Cloud network sensing processing method, apparatus, medium, and system

Abstract

The application provides a cloud network perception processing method, device, medium and system. By adopting an agent probe in a cloud network perception center to obtain a monitoring category of each cloud network perception probe, at least part of all cloud network perception probes is subjected to deduplication processing according to the monitoring category and a corresponding access time, and a final cloud network perception probe group is obtained, so that the occupation of bandwidth by a test channel is reduced, more bandwidth is used to improve the actual service quality of user services, and thus the problem that bandwidth resources are used for network quality monitoring in the prior art, resulting in that the user service bandwidth will become less, is solved.

Description

Technical Field

[0001] This application relates to the field of cloud network sensing technology, and more specifically, to a cloud network sensing processing method, apparatus, medium, and system. Background Technology

[0002] Based on various forms of network sensing neuron probes, such as webpage embedded probes, ONU optical modem probes, and OLT backbone network probes, network sensing neuron probes are used to actively detect and monitor the network quality at various levels. For ease of description, the various forms of existing network sensing neuron probes will be referred to as Smart probes.

[0003] like Figure 1 As shown, it is currently possible to monitor the average latency, maximum latency, minimum latency, latency variance, and network jitter of backbone network access to PING-aware services, target video portals, target game websites, and target portals using Smart probes. It can also monitor video access pauses, download speeds, and buffering latency.

[0004] Smart probes can be used to send data packets to simulate user access to a target website portal, obtaining data such as page loading latency, homepage latency, DNS latency, initial screen latency, connection latency, and response latency. Smart probes can also be used to execute video download interfaces, simulating user access to a target video server, obtaining data such as the number of video access pauses, download speed, and buffering latency. Furthermore, Smart probes can be used to simulate user access to and execution of a complete game process through game interfaces, obtaining data such as average game access latency, game server latency, and network jitter.

[0005] Currently, with a large number of users randomly initiating network quality monitoring, especially during peak evening hours when many users access video or game servers, network congestion leads to users actively initiating network quality checks. This forces the allocation of extremely valuable bandwidth resources to network quality monitoring, reducing bandwidth available for other users' business needs and resulting in a poor user experience. This, in turn, attracts even more users to network quality monitoring, creating a vicious cycle. A significant amount of bandwidth is consumed by monitoring traffic, severely impacting the user experience. The most noticeable effect for customers is slower video streaming or gaming during peak evening hours, leading them to actively initiate network quality monitoring on web pages, only to experience increasingly laggy performance until some users exit. This phenomenon directly degrades the gaming or video experience, leading to customer complaints.

[0006] 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 scheme uses bandwidth resources for network quality monitoring, resulting in less user service bandwidth.

[0008] To achieve the above-mentioned purpose, according to one aspect of the present application, a cloud network perception processing method is provided, the method comprising:

[0009] Using ITMS and cloud platform technology and network perception neuron detection technology, a cloud network perception center is established to deploy and access massive cloud network perception probes;

[0010] In the cloud network perception center, proxy probes are used to obtain the monitoring categories of each cloud network perception probe, including PING perception monitoring, video perception monitoring, webpage perception monitoring and game perception monitoring;

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

[0012] Optionally, according to the monitoring categories and corresponding access times, at least part of all cloud network perception probes are de-duplicated to obtain a final cloud network perception probe group, including: in the case that the access time is less than a first preset time length, retaining the corresponding cloud network perception probe; in the case that the access time is greater than or equal to the first preset time length, deleting the corresponding cloud network perception probe.

[0013] Optionally, in the case that the access time is less than a first preset time length, retaining the corresponding cloud network perception probe includes: retaining the corresponding cloud network perception probe in an execution queue; in the case that the access time is greater than or equal to the first preset time length, deleting the corresponding cloud network perception probe includes: deleting the corresponding cloud network perception probe from the execution queue; before de-duplicating at least part of all cloud network perception probes according to the monitoring categories and corresponding access times to obtain a final cloud network perception probe group, the method further includes: first storing all cloud network perception probes in a waiting queue, and then transferring part of the cloud network perception probes in the waiting queue to the execution queue every second preset time length, the second preset time length being less than the first preset time length.

