CN112954414B - Streaming media transmission optimization method and system - Google Patents
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
- H04N21/25—Management operations performed by the server for facilitating the content distribution or administrating data related to end-users or client devices, e.g. end-user or client device authentication, learning user preferences for recommending movies
- H04N21/262—Content or additional data distribution scheduling, e.g. sending additional data at off-peak times, updating software modules, calculating the carousel transmission frequency, delaying a video stream transmission, generating play-lists
- H04N21/26208—Content or additional data distribution scheduling, e.g. sending additional data at off-peak times, updating software modules, calculating the carousel transmission frequency, delaying a video stream transmission, generating play-lists the scheduling operation being performed under constraints
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
- H04N21/23—Processing of content or additional data; Elementary server operations; Server middleware
- H04N21/24—Monitoring of processes or resources, e.g. monitoring of server load, available bandwidth, upstream requests
- H04N21/2402—Monitoring of the downstream path of the transmission network, e.g. bandwidth available
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
- H04N21/25—Management operations performed by the server for facilitating the content distribution or administrating data related to end-users or client devices, e.g. end-user or client device authentication, learning user preferences for recommending movies
- H04N21/266—Channel or content management, e.g. generation and management of keys and entitlement messages in a conditional access system, merging a VOD unicast channel into a multicast channel
- H04N21/2662—Controlling the complexity of the video stream, e.g. by scaling the resolution or bitrate of the video stream based on the client capabilities
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/60—Network structure or processes for video distribution between server and client or between remote clients; Control signalling between clients, server and network components; Transmission of management data between server and client, e.g. sending from server to client commands for recording incoming content stream; Communication details between server and client
- H04N21/63—Control signaling related to video distribution between client, server and network components; Network processes for video distribution between server and clients or between remote clients, e.g. transmitting basic layer and enhancement layers over different transmission paths, setting up a peer-to-peer communication via Internet between remote STB's; Communication protocols; Addressing
- H04N21/647—Control signaling between network components and server or clients; Network processes for video distribution between server and clients, e.g. controlling the quality of the video stream, by dropping packets, protecting content from unauthorised alteration within the network, monitoring of network load, bridging between two different networks, e.g. between IP and wireless
- H04N21/64723—Monitoring of network processes or resources, e.g. monitoring of network load
- H04N21/64738—Monitoring network characteristics, e.g. bandwidth, congestion level
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/60—Network structure or processes for video distribution between server and client or between remote clients; Control signalling between clients, server and network components; Transmission of management data between server and client, e.g. sending from server to client commands for recording incoming content stream; Communication details between server and client
- H04N21/63—Control signaling related to video distribution between client, server and network components; Network processes for video distribution between server and clients or between remote clients, e.g. transmitting basic layer and enhancement layers over different transmission paths, setting up a peer-to-peer communication via Internet between remote STB's; Communication protocols; Addressing
- H04N21/647—Control signaling between network components and server or clients; Network processes for video distribution between server and clients, e.g. controlling the quality of the video stream, by dropping packets, protecting content from unauthorised alteration within the network, monitoring of network load, bridging between two different networks, e.g. between IP and wireless
- H04N21/64784—Data processing by the network
- H04N21/64792—Controlling the complexity of the content stream, e.g. by dropping packets
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- Computer Networks & Wireless Communication (AREA)
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- Two-Way Televisions, Distribution Of Moving Picture Or The Like (AREA)
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Abstract
The invention discloses a method and a system for optimizing streaming media transmission, wherein the method part comprises the following steps: s1, receiving streaming media data, counting streaming media code rates and predicting network bandwidth by using a Kalman filtering model; s2, carrying out code rate estimation prediction by using a streaming media code rate and a network bandwidth prediction result in a non-packet-loss input mode; s3, performing bidirectional predictive code rate verification on the round trip time, the packet loss rate and the code rate estimation predicted value to obtain the output code rate of the sending end; and S4, outputting the corresponding streaming media code rate to control the flow according to the given code rate. The method is suitable for network condition prediction in wired and wireless scenes, can meet the requirement of rapidly predicting the current network speed in real time, ensures smooth transition of code rate to enable streaming media to be played more smoothly, ensures the video code rate under low bandwidth while ensuring the TCP friendliness by combining a TFRC algorithm, reduces the occurrence of the situations of video jam and pause due to too low predicted speed and the like, and is a congestion control solution based on streaming media transmission.
