Method and apparatus for acquiring node performance data, and computer device and storage medium

Abstract

The present application relates to a method and apparatus for acquiring node performance data, and a computer device and a storage medium, and relates to the technical field of artificial intelligence. The method comprises: predicting the popularity of media to be played to obtain a predicted popularity value of said media; on the basis of the predicted popularity value of said media, simulating a user terminal sending a media access request to a service node to be tested; and in the process of said service node responding to the media access request, monitoring said service node to acquire performance indicator data of said service node. By means of the present application, acquired performance indicator data can more accurately reflect the operation performance of a service node to be tested in actual operation scenarios.

Description

Method, device, computer equipment and storage medium for obtaining node performance data

[0001] Related applications

[0002] This application claims priority to Chinese patent application number 202311284590.0, filed on September 28, 2023, entitled “Method, device, computer equipment and storage medium for obtaining node performance data,” the entire text of which is hereby incorporated by reference. Technical Field

[0003] The present application relates to the field of artificial intelligence technology, and in particular to a method, apparatus, computer equipment, and storage medium for acquiring node performance data. Background Art

[0004] Before performing performance analysis on a service node, it is necessary to randomly generate the media that the user wants to access, and then simulate the user's playback operation of the media by accessing the service node. During this process, the service node is monitored to obtain performance indicator data of the service node.

[0005] However, when simulating user access to service nodes, the impact of user access popularity on node performance data is not considered. As a result, the performance indicator data obtained through traditional technologies is less accurate and cannot accurately reflect the actual situation of the service nodes.

[0006] Summary of the Invention

[0007] In view of this, it is necessary to provide a method, apparatus, computer equipment and storage medium for obtaining node performance data that can accurately obtain performance indicator data in response to the above technical problems.

[0008] In a first aspect, the present application provides a method for obtaining node performance data. The method comprises:

[0009] Predict the popularity of the media to be played and obtain the predicted popularity value of the media to be played;

[0010] According to the predicted popularity value of the media to be played, the simulated user terminal sends a media access request to the service node to be detected;

[0011] During the process of the service node to be detected responding to the media access request, the service node to be detected is monitored to obtain performance indicator data of the service node to be detected.

[0012] In one embodiment, based on the predicted popularity value of the to-be-played media, simulating a user terminal to send a media access request to a service node to be detected includes:

[0013] A traffic transmitter is used to simulate a user terminal sending a media access request to the service node to be detected based on the predicted popularity value of the media to be played.

[0014] In one embodiment, a traffic transmitter is used to simulate a user terminal sending a media access request to a service node to be detected based on the predicted popularity value of the media to be played, including:

[0015] A traffic transmitter is used to simulate a user terminal to construct a media access request carrying a resource locator (URL) according to the predicted popularity value of the media to be played, and send the media access request to the service node to be detected.

[0016] In one embodiment, the number of media to be played is at least two, and a traffic transmitter is used to simulate a user terminal to construct a media access request carrying a resource locator (URL) based on the predicted popularity value of the media to be played, including:

[0017] For each medium to be played, the predicted number of visits of the medium to be played is determined according to the predicted popularity value of the medium to be played;

[0018] A traffic transmitter is used to simulate a user terminal to construct a predicted number of media access requests for the media to be played; each media access request carries the URL corresponding to the media to be played.

[0019] In one embodiment, predicting the popularity of the to-be-played media to obtain the predicted popularity value of the to-be-played media includes:

[0020] The media to be played is input into the heat analysis model to obtain the predicted heat value of the media to be played output by the heat analysis model.

[0021] In one embodiment, the training process of the heat analysis model includes:

[0022] Obtain the historical playback media and historical popularity values ​​of IPTV;

[0023] The initial model is trained based on the historical playback media and the historical popularity values ​​of the historical playback media to obtain a popularity analysis model.

[0024] In one embodiment, the media to be played is a video to be played.

[0025] In a second aspect, the present application also provides a device for acquiring node performance data. The device includes:

[0026] A prediction module is used to predict the popularity of the media to be played and obtain a predicted popularity value of the media to be played;

[0027] A sending module, configured to simulate a user terminal sending a media access request to a service node to be detected based on the predicted popularity value of the media to be played;

[0028] The monitoring module is used to monitor the service node to be detected during the process of the service node to be detected responding to the media access request, so as to obtain performance indicator data of the service node to be detected.

[0029] In one embodiment, the sending module further includes:

[0030] a determination unit, configured to determine, for each medium to be played, a predicted number of visits of the medium to be played according to the predicted popularity value of the medium to be played;

[0031] The construction unit is used to use a traffic transmitter to simulate a user terminal to construct a media access request of the to-be-played media with a predicted access volume; each media access request carries a resource locator (URL) corresponding to the to-be-played media.