[0014] Optionally, in the process of acquiring the monitoring categories of the cloud network perception probes by the proxy probe in the cloud network perception center, the method further comprises: acquiring network quality parameters by the proxy probe in the cloud network perception center, the network quality parameters comprising PING average delay, maximum delay, minimum delay, buffer delay and packet loss; after executing the cloud network perception probes of the final cloud network perception probe group, the method further comprises: determining whether the cloud network perception probe is qualified according to the network quality parameters and the corresponding access time.

[0015] Optionally, determining whether the cloud network perception probe is qualified according to the network quality parameters and the corresponding access time comprises: determining whether the cloud network perception probe is qualified according to at least the size of all delay difference values and a reference difference value, the delay difference value being the difference between the delay in the network quality parameters and a preset delay of the cloud network perception probe.

[0016] Optionally, determining whether the cloud network perception probe is qualified according to at least the size of all delay difference values and a reference difference value comprises: summing all the delay difference values to obtain a sum value of delay difference values; in the case that the sum value of delay difference values is less than or equal to the reference difference value, determining that the cloud network perception probe is qualified to be applied to subsequent monitoring work; in the case that the sum value of delay difference values is greater than the reference difference value, determining that the cloud network perception probe is unqualified.

[0017] Optionally, determining whether the cloud network perception probe is qualified according to at least the size of all delay difference values and a reference difference value comprises: determining a plurality of delay difference correction results, the delay difference correction result being the sum of the delay difference value and a corresponding correction value, the correction value having a mapping relationship with the monitoring category of the delay difference value; summing all the delay difference correction results to obtain a final delay sum value; in the case that the final delay sum value is less than or equal to the reference difference value, determining that the cloud network perception probe is qualified to be applied to subsequent monitoring work; in the case that the final delay sum value is greater than the reference 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, which comprises:

[0019] The acquisition unit is configured to acquire network quality parameters by the proxy probe in the cloud network perception center, the network quality parameters comprising PING average delay, maximum delay, minimum delay, buffer delay and packet loss; after executing the cloud network perception probes of the final cloud network perception probe group, the method further comprises: determining whether the cloud network perception probe is qualified according to the network quality parameters and the corresponding access time.

[0020] The first processing unit is configured to obtain, by using a proxy probe in the cloud network perception center, a monitoring category of each cloud network perception probe, wherein the monitoring category comprises PING perception monitoring, video perception monitoring, webpage perception monitoring and game perception monitoring.

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

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

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

[0024] By using a proxy probe in the cloud network perception center to obtain a monitoring category of each cloud network perception probe, and performing deduplication processing on at least part of all the cloud network perception probes according to the monitoring category and a corresponding access time to obtain a final cloud network perception probe group, the bandwidth occupied by the test channel is reduced, more bandwidth is used to improve the actual service quality of user business, and the problem that the bandwidth resource is used for network quality monitoring in the prior art, resulting in that the user business bandwidth becomes less, is solved. BRIEF DESCRIPTION OF DRAWINGS

[0025] The drawings accompanying the specification of the present application form a part of the specification and serve to further understand the present application, the illustrative embodiments of the present application and the description thereof, and do not constitute an improper limitation to the present application. In the drawings:

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

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

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

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

[0030] Figure 5 A flowchart of another cloud network perception processing method is shown according to an embodiment of the present application;

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

[0032] It should be noted that the embodiments and features of the embodiments in the present application can be combined with each other without conflict. 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 persons skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by persons skilled in the art without creative labor should belong to the scope of protection of the present application.

[0034] It should be noted that the terms "first", "second", and the like in the specification and claims of the present application and the above-described accompanying drawings are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device that includes a series of steps or units does not have to be limited to those steps or units clearly listed, but can 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, in the case of a large number of users randomly initiating network quality monitoring, especially in the evening peak period when a large number of users access video servers or game servers, once the network is congested, the user will actively initiate network quality detection, thereby having to use extremely valuable bandwidth resources for network quality monitoring, and the user service bandwidth will become less, the user experience is not good, then more users will enter the network quality monitoring, thus forming a vicious cycle, causing a large amount of bandwidth to be occupied by monitoring traffic, greatly affecting the user experience, and the biggest feeling of the customer is that the video or game is slow in the evening peak period, so the user initiates network quality monitoring on the webpage, and it becomes more and more slow until some users exit to relieve. This phenomenon will directly reduce the experience of games or videos, thereby causing customer complaints. To solve the problem that the existing scheme uses bandwidth resources for network quality monitoring, resulting in less user service bandwidth, 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 application will be clearly and completely described below with reference to the drawings in the embodiments of the present application.

