Content distribution network node bandwidth optimization method, device, electronic device and medium

Abstract

The present disclosure is about a method, device, electronic device and medium for optimizing bandwidth of a content distribution network node, and relates to the field of computer technology. The method includes: determining a first bandwidth curve within a first time period based on historical bandwidth data, wherein the first bandwidth curve represents the corresponding relationship between bandwidth and time within the first time period, wherein the first time period includes multiple bandwidth measurement intervals, and the bandwidth measurement interval has a first time granularity; determining a bandwidth threshold within the first time period; determining one or more candidate intervals within the first time period based on the first bandwidth curve and the bandwidth threshold, wherein the candidate interval has a second time granularity, and the second time granularity is greater than or equal to the first time granularity; determining one or more degradation intervals from the one or more candidate intervals to perform bandwidth reduction processing, so that the bandwidth of the bandwidth measurement intervals in a predetermined order within the first time period meets the preset bandwidth conditions. The present disclosure can optimize the bandwidth of the degradation interval and reduce the pressure on the server during peak hours.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, and in particular to a method, device, electronic device and medium for optimizing bandwidth of a content distribution network node. Background Art

[0002] With the maturity of Internet technology, media services based on the Internet are becoming more mature. Media services can rely on Internet technology to transmit data of media objects. Media objects can be songs, audio or video.

[0003] For media business operators, they can accelerate services based on CDN (Content Delivery Network) to provide users with higher quality media objects and improve users' media object usage experience.

[0004] Due to the centralized viewing habits and work and rest schedules of most users, the CDN bandwidth usage curve has obvious peaks, which may occur at night, causing greater pressure on the server. However, directly optimizing bandwidth for the evening time period (e.g., 18:00 to 23:00) may not be optimal and may even affect user experience. Therefore, how to better optimize CDN bandwidth has become an urgent problem to be solved. Summary of the invention

[0005] The present disclosure provides a method, device and system for optimizing bandwidth of a content distribution network node, so as to at least solve the problem of optimizing bandwidth of a content distribution network in the related art. The technical solution of the present disclosure is as follows:

[0006] According to a first aspect of an embodiment of the present disclosure, a method for optimizing bandwidth of a content distribution network node is provided, comprising:

[0007] Determine a first bandwidth curve within a first time period based on historical bandwidth data, wherein the first bandwidth curve represents a corresponding relationship between bandwidth and time within the first time period, wherein the first time period includes a plurality of bandwidth measurement intervals, and the bandwidth measurement intervals have a first time granularity;

[0008] Determining a bandwidth threshold within the first time period;

[0009] determining one or more candidate intervals within the first time period based on the first bandwidth curve and the bandwidth threshold, wherein the bandwidth of the candidate interval is greater than or equal to the bandwidth threshold, and the candidate interval has a second time granularity, and the second time granularity is greater than or equal to the first time granularity;

[0010] One or more degradation intervals are determined from the one or more candidate intervals to perform bandwidth reduction processing, so that the bandwidths of bandwidth metric intervals in a predetermined order within the first time period meet preset bandwidth conditions.

[0011] In an exemplary embodiment of the present disclosure, the method further includes:

[0012] For each degradation interval, determining a bandwidth reduction corresponding to the degradation interval;

[0013] Determine one or more rate control strategies for the degradation interval based on the bandwidth reduction in the degradation interval and the degree of impact of each rate control strategy on the experience quality;

[0014] In a time period corresponding to the degradation interval, the one or more rate control strategies are called.

[0015] In an exemplary embodiment of the present disclosure, determining one or more rate control strategies of the degradation interval based on the bandwidth reduction of the degradation interval and the degree of impact of each rate control strategy on the experience quality includes:

[0016] Sorting the impact of each bit rate control strategy on the quality of experience in ascending order;

[0017] According to the ranking of the experience quality impact degrees of the various rate control strategies, one or more rate control strategies are selected, and the sum of the reduction values ​​corresponding to the one or more rate control strategies is greater than or equal to the bandwidth reduction.

[0018] In an exemplary embodiment of the present disclosure, the historical bandwidth data includes an original bandwidth curve of a content distribution network node and a rate control strategy corresponding to a bandwidth measurement interval;

[0019] The determining a first bandwidth curve within a first time period based on historical bandwidth data includes:

[0020] Based on the rate control strategy corresponding to the bandwidth metric interval, the bandwidth value in the original bandwidth curve is adjusted to obtain the first bandwidth curve, where the first bandwidth curve represents a bandwidth time curve without applying the rate control strategy to reduce the bandwidth.

[0021] In an exemplary embodiment of the present disclosure, determining a bandwidth threshold within the first time period includes:

[0022] The rate control strategy corresponding to the first time period in the original bandwidth curve is adjusted to a target rate control strategy to obtain a second bandwidth curve, wherein the target rate control strategy is a strategy whose bandwidth reduction value is greater than a preset reduction threshold among multiple rate control strategies;

[0023] The bandwidth value corresponding to the bandwidth measurement interval of the predetermined order in the second bandwidth curve is determined as the bandwidth threshold.

[0024] In an exemplary embodiment of the present disclosure, the method further includes:

[0025] Monitoring bandwidth information of the content distribution network node;

[0026] When the duration that the bandwidth information of the content distribution network node does not meet the preset condition is greater than the preset duration, the rate control strategy corresponding to the second time period is adjusted to the preset rate control strategy.

[0027] In an exemplary embodiment of the present disclosure, the bandwidth information of the content distribution network node includes one or more of the following information:

[0028] The proportion of the content distribution network operator's bandwidth to the total bandwidth, the proportion of streaming bandwidth and static bandwidth.

[0029] In an exemplary embodiment of the present disclosure, determining one or more degradation intervals from the one or more candidate intervals to perform bandwidth reduction processing includes:

[0030] Determine, among the one or more candidate intervals, a candidate interval whose bandwidth value is smaller than a bandwidth value of a bandwidth metric interval in a predetermined order within the first time period as a degraded interval;

[0031] A bandwidth reduction process is performed on the degraded section.

[0032] According to a second aspect of an embodiment of the present disclosure, a device for optimizing bandwidth of a content distribution network node is provided, comprising:

[0033] A data processing module, configured to determine a first bandwidth curve within a first time period based on historical bandwidth data, wherein the first bandwidth curve represents a corresponding relationship between bandwidth and time within the first time period, wherein the first time period includes a plurality of bandwidth measurement intervals, and the bandwidth measurement intervals have a first time granularity;

[0034] A threshold determination module, used to determine a bandwidth threshold within the first time period;

[0035] a candidate interval determination module, configured to determine one or more candidate intervals within the first time period based on the first bandwidth curve and the bandwidth threshold, wherein the bandwidth of the candidate interval is greater than or equal to the bandwidth threshold, and the candidate interval has a second time granularity, and the second time granularity is greater than or equal to the first time granularity;

[0036] The bandwidth optimization module is used to determine one or more degradation intervals from the one or more candidate intervals to perform bandwidth reduction processing, so that the bandwidth of the bandwidth measurement intervals in a predetermined order within the first time period meets the preset bandwidth condition.