[0032] In one embodiment, the apparatus further includes a training module for inputting the to-be-played media into a heat analysis model to obtain a predicted heat value of the to-be-played media output by the heat analysis model.

[0033] In one embodiment, the training module further includes:

[0034] An acquisition unit, configured to acquire historical playback media and historical popularity values ​​of the historical playback media of an Internet Protocol television (IPTV);

[0035] The training unit is used to train the initial model according to the historical playback media and the historical popularity values ​​of the historical playback media to obtain the popularity analysis model.

[0036] In a third aspect, the present application further provides a computer device. The computer device includes a memory and a processor. The memory stores a computer program. When the processor executes the computer program, the following steps are performed:

[0037] Predict the popularity of the media to be played and obtain the predicted popularity value of the media to be played;

[0038] According to the predicted popularity value of the media to be played, the simulated user terminal sends a media access request to the service node to be detected;

[0039] During the process of the service node to be detected responding to the media access request, the service node to be detected is monitored to obtain performance indicator data of the service node to be detected.

[0040] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the following steps:

[0041] Predict the popularity of the media to be played and obtain the predicted popularity value of the media to be played;

[0042] According to the predicted popularity value of the media to be played, the simulated user terminal sends a media access request to the service node to be detected;

[0043] During the process of the service node to be detected responding to the media access request, the service node to be detected is monitored to obtain performance indicator data of the service node to be detected.

[0044] In a fifth aspect, the present application further provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the following steps:

[0045] Predict the popularity of the media to be played and obtain the predicted popularity value of the media to be played;

[0046] According to the predicted popularity value of the media to be played, the simulated user terminal sends a media access request to the service node to be detected;

[0047] During the process of the service node to be detected responding to the media access request, the service node to be detected is monitored to obtain performance indicator data of the service node to be detected.

[0048] The above-mentioned method, apparatus, computer device, and storage medium for obtaining node performance data predict the predicted heat value of the media to be played, thereby simulating a user terminal to send a media access request to the service node to be detected based on the predicted heat value of the media to be played. Furthermore, during the process of the service node to be detected responding to the media access request, the service node to be detected is monitored to obtain performance indicator data of the service node to be detected. Because in the above-mentioned process, when the simulated user terminal sends a media access request to the service node to be detected, it does not send the media access request to the service node to be detected based on a randomly generated media simulated user, but rather uses a simulated user of the media to be played in an actual scenario to send the media access request to the service node to be detected. Furthermore, when the simulated user terminal sends a media access request to the service node to be detected, the predicted number of visits to the media to be played is determined based on the predicted heat value of the media to be played, so as to adjust the situation of sending the media access request to the service node to be detected. Therefore, the obtained performance indicator data can more accurately reflect the operating performance of the service node to be detected in the actual operating scenario. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the following briefly introduces the drawings required for use in the embodiments or related technology descriptions. Obviously, the drawings described below are only some embodiments of this application. For those of ordinary skill in the art, other drawings can be derived from these drawings without inventive effort.

[0050] FIG1 is a diagram showing an application environment of a method for acquiring node performance data provided in an embodiment of the present application.

[0051] FIG2 is a flowchart of a method for obtaining node performance data provided in an embodiment of the present application.

[0052] FIG3 is a schematic diagram of a process for constructing a media access request according to an embodiment of the present application.

[0053] FIG4 is a flow chart of a training heat analysis model according to an embodiment of the present application.

[0054] FIG5 is a flowchart of a method for obtaining node performance data provided in another embodiment of the present application.

[0055] FIG6 is a flowchart of a method for obtaining node performance data provided in an embodiment of the present application.

[0056] Figure 7 is a structural block diagram of a method for obtaining node performance data provided in Example I of the present application.

[0057] Figure 8 is a structural block diagram of a method for obtaining node performance data provided in Example II of the present application.

[0058] Figure 9 is a structural block diagram of a method for obtaining node performance data provided in Example III of the present application.

[0059] Figure 10 is a structural block diagram of a method for obtaining node performance data provided in Example IV of the present application.

[0060] FIG11 is a diagram showing the internal structure of a computer device according to an embodiment of the present application. DETAILED DESCRIPTION

[0061] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0062] It should be understood that the specific embodiments described herein are merely used to explain the present application and are not intended to limit the present application. In the description of the present application, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms are not necessarily directed to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they contradict each other.

[0063] Based on the above situation, the method for obtaining node performance data provided in an embodiment of the present application can be applied to the application environment shown in Figure 1. In one embodiment, a computer device is provided, which can be a server, and its internal structure diagram can be shown in Figure 1. The computer device includes a processor, a memory and a network interface connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the acquisition data of the method for obtaining node performance data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for obtaining node performance data is implemented.

