Cloud network sensing processing method, device, medium and system

Abstract

The invention provides a cloud network sensing processing method, device, medium and system. The monitoring category of each cloud network sensing probe is acquired by adopting the proxy probe in the cloud network sensing center, and at least part of all the cloud network sensing probes are subjected to de-duplication processing according to the monitoring category and the corresponding access time to obtain the final cloud network sensing probe group, so that the bandwidth occupation of a test channel is reduced, and the test efficiency is improved. And more bandwidths are used for improving the actual business service quality of the user, so that the problem that the business bandwidth of the user becomes less due to the fact that the bandwidth resources are used for monitoring the network quality in the existing scheme is solved.

Description

Technical Field

[0001] The present application relates to the field of cloud network perception technology, and specifically, to a cloud network perception processing method, device, medium and system. Background Art

[0002] Based on this, various forms of network-aware neuron probes, such as web page embedded probes, ONU optical modem probes, and OLT backbone network probes, actively detect and monitor the network quality at all levels. For the sake of convenience, the various existing forms of network-aware neuron probes are referred to as Smart probes.

[0003] like Figure 1 As shown in the figure, it is now possible to use Smart probes to monitor the average latency, maximum latency, minimum latency, latency variance, network jitter, etc. of the backbone network reaching the PING perception service, the target video portal website, the target game website, and the target portal website. It also monitors the number of pauses in video access, download rate, buffering latency, etc.

[0004] Smart probes can be used to send data packets to simulate users accessing the target website portal, and obtain web page access white screen delay, home page delay, DNS delay, first screen delay, connection delay, response delay, etc. Smart probes can be used to execute the video download interface to simulate users accessing the target video server, and obtain the number of video access pauses, download rate, buffer delay, etc. Smart probe game interfaces can be used to simulate users accessing and executing a complete game process, and obtain game access average delay, game server delay, network jitter, etc.

[0005] At present, when a large number of users randomly initiate network quality monitoring, especially during the evening peak hours when a large number of users access video servers or game servers, once the network is congested, users will actively initiate network quality detection, and thus have to use extremely precious bandwidth resources for network quality monitoring. User service bandwidth will become less, and the user experience will be poor. Then more users will be asked to enter network quality monitoring, thus forming a vicious circle, resulting in a large amount of bandwidth being occupied by monitoring traffic, which greatly affects the user experience. The biggest feeling brought to customers is that it becomes slower to watch videos or play games during the evening peak hours, so they actively initiate network quality monitoring when entering the web page, and the situation becomes more and more stuck until some users exit to alleviate it. This phenomenon will directly reduce the game or video experience, thereby causing customer complaints.

[0006] That is, the existing solution uses bandwidth resources for network quality monitoring, resulting in less bandwidth for user services. Summary of the invention

[0007] The main purpose of the present application is to provide a cloud network perception processing method, device, medium and system to at least solve the problem that the existing solution uses bandwidth resources for network quality monitoring, resulting in less user service bandwidth.

[0008] In order to achieve the above objective, according to one aspect of the present application, a cloud network perception processing method is provided, the method comprising:

[0009] Adopt ITMS and cloud platform technology and network perception neuron detection technology to establish a cloud network perception center to deploy and access massive cloud network perception probes;

[0010] In the cloud network perception center, a proxy probe is used to obtain the monitoring category of each cloud network perception probe, and the monitoring category includes PING perception monitoring, video perception monitoring, web page perception monitoring and game perception monitoring;

[0011] According to the monitoring category and the corresponding access time, at least part of all the cloud network perception probes are deduplicated to obtain a final cloud network perception probe group, and the cloud network perception probes of the final cloud network perception probe group are executed. The access time represents the time interval for accessing two adjacent cloud network perception probes with the same monitoring category.

[0012] Optionally, according to the monitoring category and the corresponding access time, at least part of all the cloud network perception probes are deduplicated to obtain a final cloud network perception probe group, including: when the access time is less than a first preset duration, retaining the corresponding cloud network perception probe; when the access time is greater than or equal to the first preset duration, deleting the corresponding cloud network perception probe.

[0013] Optionally, when the access time is less than a first preset duration, retaining the corresponding cloud network perception probe includes: retaining the corresponding cloud network perception probe in the execution queue; when the access time is greater than or equal to the first preset duration, deleting the corresponding cloud network perception probe includes: deleting the corresponding cloud network perception probe from the execution queue; before deduplicating at least part of all the cloud network perception probes according to the monitoring category and the corresponding access time to obtain the final cloud network perception probe group, the method also includes: first storing all the cloud network perception probes in a waiting queue, and then transferring part of the cloud network perception probes from the waiting queue to the execution queue every second preset duration, and the second preset duration is less than the first preset duration.