[0037] In an exemplary embodiment of the present disclosure, the device further includes:

[0038] A reduction calculation module, used to determine, for each degradation interval, a bandwidth reduction corresponding to the degradation interval;

[0039] A strategy selection module, configured to determine one or more rate control strategies for the degradation interval based on the bandwidth reduction in the degradation interval and the degree of impact of each rate control strategy on the quality of experience;

[0040] The strategy calling module is used to call the one or more rate control strategies to reduce the bandwidth in the time period corresponding to the degradation interval.

[0041] In an exemplary embodiment of the present disclosure, the strategy selection module includes:

[0042] A sorting unit, used to sort the experience quality impact of each rate control strategy in order from small to large;

[0043] The strategy selection unit is used to select one or more rate control strategies according to the order of the experience quality impact of the various rate control strategies, and the sum of the reduction values ​​corresponding to the one or more rate control strategies is greater than or equal to the bandwidth reduction.

[0044] In an exemplary embodiment of the present disclosure, the historical bandwidth data includes an original bandwidth curve of a content distribution network node and a rate control strategy corresponding to a bandwidth measurement interval;

[0045] The data processing module is used to adjust the bandwidth value in the original bandwidth curve based on the rate control strategy corresponding to the bandwidth metric interval to obtain the first bandwidth curve, where the first bandwidth curve represents a bandwidth time curve without applying the rate control strategy to reduce the bandwidth.

[0046] In an exemplary embodiment of the present disclosure, the threshold determination module includes:

[0047] a data processing unit, configured to adjust the rate control strategy corresponding to the first time period in the original bandwidth curve to a target rate control strategy, to obtain a second bandwidth curve, wherein the target rate control strategy is a strategy whose bandwidth reduction value is greater than a preset reduction threshold among multiple rate control strategies;

[0048] The threshold determination unit is used to determine the bandwidth value corresponding to the bandwidth measurement interval of the predetermined order in the second bandwidth curve as the bandwidth threshold.

[0049] In an exemplary embodiment of the present disclosure, the device further includes:

[0050] An information monitoring module, used to monitor bandwidth information of the content distribution network node;

[0051] The judgment processing module is used to adjust the bit rate control strategy corresponding to the second time period to the preset bit rate control strategy when the duration of the bandwidth information of the content distribution network node not meeting the preset condition is greater than the preset duration.

[0052] In an exemplary embodiment of the present disclosure, the bandwidth information of the content distribution network node includes one or more of the following information:

[0053] The proportion of the content distribution network operator's bandwidth to the total bandwidth, the proportion of streaming bandwidth and static bandwidth.

[0054] In an exemplary embodiment of the present disclosure, a bandwidth optimization module includes:

[0055] a degradation interval determination unit, configured to determine, among the one or more candidate intervals, a candidate interval whose bandwidth value is smaller than a bandwidth value of a bandwidth metric interval in a predetermined order within the first time period as a degradation interval;

[0056] The bandwidth optimization unit is used to perform bandwidth reduction processing on the degradation interval.

[0057] According to a third aspect of the present disclosure, an electronic device is provided, comprising: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to execute instructions to implement any one of the above-mentioned methods for optimizing bandwidth of a content distribution network node.

[0058] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided. When instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute any one of the above-mentioned methods for optimizing bandwidth of a content distribution network node.

[0059] According to a fifth aspect of an embodiment of the present disclosure, a computer program product is provided, including a computer program / instruction, and when the computer program / instruction is executed by a processor, the content distribution network node bandwidth optimization method described in any one of the above items is implemented.

[0060] The technical solution provided by the embodiments of the present disclosure brings at least the following beneficial effects:

[0061] The present disclosure provides a content distribution network node bandwidth optimization method, device, electronic device and storage medium. The method determines a first bandwidth curve within a first time period based on historical bandwidth data, then determines one or more candidate intervals within the first time period based on the first bandwidth curve and a bandwidth threshold, determines a degradation interval in the candidate interval, and optimizes the degradation interval. The bandwidth of a bandwidth measurement interval in a predetermined order within the first time period can be optimized to a lower level, thereby achieving optimization of the content distribution network bandwidth.

[0062] In addition, the present disclosure only optimizes the degraded intervals in some candidate intervals, so that fewer users are affected by bandwidth optimization, thereby improving user experience.

[0063] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] The drawings herein are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the description are used to explain the principles of the present disclosure, and do not constitute improper limitations on the present disclosure.

[0065] Figure 1 The diagram is a schematic diagram of a scenario of optimizing bandwidth of a content distribution network node according to an exemplary embodiment.

[0066] Figure 2 The diagram is a schematic diagram of another scenario of optimizing bandwidth of a content distribution network node according to an exemplary embodiment.

[0067] Figure 3 The present invention is a flowchart of a method for optimizing bandwidth of a content distribution network node according to an exemplary embodiment.

[0068] Figure 4 It is a schematic diagram of a first bandwidth curve according to an exemplary embodiment.

[0069] Figure 5 The figure is a schematic diagram showing the relationship between a bandwidth threshold and different bandwidth curves according to an exemplary embodiment.

[0070] Figure 6 The figure is a flow chart of selecting a rate control strategy according to an exemplary embodiment.

[0071] Figure 7 The figure is a schematic diagram showing the relationship between different levels of bit rate control strategies and time according to an exemplary embodiment.

[0072] Figure 8 The present invention is a flowchart showing another method for optimizing bandwidth of a content distribution network node according to an exemplary embodiment.

[0073] Fig. 9 The figure is a schematic diagram showing the effect of a method for optimizing bandwidth of a content distribution network node according to an exemplary embodiment.

[0074] Fig.10 The present invention is a block diagram showing a device for optimizing bandwidth of a content distribution network node according to an exemplary embodiment.

[0075] Fig.11 It is a block diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0076] In order to enable ordinary persons in the art to better understand the technical solutions of the present disclosure, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the accompanying drawings.

[0077] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0078] First, some terms in the embodiments of the present disclosure are explained below to facilitate understanding by those skilled in the art.

[0079] CDN (Content Delivery Network) refers to a group of servers distributed in different geographical locations, working together to provide fast delivery of Internet content. CDN can be an intelligent virtual network built on the existing network. It relies on edge servers deployed in various places, through the load balancing, content distribution, scheduling and other functional modules of the central platform, so that users can obtain the required content nearby, reduce network congestion, and improve user access response speed and hit rate.

[0080] QoE (Quality of Experience) refers to the user's subjective feeling about the quality and performance of a device, network, system, application, or service. QoE is the user's perceived ease of completing the entire process. As an example, QoE can be used to measure the user's satisfaction when watching a short video, and the user's viewing time is often used as the indicator.