[0064] The present application discloses a method, apparatus, computer equipment and storage medium for obtaining node performance data. By predicting the predicted heat value of the media to be played, it is possible to simulate a user terminal sending a media access request to the service node to be detected based on the predicted heat value of the media to be played. Then, during the process of the service node to be detected responding to the media access request, the service node to be detected is monitored to obtain performance indicator data of the service node to be detected.

[0065] In one embodiment, as shown in Figure 2, Figure 2 is a flowchart of a method for obtaining node performance data provided in an embodiment of the present application, which shows a method for obtaining node performance data. The method for obtaining node performance data executed by the computer device in Figure 1 may include the following steps S201 to S203.

[0066] Step S201: predicting the popularity of the media to be played, and obtaining a predicted popularity value of the media to be played.

[0067] The media to be played may be a video to be played or an audio to be played, etc. The predicted popularity value of the media to be played may represent the number of views of the media to be played, the number of listens to the media to be played, the number of interactions with the media to be played, and the number of shares of the media to be played, etc.

[0068] Furthermore, if the number of media to be played is at least two, the predicted popularity value of each media to be played is trend analyzed to obtain the predicted popularity value change trend of each media to be played, wherein the predicted popularity value change trend can be represented by a line graph.

[0069] It should be noted that obtaining the predicted heat value of the media to be played may include the following steps: a heat analysis model may be pre-trained, the media to be played is input into the heat analysis model, and the output result of the heat analysis model is obtained, which is the predicted heat value of the media to be played.

[0070] For example, in one embodiment of the present application, if the predicted popularity value of a piece of media to be played on the 24th is to be predicted, the first step is to determine the media to be played on the 24th, input each of the media to be played on the 24th into a popularity analysis model, and obtain the output of the popularity analysis model, which is the predicted popularity value of the media to be played on the 24th. Furthermore, the predicted popularity value of the media to be played on the 24th is represented by a line graph to obtain the trend of the predicted popularity value of the media to be played on the 24th.

[0071] To further illustrate, obtaining the predicted popularity value of the to-be-played media may further include the following steps: obtaining the historical popularity value of the to-be-played media, and using the historical popularity value as the predicted popularity value of the to-be-played media at the current moment.

[0072] For example, in one embodiment of the present application, if it is necessary to predict the predicted heat value of the media to be played throughout the day on the 24th, first determine that there are three media to be played throughout the day on the 24th, for example, the three media to be played are media A to be played, media B to be played, and media C to be played, and determine the historical heat values ​​of media A to be played, media B to be played, and media C to be played in the historical playback records respectively, and use the historical heat values ​​of media A to be played, media B to be played, and media C to be played as the predicted heat values ​​of media A to be played, media B to be played, and media C to be played respectively. Furthermore, the predicted heat values ​​of the three media to be played throughout the day on the 24th are represented by a line graph to obtain the change trend of the predicted heat values ​​of the three media to be played throughout the day on the 24th.

[0073] Step S202: According to the predicted popularity value of the to-be-played media, the simulated user terminal sends a media access request to the service node to be detected.

[0074] It should be noted that if the predicted heat value of a certain media to be played is high, it means that when the media to be played is played, a large number of users send media access requests to the service node to be detected, thereby playing the media to be played; if the predicted heat value of a certain media to be played is low, it means that when the media to be played is played, only a small number of users send media access requests to the service node to be detected, thereby playing the media to be played.

[0075] Further explanation: when it is necessary to simulate a user terminal sending a media access request to the service node to be detected, the predicted visits to the media to be played are predicted based on the predicted heat value of the media to be played. If the predicted visits are high, more user terminals are simulated to send media access requests to the service node to be detected; if the predicted visits are small, fewer user terminals are simulated to send media access requests to the service node to be detected.

[0076] In one embodiment of the present application, the predicted visits of the media to be played can be predicted based on the predicted popularity value of the media to be played according to a pre-set visit volume comparison table. The visit volume comparison table records different predicted visits corresponding to different predicted popularity values. Specifically, when it is necessary to predict the predicted visits of the media to be played, the visit volume comparison table can be searched for the visits corresponding to the predicted popularity value. The visits corresponding to the predicted popularity value recorded in the visit volume comparison table are the predicted visits of the media to be played.

[0077] Step S203: During the process of the service node to be detected responding to the media access request, the service node to be detected is monitored to obtain performance indicator data of the service node to be detected.

[0078] There are many types of performance indicator data, for example, the performance indicator data may be access delay of a detection service node, access efficiency of a detection service node, overload rate of a detection service node, etc. The types of performance indicator data are not limited here.

[0079] It should be noted that when it is necessary to obtain the performance indicator data of the service node to be detected, corresponding data acquisition equipment can be deployed according to the data type of the performance indicator data to obtain the performance indicator data of the service node to be detected.

[0080] For example, if the data type of the performance indicator data is the access delay of the service node, an access delay collection device is deployed in the node to be detected, and when the service node to be detected responds to the media access request, the collection function of the access delay collection device is triggered to obtain the performance indicator data of the service node to be detected.