[0014] Optionally, in the process of using the proxy probe in the cloud network perception center to obtain the monitoring category of each cloud network perception probe, the method also includes: using the proxy probe in the cloud network perception center to obtain network quality parameters, the network quality parameters including PING average delay, maximum delay, minimum delay, buffer delay and packet loss; after executing the cloud network perception probe of the final cloud network perception probe group, the method also includes: determining whether the cloud network perception probe is qualified based on the network quality parameters and the corresponding access time.

[0015] Optionally, determining whether the cloud network perception probe is qualified is based on the network quality parameters and the corresponding access time, including: determining whether the cloud network perception probe is qualified at least based on the size of all delay differences and benchmark differences, the delay difference being the difference between the delay in the network quality parameters and the preset delay of the cloud network perception probe.

[0016] Optionally, whether the cloud network perception probe is qualified is determined at least based on the size of all the delay differences and the benchmark differences, including: summing all the delay differences to obtain the sum of the delay differences; when the sum of the delay differences is less than or equal to the benchmark difference, determining that the cloud network perception probe is qualified so that the cloud network perception probe can be applied to subsequent monitoring work; when the sum of the delay differences is greater than the benchmark difference, determining that the cloud network perception probe is unqualified.

[0017] Optionally, whether the cloud network perception probe is qualified is determined at least based on the size of all delay differences and a benchmark difference, including: determining multiple delay difference correction results, the delay difference correction result being the sum of the delay difference and the corresponding correction value, the correction value having a mapping relationship with the monitoring category of the delay difference; summing all the delay difference correction results to obtain a final delay sum value; when the final delay sum value is less than or equal to the benchmark difference value, determining that the cloud network perception probe is qualified so that the cloud network perception probe can be applied to subsequent monitoring work; when the final delay sum value is greater than the benchmark difference value, determining that the cloud network perception probe is unqualified.

[0018] According to another aspect of the present application, a cloud network perception processing device is provided, the device comprising:

[0019] The acquisition unit is used to establish a cloud network perception center using ITMS and cloud platform technology and network perception neuron detection technology to deploy and access massive cloud network perception probes;

[0020] A first processing unit is used to use a proxy probe in the cloud network perception center to obtain a monitoring category of each cloud network perception probe, where the monitoring category includes PING perception monitoring, video perception monitoring, web page perception monitoring, and game perception monitoring;

[0021] The second processing unit is used to deduplicate at least part of all the cloud network perception probes according to the monitoring category and the corresponding access time to obtain a final cloud network perception probe group, and execute the cloud network perception probes of the final cloud network perception probe group, wherein the access time represents the time interval for accessing two adjacent cloud network perception probes with the same monitoring category.

[0022] According to another aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute any one of the methods described.

[0023] According to another aspect of the present application, a cloud network awareness processing system is provided, which includes: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include methods for executing any one of the described methods.

[0024] By applying the technical solution of the present application, a proxy probe is used in the cloud network perception center to obtain the monitoring category of each cloud network perception probe, and at least part of all the cloud network perception probes are deduplicated according to the monitoring category and the corresponding access time to obtain the final cloud network perception probe group, thereby reducing the bandwidth occupancy of the test channel and using more bandwidth to improve the actual business service quality of users, thereby solving the problem that the existing solution uses bandwidth resources for network quality monitoring, resulting in less user business bandwidth. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The drawings constituting part of the present application are used to provide a further understanding of the present application. The exemplary embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0026] Figure 1 A schematic diagram of a conventional Smart probe provided in an embodiment of the present application is shown;

[0027] Figure 2 A schematic diagram of a process of a cloud network perception processing method provided according to an embodiment of the present application is shown;

[0028] Figure 3A schematic diagram of a cloud network perception probe provided according to an embodiment of the present application is shown;

[0029] Figure 4 A schematic diagram of a cloud network perception center provided according to an embodiment of the present application is shown;

[0030] Figure 5 A schematic diagram of a process of another cloud network perception processing method provided according to an embodiment of the present application is shown;

[0031] Figure 6 A structural block diagram of a cloud network perception processing device provided according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0032] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0033] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0034] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0035] As introduced in the background technology, when a large number of users randomly initiate network quality monitoring, especially when a large number of users access video servers or game servers during the evening peak hours, once the network is congested, users will actively initiate network quality detection, and thus extremely precious bandwidth resources will have to be used for network quality monitoring, and user service bandwidth will become less, and the user experience will be poor. Then more users will be asked to enter network quality monitoring, thus forming a vicious circle, resulting in a large amount of bandwidth being occupied by monitoring traffic, which greatly affects the user experience. The biggest feeling brought to customers is that it becomes slower to watch videos or play games during the evening peak hours, so entering the web page to actively initiate network quality monitoring, which becomes more and more stuck until some users exit to alleviate the problem. This phenomenon will directly reduce the experience of games or videos, thereby causing customer complaints. In order to solve the problem that the existing solution uses bandwidth resources for network quality monitoring, resulting in less user service bandwidth, the embodiments of the present application provide a cloud network perception processing method, device, medium and system.