[0081] QoS (Quality of Service) is used to measure the quality of service provided by operators to users. It is often measured by indicators such as freeze frequency and first screen time.

[0082] Figure 1 FIG. 1 shows a schematic diagram of a scenario for optimizing bandwidth of a content distribution network node. Figure 1 As shown, the scenario includes a server 110 and a terminal device 120 , and the server 110 and the terminal device 120 are in communication connection.

[0083] The server 110 may be a content distribution network node server of a content distribution network operator in the present disclosure.

[0084] The terminal device 120 may be configured with a client, wherein the client configured in the terminal may realize communication connection with the server 110 via HTTP (HyperText Transfer Protocol) or Websocket protocol.

[0085] The client in the terminal device 120 may be a multimedia platform client.

[0086] In one embodiment, the client may be a short video platform client. The short video platform client may send a resource request to the server 110, and the server 110 transmits the resource to the terminal device 120 in response to the resource request, so as to display the resource on the terminal device 120. The resource transmitted by the server 110 may be a multimedia resource. As an example, the multimedia resource may be a streaming media resource such as video or audio.

[0087] In another embodiment, the client may be a music platform client. The music platform client may send a resource request to the server 110, and the server 110 transmits the resource to the terminal device 120 in response to the resource request, so as to display the resource on the terminal device 120. The resource transmitted by the server 110 is similar to that in the above embodiment, and will not be described in detail here.

[0088] In another embodiment, the client may be a shopping platform client. The shopping platform client may send a resource request to the server 110, and the server 110 transmits the resource to the terminal device 120 in response to the resource request, so as to display the resource on the terminal device 120. The resource transmitted by the server 110 is similar to that in the above embodiment, and will not be described in detail here.

[0089] In the above embodiment, the server 110 can adjust the bit rate of resource transmission to the terminal device 120 by adjusting the bit rate control strategy (also called broadcast control strategy). The size of the resource transmission bit rate affects the bandwidth value occupied at that moment.

[0090] It should be noted that the resources transmitted by the server 110 may be resources cached by the server 110 from the source station.

[0091] It should be understood that the terminal device 120 may be, for example, a smart phone, a personal computer, a tablet computer, etc. The server 110 may be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms. The present disclosure does not limit the specific architecture of the server 110.

[0092] Figure 2 FIG. 1 shows a schematic diagram of a scenario for optimizing bandwidth of a content distribution network node. Figure 2 As shown, the scenario includes a source station 210 , a server 220 , and a server 230 .

[0093] exist Figure 2 In the illustrated embodiment, server 220 and server 230 are cluster servers.

[0094] In one embodiment, the content distribution network node server of the content distribution network operator in the present disclosure may be server 220 or server 230, that is, the content distribution network node server of the content distribution network operator in the present disclosure may be a cluster server.

[0095] In some embodiments, the content distribution network node in the present disclosure may be a content distribution network system. The content distribution network system may include a distribution service system, a load balancing system, and an operation management system.

[0096] In one embodiment, the execution subject of the content distribution network node bandwidth optimization method provided in the embodiment of the present disclosure may be a content distribution network system. As an example, the execution subject of the content distribution network node bandwidth optimization method may be a load balancing system or a distribution service system in a content distribution network node.

[0097] In another embodiment, the content distribution network node bandwidth optimization method provided in the embodiment of the present disclosure may be executed by any electronic device with computing and processing capabilities, and the electronic device is communicatively connected to the content distribution network node.

[0098] The technical solution of the present disclosure is described in detail with specific embodiments below. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0099] Figure 3 is a flow chart of a method for optimizing bandwidth of a content distribution network node according to an exemplary embodiment. Figure 3 As shown, the content distribution network node bandwidth optimization method includes the following steps:

[0100] In S310, a first bandwidth curve in a first time period is determined based on historical bandwidth data, where the first bandwidth curve represents a corresponding relationship between bandwidth and time in the first time period, wherein the first time period includes a plurality of bandwidth measurement intervals, and the bandwidth measurement intervals have a first time granularity.

[0101] The historical bandwidth data may be the historical bandwidth data of the content distribution network node of the content distribution network operator. For example, when the first time period is a day, the historical data may be the bandwidth data of the previous day, or the historical bandwidth data of each day in a week, a month, or a year. The first time period may also be other time periods, such as 12 hours, or a week. The historical bandwidth data may have a certain periodicity.

[0102] The first time period includes a plurality of bandwidth measurement intervals, each bandwidth measurement interval corresponds to a bandwidth value, and the bandwidth value may be a peak value or an average value within the bandwidth measurement interval.

[0103] The duration of the first time granularity is usually smaller than the duration of the first time period.

[0104] The first bandwidth curve may represent a bandwidth curve that is not affected by the bandwidth optimization policy. When the bandwidth value in the historical bandwidth data is a bandwidth value optimized using the bandwidth optimization policy, the influence of the bandwidth optimization policy may be removed to obtain the first bandwidth curve. When the bandwidth optimization policy reduces the bandwidth value, the first bandwidth curve may be obtained by increasing the bandwidth value.

[0105] Figure 4 A schematic diagram of a first bandwidth curve is shown, such as Figure 4 As shown, the first bandwidth curve 401 has different bandwidth values ​​at different times, and there are multiple peaks in the curve. Figure 4 In the example, the first time period is 24 hours, and the first time granularity of the bandwidth measurement interval may be 2 hours.

[0106] In S320, a bandwidth threshold within a first time period is determined.

[0107] The bandwidth threshold may be determined according to the first bandwidth curve, may be set according to relevant information of the server, or may be obtained by combining the first bandwidth curve and relevant information of the server.

[0108] In addition, the bandwidth threshold may also be determined based on other information, such as a bandwidth billing method. The process of determining the bandwidth threshold based on the bandwidth billing method is described in detail in the specific embodiments below and will not be described in detail here.

[0109] In S330, one or more candidate intervals within the first time period are determined based on the first bandwidth curve and the bandwidth threshold, the bandwidth of the candidate interval is greater than or equal to the bandwidth threshold, the candidate interval has a second time granularity, and the second time granularity is greater than or equal to the first time granularity.

[0110] As an example, the minimum bandwidth of the candidate interval is greater than or equal to the bandwidth threshold.

[0111] The bandwidth threshold can be used to assist in determining the degradation interval that requires bandwidth optimization. As an example, a time interval in which the bandwidth value in the first bandwidth curve is greater than the bandwidth threshold can be determined as a candidate interval.

[0112] The first bandwidth curve obtained in the above steps can represent a bandwidth time curve that is not affected by the bandwidth optimization strategy. The first bandwidth curve can better show the different bandwidth demands of users at different times. In the time intervals where users have a relatively large bandwidth demand, it will also cause greater pressure on the server. Therefore, the bandwidth curve can be used to better find candidate intervals where the server pressure is relatively large.

[0113] In one embodiment, the second time granularity is greater than the first time granularity, so that the overall number of candidate intervals can be reduced, thereby reducing the amount of calculation for subsequent processing of these candidate intervals.

