Mode matching system based on OTT quality detection

Abstract

The invention relates to the technical field of OTT videos, in particular to a mode matching system based on OTT quality detection, which comprises an OTT video module and TV terminal equipment, data transmission between the TV terminal equipment and the OTT video module is divided into two modes, when the OTT video module is in a TVOD mode, an SVOD mode and an AVOD mode, an auxiliary module for the OTT video module is started, and when the OTT video module is in the AVOD mode, the auxiliary module is started; when the OTT video module is in a live broadcast mode, the auxiliary module for the OTT video module is started, and when the OTT video module is in a live broadcast mode, the auxiliary module for the OTT video module is started. The invention discloses a two-mode matching system for an OTT video, which is used for reducing coding delay, slicing time, stream pushing time, CDN (Content Delivery Network) transmission time, round-trip time of data end transmission and buffer time when a player is started. The classification mode matching degree of the OTT video can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of OTT video, and in particular to a pattern matching system based on OTT quality detection. Background Art

[0002] Internet TV, or OTT TV, refers to a form of television that uses a wide area network, namely the traditional Internet or mobile Internet, as a transmission network and a television as a receiving terminal to provide users with services such as video and graphic information content. It is different from interactive network television (IPTV) and is not restricted by geographical location. As long as there is a video receiving terminal such as a television, computer, tablet computer, mobile phone, etc. that can access the Internet port, it can be used.

[0003] Some OTT video modules optimize the TVOD mode, SVOD mode, AVOD mode and live broadcast mode simultaneously, which is not convenient for targeted optimization of different mode states, resulting in low optimization degree of classification mode matching of OTT videos. Therefore, a pattern matching system based on OTT quality detection is proposed to address the above problems. Summary of the invention

[0004] The purpose of the present invention is to provide a pattern matching system based on OTT quality detection, which is used to solve the problem that some OTT video modules perform synchronous optimization of TVOD mode, SVOD mode, AVOD mode and live broadcast mode, which is not convenient for targeted optimization of different mode states, resulting in low optimization degree of classified pattern matching of OTT videos.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A pattern matching system based on OTT quality detection includes an OTT video module and a TV terminal device. The OTT video module includes a video source module, a video segment encoding module, a content aggregation module, a video source server module and a CDN platform module. The CDN platform module includes multiple groups of CDN node modules. The CDN node module and the TV terminal device both interact with each other through a transmission network. The TV terminal device is equipped with a set-top box EVA probe. The set-top box EVA probe interacts with the EVA probe manager through the transmission network. The OTT video module displayed by the TV terminal device is divided into a TVOD mode, a SVOD mode, an AVOD mode and a live broadcast mode.

[0007] When the CDN node module interacts with the TV terminal device, the user initiates a content URL access request to the load balancing device of the CDN node module. The CDN load balancing device selects a cache server in the user's area based on the user's IP address and the content URL requested by the user. The load balancing device tells the user the IP address of the cache server and allows the user to initiate a request to the selected cache server. The user initiates a request to the cache server, and the cache server responds to the user's request and transmits the content required by the user to the user terminal.

[0008] Preferably, the set-top box EVA probe can actively test the OTT video module after installation, and the content of the active test includes:

[0009] (1) Automatically identify progressive download (PD) or HLS-based OTT video streams (including URL address and video file name);

[0010] (2) Extract key video information (such as video file size, program duration, video resolution, audio and video encoding) from various video packaging formats (such as FLV / MP4 / 3GP files or TS streams);

[0011] (3) Real-time playback of selected OTT video media streams, supporting MPEG4 and H.264 encoding formats;

[0012] (4) Real-time measurement of various QoS indicators of OTT videos, such as video playback delay, video download rate (HTTP throughput), download percentage, number of download requests, number of downloaded bytes, number of fast-forward bytes, and number of redundant bytes;

[0013] (5) Parse and display the playlist of the HLS video, and track the segment download and video bitrate switching;

[0014] (6) Real-time measurement of various QoS / QoE performance indicators of HLS video, such as: OV-Score (1-5 points), card number, card duration, fragment interval deviation (seconds), fragment download time deviation (seconds), and number of out-of-order fragments;

[0015] (7) Color grading (green, light green, blue, yellow, red) is used to intuitively display the QoS indicators of each slice;

[0016] (8) Error code detection for OTT / HLS videos, including HTTP error return code and error count, and HLS playlist syntax errors;

[0017] (9) Real-time measurement of various QoS performance indicators of TCP / IP networks, such as: number of TCP out-of-order packets, number of TCP retransmitted packets, TCP retransmission rate (%), number of TCP resets, number of TCP low window packets, TCP low window size, and Ethernet throughput indicators;

[0018] (10) Select Q0S / QOE parameters to be displayed in the table and trend chart, sort by any column in the table, and quickly find the OTT video stream with the best or worst indicators in a certain category;

[0019] (11) Output the contents of the OTT video media stream table to a CSV file;

[0020] (12) Record and play HLS video segments.