[0036] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0037] In this embodiment, a cloud network awareness processing method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0038] Figure 2 1 is a flow chart of a cloud network perception processing method provided according to an embodiment of the present application. Figure 2 As shown, the method comprises the following steps:

[0039] Step S201, using ITMS and cloud platform technology and network perception neuron detection technology to establish a cloud network perception center to deploy and access massive cloud network perception probes;

[0040] ITMS and cloud platform technology refers to the Intelligent Transportation Management System (ITMS) based on the Internet of Things technology, combined with the technology of the cloud computing platform to achieve the monitoring, management and optimization of the transportation system. By collecting, processing and analyzing traffic data, ITMS can achieve real-time traffic monitoring, intelligent signal control, traffic flow prediction and other functions, improve traffic efficiency and reduce traffic congestion.

[0041] Network perception neuron detection technology refers to traffic detection technology based on neural network and perception technology. It can obtain traffic data through monitoring cameras, sensors and other equipment, and use neural network algorithms to analyze and identify data, so as to achieve real-time monitoring and detection of traffic flow, vehicle type, speed and other information. This technology can help traffic management departments understand road conditions more accurately and take timely measures to optimize traffic flow.

[0042] Based on the ITMS and cloud platform technology of telecommunications, combined with network perception neuron technology, a cloud network perception center is established, which can deploy and access cloud network perception probes in large quantities. When each cloud network perception probe is initially started, it initiates network quality detection according to the instructions of ITMS to obtain initial network quality data.

[0043] Collect parameters: Collect network quality parameters and network attributes of each cloud network perception probe. Network quality parameters include PING perception quality, portal website access quality, video service perception quality and game service perception quality (PING perception quality includes, but is not limited to, monitoring the average access delay, maximum delay, minimum delay, delay variance, network jitter, etc. of the backbone network to the PING perception service, target video portal website, target game website, and target portal website; video access pause times, download rate, buffering delay, etc.; portal website access quality includes, but is not limited to, sending data packets through cloud network perception probes to simulate users accessing the target website portal, obtaining web page access white screen delay, homepage delay, DNS delay, first screen delay, connection delay, response delay, etc.; video service perception quality includes, but is not limited to, executing the video download interface through cloud network perception probes, simulating users accessing the target video server, obtaining video access pause times, download rate, buffering delay, etc.; game service perception quality includes, but is not limited to, simulating users accessing and executing a complete game process through the cloud network perception probe game interface, obtaining game access average delay, game server delay, network jitter, etc.).

[0044] Step S202, using a proxy probe in the cloud network perception center to obtain the monitoring category of each cloud network perception probe, the monitoring category including PING perception monitoring, video perception monitoring, web page perception monitoring and game perception monitoring;

[0045] Select network quality proxy cloud network perception probe: Based on the data collected in step 2, perform big data mining and select reasonable proxy probes, such as Figure 3 As shown, the method for selecting a network quality agent perception probe is as follows:

[0046] When the user accesses the backbone network through an optical modem, the system selects the cloud network perception probe of the upstream backbone network as the proxy perception probe of LAN 1 according to the network level and network structure;

[0047] When the typical structure of the user is similar to an Internet cafe, and a web-based cloud network perception probe is used to detect network quality, one of the responding parallel nodes is selected as the proxy perception probe through an arbitration-like method.

[0048] like Figure 3 2.1 is used as the proxy probe. The principle of selecting the network quality proxy cloud network perception probe is to try to be close to the user-side cloud network perception probe, and to be at the same level or one level higher. After the cloud network perception center selects the proxy monitoring point for each cloud network perception probe, it also sends a list of positive and negative deviations of various parameters of the cloud network perception probe and the proxy perception probe (for ease of description, assume that the network delay from proxy probe 2.1 to the download server is 5.1S, probe 2.2 is 5.2S, probe 2.3 is 5.3S, and probe 2.4 is 5.0S, and the positive and negative deviation list is (0.1, 0.2, -0.1)).

[0049] like Figure 4 As shown, for the convenience of description, ITMS services, probe file management services, probe registration services, routine test task management services, real-time task management services, traffic collection storage services, and active monitoring data storage services are collectively referred to as the cloud network perception center.

[0050] Step S203: Deduplication processing is performed on at least part of all the cloud network perception probes according to the above-mentioned monitoring categories and corresponding access times to obtain a final cloud network perception probe group, and the above-mentioned cloud network perception probes of the above-mentioned final cloud network perception probe group are executed. The above-mentioned access time represents the time interval for accessing two adjacent cloud network perception probes of the same monitoring category.

[0051] In the above steps, the monitoring category of each cloud network perception probe is obtained by using a proxy probe in the above cloud network perception center, and at least part of all the above cloud network perception probes are deduplicated according to the above monitoring category and the corresponding access time to obtain the final cloud network perception probe group, thereby reducing the bandwidth occupancy of the test channel and using more bandwidth to improve the actual business service quality of users, thereby solving the problem that the existing solution uses bandwidth resources for network quality monitoring, resulting in less user business bandwidth.