Description
Technical Field
The invention is applied to the field of streaming media transmission, and particularly relates to a method and a system for optimizing streaming media transmission.
Background
The scheme that the current mainstream streaming media communication deals with network congestion: one is based on RTCP control protocol, and the round-trip time and packet loss rate of the network are fed back, so that the situation of the network is reflected comparatively, a sending end is only responsible for ensuring the bandwidth of the sending end, and the TCP friendliness is not provided, and the network congestion is also aggravated; another method is to emulate the TCP flow control principle to be applied to UDP transmission, wherein the most representative algorithm is TFRC algorithm, and there are also the following: the lower the bandwidth is, the streaming media rate cannot be guaranteed, and the bandwidth is predicted incorrectly in a wireless mode. The current field predicts the bandwidth by the packet loss rate and the round trip time which are generally adopted, and the packet loss rate is not accurate to the wireless network condition. The congestion control based on the AIMD algorithm mainly has the problems that the amplitude of rate adjustment is large, the burst and jitter are easy, and the stability of streaming media is not facilitated; the congestion control based on the TFRC algorithm mainly has the problems that when congestion occurs, the speed of a receiving end is too low, video is blocked, playing is not consistent and the like, and secondly, when wireless connection is performed, the bandwidth is estimated wrongly, and the code rate is reduced.
Disclosure of Invention
The technical problem to be solved by the present invention is to provide a method and a system for optimizing streaming media transmission, aiming at the defects of the prior art.
In order to solve the above technical problem, the present invention provides a method for optimizing streaming media transmission, which comprises the following steps:
s1, receiving streaming media data, counting streaming media code rates and predicting network bandwidth by using a Kalman filtering model;
s2, carrying out code rate estimation prediction by using a streaming media code rate and a network bandwidth prediction result in a non-packet-loss input mode;
s3, performing bidirectional predictive code rate verification on the round trip time, the packet loss rate and the code rate estimation predicted value to obtain the output code rate of the sending end;
s4, outputting the corresponding streaming media code rate to control the flow according to the given code rate;
and S5, repeating the steps S1 to S4 to complete optimization.
As a possible implementation manner, further, the kalman filtering model in step S1 is constructed by the frame-to-frame delay and the data amount difference of the input real-time streaming media data.
As a possible implementation manner, further, step S2 is specifically: and (3) performing code rate estimation prediction at the next moment by combining the current streaming media code rate and the network state in a mode of combining an AIMD algorithm and EWMA low-pass filtering.
As a possible implementation manner, further, step S3 is specifically: and the sending end simultaneously adopts a TFRC algorithm and a rate estimation module to carry out code rate bidirectional prediction for ensuring TCP friendliness.
As a possible implementation manner, further, the step S2 specifically includes the following steps:
s21, the system quickly approaches the current network code rate by using an AIMD algorithm;
and S22, when the rate enters a relatively stable period, predicting the current network condition by using an EWMA low-pass filter to obtain a current code rate estimation predicted value.
As a possible implementation manner, further, the step S3 specifically includes the following steps:
s31, packaging the code rate estimation predicted value into a REMB packet, sending the REMB packet by using an RTCP protocol, and finally delivering the sending packet to a sending end;
s32, analyzing and estimating the code rate, the round-trip time and the packet loss rate;
s33, estimating the TCP friendly bandwidth by using a formula, and obtaining a basic bandwidth estimation through a TFRC algorithm;
and S34, using the opposite end estimated rate and the TFRC rate estimation as input, and obtaining a bandwidth predicted value finally through an AIMD algorithm correction value.