[0114] In S340, one or more degraded intervals are determined from the one or more candidate intervals to perform bandwidth reduction processing, so that the bandwidths of bandwidth metric intervals in a predetermined order within the first time period meet the preset bandwidth conditions.

[0115] For each candidate interval, we can choose to optimize the bandwidth of the candidate interval, or we can choose not to optimize the bandwidth of the candidate interval, so there can be multiple combinations of degraded intervals.

[0116] Meeting the preset bandwidth condition may be to minimize the bandwidth of bandwidth measurement intervals in a predetermined order within the first time period.

[0117] Here, the degradation interval is selected based on a strategy in which the bandwidth of bandwidth metric intervals in a predetermined order within a first time period after bandwidth optimization is the smallest.

[0118] In one embodiment, the predetermined order is 15, and the number of candidate intervals is 20. When selecting downgrade intervals from the 20 candidate intervals, 6 candidate intervals can be selected as downgrade intervals. Then, bandwidth reduction processing is performed on the selected downgrade intervals, so that the bandwidth value ranked as 15 can be reduced without optimizing the other 14 candidate intervals.

[0119] That is, in the above embodiment, multiple candidate intervals with higher bandwidth values ​​are found based on the first bandwidth curve, and then degradation intervals are determined in the candidate intervals and optimized, so that the bandwidth of the bandwidth metric intervals in a predetermined order within the first time period can be optimized to a lower value.

[0120] In addition, the present disclosure only optimizes the degraded intervals in some candidate intervals instead of optimizing all of them, so that fewer users are affected by bandwidth optimization, thereby improving user experience.

[0121] In some embodiments, Figure 6 As shown, the embodiment of the present disclosure may also include the following steps:

[0122] In S610, for each degradation interval, a bandwidth reduction corresponding to the degradation interval is determined.

[0123] In one embodiment, the bandwidth reduction may be an average of bandwidth values ​​of multiple bandwidth metric intervals in the degradation interval.

[0124] In another embodiment, the bandwidth reduction may be a median of bandwidth values ​​of a plurality of bandwidth metric intervals in the degradation interval.

[0125] In yet another embodiment, the bandwidth reduction may be the maximum value among bandwidth values ​​of multiple bandwidth metric intervals in the degradation interval, or may be the bandwidth values ​​of bandwidth metric intervals in a predetermined order in the degradation interval.

[0126] In S620, one or more rate control strategies for the degradation interval are determined based on the bandwidth reduction in the degradation interval and the degree of impact of each rate control strategy on the quality of experience.

[0127] For the degradation interval, the rate control policy to be issued is determined based on the required bandwidth reduction and the impact of each rate control policy on the quality of experience. By adjusting the rate control policy of the degradation interval, the bandwidth of the degradation interval can be reduced.

[0128] The bitrate control strategy is used to adjust the bitrate of the resource transmitted to the terminal in the time interval. Generally, the bandwidth value can be reduced by reducing the bitrate.

[0129] In S630, during a time period corresponding to the degradation interval, one or more rate control strategies are invoked to reduce the bandwidth.

[0130] In the present disclosure, the bit rate control strategy of the degradation interval can be adjusted to adjust the bit rate of the resource transmitted to the terminal, thereby reducing the bandwidth of the degradation interval. The bandwidth and bit rate required for transmitting different resources are different. Generally speaking, to achieve the level of process playback, the bandwidth required for video resources is greater than the bandwidth required for audio resources. The higher the definition (higher the resolution) of the video, the greater the bandwidth required.

[0131] The degradation interval corresponds to the peak interval of bandwidth, which has a large bandwidth and a large server pressure. Adjusting the bitrate control strategy in the degradation interval can reduce the bitrate of resources transmitted to the terminal, thereby reducing the pressure on the content distribution network node server.

[0132] In some embodiments, the resource transmitted in the present disclosure may be a streaming media resource (including video, audio, etc.) In the present disclosure, multiple levels of bit rate control strategies may be provided, and different levels may correspond to different resolutions.

[0133] In some embodiments, the present disclosure may be provided with multiple levels of rate control strategies, and different levels may correspond to different resolutions, and correspondingly different bit rates. The present disclosure may select a suitable rate control strategy according to the degree of influence of different levels of rate control strategies on user experience.

[0134] In some embodiments, S620 includes the following steps:

[0135] The impact of each bitrate control strategy on the quality of experience is ranked in ascending order;

[0136] Based on the bandwidth reduction and the ranking of the impact of each rate control strategy on the quality of experience, one or more rate control strategies are selected for the degradation interval.

[0137] Here, a rate control strategy matching the bandwidth reduction may be selected from multiple rate control strategies according to the size of the bandwidth reduction.

[0138] In one embodiment, a correlation table between bandwidth reduction and bit rate control strategy may be preset, and a matching bit rate control strategy may be obtained by looking up the table.

[0139] In another embodiment, multiple rate control strategies may be preset, and each rate control strategy may correspond to a reduction value. In S620, the bandwidth reduction may be combined by the reduction values ​​corresponding to the multiple rate control strategies, and then the multiple matching rate control strategies may be obtained. In one embodiment, one or more rate control strategies may be selected according to the order of the degree of impact of the experience quality of each rate control strategy, wherein the sum of the reduction values ​​corresponding to the one or more selected rate control strategies is greater than or equal to the bandwidth reduction.

[0140] like Figure 7 As shown, curve 701, curve 702 and curve 703 respectively represent the corresponding relationship between different levels of rate control strategies and time. As the bandwidth value changes, different levels of rate control strategies can be selected for combination.

[0141] Different levels of bit rate control strategies have different impacts on user experience quality. The present disclosure can select a more appropriate bit rate control strategy by reducing bandwidth to avoid the impact of excessive bit rate adjustment on user experience.

[0142] In the above S630, based on the bandwidth reduction and the ranking of the experience quality impact of each rate control strategy, one or more rate control strategies are selected for the degradation interval. Different rate control strategies correspond to different experience quality values, and the rate control strategy with less impact on user experience can be preferentially selected to improve user experience.

[0143] In addition, in the present disclosure, a degradation interval can set multiple rate control strategies, and each rate control strategy can correspond to different users of the content distribution network node. That is to say, the rate control strategy in the present disclosure may not be targeted at all users in the content distribution network node, thereby ensuring the user experience of some users.

[0144] In some embodiments, the historical bandwidth data in the above embodiments may include an original bandwidth curve of a content distribution network node and a rate control strategy corresponding to a bandwidth metric interval.

[0145] Accordingly, the above S310 may be to adjust the bandwidth value in the original bandwidth curve based on the rate control strategy corresponding to the bandwidth metric interval to obtain a first bandwidth curve, where the first bandwidth curve represents a bandwidth time curve without applying the rate control strategy to reduce the bandwidth.

