CN117938934A

CN117938934A - Cloud access point determining method and device and electronic equipment

Info

Publication number: CN117938934A
Application number: CN202410138180.3A
Authority: CN
Inventors: 张照; 林蔡宗
Original assignee: Hillstone Networks Co Ltd
Current assignee: Hillstone Networks Co Ltd
Priority date: 2024-01-31
Filing date: 2024-01-31
Publication date: 2024-04-26

Abstract

The application discloses a cloud access point determining method and device and electronic equipment. Wherein the method comprises the following steps: acquiring historical access behaviors of a user to M application services by using a terminal, wherein M is an integer greater than 1; determining the access probability of the terminal to each of the M application services based on the historical access behaviors; determining a target application service from M application services according to the access probability of each application service; according to network performance data corresponding to each cloud access point in the N cloud access points when the terminal accesses the target application service, determining the target cloud access point from the N cloud access points, wherein N is a positive integer, and the target cloud access point is used for establishing connection with the terminal. The method and the device solve the technical problem of poor selection accuracy in the prior art when the cloud access point is selected.

Description

Cloud access point determining method and device and electronic equipment

Technical Field

The application relates to the technical field of cloud computing, in particular to a method and a device for determining a cloud access point and electronic equipment.

Background

With the rapid development of internet technology and cloud computing technology, more and more enterprises choose to migrate application resources and data resources of the enterprises to the cloud, so that the dependence of users and technicians on original data centers in the enterprises is reduced. In addition, current enterprise networks need to transition from an old centralized architecture mode to a more flexible distributed architecture mode because of the increasing number of people in mobile offices in modern digital enterprises, resulting in traffic within the enterprise coming from different regions and being used to access resources in different regions.

In the prior art, when a user needs to access a certain application resource through the cloud, the cloud access points are allocated to the user according to the geographic position of the device for providing the application resource, but the selection mode of the cloud access points cannot accurately reflect the actual requirements of the user, so that the cloud access points allocated to the user are not the best cloud access points for accessing the application resource, and further the technical problem of low selection accuracy in the prior art is caused.

In view of the above problems, no effective solution has been proposed at present.

Disclosure of Invention

The application provides a method and a device for determining a cloud access point and electronic equipment, and aims to at least solve the technical problem of poor selection accuracy in the prior art when the cloud access point is selected.

According to one aspect of the present application, there is provided a method for determining a cloud access point, including: acquiring historical access behaviors of a user to M application services by using a terminal, wherein M is an integer greater than 1; determining the access probability of the terminal to each of the M application services based on the historical access behaviors; determining a target application service from M application services according to the access probability of each application service; according to network performance data corresponding to each cloud access point in the N cloud access points when the terminal accesses the target application service, determining the target cloud access point from the N cloud access points, wherein N is a positive integer, and the target cloud access point is used for establishing connection with the terminal.

Optionally, the method for determining the cloud access point further includes: acquiring N access paths corresponding to the target application service accessed by the terminal, wherein different access paths in the N access paths correspond to different cloud access points in the N cloud access points; detecting network performance data corresponding to the terminal when the terminal accesses the target application service through each access path; and taking the network performance data corresponding to the terminal when accessing the target application service through the nth access path as the network performance data corresponding to the cloud access point of the nth access path, wherein N is a positive integer less than or equal to N.

Optionally, the method for determining the cloud access point further includes: determining access statistical data of a user to each of the M application services in a historical time period through a terminal according to the historical access behaviors, wherein the access statistical data at least comprises access times and/or access flow in the historical time period; and determining the access probability of the terminal to each application service in the M application services according to the access statistical data.

Optionally, the method for determining the cloud access point further includes: determining the access times of the terminal to each of the M application services in the historical time period from the access statistical data; summing up and calculating the access times of each application service in M application services in a historical time period by the terminal to obtain a calculation result; and calculating the ratio of the access times of the terminal to each application service to the calculation result to obtain the access probability of the terminal to each application service in the M application services.

Optionally, the method for determining the cloud access point further includes: dividing the time period into a plurality of time intervals; determining the access times of a user to each application service in M application services in each time interval of a plurality of time intervals through a terminal according to the access times in the access statistical data; taking the time interval in which the current moment is located as a target time interval; and determining the access probability of the terminal to each application service in the M application services according to the access times of the user to each application service in the target time interval through the terminal.

Optionally, the method for determining the cloud access point further includes: when the number of the target application services is X, acquiring network performance data corresponding to the situation that each cloud access point is accessed by a terminal to access each target application service, wherein X is a positive integer; according to network performance data corresponding to each cloud access point when the terminal accesses each target application service, N data sets are established, wherein each data set in the N data sets corresponds to one cloud access point in the N cloud access points, and each data set comprises X network performance data corresponding to X target application services after the terminal accesses the cloud access point corresponding to the data set; according to the access probability of the terminal to each target application service in the X target application services, carrying out weighted calculation on X network performance data in each data set to obtain a weighted calculation result corresponding to each data set, wherein the weight corresponding to each network performance data in the X network performance data is determined by the access probability of the target application service corresponding to the network performance data; and determining a target cloud access point from the N cloud access points according to the weighted calculation result corresponding to each data set.

Optionally, the method for determining the cloud access point further includes: under the condition that the network performance data is the first type data, taking the data set with the smallest weighted calculation result in the N data sets as a target data set, wherein the larger the value of the first type data is, the worse the network performance is represented; and taking the cloud access point corresponding to the target data set as a target cloud access point.

Optionally, the method for determining the cloud access point further includes: taking an application service with the access probability larger than a preset probability in the M application services as a target application service; or in the sequence of the access probability of the M application services from large to small, taking the application service arranged in the preset position before as the target application service.