[0052] That is, this application selects appropriate network quality proxy perception probes based on the statistics of the network architecture level and network quality parameters of each cloud network perception probe by the cloud network perception center. Then, when the test applications sent by each are handed over to the proxy perception probe for execution, they are screened according to Δt and test items, rather than forwarded completely in sequence, thereby greatly reducing the bandwidth occupied by the test channel, and using more bandwidth to improve the actual service quality of users. For example, when watching TV series or videos, or playing games, the network will not become further stuck due to a large number of users initiating active tests, thereby improving user satisfaction and reducing customer complaints.

[0053] At the cloud network perception center, the network properties and initial network detection quality data of each probe are collected during initialization, and a network quality equivalent proxy detection point (a cloud network perception probe of the entire cloud network perception system) is found for it. For the convenience of description, the network quality equivalent proxy detection point is referred to as a proxy probe. The proxy probe is a network quality equivalent probe calculated by the cloud network perception center based on the network properties and the initial network quality data of each probe. It can be a probe of the same level or a backbone network probe of the previous level. The proxy is not a forwarding agent in the traditional sense, but it filters part of the same type of monitoring tasks according to the set network sensitivity (Δt) to reduce the consumption of network bandwidth.

[0054] According to the monitoring categories and corresponding access times, at least part of all the cloud network sensing probes are deduplicated to obtain a final cloud network sensing probe group, including:

[0055] When the access time is less than the first preset duration, retain the corresponding cloud network sensing probe;

[0056] Among them, the specific implementation method is: retain the corresponding cloud network perception probes mentioned above to the execution queue.

[0057] When the access time is greater than or equal to the first preset time period, the corresponding cloud network perception probe is deleted.

[0058] Among them, the specific implementation method is: delete the corresponding cloud network perception probe from the above-mentioned execution queue.

[0059] In addition, before deduplicating at least part of all the above-mentioned cloud network perception probes according to the above-mentioned monitoring categories and corresponding access times to obtain the final cloud network perception probe group, the above-mentioned method also includes: first storing all of the above-mentioned cloud network perception probes in a waiting queue, and then transferring part of the above-mentioned cloud network perception probes from the above-mentioned waiting queue to the above-mentioned execution queue every second preset time period, and the above-mentioned second preset time period is less than the above-mentioned first preset time period.

[0060] Specifically, the agent-aware probe performs network quality monitoring: the network quality-aware probe does not simply initiate network monitoring upon receiving relevant instructions, which does not achieve the purpose of reducing network bandwidth usage. In the agent, two queues will be established: the first queue is the monitoring application queue, which records the actual entry time, source, monitoring category, monitoring target service address and monitoring items of each task, as shown in Table 1.

[0061] Table 1

[0062]

[0063]

[0064]

[0065] The second queue is the monitoring execution queue: the proxy perception probe is based on a deduplication time (Δt, i.e., the first preset duration, and the second preset duration can be 10s) set during initialization. To facilitate observation of the effect, it is assumed that Δt is 30 seconds. Then, the same monitoring requirements arriving within 30 seconds will not be added to the monitoring execution queue, but will directly return the execution results of the items in the monitoring queue. The size of Δt can be freely adjusted according to the user's sensitivity to monitoring data, and is not fixed at 30 seconds. The deduplication process is shown in Table 2.

[0066] Table 2

[0067]

[0068]

[0069]

[0070] The proxy probe 2.1 in Table 2 received a total of 37 monitoring applications from the proxied probes 2.2, 2.3, and 2.4, and actually executed 5 times. Compared with the traditional way of directly connecting to each monitoring service, the monitoring network speed time is shorter, the number of connections initiated is less, and the bandwidth is saved. After obtaining the monitoring results, they are sent to the corresponding cloud network perception probes. The same monitoring application that enters within Δt will directly return the current valid monitoring results.

[0071] In one embodiment of the present application, in the process of using the proxy probe in the cloud network perception center to obtain the monitoring category of each cloud network perception probe, the method further includes: using the proxy probe in the cloud network perception center to obtain network quality parameters, the network quality parameters including PING average delay, maximum delay, minimum delay, buffer delay and packet loss;

[0072] After executing the above-mentioned cloud network perception probe of the above-mentioned final cloud network perception probe group, the above-mentioned method also includes: determining whether the above-mentioned cloud network perception probe is qualified according to the above-mentioned network quality parameters and the corresponding above-mentioned access time.

[0073] Among them, as to how to determine whether the above-mentioned cloud network perception probe is qualified, it is necessary to at least determine whether the above-mentioned cloud network perception probe is qualified based on the size of all delay differences and benchmark differences. The above-mentioned delay difference is the difference between the delay in the above-mentioned network quality parameters and the preset delay of the above-mentioned cloud network perception probe.

