CN115801639A - Bandwidth detection method and device, electronic equipment and storage medium - Google Patents
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Abstract
The embodiment of the application provides a bandwidth detection method, a bandwidth detection device, electronic equipment and a storage medium, the method is applied to a receiving end of a network to be detected, overload detection is carried out on calculated packet cluster intervals through a preset trend line filter, and a corresponding network overload state is obtained, wherein the trend line filter calculates packet cluster delay gradient of the network by adopting a least square method, so that the number of feedback packets needing to be received and sent is reduced, meanwhile, the delay trend of the network is rapidly and accurately obtained, and rapid convergence of an algorithm is guaranteed. Further, the corresponding network estimated bandwidth is calculated by adopting the determined network overload state, and the calculated network estimated bandwidth is dynamically adjusted when the network to be detected is determined to be in a stable state based on the preset stable state condition.
Description
Technical Field
The present invention relates to the field of bandwidth data detection technologies, and in particular, to a bandwidth detection method and apparatus, an electronic device, and a storage medium.
Background
In a Real-Time communication (WebRTC) transmission module, a Congestion Control algorithm (GCC) or a bandwidth estimation algorithm (Transport connection Control, TCC) is adopted to perform effective dynamic detection and dynamic evaluation on network bandwidth change between a sending end and a receiving end, and then network Congestion is identified through a detection result, so that important effects are played on Quality of Service (QoS) of video transmission, user experience and the like in a WebRTC system.
However, in the related art, the above method still has the following defects:
on the first hand, when a congestion control algorithm GCC is adopted to carry out network detection, the available bandwidth of a network is estimated through the change of network characteristics such as time delay information sensed by a receiving end, and the like; meanwhile, the detection result is too sensitive to delay jitter, and delayed false sampling occurs with a high probability under a weak network with large packet loss and jitter, so that misjudgment of available bandwidth is caused, and the finally obtained bandwidth detection result is influenced.
In the second aspect, when a bandwidth estimation algorithm TCC is used for network detection, the available bandwidth of the network is estimated through the delay information received by the transmitting end, and this method requires the receiving end to transmit a large number of feedback packets back to the transmitting end, so that a certain network bandwidth is usually occupied.
Disclosure of Invention
The embodiment of the application provides a bandwidth detection method and device, electronic equipment and a storage medium, which are used for improving the accuracy and the real-time performance of bandwidth detection.
In a first aspect, an embodiment of the present application provides a bandwidth detection method, including:
and responding to each audio and video data packet received in real time, and calculating the packet cluster interval of the network.
And carrying out overload detection on the packet cluster intervals by adopting a preset trend line filter to obtain a corresponding network overload state, wherein the trend line filter calculates the packet cluster delay gradient of the network by adopting a least square method.
And based on the network overload state, performing bandwidth estimation on the receiving code rate of the receiving end, and calculating the corresponding network estimation bandwidth.
And responding to the condition that the network overload state meets a preset steady state condition, and dynamically adjusting the network estimated bandwidth to obtain a corresponding bandwidth detection result.
In a second aspect, an embodiment of the present application provides a bandwidth detecting device, including:
and the receiving module is used for responding to each audio and video data packet received in real time and calculating the packet cluster interval of the network.
And the detection module is used for carrying out overload detection on the packet cluster intervals by adopting a preset trend line filter to obtain a corresponding network overload state, wherein the trend line filter calculates the packet cluster delay gradient of the network by adopting a least square method.
And the estimation module is used for estimating the bandwidth of the receiving code rate of the receiving end based on the network overload state and calculating the corresponding network estimation bandwidth.
And the adjusting module is used for responding to the condition that the network overload state meets the preset steady state condition, dynamically adjusting the network estimated bandwidth and obtaining a corresponding bandwidth detection result.
In an optional embodiment, the packet cluster interval of the network is calculated in response to each audio/video data packet received in real time, and the receiving module is specifically configured to:
responding to each audio and video data packet received in real time, and respectively executing the following operations aiming at each audio and video data packet: and judging whether a first sending time stamp carried by one audio and video data packet is greater than a second sending time stamp carried by an audio and video data packet cluster of adjacent receiving time, wherein the second sending time stamp is used for indicating the latest sending time of each audio and video data packet in the audio and video data packet cluster of adjacent receiving time. And when the first sending time stamp is determined to be larger than the second sending time stamp, taking the audio and video data packet as a detection data packet aiming at the network.
Calculating packet cluster intervals for the network based on the determined respective probe packets.
In an optional embodiment, the packet cluster interval is subjected to overload detection by using a preset trend line filter to obtain a corresponding network overload state, and the detection module is specifically configured to:
and calculating the packet cluster delay gradient of the network based on the packet cluster interval by adopting a preset trend line filter.
And if the packet cluster delay gradient belongs to a preset first gradient interval, determining that the network overload state is an underload state.
And if the packet cluster delay gradient belongs to a preset second gradient interval, determining that the network overload state is a common state.
And if the packet cluster delay gradient belongs to a preset third gradient interval, determining that the network overload state is a common overload state.