According to another aspect of the present application, there is also provided a device for determining a cloud access point, including: the first acquisition unit is used for acquiring historical access behaviors of a user to M application services by using a terminal, wherein M is an integer greater than 1; a first determining unit configured to determine an access probability of the terminal to each of the M application services based on the historical access behavior; a second determining unit configured to determine a target application service from the M application services according to an access probability of each application service; the third determining unit is configured to determine, from the N cloud access points, a target cloud access point according to network performance data corresponding to when the terminal accesses the target application service by respectively accessing each of the N cloud access points, where N is a positive integer, and the target cloud access point is configured to establish connection with the terminal.

According to another aspect of the present application, there is further provided a computer readable storage medium, where a computer program is stored in the computer readable storage medium, and when the computer program runs, a device where the computer readable storage medium is located is controlled to execute the method for determining a cloud access point according to any one of the above.

According to another aspect of the present application, there is also provided an electronic device, where the electronic device includes one or more processors and a memory, and the memory is configured to store one or more programs, and when the one or more programs are executed by the one or more processors, cause the one or more processors to implement the method for determining a cloud access point of any of the above.

According to the method, firstly, historical access behaviors of a user to M application services are obtained, then, the access probability of the terminal to each application service in the M application services is determined based on the historical access behaviors, then, a target application service is determined from the M application services according to the access probability of each application service, finally, network performance data corresponding to the situation that each cloud access point in N cloud access points accesses the target application service respectively are accessed according to the terminal, and a target cloud access point is determined from the N cloud access points, wherein N is a positive integer, and the target cloud access point is used for establishing connection with the terminal.

According to the method and the system, before the target cloud access point is selected and allocated for the user, the historical access behaviors corresponding to the user are analyzed from two dimensions of the user behavior information and the network performance information, the target application service is determined according to the access probability of the user corresponding to each application service obtained through analysis, then the network performance data corresponding to the target application service accessed by the user through accessing each cloud access point is obtained, the purpose of automatically selecting and allocating one cloud access point for the user from N cloud access points according to the user behavior information and the network performance information is achieved, the selection accuracy of selecting the cloud access point for the user is improved, access of the application service by the terminal is facilitated to be achieved through an optimal access path, the access duration is shortened, and the user experience is improved.

Therefore, the technical scheme of the application achieves the aim of determining the cloud access point corresponding to the user according to the network performance data between different cloud access points and the user terminal and the historical access behaviors of the user, thereby realizing the technical effect of improving the selection accuracy of selecting the cloud access point for the user, and further solving the technical problem of poor selection accuracy in the prior art when selecting the cloud access point.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:

FIG. 1 is a flow chart of an alternative method of determining a cloud access point according to an embodiment of the present application;

FIG. 2 is a schematic illustration of an alternative user accessing a target application service according to an embodiment of the present application;

FIG. 3 is a schematic diagram of an alternative set of data generated during user access to a target application service in accordance with an embodiment of the present application;

FIG. 4 is a flow chart of an alternative method of determining cloud access points at different stages according to an embodiment of the present application;

fig. 5 is a schematic diagram of an optional determining device of a cloud access point according to an embodiment of the present application;

fig. 6 is a schematic diagram of an alternative electronic device according to an embodiment of the application.

Detailed Description

In order that those skilled in the art will better understand the present application, a technical solution in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present application without making any inventive effort, shall fall within the scope of the present application.

It should be noted that the terms "first," "second," and the like in the description and the claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

It should be further noted that, the related information (including the historical access behavior information corresponding to the user) and the data (including, but not limited to, the data for presentation and the analyzed data) related to the present application are both information and data authorized by the user or sufficiently authorized by each party. For example, an interface is provided between the system and the relevant user or institution, before acquiring the relevant information, the system needs to send an acquisition request to the user or institution through the interface, and acquire the relevant information after receiving the consent information fed back by the user or institution.

In some embodiments, a SASE (Secure ACCESS SERVICE EDGE ) device embodiment is provided. SASE is an emerging network and security product for achieving the goal of better meeting modern enterprise network requirements by fusing network connectivity with cloud security services.

Optionally, the SASE product includes a plurality of cloud access points, and a terminal can automatically select one cloud access point to access to the SASE server, so as to achieve the purpose of safely accessing the private application, the internet and the SaaS (Software application AS A SERVICE).

Optionally, for a plurality of cloud access points in the SASE product, determining the cloud access point allocated to the user mainly according to the geographic location of the server where the target application service is located. However, the current connection mode can ensure the basic connection between the user and the access terminal, but the selection mode ignores the connection condition between the cloud access point and the user access terminal and does not analyze the historical behavior information of the user, so the cloud access point allocated to the user by the current selection mode may not be the optimal cloud access point.

In some embodiments, a cloud access point determination method embodiment is provided, and it should be noted that the steps illustrated in the flowchart of the figures may be performed in a computer system, such as a set of computer executable instructions, and that although a logical order is illustrated in the flowchart, in some cases, the steps illustrated or described may be performed in an order other than that illustrated herein.

The application provides a method for determining a cloud access point, an execution subject of the method can be a terminal or network equipment, and the terminal can be: electronic devices such as tablet computers, smart phones, notebook computers, palm computers or Mobile Internet Devices (MIDs), or may be clients in the electronic devices; the network devices may include, but are not limited to: an access service device (e.g., an access controller (Access Controller, AC)), a gateway server, or a network security device (e.g., a Secure Access Service Edge (SASE) device) connected to a cloud access point, etc., although embodiments of the application are not limited in this respect.