[0074] Based on this, this application provides two specific implementation methods:

[0075] The first specific implementation method (based only on the size of all delay differences and benchmark differences) is:

[0076] All the above delay differences are summed to obtain the sum of the delay differences;

[0077] When the sum of the delay differences is less than or equal to the reference difference, the cloud network perception probe is determined to be qualified, so that the cloud network perception probe can be applied to subsequent monitoring work;

[0078] When the sum of the delay differences is greater than the benchmark difference, it is determined that the cloud network perception probe is unqualified.

[0079] Specifically, a mapping relationship between the benchmark difference and the name of the monitoring category is constructed, and the sum of the delay differences and the benchmark difference are compared in a mapping manner to determine whether the cloud network perception probe is qualified, thereby screening out cloud network perception probes with better network quality.

[0080] The second specific implementation method (based on the size of all delay differences, reference differences and correction values) is:

[0081] Determine a plurality of delay difference correction results, wherein the delay difference correction result is a sum of the delay difference and a corresponding correction value, and the correction value has a mapping relationship with the monitoring category of the delay difference;

[0082] Sum all the above delay difference correction results to obtain the final delay sum value;

[0083] When the final delay sum is less than or equal to the reference difference, the cloud network perception probe is determined to be qualified, so that the cloud network perception probe can be applied to subsequent monitoring work;

[0084] When the above-mentioned final delay sum value is greater than the above-mentioned benchmark difference value, it is determined that the above-mentioned cloud network perception probe is unqualified.

[0085] A mapping relationship is established between the name of each monitoring category and the correction value, and the corresponding correction value is found in the mapping relationship. The difference between the delay in the above network quality parameter and the preset delay of the above cloud network perception probe (set delay difference) and the correction value are summed, and accumulated according to this calculation method. When the above final delay sum is less than or equal to the above benchmark difference, the cloud network perception probe is deemed to be qualified, and the above cloud network perception probe is applied to subsequent monitoring work, thereby ensuring that the network environment for subsequent monitoring work is more stable. Therefore, compared with the first specific implementation method, the result obtained by the second specific implementation method is more in line with the actual working conditions.

[0086] The accumulation process is shown in Table 3.

[0087] Table 3

[0088]

[0089]

[0090]

[0091] In order to enable those skilled in the art to more clearly understand the technical solution of the present application, the implementation process of the cloud network perception processing method of the present application will be described in detail below in combination with specific embodiments.

[0092] This embodiment relates to a specific cloud network perception processing method, such as Figure 5 As shown, the following steps are included:

[0093] Initialization of the cloud network perception center: Based on the telecommunications ITMS and cloud platform technology, combined with network perception neuron technology, a cloud network perception center is established, which can deploy and access a large number of cloud network perception probes; when each cloud network perception probe is initially started, it initiates network quality detection according to the instructions of ITMS to obtain initial network quality data;

[0094] Specifically, ITMS and cloud platform technologies and network perception neuron detection technologies are used to establish a cloud network perception center to deploy and access massive cloud network perception probes;

[0095] Collect parameters: collect network quality parameters and network attributes of each cloud network perception probe; network quality parameters include PING perception quality, portal website access quality, video service perception quality and game service perception quality (PING perception quality includes, but is not limited to, monitoring the average access delay, maximum delay, minimum delay, delay variance, network jitter, etc. of the backbone network to the PING perception service, target video portal website, target game website, and target portal website; video access pause times, download rate, buffering delay, etc.; portal website access quality includes, but is not limited to, sending data packets through cloud network perception probes to simulate users accessing the target website portal, obtaining web page access white screen delay, homepage delay, DNS delay, first screen delay, connection delay, response delay, etc.; video service perception quality includes, but is not limited to, executing the video download interface through the cloud network perception probe, simulating users accessing the target video server, obtaining the number of video access pauses, download rate, buffering delay, etc.; game service perception quality includes, but is not limited to, simulating users accessing and executing a complete game process through the cloud network perception probe game interface, obtaining the average game access delay, game server delay, network jitter, etc.);

[0096] Specifically, proxy probes are used in the cloud network perception center to obtain the monitoring categories of each cloud network perception probe, including PING perception monitoring, video perception monitoring, web page perception monitoring and game perception monitoring; proxy probes are used in the cloud network perception center to obtain network quality parameters, including PING average delay, maximum delay, minimum delay, buffer delay and packet loss;

[0097] Select network quality proxy cloud network perception probes: Based on the collected data, conduct big data mining and select reasonable proxy cloud network perception probes;

[0098] Initiate network quality detection: The cloud network perception center sends the IP address and interface information of the selected proxy cloud network perception probe to each cloud network perception probe. When the cloud network perception probe receives a request from a user to initiate network quality monitoring, it sends the network monitoring category, terminal server address, quality items of the network to be monitored and other related parameters to the proxy perception probe;

[0099] Proxy-aware probes perform network quality monitoring: Network quality-aware probes do not simply initiate network monitoring upon receiving relevant instructions, which does not achieve the purpose of reducing network bandwidth usage. In the proxy, two queues will be established;