[0081] To further explain, in order to ensure that the performance indicator data of the service node to be detected can effectively reflect the actual situation of the process of the service node to be detected responding to the media access request, it is necessary to monitor every moment when the service node to be detected responds to the media access request.

[0082] In one embodiment of the present application, if the simulated user terminal needs to send a media access request to the service node to be detected for N hours, the monitoring of the service node to be detected begins when the service node to be detected responds to the media access request for the first time, and the monitoring of the service node to be detected ends when the service node to be detected responds to the media access request for the last time.

[0083] The above-mentioned method for obtaining node performance data predicts the predicted heat value of the media to be played, and realizes that according to the predicted heat value of the media to be played, the user terminal is simulated to send a media access request to the service node to be detected, and then the service node to be detected is monitored during the process of the service node to be detected responding to the media access request to obtain performance indicator data of the service node to be detected. Because in the above process, when the simulated user terminal sends a media access request to the service node to be detected, it does not send the media access request to the service node to be detected based on a randomly generated media simulated user, but uses the media to be played in an actual scenario to send the media access request to the service node to be detected. Moreover, when the simulated user terminal sends a media access request to the service node to be detected, the predicted number of visits to the media to be played is determined according to the predicted heat value of the media to be played, so as to adjust the situation of sending the media access request to the service node to be detected. Therefore, the obtained performance indicator data can more accurately reflect the operating performance of the service node to be detected in the actual operating scenario.

[0084] In one embodiment, existing technologies fail to consider the impact of user access popularity on node performance data when simulating user access to service nodes. Consequently, the performance indicator data obtained using these traditional technologies is inaccurate and fails to accurately reflect the actual performance of the service node. To address this technical issue, the computer device of this embodiment can utilize a traffic transmitter to simulate a user terminal sending a media access request to the service node under test based on the predicted popularity of the media to be played.

[0085] The traffic sender is a CDN (Content Delivery Network) traffic sender, and the service node to be detected is a CDN service node.

[0086] It should be noted that in order to ensure that media access requests can be sent to the service node to be detected stably for a long time, a traffic transmitter can be used to simulate the user terminal to construct a media access request carrying a resource locator (URL) based on the predicted heat value of the media to be played, and send the media access request to the service node to be detected.

[0087] Among them, the traffic sender can automatically build a large-scale resource locator (URL) based on the predicted popularity value of the media to be played, so as to send a media access request to the service node to be detected.

[0088] The above-mentioned method for obtaining node performance data adopts a traffic transmitter to simulate the user terminal sending a media access request to the service node to be detected, thereby ensuring that the service node to be detected can smoothly respond to the media access request, so that the simulation operation of the service node to be detected can run stably, and the accuracy of the performance indicator data subsequently obtained is guaranteed.

[0089] In one embodiment, as shown in FIG3 , simulating a user terminal to construct a media access request carrying a resource locator (URL) may specifically include the following steps S301 to S302 .

[0090] Step S301 : for each medium to be played, the predicted number of visits of the medium to be played is determined according to the predicted popularity value of the medium to be played.

[0091] It should be noted that when it is necessary to determine the predicted visits of the media to be played, the predicted popularity value of the media to be played can be input into a pre-trained visit prediction model, and the output result of the visit prediction model can be obtained. The output result is the predicted visit of the media to be played.

[0092] Among them, the training process of the visit prediction model includes: obtaining the historical heat value of the historical playback media, and marking each historical heat value according to the historical visit volume of the historical playback media to obtain the marked historical heat value, and training the visit prediction model according to the marked historical heat value to obtain the trained visit prediction model.

[0093] To further illustrate, the conversion relationship between the predicted popularity value and the predicted number of visits can be determined in advance, and then the predicted popularity value can be converted into the number of visits based on the conversion relationship to obtain the converted predicted number of visits.

[0094] Among them, the conversion relationship can be a pre-set conversion formula for converting the predicted heat value into the predicted visit volume, or it can be a pre-set conversion rule for converting the predicted heat value into the predicted visit volume, for example, taking the Nth power value of the predicted heat value as the converted predicted visit volume.

[0095] Step S302: Using a traffic transmitter, simulating a user terminal to construct a media access request for the to-be-played media with a predicted access volume.

[0096] Each media access request carries the URL corresponding to the media to be played.

[0097] It should be noted that the more predicted visits, the more user terminals will send media access requests to the service node to be detected; similarly, the fewer predicted visits, the fewer user terminals will send media access requests to the service node to be detected; therefore, when it is determined to use a traffic transmitter to simulate the user terminal to construct the media access request for the media to be played with the predicted visit volume, it is necessary to adjust the traffic sending volume of the traffic transmitter in real time according to the predicted visit volume; to ensure that the media access request sent to the service node to be detected at each moment is in line with the predicted visit volume.