[0021] Preferably, when the TV terminal device displays access to the OTT video module, the TV terminal device becomes a data network switching terminal, and the OTT video module includes TVOD mode, SVOD mode and AVOD mode, the auxiliary module for the OTT video module is turned on to optimize the media stream, monitor the network status, turn on the packet loss retransmission mechanism, and optimize the weak network resistance algorithm.

[0022] Preferably, when the TV terminal device displays access to the OTT video module, the TV terminal device becomes a data network switching terminal, and when the OTT video module is in live broadcast mode, the auxiliary module for the OTT video module is turned on to reduce encoding delay, reduce slicing time, reduce streaming time, reduce CDN transmission time, reduce the round-trip time of data terminal transmission, and reduce buffering time when the player starts.

[0023] Compared with the prior art, the present invention has the following beneficial effects:

[0024] In the present invention, the data transmission between the TV terminal device and the OTT video module is divided into two modes. When the OTT video module is in the TVOD mode, the SVOD mode and the AVOD mode, the auxiliary module for the OTT video module is turned on to optimize the media stream, monitor the network status, turn on the packet loss retransmission mechanism and optimize the weak network resistance algorithm. When the OTT video module is in the live broadcast mode, the auxiliary module for the OTT video module is turned on to reduce the encoding delay, reduce the slicing time, reduce the streaming time, reduce the CDN transmission time, reduce the round-trip time of the data terminal transmission and reduce the buffering time when the player is started. Through the above-mentioned two mode matching systems for OTT video, targeted optimization is performed for different mode states, which can improve the classification mode matching optimization degree of OTT video. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 This is a schematic diagram of the OTT video network architecture of the present invention;

[0026] Figure 2 This is a schematic diagram of the CDN platform module architecture of the present invention;

[0027] Figure 3 This is a schematic diagram of the OTT video application architecture of the present invention;

[0028] Figure 4 It is a schematic diagram of the EVA probe module architecture of the present invention. DETAILED DESCRIPTION

[0029] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0030] See also Figure 1-4 , the present invention provides a technical solution:

[0031] A pattern matching system based on OTT quality detection includes an OTT video module and a TV terminal device. The OTT video module includes a video source module, a video segment encoding module, a content aggregation module, a video source server module and a CDN platform module. The CDN platform module includes multiple groups of CDN node modules. The CDN node module and the TV terminal device both interact with each other through a transmission network. The TV terminal device is equipped with a set-top box EVA probe. The set-top box EVA probe interacts with the EVA probe manager through the transmission network. The OTT video module displayed by the TV terminal device is divided into a TVOD mode, a SVOD mode, an AVOD mode and a live broadcast mode.

[0032] When the CDN node module interacts with the TV terminal device, the user initiates a content URL access request to the load balancing device of the CDN node module. The CDN load balancing device selects a cache server in the user's area based on the user's IP address and the content URL requested by the user. The load balancing device tells the user the IP address of the cache server and allows the user to initiate a request to the selected cache server. The user initiates a request to the cache server, and the cache server responds to the user's request and transmits the content required by the user to the user terminal.

[0033] Specifically, as the core component of the CDN node module, the CDN scheduling system is responsible for quickly and reliably distributing content to user terminals. Load balancing is one of the important functions of the CDN scheduling system. Its main purpose is to select the best server to respond to user requests based on the load of each server to avoid request overload. Common load balancing scheduling algorithms include polling, weighted polling, and least connections. These algorithms can reasonably distribute user requests based on the load of the server to ensure the stability and availability of the server.

[0034] In actual applications, when a user initiates a request to the CDN node module, the CDN scheduling system will select an optimal server to respond to the user request based on the load balancing algorithm. If this server fails or the load is too high, the scheduling system will automatically switch to other available servers to ensure service continuity and stability.

[0035] In addition to load balancing, the CDN scheduling system also needs to select the server closest to the user to respond to the request based on information such as the user's location. This capability is called content positioning. By measuring the network delay between the user and each server, the CDN node can obtain the distance between the user and each server, thereby determining the optimal server to respond to the user request.

[0036] In actual applications, when a user initiates a request to the CDN, the CDN scheduling system will select a server closest to the user to respond to the user request based on information such as the user's IP address. This strategy can significantly reduce network latency and improve user access speed and experience.