[0100] According to the monitoring category and the corresponding access time, at least part of all cloud network perception probes are deduplicated to obtain a final cloud network perception probe group, and the cloud network perception probes of the final cloud network perception probe group are executed, where the access time represents the time interval between accessing two adjacent cloud network perception probes with the same monitoring category;

[0101] After executing the cloud network perception probe of the final cloud network perception probe group, multiple delay difference correction results are determined, where the delay difference correction result is the sum of the delay difference and the corresponding correction value, and the correction value has a mapping relationship with the monitoring category of the delay difference; all delay difference correction results are summed to obtain the final delay sum value;

[0102] When the final delay sum is less than or equal to the benchmark difference, the cloud network perception probe is determined to be qualified so that the cloud network perception probe can be applied to subsequent monitoring work; when the final delay sum is greater than the benchmark difference, the cloud network perception probe is determined to be unqualified.

[0103] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0104] The embodiment of the present application also provides a cloud network perception processing device. It should be noted that the cloud network perception processing device of the embodiment of the present application can be used to execute the cloud network perception processing method provided by the embodiment of the present application. The device is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware for a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceived.

[0105] The following is an introduction to the cloud network perception processing device provided in the embodiment of the present application.

[0106] Figure 6 is a structural block diagram of a cloud network perception processing device provided according to an embodiment of the present application. Figure 6 As shown, the device comprises:

[0107] The acquisition unit 61 is used to establish a cloud network perception center by using ITMS and cloud platform technology and network perception neuron detection technology to deploy and access massive cloud network perception probes;

[0108] The first processing unit 62 is used to use probes in the cloud network perception center to obtain monitoring categories of each cloud network perception probe, where the monitoring categories include PING perception monitoring, video perception monitoring, web page perception monitoring, and game perception monitoring;

[0109] The second processing unit 63 is used to deduplicate at least part of all the above-mentioned cloud network perception probes according to the above-mentioned monitoring categories and corresponding access times to obtain a final cloud network perception probe group, and execute the above-mentioned cloud network perception probes of the above-mentioned final cloud network perception probe group, wherein the above-mentioned access time represents the time interval for accessing two adjacent above-mentioned cloud network perception probes of the same monitoring category.

[0110] In the above-mentioned device, by using a proxy probe in the above-mentioned cloud network perception center to obtain the monitoring category of each cloud network perception probe, at least part of all the above-mentioned cloud network perception probes are deduplicated according to the above-mentioned monitoring category and the corresponding access time, to obtain the final cloud network perception probe group, thereby reducing the bandwidth occupancy of the test channel and using more bandwidth to improve the actual business service quality of users, thereby solving the problem that the existing solution uses bandwidth resources for network quality monitoring, resulting in less user business bandwidth.

[0111] In one embodiment of the present application, the second processing unit includes a first processing module and a second processing module. The first processing module is used to retain the corresponding cloud network perception probe when the above-mentioned access time is less than the first preset duration; the second processing module is used to delete the corresponding cloud network perception probe when the above-mentioned access time is greater than or equal to the first preset duration.

[0112] In one embodiment of the present application, the first processing module includes a first processing submodule, which is used to retain the corresponding cloud network perception probe in the execution queue;

[0113] The second processing module includes a second processing submodule, which is used to delete the corresponding cloud network perception probe from the execution queue when the access time is greater than or equal to the first preset duration;

[0114] The above-mentioned device also includes a third processing unit, which is used to deduplicate at least part of all the above-mentioned cloud network perception probes according to the above-mentioned monitoring category and the corresponding access time, and before obtaining the final cloud network perception probe group, first store all the above-mentioned cloud network perception probes in a waiting queue, and then transfer part of the above-mentioned cloud network perception probes from the waiting queue to the above-mentioned execution queue every second preset time period, and the above-mentioned second preset time period is less than the above-mentioned first preset time period.

[0115] In one embodiment of the present application, the first processing unit includes a third processing module, which is used to use the proxy probe in the cloud network perception center to obtain the monitoring category of each cloud network perception probe, and to use the proxy probe in the cloud network perception center to obtain network quality parameters, wherein the network quality parameters include PING average delay, maximum delay, minimum delay, buffer delay and packet loss;

[0116] The above-mentioned device also includes a determination unit, which is used to determine whether the above-mentioned cloud network perception probe is qualified according to the above-mentioned network quality parameters and the corresponding access time after executing the above-mentioned cloud network perception probe of the above-mentioned final cloud network perception probe group.

[0117] In one embodiment of the present application, the determination unit includes a determination module, which is used to determine whether the above-mentioned cloud network perception probe is qualified based on at least the size of all delay differences and benchmark differences, and the above-mentioned delay difference is the difference between the delay in the above-mentioned network quality parameters and the preset delay of the above-mentioned cloud network perception probe.