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

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

[0039] Step S201, using ITMS and cloud platform technology and network perception neuron detection technology, establishing a cloud network perception center to deploy and access a large number of cloud network perception probes;

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

[0041] Network-aware neuron detection technology refers to a traffic detection technology based on neural networks and perception technology. It can obtain traffic data through monitoring cameras, sensors and other devices, and use neural network algorithms for data analysis and recognition to realize real-time monitoring and detection of traffic flow, vehicle type, speed and other information. This technology can help traffic management departments better understand road conditions and take timely measures to optimize traffic flow.

[0042] Based on the ITMS and cloud platform technology of telecommunications, combined with the network-aware 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 the ITMS and obtains the 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 backbone network arrival PING perception service, target video portal website, target game website, target portal website access average delay, maximum delay, minimum delay, delay variance, network jitter, etc.; 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 user access to target website portal to obtain webpage 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 video download interfaces through cloud network perception probes to simulate user access to target video server to obtain video access pause times, download rate, buffering delay, etc.; game service perception quality includes, but is not limited to, executing game interfaces through cloud network perception probes to simulate user access to execute a complete game process to obtain game access average delay, game server delay, network jitter, etc.).

[0044] Step S202, in the cloud network perception center, proxy probes are used to obtain the monitoring categories of each cloud network perception probe, including PING perception monitoring, video perception monitoring, webpage perception monitoring, and game perception monitoring.

[0045] Select network quality proxy cloud network perception probes: based on the data collected in step 2, perform big data mining to select reasonable proxy probes, such as Figure 3 As shown in the figure, the network quality proxy perception probe selection method 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 uplink backbone network as the proxy perception probe of the local area network 1 according to the network level and network structure.

[0047] When the user's typical structure is similar to a cybercafe, and the web version cloud network sensing probe is used to detect network quality, then in the parallel nodes of the response, one of them is selected as the proxy sensing probe by a method similar to arbitration.

[0048] As Figure 3 2.1 as a proxy probe. The selection principle of the network quality proxy cloud network sensing probe is to be as close as possible to the user's cloud network sensing probe, at the same level or one level higher. After the cloud network sensing center selects the proxy monitoring point for each cloud network sensing probe, it simultaneously issues the positive and negative deviation list of each parameter of the cloud network sensing probe and the proxy sensing probe (for ease of description, assume that the network delay of 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. The positive and negative deviation list is (0.1, 0.2, -0.1)).

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

[0050] Step S203, according to the above monitoring category and the corresponding access time, at least part of all the above cloud network sensing probes is processed to obtain the final cloud network sensing probe group, and the above cloud network sensing probe of the above final cloud network sensing probe group is executed. The access time represents the time interval of accessing two adjacent cloud network sensing probes with the same monitoring category.

[0051] In the above steps, the monitoring category of each cloud network sensing probe is obtained by using a proxy probe in the cloud network sensing center, and at least part of all the cloud network sensing probes is processed according to the monitoring category and the corresponding access time to obtain the final cloud network sensing probe group, thereby reducing the occupation of the test channel to the bandwidth, and more bandwidth is used to improve the actual service quality of the user's business, thereby solving the problem that the existing scheme uses bandwidth resources for network quality monitoring, resulting in that the user's business bandwidth will become less.

[0052] That is, the application selects appropriate network quality proxy perception probes based on the network architecture level and network quality parameter statistics of each cloud network perception probe in the cloud network perception center. Then, when the test application sent by each is executed by the proxy perception probe, it is filtered according to Δt and the test item, rather than completely forwarded in order, thereby greatly reducing the bandwidth occupation of the test channel and using more bandwidth to improve the actual service quality of users, such as brushing videos or playing games, and the network will not be further jammed due to the large number of active tests initiated by users, thereby improving user satisfaction and reducing complaints.

[0053] In 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 certain cloud network perception probe of the entire cloud network perception system) is found. For 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 peer probe or a backbone network probe at the next level. The proxy is not a traditional forwarding proxy, but a proxy that filters a part of the same type of monitoring tasks according to the set network sensitivity (Δt) to reduce network bandwidth consumption.