A stream media transmission optimization system comprises a network detection module, a code rate estimation module, an RTCP assembly module for feeding back packet loss rate and round trip time, an RTCP analysis module, a code rate check module and a flow control module;
the network detection module receives streaming media data from a sending end, counts the current streaming media code rate, predicts the current network condition, and reports the network state and the current actual streaming media code rate to the code rate estimation module;
the code rate estimation module obtains code rate prediction of a sending end at the next moment by combining the current streaming media code rate and the network state by using a combined scheme of an AIMD algorithm and an EWMA low-pass filter, and transmits a code rate prediction value to an RTCP assembly module;
the RTCP assembly module packages the code rate estimation value into a REMB packet, sends the code rate estimation value by using an RTCP protocol, the sending interval is 1s, the sending packet is finally delivered to the RTCP analysis module of the sending end, and meanwhile, the RTCP assembly module also sends an SR packet to the RTCP analysis module every 5 s;
the RTCP analysis module analyzes the estimated code rate, the round-trip time and the packet loss rate of the receiving end and feeds back the obtained result to the code rate check module;
the sending end of the code rate checking module obtains a TFRC rate by using the round-trip time and the packet loss rate, compares the TFRC rate with the estimated rate of the receiving end in combination with the minimum bandwidth threshold value to finally obtain the output code rate of the sending end, and sends the output code rate to the flow control module;
and the flow control module outputs a corresponding streaming media code stream according to the given code rate, and finally the code stream is transmitted to the network detection module.
As a possible implementation manner, further, the current network conditions predicted by the network detection module are divided into three types, namely normal, overload and underload.
By adopting the technical scheme, the invention has the following beneficial effects:
1. the invention provides network condition prediction suitable for wired and wireless scenes, which not only meets the requirement of rapidly predicting the current network speed in real time, but also ensures smooth transition of the code rate to ensure that the stream media is played more smoothly, ensures the video code rate under low bandwidth while ensuring the TCP friendliness by combining a TFRC algorithm, reduces the occurrence of the conditions of video jam and pause caused by over-low predicted speed and the like, and is a congestion control solution based on stream media transmission.
2. According to the method, the inter-frame delay and the inter-frame volume are used as input to construct the Kalman filtering model, and the network state at the next moment is predicted more accurately.
3. The invention provides a combined scheme based on AIMD algorithm and EWMA low-pass filter, which utilizes the characteristic of AIMD increasing multiplicative subtraction to calculate the network rate and simultaneously carries out exponential weighting moving average smoothing processing on the result to ensure the smooth change of the stream media code rate;
4. the invention provides a scheme based on bidirectional control of a TFRC algorithm and an AIMD algorithm, which gives consideration to TCP friendliness on the premise of ensuring the lowest video rate, thereby ensuring the basic fluency of the streaming media under low bandwidth, and meanwhile, the scheme is also suitable for wireless streaming media transmission.
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The invention is described in further detail below with reference to the following figures and embodiments:
FIG. 1 is a partial schematic flow diagram of the method of the present invention;
FIG. 2 is a schematic diagram of a portion of the system of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be described in detail and completely with reference to the accompanying drawings.
As shown in fig. 1-2, the present invention provides a method for optimizing streaming media transmission, which comprises the following steps:
s1, receiving streaming media data, counting streaming media code rates and predicting network bandwidth by using a Kalman filtering model; the method can quickly respond to the network change and can predict the wireless network condition more accurately.
S2, carrying out code rate estimation prediction by using a streaming media code rate and a network bandwidth prediction result in a non-packet-loss input mode; and smoothness is considered under the condition of ensuring the rapid rate convergence.
S3, performing bidirectional predictive code rate verification on the round trip time, the packet loss rate and the code rate estimation predicted value to obtain the output code rate of the sending end; and ensuring the TCP friendliness, and meeting the TCP friendliness on the premise of ensuring the minimum bandwidth of the streaming media.
S4, outputting the corresponding streaming media code rate to control the flow according to the given code rate;
and S5, repeating the step S1 to the step S4 to complete optimization.