[0098] For example, if the predicted number of visits to a certain media to be played at the current moment is three, the traffic transmitter is used to simulate the user terminal to construct three media access requests for the media to be played. If the predicted number of visits to a certain media to be played at the current moment is one, the traffic transmitter is used to simulate the user terminal to construct one media access request for the media to be played.

[0099] The above-mentioned method for obtaining node performance data, by determining the predicted access volume of the media to be played, realizes the use of a traffic transmitter to construct a media access request for the media to be played with the predicted access volume, thereby ensuring that the service node to be detected can be monitored smoothly in the future and the performance indicator data of the service node to be detected can be obtained, thereby ensuring the accuracy and authenticity of the performance indicator data.

[0100] In one embodiment, the step of predicting the popularity of the media to be played and obtaining the predicted popularity value of the media to be played may specifically include the following: inputting the media to be played into a popularity analysis model and obtaining the predicted popularity value of the media to be played output by the popularity analysis model.

[0101] It should be noted that, as shown in FIG4 , the training process of the heat analysis model may specifically include the following steps S401 to S402 .

[0102] Step S401: Acquire the historical playback media and historical popularity values ​​of the IPTV.

[0103] It should be noted that when it is necessary to obtain the historical playback media and the historical popularity value of the historical playback media of the Internet TV IPTV, the historical playback media and the historical popularity value of the historical playback media can be determined from the historical playback records of the Internet TV IPTV; thereby obtaining the historical playback media and the historical popularity value of the historical playback media of the Internet TV IPTV.

[0104] Further explanation: if the historical popularity value of the historical playback media cannot be obtained from the historical playback record of the Internet TV IPTV, the historical playback media in the historical playback record will be sent to the staff's terminal device, so that the staff can determine the historical popularity value of the historical playback media based on historical experience and actual conditions, thereby obtaining the historical playback media and the historical popularity value of the historical playback media of the Internet TV IPTV.

[0105] Step S402: Based on the historical playback media and the historical popularity values ​​of the historical playback media, the initial model is trained to obtain a popularity analysis model.

[0106] It should be noted that when training the initial model, the historical playback media can be input into the initial model, and the initial heat value output by the initial model can be obtained to determine the difference between the initial heat value and the historical heat value; and based on the difference, the parameters of the initial model are adjusted until the initial heat value output by the initial model is the same as the historical heat value, or when the difference between the initial heat value and the historical heat value is less than the difference threshold, the training of the initial model is completed to obtain a heat analysis model.

[0107] In one embodiment of the present application, the Zipf's law distribution function (1) corresponding to the heat analysis model is as follows: F k =C / k α (1)

[0108] Among them, F k Refers to the predicted popularity value of the kth media to be played, k refers to the number of the media to be played, C refers to the normalization constant, and α is the Zipf exponent.

[0109] Furthermore, the average value of α satisfies calculation formula (2), which is as follows:

[0110] Among them, α ave It refers to the average value of α, α is the Zipf index, and k refers to the number of the media to be played.

[0111] To further explain, the training time interval of the heat analysis model can be specified. If the time interval between the current moment and the last training of the heat analysis model is equal to the training time interval, the new historical playback media and the historical heat value of the new historical playback media are obtained to train the heat analysis model and obtain the heat analysis model.

[0112] The above-mentioned method for obtaining node performance data obtains the historical playback media and the historical heat values ​​of the historical playback media of the Internet TV IPTV, and trains a heat analysis model based on the historical playback media and the historical heat values ​​of the historical playback media; so that the heat analysis model can accurately predict the predicted heat value of the media to be played, providing a data basis for obtaining the performance indicator data of the service node to be tested.

[0113] In one embodiment, as shown in FIG5 , obtaining performance indicator data of the service node to be detected may include the following steps S501 to S504 .

[0114] Step S501: predict the popularity of the to-be-played media to obtain the predicted popularity value of the to-be-played media.

[0115] Step S502: for each medium to be played, the predicted number of visits of the medium to be played is determined according to the predicted popularity value of the medium to be played.

[0116] Step S503: Using a traffic transmitter, simulate the user terminal to construct a media access request for the media to be played with a predicted number of visits; each media access request carries the URL corresponding to the media to be played, and sends the media access request to the service node to be detected.

[0117] Step S504: During the process of the service node to be detected responding to the media access request, the service node to be detected is monitored to obtain performance indicator data of the service node to be detected.