Fig. 1 is a flowchart of an alternative method for determining a cloud access point according to an embodiment of the present application, as shown in fig. 1, the method includes the following steps:

step S101, acquiring historical access behaviors of a user to M application services by using a terminal, wherein M is an integer greater than 1.

In some examples, historical access behavior of a user to M application services using an access client installed on a terminal may be obtained, but embodiments of the application are not limited thereto.

In some examples, the access client may be a VPN (Virtual Private Network ) client, for example, the access client may be an IPSec (Internet Protocol Security, internet security protocol) VPN client, and further, the access client may be a SSL (Secure Socket Layer) secure sockets layer) VPN client.

For example, after a terminal (i.e., a user terminal) and a server providing an application service access a network by using an access client and a cloud access point, data transmission is implemented through a tunnel between the access client and the cloud access point. The access client can be used for enabling the terminal to access the network, and the cloud access point can be used for enabling the server to access the network.

In some examples, the application service may include, but is not limited to, one of the following: instant messaging services, gaming application services, video application services, music application services, map application services, and the like.

In some examples, the application service may include an application service resource.

In some examples, the terminal may access a certain application service via HTTP protocol (Hyper Text Transfer Protocol ) or HTTPs (Hyper Text Transfer Protocol over Secure Socket Layer, hypertext transfer security protocol), thereby generating historical access behaviors for the application service.

Alternatively, a historical access behavior generated by the user accessing the M application services by using the terminal in the historical time period may be collected, for example, in the case of a user working remotely, the server providing the application service C needs to be accessed, and the geographic location of the server where the application service C is located may be in the same area as the geographic location of the cloud access point 1, where the user's historical access behavior record generated by the user accessing the application service C in the historical time period (for example, the last month) is queried by using the terminal (i.e., accessing the controller) and the historical access behavior corresponding to the user is determined according to the user behavior record collected by the controller.

In addition, it should be noted that the above-mentioned historical time period may be set in a customized manner, for example, a day, a week, a month or a quarter, etc., and the specific selection of the historical time period is not particularly limited in the present application, and may be selected according to actual needs when the present application is implemented.

Step S102, determining the access probability of the terminal to each of the M application services based on the historical access behaviors.

In some examples, access statistics for each application service over a historical period of time may be determined based on historical access behavior, and a probability of access for each application service is determined based on the access statistics.

In some examples, the access statistics for each application service may include, but are not limited to, at least one of: the number of accesses to the application service in the history period, the access traffic, the access time at a single access, the access duration at each access.

Optionally, the probability of the user accessing each of the M application services is determined based on the access statistics corresponding to the application service by the user through the terminal over the historical time period.

And step S103, determining a target application service from M application services according to the access probability of each application service.

In some examples, the determining system takes an application service with the largest access probability or an application service with the access probability greater than a preset probability of the M application services as the target application service by analyzing the access probability of the user for each of the M application services.

Step S104, determining a target cloud access point from the N cloud access points according to network performance data corresponding to the situation that each of the N cloud access points is accessed by the terminal to access the target application service, wherein N is a positive integer, and the target cloud access point is used for establishing connection with the terminal.

Optionally, before determining the cloud access point to be allocated for the terminal of the user, detecting N links formed by the servers where each cloud access point in the N cloud access points accesses the target application service to obtain an optimal link, where the user accesses the target application service through the cloud access point, and the links corresponding to the target application service at least include the terminal, the cloud access point and the server where the target application service is located, where the optimal link is a link with the minimum network resource overhead or the shortest communication time in the N links, and then the user accesses the target application service by selecting the obtained optimal link, thereby improving the user experience of the user accessing the target application service.

In some examples, if the determined target cloud access points are multiple, one target cloud access point may be randomly selected as the target cloud access point to be connected with the terminal of the user.

It should be noted that, the network performance data corresponding to each cloud access point when accessing the target application service may be network performance data corresponding to the entire access path corresponding to each cloud access point when accessing the target application service, for example, the network performance data may include: all time consumption corresponding to the whole access path, and/or the whole network packet loss rate corresponding to the whole access path, etc.

Optionally, in the embodiment of the present application, the target cloud access point may be determined from the N cloud access points according to the partial network performance data corresponding to the target application service accessed by each cloud access point, for example, the target cloud access point may be determined from the N cloud access points according to the network performance data corresponding to the path from the terminal to the cloud access point. However, in order to ensure that the finally selected target cloud access point is the cloud access point with the best network performance data, preferably, the target cloud access point may be determined from the N cloud access points according to the network performance data corresponding to the entire access path corresponding to each cloud access point when each cloud access point accesses the target application service.

It should be noted that if the cloud access point is selected only depending on network performance indexes (such as jitter, delay and packet loss rate), the actual needs of the user cannot be accurately reflected, so the embodiment of the application proposes a method for comprehensively determining the scheme of the target cloud access point corresponding to the user by combining the acquired network performance data between different cloud access points and the user access terminal and the historical access behaviors of the user, thereby achieving the purpose of matching the cloud access point which takes the actual needs of the user and the network performance data into consideration for the user, realizing the technical effect of improving the selection accuracy of the cloud access point, and further solving the technical problem of poor selection accuracy when the cloud access point is selected in the prior art.

In an optional embodiment, N access paths corresponding to access to a target application service through a terminal are first obtained, wherein different access paths in the N access paths include different cloud access points in N cloud access points, then network performance data corresponding to the terminal when accessing to the target application service through each access path is detected, and then the network performance data corresponding to the terminal when accessing to the target application service through the nth access path is taken as the network performance data corresponding to the cloud access points in the access paths, where N is a positive integer less than or equal to N.