[0037] In order to achieve the content positioning function, the CDN scheduling system adopts a variety of technologies, among which the most commonly used technologies are DNS resolution and IP acquisition. When a user initiates a request to the CDN, the scheduling system first obtains the user's IP address through DNS resolution, and determines the optimal server based on the address to respond to the user request. In addition, the CDN scheduling system can also achieve content positioning through technologies such as BGP routing selection, further optimizing the server selection strategy.

[0038] After installation, the set-top box EVA probe can actively test the OTT video module. The active test content includes:

[0039] (1) Automatically identify progressive download (PD) or HLS-based OTT video streams (including URL address and video file name);

[0040] (2) Extract key video information (such as video file size, program duration, video resolution, audio and video encoding) from various video packaging formats (such as FLV / MP4 / 3GP files or TS streams);

[0041] (3) Real-time playback of selected OTT video media streams, supporting MPEG4 and H.264 encoding formats;

[0042] (4) Real-time measurement of various QoS indicators of OTT videos, such as video playback delay, video download rate (HTTP throughput), download percentage, number of download requests, number of downloaded bytes, number of fast-forward bytes, and number of redundant bytes;

[0043] (5) Parse and display the playlist of the HLS video, and track the segment download and video bitrate switching;

[0044] (6) Real-time measurement of various QoS / QoE performance indicators of HLS video, such as: OV-Score (1-5 points), card number, card duration, fragment interval deviation (seconds), fragment download time deviation (seconds), and number of out-of-order fragments;

[0045] (7) Color grading (green, light green, blue, yellow, red) is used to intuitively display the QoS indicators of each slice;

[0046] (8) Error code detection for OTT / HLS videos, including HTTP error return code and error count, and HLS playlist syntax errors;

[0047] (9) Real-time measurement of various QoS performance indicators of TCP / IP networks, such as: number of TCP out-of-order packets, number of TCP retransmitted packets, TCP retransmission rate (%), number of TCP resets, number of TCP low window packets, TCP low window size, and Ethernet throughput indicators;

[0048] (10) Select Q0S / QOE parameters to be displayed in the table and trend chart, sort by any column in the table, and quickly find the OTT video stream with the best or worst indicators in a certain category;

[0049] (11) Output the contents of the OTT video media stream table to a CSV file;

[0050] (12) Record and play HLS video segments.

[0051] When the TV terminal device shows that the OTT video module is connected, the TV terminal device becomes a data network switching terminal. When the OTT video module includes TVOD mode, SVOD mode and AVOD mode, the auxiliary module for the OTT video module is turned on to optimize the media stream, monitor the network status, turn on the packet loss retransmission mechanism, and optimize the weak network resistance algorithm.

[0052] Media stream optimization is the key to optimizing video and audio quality performance. First, we can choose to convert the appropriate codec to reduce bandwidth usage and improve audio and video quality. For example, the H.264 codec has a high compression ratio, which can reduce data transmission and improve communication efficiency. Secondly, limiting the frame rate and resolution can also reduce data transmission and processing requirements, and improve communication stability. In addition, adaptive bitrate control is also an important optimization method. It can dynamically adjust the encoding bitrate according to the network conditions to ensure the stability and continuity of audio and video communications.

[0053] The network status has a crucial impact on the quality of video and audio communications. Therefore, we need to monitor the network status in real time, detect network delays, packet loss and other problems in a timely manner, and take corresponding measures to optimize the service quality. For example, when high network delay is detected, the network load can be reduced by adjusting codec parameters, reducing frame rate and resolution, etc., to improve communication quality.

[0054] Packet loss is one of the common problems in video and audio communications. To solve this problem, we can enable the packet loss retransmission mechanism. When data packet loss is detected, the lost data packet can be resent to ensure data integrity and continuity. In this way, the quality and stability of audio and video communications can be guaranteed even in poor network conditions.

[0055] Resistance algorithms for weak network environments are also an important means to optimize video and audio quality performance. At the access end, we can resist network packet loss, delay and jitter problems by optimizing bandwidth estimation, negative confirmation, forward error correction and packet loss concealment algorithms. The server improves the efficiency and stability of network communications by optimizing node coverage, scheduling systems and routing distribution algorithms.

[0056] When the TV terminal device shows that the OTT video module is connected, the TV terminal device becomes a data network switching terminal. When the OTT video module is in live broadcast mode, the auxiliary module for the OTT video module is turned on to reduce encoding delay, reduce slicing time, reduce streaming time, reduce CDN transmission time, reduce the round-trip time of data terminal transmission, and reduce the buffering time when the player starts.

[0057] First, reduce the encoding delay. The encoder can take 4 seconds to complete a 1-second slice or 1 second to complete the same slice. The encoder is configurable and you can optimize the delay through various settings. You need to make sure that the encoder is not running in the default mode, but in the optimized mode that can generate slices faster. However, to some extent, you need to choose between speed and quality. The longer the slice generation time, the higher the video quality, so a certain delay is also worth it. The trade-off needs to be determined according to user needs.