The method can quickly respond to the current network condition, ensure that the dynamic adjustment of the streaming media rate adapts to the congested network and also consider the TCP friendliness.
As a possible implementation manner, further, the kalman filtering model in step S1 is constructed by the frame-to-frame delay and the data amount difference of the input real-time streaming media data.
As a possible implementation manner, further, the step S2 is specifically: and performing rate estimation by combining an AIMD algorithm and EWMA low-pass filtering.
As a possible implementation manner, further, the step S3 is specifically: and the TFRC algorithm and the rate estimation module are adopted at the sending end simultaneously to carry out code rate bidirectional prediction for ensuring TCP friendliness.
(1) According to the method, the inter-frame delay and the inter-frame volume are used as input to construct the Kalman filtering model, and the network state at the next moment is predicted more accurately. The Kalman filtering algorithm provided by the invention takes inter-frame delay and data volume change as input, and is more accurate in prediction of a network state.
(2) The invention provides a combined scheme based on AIMD algorithm and EWMA low-pass filter, which utilizes the characteristic of AIMD increasing multiplicative decreasing to calculate the network rate, and simultaneously, the result is processed by exponential weighting moving average smoothing to ensure the smooth change of the stream media code rate; the AIMD algorithm and the EWMA low-pass filter combination scheme well play respective advantages, the AIMD can quickly predict the rate of the streaming media at the next moment, and the EWMA exponential weighted moving average can smooth the code rate, so that the rate at the next moment is not mutated, and the streaming media is smoothly played;
(3) the invention provides a scheme based on bidirectional control of a TFRC algorithm and an AIMD algorithm, which gives consideration to TCP friendliness on the premise of ensuring the lowest video rate, thereby ensuring the basic fluency of the streaming media under low bandwidth, and meanwhile, the scheme is also suitable for wireless streaming media transmission. The invention provides TFRC and AIMD algorithms to creatively solve the requirement of network TCP friendliness on the premise of ensuring the lowest code rate of streaming media playing. The AIMD algorithm has no reference of packet loss rate, so that the current network situation can be well predicted in a wireless scene.
As a possible implementation manner, further, the step S2 specifically includes the following steps:
s21, the system quickly approaches the current network code rate by using an AIMD algorithm;
and S22, when the speed enters a relatively stable period, predicting the current network condition by using an EWMA low-pass filter to obtain the current network state.
As a possible implementation manner, further, the step S3 specifically includes the steps of:
s31, packaging the code rate estimation predicted value into a REMB packet, sending the REMB packet by using an RTCP protocol, and finally delivering the sending packet to a sending end;
s32, analyzing and estimating the code rate, the round trip time and the packet loss rate;
s33, estimating the TCP friendly bandwidth by using a formula, and obtaining a basic bandwidth estimation through a TFRC algorithm;
and S34, using the opposite end estimated rate and the TFRC rate estimation as input, and obtaining a bandwidth predicted value finally through an AIMD algorithm correction value.
A stream media transmission optimization system comprises a network detection module, a code rate estimation module, an RTCP assembly module for feeding back packet loss rate and round trip time, an RTCP analysis module, a code rate check module and a flow control module;
the network detection module receives streaming media data from a sending end, counts the current streaming media code rate, predicts the current network condition, and reports the network state and the current actual streaming media code rate to the code rate estimation module;
the code rate estimation module obtains code rate prediction of a sending end at the next moment by combining the current streaming media code rate and the network state by using a combined scheme of an AIMD algorithm and an EWMA low-pass filter, and transmits a code rate prediction value to an RTCP assembly module;
the RTCP assembly module packages the code rate estimation value into a REMB packet, sends the code rate estimation value by using an RTCP protocol, the sending interval is 1s, the sending packet is finally delivered to the RTCP analysis module of the sending end, and meanwhile, the RTCP assembly module also sends an SR packet to the RTCP analysis module every 5 s;
the RTCP analysis module analyzes the estimated code rate, the round-trip time and the packet loss rate of the receiving end and feeds back the obtained result to the code rate check module;
the sending end of the code rate checking module obtains a TFRC rate by using the round-trip time and the packet loss rate, compares the TFRC rate with the estimated rate of the receiving end in combination with the minimum bandwidth threshold value to finally obtain the output code rate of the sending end, and sends the output code rate to the flow control module;
and the flow control module outputs a corresponding streaming media code stream according to the given code rate, and finally the code stream is transmitted to the network detection module.