[0146] The rate control strategy may be a strategy for optimizing bandwidth, which may also be called a bandwidth optimization strategy or a peak shaving strategy. The rate control strategy may be a set of coding and decoding methods for reducing the bit rate of resources transmitted to the terminal in the degradation interval.

[0147] The original bandwidth curve of the content distribution network node can be a curve of the relationship between the bandwidth and time of a content distribution network operator. The content distribution network operator can be an organization that provides content distribution network services. The content distribution network operator can also be called a content distribution network service provider, which is not limited here. In the embodiment of the present disclosure, the domain names used by each content distribution network operator can be read in real time, and the domain name granularity can be scheduled to achieve bandwidth optimization of the content distribution network.

[0148] A content distribution network node may be a content distribution network system or a content distribution network server that provides content distribution network services.

[0149] In the time interval corresponding to the rate control strategy, the bandwidth value will change due to the application of the rate control strategy. Generally speaking, the rate control strategy is applied during the bandwidth peak period to reduce the peak bandwidth.

[0150] In one embodiment, the bandwidth change value caused by the rate control strategy in the time interval, such as the bandwidth reduction range, can be calculated according to the rate control strategy and the time interval corresponding to the rate control strategy. Then, the bandwidth value in the original bandwidth curve can be adjusted according to the bandwidth change value to obtain a bandwidth time curve without applying the rate control strategy, that is, a first bandwidth curve.

[0151] like Figure 5 As shown, the first bandwidth curve 502 can be obtained through the original bandwidth curve 501. In this example, the first bandwidth curve 502 has more parts above the bandwidth threshold 503 than the original bandwidth curve 501, that is, more candidate intervals that may need to optimize bandwidth are found. By optimizing these degraded intervals, the pressure on the server can be better relieved.

[0152] In the above embodiment, the first bandwidth curve represents a bandwidth time curve without applying the bit rate control strategy. Based on the first bandwidth curve, the degradation interval that needs to optimize the bandwidth can be more accurately determined. By adjusting the bit rate control strategy of the degradation interval to adjust the bit rate of the resource transmitted to the terminal, the bandwidth of the degradation interval can be optimized and the pressure on the server during the peak period can be reduced.

[0153] In some embodiments, the first bandwidth curve may be determined based on a plurality of original bandwidth curves.

[0154] The historical bandwidth data has a certain periodicity. As an example, the period may be one day, and the multiple original bandwidth curves here may include yesterday's original bandwidth curve and last week's original bandwidth curve. The multiple original bandwidth curves may also include original bandwidth curves at other times, which is not limited here.

[0155] In the disclosed embodiment, based on the periodicity principle, multiple original bandwidth curves are selected to synthesize the first bandwidth curve, which can reduce the impact of individual inaccurate data on the overall curve change, improve the accuracy of candidate interval selection, and improve the bandwidth optimization effect.

[0156] In some embodiments, the bandwidth threshold may be determined according to the first bandwidth curve, may be set according to relevant information of the server, or may be obtained by combining the first bandwidth curve and relevant information of the server.

[0157] The bandwidth threshold can be used to assist in determining the candidate interval. As an example, a time interval with a bandwidth value greater than the bandwidth threshold can be determined as a candidate interval.

[0158] In one embodiment, the rate control strategy corresponding to the first time period in the original bandwidth curve can be adjusted to a target rate control strategy to obtain a second bandwidth curve, and the bandwidth values ​​corresponding to the bandwidth measurement intervals in a predetermined order in the second bandwidth curve are determined as bandwidth thresholds. The target rate control strategy is a strategy with a bandwidth reduction value greater than a preset reduction threshold among multiple rate control strategies. As an example, the target rate control strategy is a strategy with the largest bandwidth reduction value among multiple rate control strategies.

[0159] In one embodiment, the first bandwidth curve may be a curve whose horizontal axis is time and whose vertical axis is bandwidth value. When determining the bandwidth threshold, the highest peaks in the curve may be selected according to the changing trend of the curve. The height of the peak may be determined according to the value of the vertical axis of the curve, that is, according to the bandwidth value.

[0160] In one embodiment, the bandwidth threshold may be determined according to a preset rate control strategy and a first bandwidth curve.

[0161] The preset rate control strategies may include the following strategies:

[0162] 1080P, that is, the user's resolution is adjusted to 1080P. Applying this policy has little impact on user experience;

[0163] 720P 60 frames, that is, the user's resolution is adjusted to 1080P, and the refresh rate frame rate is adjusted to 60 frames, which has little impact on the user experience;

[0164] 720P low-end, that is, adjusting the user's resolution to 1080P and the refresh rate to low-end. Applying this policy will affect the user experience and viewing time.

[0165] In the above steps, the 720P low-end bit rate control strategy can be applied to the first bandwidth curve, and then the bandwidth value of the bandwidth measurement interval in a predetermined order within the first time period is selected as the bandwidth threshold.

[0166] In the above steps, the bit rate control strategy of 720P 60 frames may also be applied to the first bandwidth curve, and then the bandwidth value of the bandwidth measurement interval in a predetermined order within the first time period is selected as the bandwidth threshold.

[0167] It should also be noted that the above-mentioned rate control strategy can be implemented by adjusting the encoding and decoding algorithm.

[0168] The disclosed embodiments can adaptively determine the bandwidth threshold according to different curves, and thus can be better applicable to different content distribution network operators.

[0169] In some embodiments, the present disclosure may also monitor the changes in bandwidth values ​​of various content distribution network operators, so as to switch the bandwidth optimization method when the bandwidth value is abnormal. As an example, when the bandwidth value is abnormal, the original bandwidth optimization method may be returned to be executed, and the rate control strategy corresponding to the second time period may be adjusted to the preset rate control strategy, wherein the second time period may be the time period corresponding to the night peak period.

[0170] In one embodiment, the present disclosure may further include the following steps:

[0171] Monitor bandwidth information of content distribution network nodes;

[0172] When the duration that the bandwidth information of the content distribution network node does not meet the preset condition is longer than the preset duration, the original bandwidth optimization method is returned to be executed.

[0173] In the above embodiment, the bandwidth information of the content distribution network node may include one or more of the following information:

[0174] The ratio of the content distribution network operator's bandwidth to the total bandwidth, and the ratio of streaming bandwidth to static bandwidth. The streaming bandwidth can be video bandwidth.

[0175] In the disclosed embodiment, multiple key indicators such as the ratio of bandwidth to total bandwidth, the ratio of video bandwidth to static bandwidth, etc. of each content distribution network operator can be monitored through real-time data sources, and compared with the same-month data. If the difference between the same-month and year-on-year key indicators of a content distribution network operator is higher than a certain threshold, and the duration is higher than a certain time threshold, it can be determined that the traffic ratio of the content distribution network operator has changed, and the original bandwidth optimization method can be returned to effectively avoid bandwidth peak anomalies.

[0176] The original bandwidth optimization method in the present disclosure may be a fixed time peak shaving strategy. The fixed time may be a time set based on experience. As an example, the fixed time may be from 18:00 to 23:00.