[0118] In one embodiment of the present application, the determination module includes a third processing sub-module, a first determination sub-module and a second determination sub-module; the third processing sub-module is used to sum all the above-mentioned delay differences to obtain the sum of the delay differences; the first determination sub-module is used to determine that the above-mentioned cloud network perception probe is qualified when the sum of the above-mentioned delay differences is less than or equal to the above-mentioned benchmark difference, so as to apply the above-mentioned cloud network perception probe to subsequent monitoring work; the second determination sub-module is used to determine that the above-mentioned cloud network perception probe is unqualified when the sum of the above-mentioned delay differences is greater than the above-mentioned benchmark difference.

[0119] In one embodiment of the present application, the determination module includes a third determination submodule, a fourth processing submodule, a fourth determination submodule and a fifth determination submodule; the third determination submodule is used to determine multiple delay difference correction results, the delay difference correction result is the sum of the delay difference and the corresponding correction value, and the correction value has a mapping relationship with the monitoring category of the delay difference; the fourth processing submodule is used to sum all the delay difference correction results to obtain the final delay sum value; the fourth determination submodule is used to determine that the cloud network perception probe is qualified when the final delay sum value is less than or equal to the benchmark difference value, so as to apply the cloud network perception probe to subsequent monitoring work; the fifth determination submodule is used to determine that the cloud network perception probe is unqualified when the final delay sum value is greater than the benchmark difference value.

[0120] The cloud network perception processing device includes a processor and a memory. The acquisition unit, the first processing unit, the second processing unit, etc. are all stored in the memory as program units, and the processor executes the program units stored in the memory to implement corresponding functions. The modules are all located in the same processor; or, the modules are located in different processors in any combination.

[0121] The processor includes a kernel, which calls the corresponding program unit from the memory. One or more kernels can be set, and the kernel parameters can be adjusted to solve the problem that the existing solution uses bandwidth resources for network quality monitoring, resulting in less user service bandwidth.

[0122] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0123] An embodiment of the present invention provides a computer-readable storage medium, which includes a stored program, wherein when the program is running, the device where the computer-readable storage medium is located is controlled to execute the cloud-network perception processing method.

[0124] An embodiment of the present invention provides a processor, which is used to run a program, wherein the cloud-network perception processing method is executed when the program is running.

[0125] An embodiment of the present invention provides a device, the device includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, at least the following steps are implemented: using ITMS and cloud platform technology and network perception neuron detection technology to establish a cloud network perception center to deploy and access massive cloud network perception probes; using proxy probes in the above cloud network perception center to obtain the monitoring category of each cloud network perception probe, the above monitoring category includes PING perception monitoring, video perception monitoring, web page perception monitoring and game perception monitoring; according to the above monitoring category and the corresponding access time, at least part of all the above cloud network perception probes are deduplicated to obtain the final cloud network perception probe group, and the above cloud network perception probes of the above final cloud network perception probe group are executed, the above access time represents the time interval for accessing two adjacent above cloud network perception probes with the same monitoring category. The device in this article can be a server, PC, PAD, mobile phone, etc.

[0126] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program that initializes at least the following method steps: using ITMS and cloud platform technology and network-aware neuron detection technology to establish a cloud-network perception center to deploy and access massive cloud-network perception probes; using proxy probes in the above-mentioned cloud-network perception center to obtain the monitoring category of each cloud-network perception probe, and the above-mentioned monitoring categories include PING perception monitoring, video perception monitoring, web page perception monitoring and game perception monitoring; according to the above-mentioned monitoring categories and corresponding access times, at least part of all the above-mentioned cloud-network perception probes are deduplicated to obtain a final cloud-network perception probe group, and the above-mentioned cloud-network perception probes of the above-mentioned final cloud-network perception probe group are executed, and the above-mentioned access time represents the time interval for accessing two adjacent above-mentioned cloud-network perception probes with the same monitoring category.

[0127] The present application also provides a cloud network perception processing system, which includes: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include for executing any one of the above methods.

[0128] Obviously, those skilled in the art should understand that the above modules or steps of the present invention can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order than here, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0129] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0130] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0131] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0132] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0133] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0134] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0135] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media 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 disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0136] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0137] From the above description, it can be seen that the above embodiments of the present application achieve the following technical effects:

[0138] 1) The cloud-network perception processing method of the present application adopts a proxy probe in the above-mentioned cloud-network perception center to obtain the monitoring category of each cloud-network perception probe, and deduplicates at least part of all the above-mentioned cloud-network perception probes according to the above-mentioned monitoring category and the corresponding access time to obtain the final cloud-network perception probe group, thereby reducing the bandwidth occupancy of the test channel and using more bandwidth to improve the actual business service quality of users, thereby solving the problem that the existing solution uses bandwidth resources for network quality monitoring, resulting in less user business bandwidth.