As a possible implementation manner, further, the current network conditions predicted by the network detection module are divided into three types, namely normal, overload and underload.
The foregoing is directed to embodiments of the present invention, and equivalents, modifications, substitutions and variations such as will occur to those skilled in the art, which fall within the scope and spirit of the appended claims.
Claims (4)
1. A method for optimizing streaming media transmission is characterized in that: the method comprises the following steps:
s1, receiving streaming media data, counting streaming media code rates and predicting network bandwidth by using a Kalman filtering model;
s2, carrying out code rate estimation prediction by using a streaming media code rate and a network bandwidth prediction result in a non-packet-loss input mode;
s3, performing bidirectional predictive code rate verification on the round trip time, the packet loss rate and the code rate estimation predicted value to obtain the output code rate of the sending end;
s4, outputting corresponding streaming media code rate to control flow according to the given code rate;
s5, repeating the step S1 to the step S4 to complete optimization;
wherein, S2 includes:
s21, the system quickly approaches the current network code rate by using an AIMD algorithm;
s22, when the rate enters a relatively stable period, predicting the current network condition by using an EWMA low-pass filter to obtain a current code rate estimation predicted value;
in addition, S3 includes:
s31, packaging the code rate estimation predicted value into a REMB packet, sending the REMB packet by using an RTCP protocol, and finally delivering the sending packet to a sending end;
s32, analyzing and estimating the code rate, the round trip time and the packet loss rate;
s33, estimating the TCP friendly bandwidth by using a formula, and obtaining a basic bandwidth estimation through a TFRC algorithm;
and S34, using the estimated code rate and TFRC rate estimation of the receiving end as input, and finally obtaining a bandwidth predicted value and a sending end output code rate through an AIMD algorithm correction value.
2. The method for optimizing streaming media transmission according to claim 1, wherein: the Kalman filtering model in the step S1 is constructed by inter-frame delay and data quantity difference of input real-time streaming media data.
3. A streaming media transmission optimization system, characterized by: the system comprises a network detection module, a code rate estimation module, an RTCP assembly module for feeding back packet loss rate and round trip time, an RTCP analysis module, a code rate check module and a flow control module;
the network detection module receives streaming media data from a sending end, counts the current streaming media code rate, predicts the current network condition, and reports the network state and the current actual streaming media code rate to the code rate estimation module;
the code rate estimation module obtains code rate prediction of a sending end at the next moment by combining the current streaming media code rate and the network state by using a combined scheme of an AIMD algorithm and an EWMA low-pass filter, and transmits a code rate prediction value to an RTCP assembly module;
the RTCP assembly module packages the code rate estimation value into a REMB packet, sends the code rate estimation value by using an RTCP protocol, the sending interval is 1s, the sending packet is finally delivered to the RTCP analysis module of the sending end, and meanwhile, the RTCP assembly module also sends an SR packet to the RTCP analysis module every 5 s;
the RTCP analysis module analyzes the estimated code rate, the round-trip time and the packet loss rate of the receiving end and feeds back the obtained result to the code rate check module;
the sending end of the code rate checking module obtains a TFRC rate by using the round-trip time and the packet loss rate, compares the TFRC rate with the estimated code rate of the receiving end in combination with the lowest bandwidth threshold value to finally obtain the output code rate of the sending end, and sends the output code rate to the flow control module;
and the flow control module outputs a corresponding streaming media code stream according to the given code rate, and finally the code stream is transmitted to the network detection module.
4. The system for optimizing streaming media transmission according to claim 3, wherein: the current network conditions predicted by the network detection module are divided into normal, overload and underload.
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