[0177] In some embodiments, the number of degraded intervals in the above S340 is less than or equal to the number of candidate intervals.

[0178] In S340, a candidate interval having a bandwidth value smaller than a bandwidth value of a bandwidth metric interval in a predetermined order within the first time period among the one or more candidate intervals may be determined as a degraded interval, and then bandwidth reduction processing may be performed on the degraded interval.

[0179] As an example, in the present disclosure, a candidate interval whose maximum bandwidth value among one or more candidate intervals is smaller than a bandwidth value of a bandwidth metric interval in a predetermined order within the first time period may be determined as a degraded interval.

[0180] In the disclosed embodiments, the content distribution network operator generally adopts bandwidth billing. In bandwidth billing, peak bandwidth is the main factor that determines the final content distribution network fee. In the above embodiments, the bit rate of resources transmitted to the terminal can be reduced by adjusting the broadcast control strategy, thereby reducing the bandwidth value and ultimately reducing the cost of the content distribution network service.

[0181] However, the bit rate is closely related to whether the streaming media can be played smoothly. If the streaming media resources cannot be played smoothly, the user experience will be affected.

[0182] Take the billing method of the content distribution network operator as peak 95th percentile billing as an example. In a 24-hour day, the bandwidth is calculated once every 5 minutes, and the bandwidth is calculated 288 times a day. Each content distribution network manufacturer will select the 95th percentile bandwidth value of the day, that is, the 15th highest bandwidth, as the billing bandwidth for the day.

[0183] Since a large number of users watch short videos at night, the playback time at night is longer than that during the day. Bandwidth = duration * bit rate. The bandwidth at night will be correspondingly higher. The bandwidth peak is likely to occur at night, so the billing point is likely to occur at night.

[0184] In the related art, the bit rate control strategy will be concentrated in the evening 18 ~ 23 hours to take effect, significantly reducing the bit rate to reduce the peak of the bandwidth curve, thereby reducing the billing bandwidth. The strategy of reducing the bit rate to reduce the bandwidth peak can also be referred to as "peak shaving".

[0185] There are 288 billing points every day, and because the peak is only cut at night, the billing point, which is the 15th highest bandwidth point, may fall at noon, not at the peak period at night. In this solution, the billing point is changed from night to noon. It can be seen that the rate control strategy at night has too much impact on users, resulting in a decrease in user bandwidth and a change in the billing point.

[0186] The above solution has a fixed peak shaving time period and cannot accurately cover the billing point. Based on past experience, it is believed that the billing point is likely to appear at night, so the overall peak shaving is performed at night. When the overall bandwidth curve pattern changes, such as the difference in playback time between daytime and nighttime becomes smaller during the summer vacation, the billing point may also appear during the day. The fixed time period peak shaving of the above solution cannot accurately cut to the billing point and cannot reduce the bandwidth.

[0187] Secondly, the peak shaving time of the above solution is too long, which affects the user's clarity experience. The 5-hour clarity degradation in the evening has a negative impact on the user's clarity experience. In addition, almost all bitrate reduction strategies will take effect at night, but in fact, some strategies may be effective enough to reduce bandwidth.

[0188] The embodiment of the present disclosure not only optimizes bandwidth and reduces the cost of content distribution network services, but also takes into account user experience and selects a rate control strategy based on user experience. The following is an example to illustrate the detailed process of selecting a rate control strategy based on user experience.

[0189] Figure 8 is a flow chart of a method for optimizing bandwidth of a content distribution network node according to an exemplary embodiment. Figure 7 As shown, the content distribution network node bandwidth optimization method includes the following steps:

[0190] In S810, bandwidth is simulated.

[0191] Here, the simulated bandwidth may be a first bandwidth curve determined within a first time period based on historical bandwidth data.

[0192] By acquiring historical bandwidth data of a content distribution network node of a content distribution network operator, and based on a rate control strategy in the historical bandwidth data and a time interval corresponding to the rate control strategy, adjusting a bandwidth value in an original bandwidth curve of the content distribution network node, a first bandwidth curve is obtained, wherein the first bandwidth curve represents a bandwidth time curve without applying the rate control strategy.

[0193] In one embodiment, the first time period may be a day. In the present disclosure, the bandwidth time curve of the day may be predicted based on historical data in a certain time window in the past, that is, the first bandwidth curve.

[0194] The source stations corresponding to the various content distribution network operators generally do not change, and therefore, the traffic allocation of the various content distribution network operators generally does not change. Since the traffic allocation of the various content distribution network operators remains unchanged, the changes in the bandwidth values ​​of each content distribution network operator over the past period of time will have a certain periodicity. Therefore, the present disclosure can determine the time period that needs to be optimized in the future, that is, the degradation interval, based on the historical bandwidth data.

[0195] In S820, a downgrade interval is determined.

[0196] Here, one or more degradation intervals may be determined based on the first bandwidth curve, and the bandwidth value of the degradation interval is greater than the bandwidth threshold.

[0197] When determining the downgrade interval, the billing method used by the content distribution network operator may be considered, and the downgrade interval may be selected based on the billing method.

[0198] In one embodiment, the billing method used by the content distribution network operator is the 95th percentile billing method. The bandwidth is calculated once every 5 minutes for 24 hours a day, and the bandwidth is calculated 288 times a day. The content distribution network operator selects the 95th percentile bandwidth value of the day, that is, the 15th highest bandwidth, as the billing bandwidth for the day.

[0199] In the present disclosure, the downgrade interval may be determined based on the second curve obtained in the above steps in combination with the 95th percentile billing method.

[0200] Assume that the billing point value of the second curve is bandwidth, and that the bandwidth reduction caused by the rate control strategy is ratio. If the bandwidth is downgraded 24 hours a day, the billing point bw_optimal is as follows:

[0201] bw_optimal=bandwidth*(1-ratio) (1)

[0202] Reducing the overall bandwidth by ratio is the maximum bandwidth benefit that can be obtained by this rate control strategy.

[0203] If the bandwidth at a certain time point is lower than bw_optimal, then this point can never become a billing point because it is already below the minimum boundary that can be optimized. Based on this, the time interval with a bandwidth higher than bw_optimal within 24 hours can be used as a candidate time interval.

[0204] In one embodiment, the second time granularity of the candidate interval in the embodiment of the present disclosure may be greater than 15 minutes. Generally, in the selection process of the above bandwidth threshold, the time interval is selected as 5 minutes, which is at least 3 times of 5 minutes, which can significantly reduce the amount of calculation required for the rate control strategy matching process.

[0205] In some embodiments, the second time granularity of the candidate interval may be greater than 15 minutes and less than 30 minutes. The duration of the candidate interval is not much different from the duration interval in the selection process of the bandwidth threshold, which is only slightly greater than 5 minutes, which can effectively avoid missing peak points.

[0206] In some embodiments, each candidate time interval may be cut into a smaller time granularity of 30 minutes.