[0054] Among them, according to the above monitoring category and the corresponding access time, at least part of all the above cloud network perception probes is processed to obtain a final cloud network perception probe group, including:

[0055] In the case where the above-mentioned access time is less than the first preset time length, the corresponding cloud network perception probe is retained;

[0056] Among them, the specific implementation mode is: retaining the corresponding cloud network perception probe into the execution queue.

[0057] In the case where the above-mentioned access time is greater than or equal to the first above-mentioned preset time length, the corresponding cloud network perception probe is deleted.

[0058] Among them, the specific implementation mode is: deleting the corresponding cloud network perception probe from the execution queue.

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

[0060] Specifically, the proxy-aware probe performs network quality monitoring: the network quality-aware probe does not simply receive relevant instructions to directly initiate network monitoring, which does not reduce network bandwidth occupation. In the proxy, two queues are established: the first queue is a monitoring application queue, which records the actual entry time, source, monitoring category, monitoring target service address, and monitoring item of each task, as shown in Table 1.

[0061] Table 1

[0062]

[0063]

[0064]

[0065] The second queue is a monitoring execution queue: the proxy-aware probe is based on a de-duplication time (Δt, i.e., a first preset time length, and a second preset time length can be 10s) set at initialization, for the convenience of observation, 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 directly return the execution result of the project in the monitoring queue. The size of Δt can be freely adjusted according to the sensitivity of the user to the monitoring data, and is not fixed at 30 seconds. The de-duplication process is shown in Table 2.

[0066] Table 2

[0067]

[0068]

[0069]

[0070] The 2.1 proxy probe in Table 2 receives a total of 37 monitoring applications from the 2.2, 2.3, and 2.4 probes, and actually executes 5 times, which is shorter in monitoring network speed time and fewer in connection initiation times than the traditional Smart probe directly connected to each monitoring service, thereby saving bandwidth. After obtaining the monitoring result, it is sent to the corresponding cloud network-aware probe, and the same monitoring application entering within Δt is directly returned to the current valid monitoring result.

[0071] In an embodiment of the present application, in the process of using the proxy probe in the cloud network-aware center to obtain the monitoring category of each cloud network-aware probe, the above method further comprises: using the proxy probe in the cloud network-aware center to obtain network quality parameters, the network quality parameters including PING average delay, maximum delay, minimum delay, buffer delay, and packet loss situation.

[0072] After executing the cloud network perception probe, the method further comprises: determining whether the cloud network perception probe is qualified according to the network quality parameters and the corresponding access time.

[0073] Wherein, for how to determine whether the cloud network perception probe is qualified, at least according to the size of all delay difference values and the reference difference value, determine whether the cloud network perception probe is qualified, the delay difference value is the difference between the delay time in the network quality parameter and the preset delay of the cloud network perception probe.

[0074] Based on this, the present application provides two specific implementation modes:

[0075] The first specific implementation mode (only according to the size of all delay difference values and reference difference values) is:

[0076] Sum all the delay difference values to get the sum of delay difference values;

[0077] In the case where the sum of delay difference values is less than or equal to the reference difference value, it is determined that the cloud network perception probe is qualified, so as to apply the cloud network perception probe to subsequent monitoring work;

[0078] In the case where the sum of delay difference values is greater than the reference difference value, it is determined that the cloud network perception probe is unqualified.

[0079] Specifically, a mapping relationship between the reference difference value and the name of the monitoring category is constructed, and the size of the sum of delay difference values and the reference difference value is compared in the form of the mapping relationship, so as to determine whether the cloud network perception probe is qualified, so as to filter out the cloud network perception probe with better network quality.

[0080] The second specific implementation mode (according to the size of all delay difference values, reference difference values and correction values) is:

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

[0082] Sum all the delay difference correction results to get the final delay sum;

[0083] In the case where the final delay sum is less than or equal to the reference difference value, it is determined that the cloud network perception probe is qualified, so as to apply the cloud network perception probe to subsequent monitoring work;

[0084] In the case where the final delay sum is greater than the reference difference value, it is determined that the cloud network perception probe is unqualified.

[0085] The name of each monitoring category is mapped with the correction value, the corresponding correction value is found in the mapping relationship, the difference between the delay in the network quality parameter and the preset delay of the cloud network perception probe (set delay difference) and the correction value are summed, and the summation is accumulated according to this calculation method. In the case where the final delay sum is less than or equal to the reference difference, it is determined that the cloud network perception probe is qualified. The cloud network perception probe is applied to subsequent monitoring work, so that the network environment of subsequent monitoring work is more stable. Therefore, compared with the first specific implementation mode, the result obtained by the second specific implementation mode is more consistent with the actual working condition.

