution scheme and dynamic adjustment distribution scheme. 3.The cloud computing-based intelligent gateway management platform of claim 2, wherein, The service priority-based distribution scheme specifically includes: dividing different services into high, medium and low priority levels; allocating 50% of the total traffic to high-priority services, then 30% of the total traffic to medium-priority services, and 20% of the total traffic to low-priority services. 4.The cloud computing-based intelligent gateway management platform according to claim 2, characterized in that, The dynamic adjustment distribution scheme is: continuously monitoring the load of the device and the change of network traffic; when the load of a device exceeds 80%, part of its traffic is transferred to a device with lower load; an adjustment coefficient is set to dynamically adjust the traffic distribution according to the load.

5. The cloud computing based intelligent gateway management platform according to claim 1, wherein, The intelligent optimization module comprises a historical data reading module which extracts and correspondingly arranges historical adjustment scheme contents and adjustment results, and an AI simulation module is connected to the historical data reading module, the AI simulation module simulates the current environment according to the adjustment contents, and appropriately changes the scheme contents, and tests whether the effect of the optimized adjustment scheme is better than that of the historical scheme, when the optimized scheme content is greater than the historical scheme content, it is determined that the optimized scheme content is effective, and is executed, when the historical scheme content is greater than the optimized scheme content, it is determined that the optimized scheme content is invalid, and the optimized scheme content is adjusted again for secondary AI simulation, an optimized result module is connected to the AI simulation module, the optimized result module transmits the adjusted scheme to a load balancing strategy module to replace the original historical scheme, and the optimized result module is connected with the load balancing strategy module.

6. The application of the cloud computing based intelligent gateway management platform as claimed in claim 1-5, wherein, Be applied to the gateway management field.

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