[0207] Assume that there are n candidate time intervals. In each candidate time interval, we can choose to use the rate control strategy (peak clipping) or not to clip the peak. Then there are 2 nEach strategy can simulate the bandwidth reduction and the change of billing point.

[0208] In some embodiments, the total effective time of the bit rate control strategy can be constrained, and the 2 n The combination of bandwidth billing points is searched to find the peak-shaving time combination with the largest decrease in bandwidth billing points, that is, multiple degradation intervals are selected.

[0209] In S830, a rate control strategy is matched.

[0210] By adjusting the bit rate control strategy of the degradation interval, the bit rate of the resource transmitted to the terminal is adjusted.

[0211] In one embodiment, the required bandwidth reduction can be calculated for each degradation interval, and then multiple rate control strategies can be intelligently combined.

[0212] Among multiple rate control strategies, some rate control strategies reduce bandwidth while having almost no impact on user experience, while others are relatively detrimental to user experience. In order to better balance bandwidth cost and user experience, the present disclosure intelligently issues multiple rate control strategies based on the idea of ​​prioritizing experience quality.

[0213] Assuming that within a certain degradation interval, the difference between the original bandwidth and the optimal billing point (bandwidth threshold) after peak shaving is compared to obtain the required bandwidth reduction within the interval. By sorting multiple rate control strategies according to their impact on the quality of experience, it is possible to calculate which strategies need to be issued to meet the bandwidth reduction.

[0214] like Fig. 9 As shown, the charging point in the bandwidth time curve 910 of the fixed peak shaving solution is 911, and the charging point in the bandwidth time curve 920 of the disclosed solution is 921. The charging point of the disclosed embodiment is lower than that of the fixed peak shaving solution.

[0215] In addition, the disclosed embodiment also monitors multiple key indicators such as the ratio of bandwidth to total bandwidth, the ratio of video bandwidth to static bandwidth of each content distribution network operator through real-time data source, and compares them with the same-month data. If the difference of the key indicators of a content distribution network operator is higher than a certain threshold and the duration is higher than a certain time threshold, it can be rolled back to the original fixed time peak shaving strategy to avoid bandwidth increase.

[0216] It should be noted that the content distribution network node bandwidth optimization method provided in the embodiment of the present disclosure can also be executed by a content distribution network node bandwidth optimization device, or a control module in the content distribution network node bandwidth optimization device for executing the content distribution network node bandwidth optimization method. In the following embodiments, the content distribution network node bandwidth optimization device executing the content distribution network node bandwidth optimization method is taken as an example to illustrate the content distribution network node bandwidth optimization device provided in the embodiment of the present disclosure.

[0217] Fig.10 FIG. 1 is a block diagram of a device for optimizing bandwidth of a content distribution network node according to an exemplary embodiment. Fig.10 The device includes a data processing module 1010, a threshold determination module 1020, a candidate interval determination module 1030 and a degradation interval determination module 1040.

[0218] A data processing module 1010 is used to determine a first bandwidth curve in a first time period based on historical bandwidth data, where the first bandwidth curve represents a corresponding relationship between bandwidth and time in the first time period, wherein the first time period includes a plurality of bandwidth measurement intervals, and the bandwidth measurement intervals have a first time granularity;

[0219] A threshold determination module 1020, configured to determine a bandwidth threshold within a first time period;

[0220] A candidate interval determination module 1030 is used to determine one or more candidate intervals within a first time period based on a first bandwidth curve and a bandwidth threshold, wherein a bandwidth of the candidate interval is greater than or equal to the bandwidth threshold, and the candidate interval has a second time granularity, and the second time granularity is greater than or equal to the first time granularity;

[0221] The degradation interval determination module 1040 is used to determine one or more degradation intervals from one or more candidate intervals to perform bandwidth reduction processing, so that the bandwidth of the bandwidth measurement intervals in a predetermined order within the first time period meets the preset bandwidth condition.

[0222] In some embodiments, the apparatus further comprises:

[0223] A reduction calculation module is used to determine, for each degradation interval, a bandwidth reduction corresponding to the degradation interval;

[0224] A strategy selection module, configured to determine one or more rate control strategies for the degradation interval based on the bandwidth reduction in the degradation interval and the degree of impact of each rate control strategy on the quality of experience;

[0225] The strategy calling module is used to call one or more rate control strategies to reduce bandwidth in a time period corresponding to the degradation interval.

[0226] In an exemplary embodiment of the present disclosure, the strategy selection module includes:

[0227] A sorting unit, used to sort the impact of each bit rate control strategy on the quality of experience in ascending order;

[0228] The strategy selection unit is used to select one or more rate control strategies according to the order of the experience quality impact of the various rate control strategies, and the sum of the reduction values ​​corresponding to the one or more rate control strategies is greater than or equal to the bandwidth reduction.

[0229] In some embodiments, the historical bandwidth data includes an original bandwidth curve of a content distribution network node and a rate control policy corresponding to a bandwidth metric interval;

[0230] The data processing module is used to adjust the bandwidth value in the original bandwidth curve based on the rate control strategy corresponding to the bandwidth measurement interval to obtain a first bandwidth curve, where the first bandwidth curve represents a bandwidth time curve without applying the rate control strategy to reduce the bandwidth.

[0231] In some embodiments, the threshold determination module includes:

[0232] A data processing unit, configured to adjust the rate control strategy corresponding to the first time period in the original bandwidth curve to a target rate control strategy, to obtain a second bandwidth curve, wherein the target rate control strategy is a strategy whose bandwidth reduction value is greater than a preset reduction threshold value among the multiple rate control strategies;

[0233] The threshold determination unit is used to determine the bandwidth value corresponding to the bandwidth measurement interval of the predetermined order in the second bandwidth curve as the bandwidth threshold.

[0234] In some embodiments, the apparatus further comprises:

[0235] An information monitoring module, used to monitor bandwidth information of content distribution network nodes;

[0236] The judgment processing module is used to adjust the rate control strategy corresponding to the second time period to the preset rate control strategy when the duration of the bandwidth information of the content distribution network node not meeting the preset condition is greater than the preset duration.

[0237] In some embodiments, the bandwidth information of the content distribution network node includes one or more of the following information:

[0238] The proportion of the content distribution network operator's bandwidth to the total bandwidth, the proportion of streaming bandwidth and static bandwidth.

[0239] In an exemplary embodiment of the present disclosure, a bandwidth optimization module includes:

[0240] a degradation interval determination unit, configured to determine, among the one or more candidate intervals, a candidate interval whose bandwidth value is smaller than a bandwidth value of a bandwidth metric interval in a predetermined order within a first time period as a degradation interval;

[0241] The bandwidth optimization unit is used to reduce the bandwidth of the degradation interval.

[0242] The content distribution network node bandwidth optimization device in the embodiment of the present disclosure may be a device, or a component, an integrated circuit, or a chip in a terminal.