Optionally, the network performance data at least includes connection time, communication packet loss rate, network jitter frequency and communication delay time in the connection process of the terminal, the cloud access point and the target application service, and by taking the network performance data as a reference factor for selecting the cloud access point, the problem that in the prior art, the network communication performance of the cloud access point allocated to the user terminal is poor due to the fact that connection information between the cloud access point and the target application service is ignored is solved.

In an alternative embodiment, access statistics of the user to each of the M application services in the historical time period are determined according to the historical access behaviors, wherein the access statistics at least comprise access times and/or access traffic in the historical time period, and then the access probability of the terminal to each of the M application services is determined according to the access statistics.

Alternatively, the above-mentioned history period may be set by user, for example, one day, one week, one month, one quarter, etc., and the present application is not particularly limited with respect to the specific selection of the history period. In addition, the access statistics include at least the number of accesses, the access flow rate, and the access time, and may also include other statistics that may be used to evaluate the calculated access frequency.

In an alternative embodiment, the number of times of access of the user to each of the M application services in the historical time period is determined from the access statistics data, then the number of times of access of the terminal to each of the M application services in the historical time period is summed up and calculated to obtain a calculation result, and then the ratio of the number of times of access of the terminal to each of the application services to the calculation result is calculated to obtain the probability of access of the terminal to each of the M application services.

For example, firstly, the historical access behavior corresponding to the user during the last month is obtained, the number of times of access to the application service A by the user through the terminal during the last month is 150 times according to the historical access behavior, the number of times of access to the application service B by the terminal is 250 times, and then the probability of access to the application service A by the user is The probability of user access to application service B is/>

In an alternative embodiment, the time period may be further divided into a plurality of time intervals, after that, the number of accesses to each of the M application services by the user through the terminal in each of the plurality of time intervals is determined according to the number of accesses and the access time in the access statistics data, then the time interval in which the current moment is located is taken as the target time interval, and finally, the probability of access to each of the M application services by the terminal is determined according to the number of accesses to each of the application services by the user through the terminal in the target time interval.

For example, the above time period is equal to 24 hours, the 24 hours are divided into 24 time intervals, each time interval is equal to 1 hour, and then the number of times of access to the application service a and the application service B by the user during each time interval during the last 24 hours is counted. Thus, the number of accesses to the application service a by the user is 10 times in the time interval corresponding to 8 to 9 yesterday, the number of accesses to the application service B is 15 times in the time interval corresponding to 13 to 14 yesterday, the number of accesses to the application service a by the user is 15 times, the number of accesses to the application service B is 10 times, and the user does not access the application service in the remaining 22 time intervals.

Optionally, assuming that the current time is 8:30, the user logs in the terminal at the moment, and then the access probability of the user to the application service A is determined to beThe probability of user access to application service B is/>

It should be noted that, assuming that the current time is 13:30, when the user logs in the terminal, the probability of accessing the application service a by the user is determined asThe probability of user access to application service B is

Therefore, the method and the system divide the time period into a plurality of time intervals, and respectively count the access times of the user to each application service in the M application services in each time interval, so that the accuracy of predicting and determining the application service (namely the target application service) which the user tries to access is further improved, and the selection accuracy of the subsequent cloud access point is further improved. It should be noted that the time period may be set by user, and may be a week, a month, a quarter, a year, or the like, in addition to 24 hours a day in the example.

In an alternative embodiment, the probability of the terminal accessing each application service may also be determined by using the access traffic in the access statistics data, and illustratively, the access traffic of the terminal for each application service in the M application services in a historical period may be determined from the access statistics data, then the access traffic of the terminal for each application service in the M application services in the historical period is summed up to obtain an access total traffic, and finally the ratio of the access traffic of the terminal for each application service to the access total traffic is calculated to obtain the access probability of the terminal for each application service in the M application services.

In an alternative embodiment, the probability of access by the terminal to each application service may also be determined in such a way that the number of accesses and/or the access traffic in the history period will be accessed in the statistics. For example, the time period of the historical time period may be divided into a plurality of time intervals, then the access flow of the user to each of the M application services in each of the plurality of time intervals through the terminal may be determined according to the access flow corresponding to the access statistics data at the current time, then the time interval in which the current time is located may be taken as the target time interval, and the access probability of the terminal to each of the M application services may be determined according to the access flow of the user to each of the application services in the target time interval through the terminal. For example, the sum of the access flows of the terminal to each application service in the target time interval is calculated, and then the ratio of the access flow of the terminal to each application service in the target time interval to the sum of the access flows of the terminal to each application service in the target time interval is calculated, so that the access probability of each application service is obtained.

In an optional embodiment, firstly, when the number of target application services is X, network performance data corresponding to each cloud access point when the terminal accesses each target application service are obtained, wherein X is a positive integer, then, N data sets are established according to network performance data corresponding to each cloud access point when the terminal accesses each target application service, wherein each data set in the N data sets corresponds to one cloud access point in the N cloud access points, each data set comprises X network performance data corresponding to each cloud access point when the terminal accesses X target application services after accessing the cloud access point corresponding to the data set, then, weighted calculation is performed on the X network performance data in each data set according to the access probability of the terminal to each cloud application service in the X target application services, a weighted calculation result corresponding to each data set is obtained, the access probability of each network performance data in the X network performance data corresponding to the target application service corresponding to the network performance data is determined, and finally, the weighted calculation result corresponding to each cloud access point in the N data sets is determined according to the access probability of each weighted calculation result from the cloud access point corresponding to the N data sets.