[0118] In an optional embodiment of the present application, the performance indicator data of the service node to be tested can also be obtained through the test control center, the content heat intelligent replacement system and the CDN traffic generator, as shown in Figure 6, which specifically includes the following contents: if the media to be played is a video to be played, the test control center performs data analysis and simulation playback tests on the historical playback videos and historical heat values ​​of the historical playback videos of the Internet TV IPTV to obtain the distribution function and function-related parameters of the video to be played that are suitable for the Internet TV IPTV; based on the distribution function and function-related parameters, a heat analysis model is obtained, and the heat analysis model is output to the content heat intelligent replacement system; the content heat intelligent replacement system predicts the heat of the video to be played based on the heat analysis model to obtain the predicted heat value of the video to be played; and outputs the predicted heat value of the video to be played to the CDN traffic generator. The CDN traffic generator simulates the user terminal to construct a media access request carrying a resource locator (URL) based on the predicted heat value of the video to be played, and sends the media access request to the service node to be tested. In the process of the service node to be tested responding to the media access request, the service node to be tested is monitored to obtain the performance indicator data of the service node to be tested.

[0119] The above-mentioned method for obtaining node performance data predicts the predicted heat value of the media to be played, and realizes that according to the predicted heat value of the media to be played, the simulated user terminal sends a media access request to the service node to be detected, and then, in the process of the service node to be detected responding to the media access request, the service node to be detected is monitored to obtain performance indicator data of the service node to be detected. Because in the above process, when the simulated user terminal sends a media access request to the service node to be detected, it does not send the media access request to the service node to be detected based on a randomly generated media simulated user, but uses the media to be played in an actual scenario to send the media access request to the service node to be detected. And when the simulated user terminal sends the media access request to the service node to be detected, it determines the predicted access volume of the media to be played according to the predicted heat value of the media to be played, so as to adjust the situation of sending the media access request to the service node to be detected. Therefore, the obtained performance indicator data can more accurately reflect the operating performance of the service node to be detected in the actual operating scenario.

[0120] It should be understood that, although the steps in the flowcharts of the above embodiments are shown in sequence as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be performed in other orders. Moreover, at least a portion of the steps in the flowcharts of the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily performed at the same time, but can be performed at different times. The execution order of these steps or stages is not necessarily to be performed in sequence, but can be performed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0121] Based on the same inventive concept, an embodiment of the present application further provides a device for acquiring node performance data for implementing the aforementioned method for acquiring node performance data. The implementation solution provided by this device is similar to the implementation solution described in the aforementioned method. Therefore, the specific limitations of the embodiments of one or more device for acquiring node performance data provided below can be found in the above-mentioned limitations of the method for acquiring node performance data, and will not be repeated here.

[0122] In one embodiment, as shown in FIG7 , a device for acquiring node performance data is provided, including: a prediction module 10 , a sending module 20 , and a monitoring module 30 , wherein:

[0123] The prediction module 10 is used to predict the popularity of the media to be played and obtain a predicted popularity value of the media to be played.

[0124] The media to be played is a video to be played.

[0125] The sending module 20 is configured to simulate a user terminal sending a media access request to a service node to be detected according to the predicted popularity value of the media to be played.

[0126] The sending module is specifically configured to use a traffic transmitter to simulate a user terminal sending a media access request to a service node to be detected based on the predicted popularity of the media to be played. Furthermore, the traffic transmitter is configured to simulate a user terminal constructing a media access request carrying a resource locator (URL) based on the predicted popularity of the media to be played, and then sending the media access request to the service node to be detected.

[0127] The monitoring module 30 is configured to monitor the service node to be detected during the process of the service node to be detected responding to the media access request, so as to obtain performance indicator data of the service node to be detected.

[0128] The above-mentioned node performance data acquisition device predicts the predicted heat value of the media to be played, and realizes that according to the predicted heat value of the media to be played, the simulated user terminal sends a media access request to the service node to be detected. Then, in the process of the service node to be detected responding to the media access request, the service node to be detected is monitored to obtain performance indicator data of the service node to be detected. Because in the above process, when the simulated user terminal sends a media access request to the service node to be detected, it does not send the media access request to the service node to be detected based on a randomly generated media simulated user, but uses a simulated user of the media to be played in an actual scenario to send the media access request to the service node to be detected. Moreover, when the simulated user terminal sends a media access request to the service node to be detected, the predicted number of visits to the media to be played is determined according to the predicted heat value of the media to be played, so as to adjust the situation of sending the media access request to the service node to be detected. Therefore, the obtained performance indicator data can more accurately reflect the operating performance of the service node to be detected in the actual operating scenario.

[0129] In one embodiment, as shown in FIG8 , a device for acquiring node performance data is provided. In the device for acquiring node performance data, a sending module 20 includes: a determining unit 21 and a constructing unit 22 , wherein:

[0130] The determination unit 21 is configured to determine, for each medium to be played, the predicted number of visits of the medium to be played according to the predicted popularity value of the medium to be played.

[0131] The construction unit 22 is configured to use a traffic transmitter to simulate a user terminal to construct a media access request of the to-be-played media with a predicted number of visits; each media access request carries a URL corresponding to the to-be-played media.