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

[0087] Table 3

[0088]

[0089]

[0090]

[0091] In order for those skilled in the art to more clearly understand the technical solutions 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 conjunction with specific embodiments.

[0092] The present embodiment relates to a specific cloud network perception processing method, as shown in Figure 5 The present embodiment relates to a specific cloud network perception processing method, as shown in

[0093] Cloud network perception center initialization: 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 massively deploy and access cloud network perception probes; when each cloud network perception probe is initially started, network quality detection is initiated according to the instructions of the ITMS, and initial network quality data is obtained;

[0094] Specifically, the ITMS and cloud platform technology and network perception neuron detection technology 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; the network quality parameters include PING perception quality, portal website access quality, video service perception quality and game service perception quality (the PING perception quality includes, but is not limited to, monitoring backbone network arrival PING perception service, target video portal website, target game website, target portal website access average delay, maximum delay, minimum delay, delay variance, network jitter, etc.; video access pause times, download rate, buffering delay, etc.; the portal website access quality includes, but is not limited to, sending a data packet through the cloud network perception probe, simulating user access to the target website portal to obtain webpage access white screen delay, homepage delay, DNS delay, first screen delay, connection delay, response delay, etc.; the video service perception quality includes, but is not limited to, executing a video download interface through the cloud network perception probe, simulating user access to the target video server to obtain video access pause times, download rate, buffering delay, etc.; the game service perception quality includes, but is not limited to, executing a game interface through the cloud network perception probe, simulating user access to execute a complete game process to obtain game access average delay, game server delay, network jitter, etc.);

[0096] Specifically, in the cloud network perception center, the proxy probe is used to obtain the monitoring categories of each cloud network perception probe, and the monitoring categories include PING perception monitoring, video perception monitoring, webpage perception monitoring and game perception monitoring; in the cloud network perception center, the proxy probe is used to obtain network quality parameters, and the network quality parameters include PING average delay, maximum delay, minimum delay, buffering delay and packet loss condition;

[0097] Selecting a network quality proxy cloud network perception probe: based on the collected data, big data mining is performed to select a reasonable proxy cloud network perception probe;

[0098] Initiating 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 user request to initiate network quality monitoring, the network monitoring category, terminal server address, required network quality monitoring item and other related parameters are sent to the proxy perception probe;

[0099] The proxy perception probe performs network quality monitoring: the network quality perception probe does not simply receive related instructions and directly initiate network monitoring, which cannot reduce the purpose of network bandwidth occupation. In the proxy, two queues are established;

[0100] According to the monitoring category and the corresponding access time, at least part of all cloud network perception probes are de-duplicated 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, and the access time represents a time interval of accessing two adjacent cloud network perception probes with the same monitoring category;

[0101] After the cloud network perception probes of the final cloud network perception probe group are executed, a plurality of delay difference correction results are determined, the delay difference correction result is a sum of a delay difference and a corresponding correction value, the correction value has a mapping relationship with the monitoring category of the delay difference, and a final delay sum value is obtained by summing all delay difference correction results;

[0102] In a case where the final delay sum value is less than or equal to a reference difference value, it is determined that the cloud network perception probe is qualified, so as to apply the cloud network perception probe to subsequent monitoring work; in a case where the final delay sum value is greater than the reference difference value, it is determined that the cloud network perception probe is unqualified.

[0103] 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 a logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in an order different from that shown herein.

[0104] The cloud network perception processing device provided in the embodiments of the present application can be used to execute the cloud network perception processing method provided in the embodiments of the present application. The device is used to realize the above-mentioned embodiments and preferred embodiments, and details are not repeated. As used below, the term "module" can be a combination of software and / or hardware that realizes a predetermined function. Although the device described in the following embodiments is preferably realized in software, hardware or a combination of software and hardware is also possible and is contemplated.

[0105] The cloud network perception processing device provided in the embodiments of the present application is introduced below.

[0106] Figure 6 is a structural block diagram of a cloud network perception processing device according to the embodiments of the present application. As shown in Figure 6 , the device includes:

[0107] The acquisition unit 61 is configured to use ITMS and cloud platform technology and network perception neuron detection technology to establish a cloud network perception center to deploy and access a large number of cloud network perception probes;

[0108] The first processing unit 62 is configured to obtain the monitoring categories of the cloud network perception probes by using the probe in the cloud network perception center, and the monitoring categories include PING perception monitoring, video perception monitoring, webpage perception monitoring, and game perception monitoring.