Optionally, fig. 2 is a schematic diagram of an optional user accessing a target application service according to an embodiment of the present application, where, as shown in fig. 2, the target application service that the user wants to access includes an application service a and an application service B, and a cloud access point that the user accesses to the target application service optionally includes: cloud access point 1, cloud access point 2, and cloud access point 3.

Optionally, it is assumed that a user at a remote office located in a geographic location 4 wants to access an application service a, where a server where the application service a is located in a geographic location 3, at this time, a connection may be established between the server and a cloud access point 1 located in the geographic location 1 or between the server and the cloud access point 3 located in the geographic location 3 through a terminal, after that, a historical behavior of the user accessing the application service a and the application service B is queried from a controller through the terminal, and an access probability of the user to the application service a and the application service B at a current moment through the terminal is analyzed, and then the terminal determines that the probability of the terminal accessing the application service a at the current moment is highest.

Optionally, connection is initiated to the cloud access point 1 and the cloud access point 3 through the terminals respectively, network performance data from different cloud access points of the terminal to the application service a is detected, then the collected network performance data is analyzed, finally, the optimal cloud access point (i.e. the target cloud access point) is determined to be the cloud access point 3, and connection between the terminal and the cloud access point 3 is established.

Optionally, in the case that the target application service exists, weighting calculation is performed on the access probability corresponding to the application service which is provided by the controller and is likely to be accessed by the user at the current moment, and an optimal cloud access point is determined according to the obtained result of the weighting calculation. The target application service may be an application service having an access probability of being accessed greater than a preset probability, or may be an application service having a historical access duration greater than a preset time, or may be an application service having a historical access accumulated time greater than a preset time.

Optionally, fig. 3 is a schematic diagram of a data set generated during an optional user accessing a target application service according to an embodiment of the present application, as shown in fig. 3, where the target application service includes an application service a and an application service B, the network time spent by a terminal accessing the application service a through the cloud access point 1 is 80 seconds, the network time spent by a terminal accessing the application service a through the cloud access point 2 is 70 seconds, the network time spent by a terminal accessing the application service a through the cloud access point 3 is 50 seconds, the network time spent by a terminal accessing the application service B through the cloud access point 1 is 40 seconds, the network time spent by a terminal accessing the application service B through the cloud access point 3 is 30 seconds, and the network time spent by a terminal accessing the application service B through the cloud access point 2 is 20 seconds.

Optionally, the above 6 network performance data (i.e. network time-consuming data) are divided to obtain a data set 1, a data set 2 and a data set 3, where the data set 1 includes network performance data for selecting the cloud access point 1 to communicate with the target application service, the data set 2 includes network performance data for selecting the cloud access point 2 to communicate with the target application service, and the data set 3 includes network performance data for selecting the cloud access point 3 to communicate with the target application service.

Alternatively, it is assumed that the access probability of the terminal to the application service a in fig. 3 is 80% and the access probability of the terminal to the application service B is 50%, so the weighted calculation result corresponding to each data set obtained by calculation is: the weight calculation result of the data set 1 is 0.8x80+0.5x40=84 (seconds), the weight calculation result of the data set 2 is 0.8x70+0.5x20=66 (seconds), and the weight calculation result of the data set 3 is 0.8x50+0.5x30=55 (seconds).

In an optional embodiment, first, in a case that the network performance data is first type data, a data set with a minimum weighted calculation result in the N data sets is taken as a target data set, wherein the larger the value of the first type data is, the worse the network performance is represented, then, a cloud access point corresponding to the target data set is taken as a target cloud access point, and finally, the control terminal establishes connection with the target cloud access point.

For example, the network performance data of the first type of data may include one or more of a network communication delay duration, a network fluctuation value, and a packet loss rate of the network.

Optionally, the network performance data in fig. 3 is network time-consuming data required for connecting the cloud access point selected by the terminal with the target application service, so that the cloud access point 3 corresponding to the data set 3 with the smallest weighted calculation result is first used as the target cloud access point, and the terminal corresponding to the user is controlled to establish connection with the cloud access point 3. The cloud access point 3 with the shortest network time consumption is distributed to the users for use, so that the network time consumption of accessing the target application service after the users are connected with the cloud access point through the terminal is shortened, and the user experience is improved. It should be noted that, in practical applications, the network performance data may also be a second type of data, where a larger value of the second type of data indicates a better network performance.

For example, the network performance data of the second type of data includes, but is not limited to, one or more of network bandwidth values, network signal-to-noise ratios, and network throughput. In an alternative embodiment, an application service with an access probability greater than a preset probability among the M application services is taken as a target application service; or in the sequence of the access probability of the M application services from large to small, taking the application service arranged in the preset position before as the target application service.

Optionally, first, whether an application service with an access probability greater than a preset probability exists in the M application services is judged, when the access probability is greater than the preset probability in the M application services, the application service with the access probability greater than the preset probability in the M application services is used as a target application service, and when the access probability is not greater than the preset probability in the M application services, the application service with the largest access probability in the M application services is used as the target application service.

In some embodiments, the present application provides an embodiment of a method for determining a cloud access point, where an implementation process of the method includes three stages, respectively: the system comprises a query phase, a detection phase and a decision phase, wherein during the query phase, an instruction is sent to a controller through a terminal, the instruction is used for querying historical behaviors (namely historical access behaviors) of a user for accessing different application services in a historical time period, and then historical behavior information returned by the controller is collected; during the detection phase, detecting network quality information of each cloud access point in the plurality of cloud access points through a terminal corresponding to a user; during the decision stage, an optimal cloud access point (i.e., a target cloud access point) is determined according to the collected historical behavior information and network quality information, and a connection between the user terminal and the target cloud access point is established. Optionally, fig. 4 is a flowchart of an optional method for determining cloud access points at different stages according to an embodiment of the present application, as shown in fig. 4, by using SASE equipment adopting SSE (Server-Side Encryption) technology to implement communication between a user and an application service a (corresponding to application a in fig. 4), where the SASE cloud equipment provides 3 cloud access points, corresponding to POP a, POP B and POP C in fig. 4, and the query stage specifically includes the following steps:

in step S401, a history access behavior of a user to access the application service a in a history period is monitored by the controller.