[0132] In one embodiment, as shown in FIG9 , a device for acquiring node performance data is provided. The device for acquiring node performance data further includes a training module 40 , wherein:

[0133] The training module 40 is used to input the to-be-played media into the heat analysis model to obtain the predicted heat value of the to-be-played media output by the heat analysis model.

[0134] In one embodiment, as shown in FIG10 , a device for acquiring node performance data is provided. In the device for acquiring node performance data, a training module 40 includes an acquiring unit 41 and a training unit 42 , wherein:

[0135] The acquisition unit 41 is used to acquire the historical playback media and the historical popularity values ​​of the historical playback media of the IPTV.

[0136] The training unit 42 is used to train the initial model according to the historical playback media and the historical popularity values ​​of the historical playback media to obtain a popularity analysis model.

[0137] Each module in the aforementioned node performance data acquisition device may be implemented in whole or in part through software, hardware, or a combination thereof. Each module may be embedded in or independent of a processor in a computer device in the form of hardware, or may be stored in a memory in the computer device in the form of software, so that the processor can call and execute the corresponding operations of each module.

[0138] In one embodiment, a computer device is provided, which may be a terminal. A diagram of its internal structure may be shown in FIG11 . The computer device includes a processor, memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are connected to the system bus via the input / output interface. The processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The input / output interface of the computer device is configured to exchange information between the processor and an external device. The communication interface of the computer device is configured to communicate with an external terminal via wired or wireless communication, where the wireless communication may be achieved via Wi-Fi, a mobile cellular network, NFC (near-field communication), or other technologies. When executed by the processor, the computer program implements a method for acquiring node performance data. The display unit of the computer device is configured to produce a visually visible image and may be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device casing, or an external keyboard, touchpad or mouse.

[0139] Those skilled in the art will understand that the structure shown in FIG10 is merely a block diagram of a portion of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0140] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0141] Predict the popularity of the media to be played and obtain the predicted popularity value of the media to be played;

[0142] According to the predicted popularity value of the media to be played, the simulated user terminal sends a media access request to the service node to be detected;

[0143] During the process of the service node to be detected responding to the media access request, the service node to be detected is monitored to obtain performance indicator data of the service node to be detected.

[0144] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0145] A traffic transmitter is used to simulate a user terminal sending a media access request to the service node to be detected based on the predicted popularity value of the media to be played.

[0146] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0147] A traffic transmitter is used to simulate a user terminal to construct a media access request carrying a resource locator (URL) according to the predicted popularity value of the media to be played, and send the media access request to the service node to be detected.

[0148] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0149] For each medium to be played, the predicted number of visits of the medium to be played is determined according to the predicted popularity value of the medium to be played;

[0150] A traffic transmitter is used to simulate a user terminal to construct a predicted number of media access requests for the media to be played; each media access request carries the URL corresponding to the media to be played.

[0151] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0152] The media to be played is input into the heat analysis model to obtain the predicted heat value of the media to be played output by the heat analysis model.

[0153] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0154] Get the historical playback media and historical popularity values ​​of IPTV;

[0155] The initial model is trained based on the historical playback media and the historical popularity values ​​of the historical playback media to obtain a popularity analysis model.

[0156] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0157] The media to be played is the video to be played.

[0158] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0159] Predict the popularity of the media to be played and obtain the predicted popularity value of the media to be played;

[0160] According to the predicted popularity value of the media to be played, the simulated user terminal sends a media access request to the service node to be detected;

[0161] During the process of the service node to be detected responding to the media access request, the service node to be detected is monitored to obtain performance indicator data of the service node to be detected.

[0162] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0163] A traffic transmitter is used to simulate a user terminal sending a media access request to the service node to be detected based on the predicted popularity value of the media to be played.

[0164] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0165] A traffic transmitter is used to simulate a user terminal to construct a media access request carrying a resource locator (URL) according to the predicted popularity value of the media to be played, and send the media access request to the service node to be detected.

[0166] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0167] For each medium to be played, the predicted number of visits of the medium to be played is determined according to the predicted popularity value of the medium to be played;

[0168] A traffic transmitter is used to simulate a user terminal to construct a predicted number of media access requests for the media to be played; each media access request carries the URL corresponding to the media to be played.

[0169] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0170] The media to be played is input into the heat analysis model to obtain the predicted heat value of the media to be played output by the heat analysis model.

[0171] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0172] Get the historical playback media and historical popularity values ​​of IPTV;

[0173] The initial model is trained based on the historical playback media and the historical popularity values ​​of the historical playback media to obtain a popularity analysis model.

[0174] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0175] The media to be played is the video to be played.