[0109] The second processing unit 63 is configured to perform deduplication processing on at least part of all the cloud network perception probes according to the monitoring categories and corresponding access times to obtain a final cloud network perception probe group, and execute the cloud network perception probes in the final cloud network perception probe group, and the access time represents a time interval for accessing two adjacent cloud network perception probes with the same monitoring category.

[0110] In the device, the monitoring categories of the cloud network perception probes are obtained by using the proxy probe in the cloud network perception center, and deduplication processing is performed on at least part of all the cloud network perception probes according to the monitoring categories and corresponding access times to obtain a final cloud network perception probe group, so that the occupation of the bandwidth by the test channel is reduced, more bandwidth is used to improve the actual service quality of the user, and the problem that the bandwidth resource is used for network quality monitoring in the prior art, resulting in that the user service bandwidth becomes less, is solved.

[0111] In an embodiment of the present application, the second processing unit includes a first processing module and a second processing module, the first processing module is configured to retain the corresponding cloud network perception probe when the access time is less than a first preset time length, and the second processing module is configured to delete the corresponding cloud network perception probe when the access time is greater than or equal to the first preset time length.

[0112] In an embodiment of the present application, the first processing module includes a first processing submodule configured to retain the corresponding cloud network perception probe in an execution queue.

[0113] The second processing module includes a second processing submodule configured 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 time length.

[0114] The device further includes a third processing unit configured to store all the cloud network perception probes in a waiting queue before performing deduplication processing on at least part of all the cloud network perception probes according to the monitoring categories and corresponding access times to obtain a final cloud network perception probe group, and then transfer part of the cloud network perception probes in the waiting queue to an execution queue at a second preset time length, and the second preset time length is less than the first preset time length.

[0115] In an embodiment of the present application, the first processing unit comprises a third processing module, configured to acquire network quality parameters by using the proxy probe in the cloud network perception center in the process of acquiring the monitoring category of each cloud network perception probe by using the proxy probe in the cloud network perception center, wherein the network quality parameters comprise PING average delay, maximum delay, minimum delay, buffer delay and packet loss condition.

[0116] The device further comprises a determination unit, configured to determine whether the cloud network perception probe is qualified according to the network quality parameters and the corresponding access time after executing the cloud network perception probe of the final cloud network perception probe group.

[0117] In an embodiment of the present application, the determination unit comprises a determination module, configured to determine whether the cloud network perception probe is qualified according to at least the size of all delay difference values and a reference difference value, wherein the delay difference value is the difference between the delay time in the network quality parameters and a preset delay of the cloud network perception probe.

[0118] In an embodiment of the present application, the determination module comprises a third processing submodule, a first determination submodule and a second determination submodule; the third processing submodule is configured to sum all the delay difference values to obtain a sum value of delay difference values; the first determination submodule is configured to determine that the cloud network perception probe is qualified to apply the cloud network perception probe to subsequent monitoring work in the case that the sum value of delay difference values is less than or equal to the reference difference value; and the second determination submodule is configured to determine that the cloud network perception probe is unqualified in the case that the sum value of delay difference values is greater than the reference difference value.

[0119] In an embodiment of the present application, the determination module comprises a third determination submodule, a fourth processing submodule, a fourth determination submodule and a fifth determination submodule; the third determination submodule is configured to determine a plurality of delay difference correction results, wherein the delay difference correction result is the sum of the delay difference value and a corresponding correction value, and the correction value has a mapping relationship with the monitoring category of the delay difference value; the fourth processing submodule is configured to sum all the delay difference correction results to obtain a final delay sum value; the fourth determination submodule is configured to determine that the cloud network perception probe is qualified to apply the cloud network perception probe to subsequent monitoring work in the case that the final delay sum value is less than or equal to the reference difference value; and the fifth determination submodule is configured to determine that the cloud network perception probe is unqualified in the case that the final delay sum value is greater than the reference 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, and the like are stored in the memory as program units, and the corresponding functions are realized by the processor executing the program units stored in the memory.

[0121] The processor includes a core, and the core calls the corresponding program units in the memory.

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

[0123] The embodiment of the application provides a computer readable storage medium, and the computer readable storage medium includes a stored program.