Step S402, actively inquiring historical behavior (namely, historical access behavior) of the user accessing the application to the controller through the terminal.

Step S403, analyzing the historical access behaviors of the user through the controller to obtain the access probability of the user accessing the application service A at the moment, and transmitting the access probability of the application service A to the terminal corresponding to the user.

Step S404, storing the access probability of the user to the application service A in a first data table corresponding to the terminal.

Optionally, the detection phase specifically includes the following steps:

in step S501, a connection is initiated by a terminal to a plurality of cloud access points (e.g., POP a, POP B, and POP C in fig. 4).

Step S502, network quality detection is performed through the terminal, and network performance data between the terminal and the application service A is obtained after the terminal is connected to different cloud access points, wherein the network performance data at least comprises a network packet loss rate, a network delay and a network jitter rate.

And step S503, the detected network performance data is stored in a second data table corresponding to the terminal.

Optionally, the decision stage specifically includes the following steps:

In step S601, the stored access probability information of the terminal and the detected network performance data are analyzed to determine an optimal cloud access point (i.e., the best cloud access point or the optimal cloud access point) under a comprehensive condition.

Step S602, establishing connection between a terminal of a user and an optimal cloud access point.

In step S603, the control terminal accesses the application service a through the optimal cloud access point.

According to another aspect of the embodiment of the present application, a determining device (abbreviated as determining device) for a cloud access point is further provided. Fig. 5 is a schematic diagram of an alternative determining device for a cloud access point according to an embodiment of the present application, where, as shown in fig. 5, the determining device for a cloud access point includes: a first acquisition unit 501, a first determination unit 502, a second determination unit 503, and a third determination unit 504.

Optionally, the first obtaining unit is configured to obtain historical access behaviors of a user to M application services by using a terminal, where M is an integer greater than 1; a first determining unit configured to determine an access probability of the terminal to each of the M application services based on the historical access behavior; a second determining unit configured to determine a target application service from the M application services according to an access probability of each application service; the third determining unit is configured to determine, from the N cloud access points, a target cloud access point according to network performance data corresponding to when the terminal accesses the target application service by respectively accessing each of the N cloud access points, where N is a positive integer, and the target cloud access point is configured to establish connection with the terminal.

In this embodiment, the determining device may collect historical access behaviors corresponding to the user accessing the M application services by using the terminal in the historical time period, for example, in the case of remote office of the user, the determining device needs to access the application service C located in the same area as the cloud access point 1, at this time, the determining device uses the terminal to query the controller for a user behavior record generated by the user accessing the application service C in the last month, and determines the historical access behavior corresponding to the user according to the user behavior record collected by the controller.

In this embodiment, the determining means determines the access probability of the user to each of the M application services based on the access statistics data corresponding to the application service by the user through the terminal in the history period.

In this embodiment, the determining device analyzes the access probability of the user to each application service of the M application services, and uses the application service with the largest access probability or the application service with the access probability greater than the preset probability of the M application services as the target application service.

In this embodiment, before determining a cloud access point to be allocated for a user, a determining device first detects N links corresponding to a target application service accessed by each cloud access point of N cloud access points to obtain an optimal link, where the user accesses the target application service through the cloud access point, and the links corresponding to the target software application at least include a terminal, the cloud access point, and the target application service, and the optimal link is a link with the minimum network resource overhead or the shortest communication time in the N links, and then the user accesses the target application service through the selected optimal link, thereby improving user experience of accessing the target application service by the user.

In this embodiment, if there are multiple determined target cloud access points, one target cloud access point may be randomly selected as the target cloud access point to be connected with the terminal of the user.

It should be noted that, the network performance data corresponding to each cloud access point when accessing the target application service may be network performance data corresponding to an entire access path corresponding to each cloud access point when accessing the target application service, for example, all time consumed corresponding to the entire access path, an overall network packet loss rate corresponding to the entire access path, and so on.

Therefore, the technical scheme of the application achieves the aim of determining the cloud access point corresponding to the user according to the network performance data between different cloud access points and the user access terminal and the historical access behavior of the user, thereby realizing the technical effect of improving the selection accuracy of selecting the cloud access point for the user, and further solving the technical problem of poor selection accuracy when selecting the cloud access point in the prior art.

In an optional embodiment, the determining device of the cloud access point further includes: a second acquisition unit, a detection unit and a fourth determination unit.

Optionally, the second obtaining unit is configured to obtain N access paths corresponding to the target application service accessed by the terminal, where different access paths in the N access paths correspond to different cloud access points in the N cloud access points; the detection unit is used for detecting network performance data corresponding to the terminal when the terminal accesses the target application service through each access path; and a fourth determining unit, configured to use network performance data corresponding to the terminal when accessing the target application service through the nth access path as network performance data corresponding to the cloud access point in the nth access path, where N is a positive integer less than or equal to N.

In this embodiment, the network performance data at least includes connection time, communication packet loss rate, network jitter frequency and communication delay time in the connection process of the terminal, the cloud access point and the target application service, and the determining device uses the network performance data as a reference factor for selecting the cloud access point, so that the problem of poor network communication performance of the cloud access point allocated to the user due to neglecting connection information between the cloud access point and the target application service in the prior art is solved.