[0058] Second, reduce the slicing time. Practice has shown that 2-second slicing has good stability and quality, and 1-second slicing can be used for low- and medium-level motion scenes with small masses.

[0059] Third, reduce the streaming time by placing the CDN access point close to the encoder that generates the video stream.

[0060] Fourth, reduce the transmission time of CDN. CDN is composed of many servers, and the content needs to be delivered layer by layer in the middle layer, edge layer, etc. Therefore, the ability of CDN manufacturers to reduce transmission costs and time will also affect the end-to-end delay.

[0061] Fifth, reduce the round-trip time of data transmission at the end, and deliver the video stream to the end user from the edge server closest to the end user;

[0062] Sixth, reduce the buffering time when the player starts. The number of slices and slice logic in the startup time of the player will affect the delay. Set a better player algorithm and adopt a more stable ABR rule to reduce the risk of rebuffering.

[0063] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A pattern matching system based on OTT quality detection, comprising an OTT video module and a TV terminal device, characterized in that: The OTT video module includes a video source module, a video segment encoding module, a content aggregation module, a video source server module and a CDN platform module. The CDN platform module includes multiple groups of CDN node modules. The CDN node modules and TV terminal devices interact with each other through the transmission network. The TV terminal device is equipped with a set-top box EVA probe. The set-top box EVA probe interacts with the EVA probe manager through the transmission network. The OTT video module displayed by the TV terminal device is divided into TVOD mode, SVOD mode, AVOD mode and live broadcast mode. When the CDN node module interacts with the TV terminal device, the user initiates a content URL access request to the load balancing device of the CDN node module. The CDN load balancing device selects a cache server in the user's area based on the user's IP address and the content URL requested by the user. The load balancing device tells the user the IP address of the cache server and allows the user to initiate a request to the selected cache server. The user initiates a request to the cache server, and the cache server responds to the user's request and transmits the content required by the user to the user terminal.

2. A pattern matching system based on OTT quality detection according to claim 1, characterized in that: After installation, the set-top box EVA probe can actively test the OTT video module. The active test content includes: (1) Automatically identify progressive download (PD) or HLS-based OTT video streams (including URL address and video file name); (2) Extract key video information (such as video file size, program duration, video resolution, audio and video encoding) from various video packaging formats (such as FLV / MP4 / 3GP files or TS streams); (3) Real-time playback of selected OTT video media streams, supporting MPEG4 and H.264 encoding formats; (4) Real-time measurement of various QoS indicators of OTT videos, such as video playback delay, video download rate (HTTP throughput), download percentage, number of download requests, number of downloaded bytes, number of fast-forward bytes, and number of redundant bytes; (5) Parse and display the playlist of the HLS video, and track the segment download and video bitrate switching; (6) Real-time measurement of various QoS / QoE performance indicators of HLS video, such as: OV-Score (1-5 points), card number, card duration, fragment interval deviation (seconds), fragment download time deviation (seconds), and number of out-of-order fragments; (7) Color grading (green, light green, blue, yellow, red) is used to intuitively display the QoS indicators of each slice; (8) Error code detection for OTT / HLS videos, including HTTP error return code and error count, and HLS playlist syntax errors; (9) Real-time measurement of various QoS performance indicators of TCP / IP networks, such as: number of TCP out-of-order packets, number of TCP retransmitted packets, TCP retransmission rate (%), number of TCP resets, number of TCP low window packets, TCP low window size, and Ethernet throughput indicators; (10) Select Q0S / QOE parameters to be displayed in the table and trend chart, sort by any column in the table, and quickly find the OTT video stream with the best or worst indicators in a certain category; (11) Output the contents of the OTT video media stream table to a CSV file; (12) Record and play HLS video segments.

3. A pattern matching system based on OTT quality detection according to claim 1, characterized in that: When the TV terminal device shows that the OTT video module is connected, the TV terminal device becomes a data network switching terminal. When the OTT video module includes TVOD mode, SVOD mode and AVOD mode, the auxiliary module for the OTT video module is turned on to optimize the media stream, monitor the network status, turn on the packet loss retransmission mechanism, and optimize the weak network resistance algorithm.

4. The pattern matching system based on OTT quality detection according to claim 1, characterized in that: When the TV terminal device shows that the OTT video module is connected, the TV terminal device becomes a data network switching terminal. When the OTT video module is in live broadcast mode, the auxiliary module for the OTT video module is turned on to reduce encoding delay, reduce slicing time, reduce streaming time, reduce CDN transmission time, reduce the round-trip time of data terminal transmission, and reduce the buffering time when the player starts.

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