[0124] The embodiment of the application provides a processor, and the processor is used for running a program.

[0125] The embodiment of the application provides a device, and the device includes a processor, a memory, and a program stored in the memory and capable of running on the processor.

[0126] The application also provides a computer program product, when executed on a data processing device, is adapted to execute a program which is initialized with at least the following method steps: using ITMS and cloud platform technology and network perception neuron detection technology, a cloud network perception center is established to deploy and access massive cloud network perception probes; in the cloud network perception center, an agent probe is used to obtain a monitoring category of each cloud network perception probe, the monitoring category includes PING perception monitoring, video perception monitoring, webpage perception monitoring and game perception monitoring; according to the monitoring category and a corresponding access time, at least part of all the cloud network perception probes are subjected to a deduplication process to obtain a final cloud network perception probe group, and the cloud network perception probes in the final cloud network perception probe group are executed, and the access time represents a time interval of accessing two adjacent cloud network perception probes of the same monitoring category.

[0127] The application also provides a cloud network perception processing system, which comprises 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 comprise a program for executing any one of the methods.

[0128] Obviously, those skilled in the art should understand that each module or each step of the application can be realized by a general computing device, which can be concentrated on a single computing device or distributed on a network composed of multiple computing devices, and can be realized by program codes executable by a computing device, so that they can be stored in a storage device and executed by a computing device, and in some cases, the steps shown or described can be executed in different order, or they can be respectively manufactured into each integrated circuit module, or multiple modules or steps can be manufactured into a single integrated circuit module. Therefore, the application is not limited to any specific combination of hardware and software.

[0129] Those skilled in the art should understand that the embodiments of the application can be provided as a method, a system or a computer program product. Therefore, the application can be in the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware aspects. Moreover, the application can be in the form of a computer program product implemented on one or more computer usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer usable program codes.

[0130] The computer program instructions can 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 block or blocks. Figure 1 one or more flow or blocks Figure 1 one or more flow or blocks

[0131] These computer program instructions can 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 instructions which implement the function specified in the flowchart block or blocks. Figure 1 one or more flow or blocks Figure 1 one or more flow or blocks

[0132] The computer program instructions can 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 block or blocks. Figure 1 one or more flow or blocks Figure 1 one or more flow or blocks

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

[0134] The memory can include non-persistent memory and / or persistent memory, for example, read only memory (ROM) and / or flash memory, for example, random access memory (RAM). The memory is an example of computer readable media.

[0135] Computer-readable media includes 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 disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible to a computing device. According to the definition herein, computer-readable media does not include transitory media such as modulated data signals and carriers.

[0136] It should also be noted that the terms "comprising", "including" or any other variant thereof are intended to cover non-exclusive inclusion, so that processes, methods, articles or devices including a series of elements not only include those elements, but also include other elements not explicitly listed or inherent to such processes, methods, articles or devices. Without more limitations, the element defined by the statement "comprising a" does not exclude the presence of another identical element in the process, method, article or device including the element.

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

[0138] 1) The cloud network perception processing method of the present application obtains the monitoring categories of each cloud network perception probe by using the proxy probe in the cloud network perception center, and performs deduplication processing on at least part of all cloud network perception probes according to the monitoring categories and corresponding access times, to obtain a final cloud network perception probe group, thereby reducing the occupation of bandwidth by the test channel, using more bandwidth to improve the actual service quality of user business, and thereby solving the problem that the existing scheme uses bandwidth resources for network quality monitoring, resulting in less user business bandwidth.

[0139] 2) The cloud network sensing processing device of this application obtains the monitoring category of each cloud network sensing probe by using proxy probes in the cloud network sensing center. Based on the monitoring category and the corresponding access time, at least some of the cloud network sensing probes are deduplicated to obtain the final cloud network sensing probe group. This reduces the bandwidth occupation of the test channel and allows more bandwidth to be used to improve the actual service quality of users. This solves the problem that existing solutions use bandwidth resources for network quality monitoring, resulting in less bandwidth for user services.

[0140] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A cloud-network-aware processing method, characterized in that, The method comprises the steps of: adopting 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; adopting an agent probe in the cloud network perception center to obtain the monitoring categories of each cloud network perception probe, wherein the monitoring categories comprise PING perception monitoring, video perception monitoring, webpage perception monitoring and game perception monitoring; performing the cloud network perception probes of the final cloud network perception probe group according to the monitoring categories and corresponding access times, wherein the access times represent the time intervals of accessing two adjacent cloud network perception probes with the same monitoring category.