[0243] The device may be a mobile electronic device or a non-mobile electronic device. For example, the mobile electronic device may be a mobile phone, a tablet computer, a laptop computer, a PDA, an in-vehicle electronic device, a wearable device, an ultra-mobile personal computer (UMPC), a netbook, or a personal digital assistant (PDA), etc., and the non-mobile electronic device may be a server, a network attached storage (NAS), a personal computer (PC), a television (TV), etc., which are not specifically limited in the embodiments of the present disclosure.

[0244] The content distribution network node bandwidth optimization device in the embodiment of the present disclosure may be a device having an operating system. The operating system may be an Android operating system, an IOS operating system, or other possible operating systems, which are not specifically limited in the embodiment of the present disclosure.

[0245] The inventory data processing device provided in the embodiment of the present disclosure can implement each process implemented in the above method embodiment, and will not be described again here to avoid repetition.

[0246] like Fig.11 As shown, the embodiment of the present disclosure also provides an electronic device 1100, including a processor 1101, a memory 1102, and a program or instruction stored in the memory 1102 and executable on the processor 1101. When the program or instruction is executed by the processor 1101, each process of the above-mentioned content distribution network node bandwidth optimization method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0247] It should be noted that the electronic devices in the embodiments of the present disclosure include the mobile electronic devices and non-mobile electronic devices mentioned above.

[0248] The embodiment of the present disclosure also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, each process of the above-mentioned content distribution network node bandwidth optimization method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0249] The processor is a processor in the electronic device described in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0250] The embodiment of the present disclosure further provides a chip, which includes a processor and a communication interface, the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned content distribution network node bandwidth optimization method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0251] It should be understood that the chip mentioned in the embodiments of the present disclosure may also be referred to as a system-level chip, a system chip, a chip system, or a system-on-chip chip, etc.

[0252] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0253] In addition, it should be noted that the scope of the methods and devices in the embodiments of the present disclosure is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved. For example, the described methods may be performed in an order different from that described, and various steps may be added, omitted, or combined. In addition, features described with reference to certain examples may be combined in other examples.

[0254] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present disclosure, or the part that contributes to the prior art, can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for enabling a terminal (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in each embodiment of the present disclosure.

[0255] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0256] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A method for optimizing node bandwidth of a content distribution network, characterized in that: include: Determine a first bandwidth curve within a first time period based on historical bandwidth data, wherein the first bandwidth curve represents a corresponding relationship between bandwidth and time within the first time period, wherein the first time period includes a plurality of bandwidth measurement intervals, and the bandwidth measurement intervals have a first time granularity; Determining a bandwidth threshold within the first time period; determining one or more candidate intervals within the first time period based on the first bandwidth curve and the bandwidth threshold, wherein the bandwidth of the candidate interval is greater than or equal to the bandwidth threshold, and the candidate interval has a second time granularity, and the second time granularity is greater than or equal to the first time granularity; One or more degradation intervals are determined from the one or more candidate intervals to perform bandwidth reduction processing, so that the bandwidths of bandwidth metric intervals in a predetermined order within the first time period meet preset bandwidth conditions.

2. The method according to claim 1, characterized in that The method further comprises: For each degradation interval, determining a bandwidth reduction corresponding to the degradation interval; Determining one or more rate control strategies for the degradation interval based on the bandwidth reduction in the degradation interval and the degree of impact of each rate control strategy on the experience quality; In a time period corresponding to the degradation interval, the one or more rate control strategies are called.

3. The method according to claim 2, characterized in that The determining one or more rate control strategies of the degradation interval based on the bandwidth reduction of the degradation interval and the degree of impact of each rate control strategy on the experience quality includes: Sorting the impact of each bit rate control strategy on the quality of experience in ascending order; According to the ranking of the experience quality impact degrees of the various rate control strategies, one or more rate control strategies are selected, and the sum of the reduction values ​​corresponding to the one or more rate control strategies is greater than or equal to the bandwidth reduction.

4. The method according to claim 1, characterized in that: The historical bandwidth data includes the original bandwidth curve of the content distribution network node and the bit rate control strategy corresponding to the bandwidth measurement interval; The determining a first bandwidth curve within a first time period based on historical bandwidth data includes: Based on the rate control strategy corresponding to the bandwidth metric interval, the bandwidth value in the original bandwidth curve is adjusted to obtain the first bandwidth curve, where the first bandwidth curve represents a bandwidth time curve without applying the rate control strategy to reduce the bandwidth.

5. The method according to claim 4, characterized in that The determining the bandwidth threshold within the first time period includes: The rate control strategy corresponding to the first time period in the original bandwidth curve is adjusted to a target rate control strategy to obtain a second bandwidth curve, wherein the target rate control strategy is a strategy whose bandwidth reduction value is greater than a preset reduction threshold among multiple rate control strategies; The bandwidth value corresponding to the bandwidth measurement interval of the predetermined order in the second bandwidth curve is determined as the bandwidth threshold.

6. The method according to claim 1, characterized in that The method further comprises: Monitoring bandwidth information of the content distribution network node; When the duration that the bandwidth information of the content distribution network node does not meet the preset condition is greater than the preset duration, the rate control strategy corresponding to the second time period is adjusted to the preset rate control strategy.

7. The method according to claim 6, characterized in that The bandwidth information of the content distribution network node includes one or more of the following information: The proportion of the content distribution network operator's bandwidth to the total bandwidth, the proportion of streaming bandwidth and static bandwidth.

8. The method according to claim 1, characterized in that Determining one or more degradation intervals from the one or more candidate intervals to perform bandwidth reduction processing includes: Determine, among the one or more candidate intervals, a candidate interval whose bandwidth value is smaller than a bandwidth value of a bandwidth metric interval in a predetermined order within the first time period as a degraded interval; A bandwidth reduction process is performed on the degraded section.

9. A device for optimizing bandwidth of a content distribution network node, characterized in that: include: A data processing module, configured to determine a first bandwidth curve within a first time period based on historical bandwidth data, wherein the first bandwidth curve represents a corresponding relationship between bandwidth and time within the first time period, wherein the first time period includes a plurality of bandwidth measurement intervals, and the bandwidth measurement intervals have a first time granularity; A threshold determination module, used to determine a bandwidth threshold within the first time period; a candidate interval determination module, configured to determine one or more candidate intervals within the first time period based on the first bandwidth curve and the bandwidth threshold, wherein the bandwidth of the candidate interval is greater than or equal to the bandwidth threshold, and the candidate interval has a second time granularity, and the second time granularity is greater than or equal to the first time granularity; The bandwidth optimization module is used to determine one or more degradation intervals from the one or more candidate intervals to perform bandwidth reduction processing, so that the bandwidth of the bandwidth measurement intervals in a predetermined order within the first time period meets the preset bandwidth condition.

10. An electronic device, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is configured to execute the instructions to implement the content distribution network node bandwidth optimization method according to any one of claims 1 to 8.

11. A computer-readable storage medium, when instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the content distribution network node bandwidth optimization method according to any one of claims 1 to 8.

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