[0176] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0177] Predict the popularity of the media to be played and obtain the predicted popularity value of the media to be played;

[0178] According to the predicted popularity value of the media to be played, the simulated user terminal sends a media access request to the service node to be detected;

[0179] During the process of the service node to be detected responding to the media access request, the service node to be detected is monitored to obtain performance indicator data of the service node to be detected.

[0180] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0181] A traffic transmitter is used to simulate a user terminal sending a media access request to the service node to be detected based on the predicted popularity value of the media to be played.

[0182] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0183] A traffic transmitter is used to simulate a user terminal to construct a media access request carrying a resource locator (URL) according to the predicted popularity value of the media to be played, and send the media access request to the service node to be detected.

[0184] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0185] For each medium to be played, the predicted number of visits of the medium to be played is determined according to the predicted popularity value of the medium to be played;

[0186] A traffic transmitter is used to simulate a user terminal to construct a predicted number of media access requests for the media to be played; each media access request carries the URL corresponding to the media to be played.

[0187] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0188] The media to be played is input into the heat analysis model to obtain the predicted heat value of the media to be played output by the heat analysis model.

[0189] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0190] Get the historical playback media and historical popularity values ​​of IPTV;

[0191] The initial model is trained based on the historical playback media and the historical popularity values ​​of the historical playback media to obtain a popularity analysis model.

[0192] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0193] The media to be played is the video to be played.

[0194] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processor involved in the various embodiments provided herein may be, but are not limited to, a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, and the like.

[0195] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0196] The above embodiments merely illustrate several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art may make various modifications and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for obtaining node performance data, comprising: Predicting the popularity of the media to be played to obtain a predicted popularity value of the media to be played; According to the predicted heat value of the to-be-played media, simulating the user terminal to send a media access request to the to-be-detected service node; In the process that the service node to be detected responds to the medium access request, the service node to be detected is monitored to obtain performance indicator data of the service node to be detected.

2. The method according to claim 1, wherein the step of simulating a user terminal to send a media access request to a service node to be detected according to the predicted popularity value of the media to be played comprises: A traffic transmitter is used to simulate a user terminal sending a media access request to a service node to be detected according to the predicted heat value of the to-be-played media.

3. The method according to claim 2, wherein the using of a traffic transmitter to simulate a user terminal sending a media access request to a service node to be detected according to the predicted popularity value of the media to be played comprises: A traffic transmitter is used to simulate a user terminal to construct a media access request carrying a resource locator (URL) according to the predicted heat value of the media to be played, and send the media access request to the service node to be detected.

4. The method according to claim 3, wherein the number of the media to be played is at least two, and the using of a traffic transmitter to simulate a user terminal to construct a media access request carrying a URL according to the predicted popularity value of the media to be played comprises: For each medium to be played, the predicted number of visits of the medium to be played is determined according to the predicted popularity value of the medium to be played; A traffic transmitter is used to simulate a user terminal to construct a media access request of the to-be-played media with the predicted access volume; each media access request carries a URL corresponding to the to-be-played media.

5. The method according to claim 1, wherein predicting the popularity of the to-be-played media to obtain the predicted popularity value of the to-be-played media comprises: The to-be-played media is input into a heat analysis model to obtain a predicted heat value of the to-be-played media output by the heat analysis model.

6. The method according to claim 5, wherein the training process of the thermal analysis model comprises: Obtaining historical broadcast media of Internet Protocol television (IPTV) and historical popularity values ​​of the historical broadcast media; The initial model is trained according to the historical playback media and the historical popularity value of the historical playback media, and the to the thermal analysis model. The method according to claim 1 , wherein the media to be played is a video to be played.

8. A device for acquiring node performance data, comprising: A prediction module, used to predict the popularity of the media to be played, and obtain a predicted popularity value of the media to be played; A sending module, configured to simulate a user terminal sending a media access request to a service node to be detected according to the predicted heat value of the media to be played; The monitoring module is used to monitor the service node to be detected in the process of the service node to be detected responding to the media access request, so as to obtain the performance indicator data of the service node to be detected.

9. The device according to claim 8, wherein the sending module further comprises: A determination unit, configured to determine, for each medium to be played, a predicted number of visits of the medium to be played according to the predicted popularity value of the medium to be played; The construction unit is used to use a traffic transmitter to simulate a user terminal to construct a media access request of the to-be-played media with a predicted access volume; each media access request carries a resource locator (URL) corresponding to the to-be-played media.

10. The device according to claim 8, further comprising a training module for inputting the to-be-played media into a heat analysis model to obtain a predicted heat value of the to-be-played media output by the heat analysis model.

11. The apparatus according to claim 10, wherein the training module further comprises: An acquisition unit, used to acquire historical playback media of an Internet protocol television (IPTV) and historical heat values ​​of the historical playback media; The training unit is used to train the initial model according to the historical playback media and the historical heat values ​​of the historical playback media to obtain the heat analysis model.

12. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

14. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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