In an alternative embodiment, the first determining unit comprises: an access statistics determination subunit, an access probability determination subunit.

Optionally, an access statistics data determining subunit, configured to determine, according to the historical access behavior, access statistics data of the user to each application service in the M application services in a historical time period through the terminal, where the access statistics data at least includes access times and/or access traffic in the historical time period; and the access probability determination subunit is used for determining the access probability of the terminal to each application service in the M application services according to the access statistical data.

In an alternative embodiment, the access probability determination subunit comprises: the device comprises a first access frequency determining module, a summing module and a first access probability determining module.

Optionally, the first access frequency determining module is used for determining the access frequency of the terminal to each application service in the M application services in the historical time period from the access statistical data; the summation module is used for carrying out summation calculation on the access times of each application service in the M application services in the historical time period by the terminal to obtain a calculation result; the first access probability determining module is used for calculating the ratio of the number of times of access to each application service by the terminal to the calculation result to obtain the access probability of the terminal to each application service in the M application services.

In an alternative embodiment, the access probability determination subunit comprises: the system comprises a dividing module, a second access times determining module, a target time interval determining module and a second access probability determining module of each application service.

Optionally, the dividing module is configured to divide the time period into a plurality of time intervals; the second access times determining module is used for determining the access times of the user to each application service in the M application services in each time interval of a plurality of time intervals through the terminal according to the access times in the access statistical data; the target time interval determining module is used for taking the time interval in which the current moment is located as a target time interval; and the second access probability determining module is used for determining the access probability of the terminal to each application service in the M application services according to the access times of the user to each application service in the target time interval through the terminal.

In this embodiment, the determining device counts the number of accesses to each application service in the M application services by the user in each time interval by dividing the time period into a plurality of time intervals, so as to further improve the prediction accuracy of the determining device to the application service (i.e., the target application service) that the user attempts to access, and further improve the selection accuracy of the subsequent cloud access point.

In an alternative embodiment, the third determining unit comprises: the cloud access point comprises a first acquisition subunit, a data set establishment subunit, a weight calculation subunit and a target cloud access point determination subunit.

Optionally, when the number of the target application services is X, the first obtaining subunit is configured to obtain network performance data corresponding to when the terminal accesses each cloud access point to access each target application service, where X is a positive integer; the data set establishing subunit is used for establishing N data sets according to network performance data corresponding to each cloud access point when the terminal accesses each target application service respectively, wherein each data set in the N data sets corresponds to one cloud access point in the N cloud access points, and each data set comprises X network performance data corresponding to X target application services respectively after the terminal accesses the cloud access point corresponding to the data set; the weighting calculation subunit is used for carrying out weighting calculation on the X network performance data in each data set according to the access probability of the terminal to each target application service in the X target application services to obtain a weighting calculation result corresponding to each data set, wherein the weight corresponding to each network performance data in the X network performance data is determined by the access probability of the target application service corresponding to the network performance data; the target cloud access point determining subunit is configured to determine a target cloud access point from the N cloud access points according to the weighted calculation result corresponding to each data set.

In this embodiment, when the user has application services that are habitually accessed for a long period of time (for example, application services with access probability greater than a preset probability and application services with access time greater than a preset time), weighting calculation is performed on the access probability corresponding to the application services that the user may access at the current moment and provided by the controller, and an ideal cloud access point is determined according to the obtained weighting calculation result.

In an alternative embodiment, the target cloud access point determination subunit includes: the device comprises a first determining module, a second determining module and an establishing module.

Optionally, the first determining module is configured to, in a case where the network performance data is of a first type, use a data set with a smallest weighted calculation result in the N data sets as the target data set, where a larger value of the first type data indicates a worse network performance; the second determining module is used for taking the cloud access point corresponding to the target data set as a target cloud access point; the establishing module is used for controlling the terminal to establish connection with the target cloud access point.

In an alternative embodiment, the second determining unit comprises: the target application service determines the subunit.

Optionally, the target application service determining subunit is configured to use, as the target application service, an application service with an access probability greater than a preset probability among the M application services; or in the sequence of the access probability of the M application services from large to small, the target application service determining subunit takes the application service arranged in the preset position as the target application service.

In this embodiment, the determining device first determines whether there is an application service with an access probability greater than a preset probability among the M application services, and when there is an application service with an access probability greater than a preset probability among the M application services, the determining device uses the application service with an access probability greater than a preset probability among the M application services as a target application service, and when there is no application service with an access probability greater than a preset probability among the M application services, the determining device uses the application service with a maximum access probability among the M application services as a target application service.

According to another aspect of the embodiment of the present application, there is further provided a computer readable storage medium, where the computer readable storage medium includes a stored computer program, and when the computer program runs, the device on which the computer readable storage medium is located is controlled to execute the method for determining the cloud access point of any one of the above.

According to another aspect of the embodiment of the present application, there is also provided an electronic device, including: a processor; and a memory for storing executable instructions of the processor; the processor is configured to execute the method for determining the cloud access point according to any one of the above through execution of the executable instructions.

Fig. 6 is a schematic diagram of an alternative electronic device according to an embodiment of the present application, and as shown in fig. 6, an embodiment of the present application provides an electronic device, where the electronic device includes a processor, a memory, and a program stored on the memory and capable of running on the processor, and the processor implements a method for determining a cloud access point according to any one of the above when executing the program.