2. The method of claim 1, wherein, The method for performing the cloud network perception probes of the final cloud network perception probe group according to the monitoring categories and corresponding access times comprises the steps of: in the case that the access time is less than a first preset time length, retaining the corresponding cloud network perception probe; in the case that the access time is greater than or equal to the first preset time length, deleting the corresponding cloud network perception probe.

3. The method according to claim 1, wherein in the case that the access time is less than a first preset time length, retaining the corresponding cloud network perception probe comprises retaining the corresponding cloud network perception probe in an execution queue; in the case that the access time is greater than or equal to the first preset time length, deleting the corresponding cloud network perception probe comprises deleting the corresponding cloud network perception probe from the execution queue; before performing the cloud network perception probes of the final cloud network perception probe group according to the monitoring categories and corresponding access times, the method further comprises the steps of: firstly storing all the cloud network perception probes in a waiting queue, and then transferring part of the cloud network perception probes in the waiting queue to the execution queue every second preset time length, wherein the second preset time length is less than the first preset time length.

4. The method according to claim 1, wherein in the process of adopting an agent probe in the cloud network perception center to obtain the monitoring categories of each cloud network perception probe, the method further comprises the step of: adopting the agent probe in the cloud network perception center to obtain network quality parameters, wherein the network quality parameters comprise PING average delay, maximum delay, minimum delay, buffer delay and packet loss condition; after performing the cloud network perception probes of the final cloud network perception probe group, the method further comprises the step of: determining whether the cloud network perception probes are qualified according to the network quality parameters and corresponding access times.

5. The method of claim 4, wherein, The method for determining whether the cloud network perception probes are qualified according to the network quality parameters and corresponding access times comprises the steps of: determining whether the cloud network perception probes are qualified according to at least the sizes of all delay difference values and a reference difference value, wherein the delay difference value is the difference between the delay time in the network quality parameters and a preset delay of the cloud network perception probe.

6. The method of claim 5, wherein, Determine whether the cloud network perception probe is qualified according to at least magnitudes of all delay difference values and a reference difference value, including: Sum all the delay difference values to obtain a sum value of delay difference values; In a case where the sum value of delay difference values is less than or equal to the reference difference value, determine that the cloud network perception probe is qualified, so as to apply the cloud network perception probe to subsequent monitoring work; In a case where the sum value of delay difference values is greater than the reference difference value, determine that the cloud network perception probe is unqualified.

7. The method of claim 5, wherein, Determine whether the cloud network perception probe is qualified according to at least magnitudes of all delay difference values and a reference difference value, including: Determine a plurality of delay difference correction results, the delay difference correction result being a sum value of the delay difference value and a corresponding correction value, the correction value having a mapping relationship with the monitoring category of the delay difference value; Sum all the delay difference correction results to obtain a final delay sum value; In a case where the final delay sum value is less than or equal to the reference difference value, determine that the cloud network perception probe is qualified, so as to apply the cloud network perception probe to subsequent monitoring work; In a case where the final delay sum value is greater than the reference difference value, determine that the cloud network perception probe is unqualified.

8. A cloud-aware processing apparatus, characterized by, Including: An acquisition unit is configured to establish a cloud network perception center by using ITMS and cloud platform technology and network perception neuron detection technology, so as to deploy and access a large number of cloud network perception probes; A first processing unit is configured to acquire a monitoring category of each cloud network perception probe by using a proxy probe in the cloud network perception center, the monitoring category including PING perception monitoring, video perception monitoring, webpage perception monitoring and game perception monitoring; A second processing unit is configured to perform a deduplication processing on at least part of all the cloud network perception probes according to the monitoring category and a corresponding access time, so as to obtain a final cloud network perception probe group, and execute the cloud network perception probe of the final cloud network perception probe group, the access time representing a time interval of 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 the program controls a device where the computer readable storage medium is located to execute the method in any one of claims 1 to 7 when the program is running.

10. A cloud-aware processing system, characterized in that, Including: One or more processors, memories, and one or more programs, wherein the one or more programs are stored in the memories and configured to be executed by the one or more processors, and the one or more programs include programs for executing the method in any one of claims 1 to 7.

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