[0139] 2) The cloud network perception processing device of the present application adopts a proxy probe in the above-mentioned cloud network perception center to obtain the monitoring category of each cloud network perception probe, and deduplicates at least part of all the above-mentioned cloud network perception probes according to the above-mentioned monitoring category and the corresponding access time to obtain the final cloud network perception probe group, thereby reducing the bandwidth occupancy of the test channel and using more bandwidth to improve the actual business service quality of users, thereby solving the problem that the existing solution uses bandwidth resources for network quality monitoring, resulting in less user business bandwidth.

[0140] The above description is only the preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A cloud network perception processing method, characterized in that: include: Adopt ITMS and cloud platform technology and network perception neuron detection technology to establish a cloud network perception center to deploy and access massive cloud network perception probes; In the cloud network perception center, a proxy probe is used to obtain the monitoring category of each cloud network perception probe, and the monitoring category includes PING perception monitoring, video perception monitoring, web page perception monitoring and game perception monitoring; According to the monitoring category and the corresponding access time, at least part of all the cloud network perception probes are deduplicated to obtain a final cloud network perception probe group, and the cloud network perception probes of the final cloud network perception probe group are executed. The access time represents the time interval for accessing two adjacent cloud network perception probes with the same monitoring category.

2. The method according to claim 1, characterized in that According to the monitoring category and the corresponding access time, at least part of all the cloud network perception probes are deduplicated to obtain a final cloud network perception probe group, including: When the access time is less than the first preset duration, retaining the corresponding cloud network perception probe; When the access time is greater than or equal to the first preset duration, the corresponding cloud network perception probe is deleted.

3. The method according to claim 1, characterized in that When the access time is less than the first preset duration, reserving the corresponding cloud network perception probe includes: reserving the corresponding cloud network perception probe to an execution queue; When the access time is greater than or equal to the first preset duration, deleting the corresponding cloud network perception probe includes: deleting the corresponding cloud network perception probe from the execution queue; Before deduplicating at least part of all the cloud network perception probes according to the monitoring category and the corresponding access time to obtain the final cloud network perception probe group, the method also includes: first storing all the cloud network perception probes in a waiting queue, and then transferring part of the cloud network perception probes from the waiting queue to the execution queue every second preset time period, and the second preset time period is less than the first preset time period.

4. The method according to claim 1, characterized in that: In the process of using the proxy probe in the cloud network perception center to obtain the monitoring category of each cloud network perception probe, the method further includes: using the proxy probe in the cloud network perception center to obtain network quality parameters, the network quality parameters including PING average delay, maximum delay, minimum delay, buffer delay and packet loss; After executing the cloud-network perception probe of the final cloud-network perception probe group, the method further includes: determining whether the cloud-network perception probe is qualified according to the network quality parameter and the corresponding access time.

5. The method according to claim 4, characterized in that Determining whether the cloud network perception probe is qualified according to the network quality parameter and the corresponding access time includes: Whether the cloud network perception probe is qualified is determined at least based on the size of all delay differences and benchmark differences, and the delay difference is the difference between the delay in the network quality parameter and the preset delay of the cloud network perception probe.

6. The method according to claim 5, characterized in that At least according to the magnitude of all delay differences and benchmark differences, determining whether the cloud network perception probe is qualified includes: Sum all the delay differences to obtain a sum of the delay differences; When the sum of the delay differences is less than or equal to the reference difference, determining that the cloud network perception probe is qualified, so as to apply the cloud network perception probe to subsequent monitoring work; When the sum of the delay differences is greater than the benchmark difference, it is determined that the cloud network perception probe is unqualified.

7. The method according to claim 5, characterized in that At least according to the magnitude of all delay differences and benchmark differences, determining whether the cloud network perception probe is qualified includes: Determine a plurality of delay difference correction results, wherein the delay difference correction result is a sum of the delay difference and a corresponding correction value, and the correction value has a mapping relationship with the monitoring category of the delay difference; Summing all the delay difference correction results to obtain a final delay sum value; When the final delay sum is less than or equal to the reference difference, determining that the cloud network perception probe is qualified, so as to apply the cloud network perception probe to subsequent monitoring work; When the final delay sum value is greater than the benchmark difference value, it is determined that the cloud network perception probe is unqualified.

8. A cloud network perception processing device, characterized in that: include: The acquisition unit is used to establish a cloud network perception center using ITMS and cloud platform technology and network perception neuron detection technology to deploy and access massive cloud network perception probes; A first processing unit is used to use a proxy probe in the cloud network perception center to obtain a monitoring category of each cloud network perception probe, where the monitoring category includes PING perception monitoring, video perception monitoring, web page perception monitoring, and game perception monitoring; The second processing unit is used to deduplicate at least part of all the cloud network perception probes according to the monitoring category and the corresponding access time to obtain a final cloud network perception probe group, and execute the cloud network perception probes of the final cloud network perception probe group, wherein the access time represents the time interval for accessing two adjacent cloud network perception probes with the same monitoring category.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the method according to any one of claims 1 to 7.

10. A cloud network perception processing system, characterized in that: include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include methods for executing any one of claims 1 to 7.

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