The embodiments or examples disclosed herein are not intended to be exhaustive or to limit the scope of the application to the precise forms or examples disclosed. In the case of no contradiction, each step in a certain implementation or embodiment of the present application may be implemented as an independent embodiment, and the steps may be arbitrarily combined, for example, a scheme after removing part of the steps in a certain implementation or embodiment may also be implemented as an independent embodiment, and the order of the steps in a certain implementation or embodiment may be arbitrarily exchanged, and in addition, an optional manner or an optional embodiment in a certain implementation or embodiment may be arbitrarily combined; furthermore, various embodiments or examples may be arbitrarily combined, for example, some or all steps of different embodiments or examples may be arbitrarily combined, and one embodiment or example may be arbitrarily combined with alternative modes or alternatives of other embodiments or examples.

In the foregoing embodiments of the present application, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory. The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, etc., such as Read Only Memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Disks (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises an element.

It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and variations of the present application will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the application are to be included in the scope of the claims of the present application.

Claims

1. The method for determining the cloud access point is characterized by comprising the following steps:

acquiring historical access behaviors of a user to M application services by using a terminal, wherein M is an integer greater than 1;

Determining an access probability of the terminal to each of the M application services based on the historical access behavior;

determining a target application service from the M application services according to the access probability of each application service;

and determining a target cloud access point from the N cloud access points according to network performance data corresponding to the situation that each cloud access point in the N cloud access points accesses the target application service, wherein N is a positive integer, and the target cloud access point is used for establishing connection with the terminal.

2. The method for determining a cloud access point according to claim 1, wherein before each of the N cloud access points accesses the network performance data corresponding to the target application service according to the respective access of the terminal, the method for determining a cloud access point further comprises:

acquiring N access paths corresponding to the target application service accessed by the terminal, wherein different access paths in the N access paths correspond to different cloud access points in the N cloud access points;

Detecting network performance data corresponding to the terminal accessing the target application service through each access path;

And taking the network performance data corresponding to the terminal when accessing the target application service through the nth access path as the network performance data corresponding to the cloud access point of the nth access path, wherein N is a positive integer less than or equal to N.

3. The method for determining a cloud access point according to claim 1, wherein determining the access probability of the terminal to each of the M application services based on the historical access behavior comprises:

Determining access statistical data of the user to each of the M application services in a historical time period through the terminal according to the historical access behaviors, wherein the access statistical data at least comprises access times and/or access flow in the historical time period;

And determining the access probability of the terminal to each application service in the M application services according to the access statistical data.

4. The method for determining a cloud access point according to claim 3, wherein determining the access probability of the terminal to each of the M application services according to the access statistics includes:

Determining the access times of the terminal to each of the M application services in a historical time period from the access statistical data;

summing up and calculating the access times of each application service in the M application services in the historical time period by the terminal to obtain a calculation result;

And calculating the ratio of the access times of the terminal to each application service to the calculation result to obtain the access probability of the terminal to each application service in the M application services.

5. The method for determining a cloud access point according to claim 3, wherein determining the access probability of the terminal to each of the M application services according to the access statistics includes:

Dividing the time period into a plurality of time intervals;

Determining the access times of the user to each application service in M application services in each time interval of the time intervals through the terminal according to the access times in the access statistical data;

taking the time interval in which the current moment is located as a target time interval;

and determining the access probability of the terminal to each application service in the M application services according to the access times of the user to each application service in the target time interval through the terminal.

6. The method for determining a cloud access point according to claim 1, wherein determining a target cloud access point from the N cloud access points according to network performance data corresponding to when each of the N cloud access points is accessed by the terminal to access the target application service, includes:

When the number of the target application services is X, network performance data corresponding to the situation that the terminal is respectively accessed to each cloud access point to access each target application service is obtained, wherein X is a positive integer;

Establishing N data sets according to network performance data corresponding to each cloud access point when each terminal accesses each target application service, wherein each data set in the N data sets corresponds to one cloud access point in the N cloud access points, and each data set comprises X network performance data corresponding to X target application services when the terminal accesses the cloud access point corresponding to the data set;

According to the access probability of the terminal to each target application service in the X target application services, weighting calculation is carried out on the X network performance data in each data set to obtain a weighting calculation result corresponding to each data set, wherein the weight corresponding to each network performance data in the X network performance data is determined by the access probability of the target application service corresponding to the network performance data;

And determining the target cloud access point from the N cloud access points according to the weighted calculation result corresponding to each data set.

7. The method for determining a cloud access point according to claim 6, wherein determining the target cloud access point from the N cloud access points according to the weighted calculation result corresponding to each data set comprises:

taking the data set with the smallest weighted calculation result in the N data sets as a target data set under the condition that the network performance data is the first type data, wherein the larger the value of the first type data is, the worse the network performance is represented;

And taking the cloud access point corresponding to the target data set as the target cloud access point.

8. The method for determining a cloud access point according to any of claims 1-7, wherein determining a target application service from the M application services according to the access probability of each application service includes:

taking the application service with the access probability larger than the preset probability in the M application services as the target application service; or alternatively

And in the sequence of the access probability of the M application services from large to small, taking the application service arranged in the preset position before as the target application service.

9. A cloud access point determining apparatus, comprising:

The first acquisition unit is used for acquiring historical access behaviors of a user to M application services by using a terminal, wherein M is an integer greater than 1;

a first determining unit configured to determine an access probability of the terminal to each of the M application services based on the historical access behavior;

A second determining unit, configured to determine a target application service from the M application services according to the access probability of each application service;

The third determining unit is configured to determine, according to network performance data corresponding to when each of N cloud access points is accessed by the terminal to access the target application service, a target cloud access point from the N cloud access points, where N is a positive integer, and the target cloud access point is configured to establish connection with the terminal.

10. An electronic device comprising one or more processors and a memory for storing one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of determining a cloud access point of any of claims 1-8.