And if the packet cluster delay gradient belongs to a preset fourth gradient interval, determining that the network overload state is a serious overload state.
In an optional embodiment, the bandwidth estimation is performed on the receiving code rate of the receiving end based on the network overload state, and a corresponding network estimated bandwidth is calculated, where the estimation module is specifically configured to:
and if the network overload state is an underload state, performing bandwidth estimation on the receiving code rate of the receiving end by adopting a control-keeping state, and calculating the corresponding network estimation bandwidth.
And if the network overload state is a general overload state or a severe overload state, adopting a reduction control state to carry out bandwidth estimation on the receiving code rate of the receiving end and calculate the corresponding network estimation bandwidth, wherein the reduction control state controls multiplicative reduction of the receiving code rate of the receiving end.
And if the network overload state is a common state, performing state promotion on the current control state of the receiving code rate based on a preset state control rule, performing bandwidth estimation on the receiving code rate of the receiving end by adopting a promoted corresponding target control state, and calculating a corresponding network estimation bandwidth.
In an alternative embodiment, the network overload condition is an underrun condition or a normal condition,
the response to the network overload state meeting a preset steady-state condition is performed, the network estimated bandwidth is dynamically adjusted, and a corresponding bandwidth prediction result is obtained, and the adjusting module is specifically configured to:
obtaining a historical overload state histogram of the network, wherein the historical overload state histogram at least comprises: and recording the probability distribution value of at least one historical overload state in a preset historical time range by the network.
And responding to the fact that the sum of the probability distribution values of the corresponding common state and the underload state in the historical overload state histogram meets a preset distribution threshold value, and determining that the network overload state meets a preset steady-state condition.
And based on the network overload state, promoting a bandwidth critical point of the network, and adopting the promoted bandwidth critical point to dynamically adjust the estimated bandwidth of the network to obtain a corresponding bandwidth detection result.
In an alternative embodiment, the network overload condition is a general overload condition,
the adjusting module is further configured to, after performing bandwidth estimation on the receiving bit rate of the receiving end and calculating a corresponding network estimated bandwidth, perform:
and based on the network overload state, linearly adjusting the bandwidth critical point of the network according to the recorded historical critical point, and dynamically adjusting the estimated bandwidth of the network by adopting the adjusted bandwidth critical point to obtain a corresponding bandwidth detection result.
In an alternative embodiment, the network overload condition is a severe overload condition,
after performing bandwidth estimation on the receiving bit rate of the receiving end and calculating the corresponding network estimated bandwidth, the adjusting module is further configured to:
and reducing the bandwidth critical point of the network based on the network overload state, and dynamically adjusting the estimated bandwidth of the network by adopting the reduced bandwidth critical point to obtain a corresponding bandwidth detection result.
In a third aspect, an electronic device is proposed, which comprises a processor and a memory, wherein the memory stores program code, and when the program code is executed by the processor, the processor is caused to execute the steps of the bandwidth detection method according to the first aspect.
In a fourth aspect, a computer-readable storage medium is proposed, which comprises program code for causing an electronic device to perform the steps of the bandwidth detection method of the first aspect when the program code runs on the electronic device.
The technical effects of the embodiment of the application are as follows:
the embodiment of the application provides a bandwidth detection method, a bandwidth detection device, electronic equipment and a storage medium, the method is applied to a receiving end of a network to be detected, overload detection is carried out on calculated packet cluster intervals through a preset trend line filter, and a corresponding network overload state is obtained, wherein the trend line filter calculates packet cluster delay gradient of the network by adopting a least square method, so that the number of feedback packets needing to be received and sent is reduced, meanwhile, the delay trend of the network is rapidly and accurately obtained, and rapid convergence of an algorithm is guaranteed.
Further, the determined network overload state is adopted to calculate the corresponding network estimated bandwidth, and the calculated network estimated bandwidth is dynamically adjusted when the network to be detected is determined to be in a steady state based on the preset steady state condition.
Drawings
Fig. 1 is a schematic diagram of a possible application scenario provided in an embodiment of the present application;
fig. 2 is a schematic diagram of a bandwidth detection module according to an embodiment of the present disclosure;
fig. 3 is a flowchart of a bandwidth detection method according to an embodiment of the present application;
FIG. 4 is a schematic diagram of a trend line filter according to an embodiment of the present disclosure;
fig. 5 is a schematic diagram of a packet cluster interval provided in an embodiment of the present application;
FIG. 6 is a histogram of historical overload conditions according to an embodiment of the present application;
fig. 7 is a schematic diagram of an overload buffering provided by an embodiment of the present application;
fig. 8 is a schematic view of an actual application scenario provided in the embodiment of the present application;
fig. 9 is a schematic structural diagram of a bandwidth detection apparatus according to an embodiment of the present application;
fig. 10 is a schematic view of an electronic device according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present invention will be described clearly and completely below with reference to the drawings in the embodiments of the present invention, and it is obvious that the embodiments described are only some embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that "a plurality" is understood as "at least two" in the description of the present application. "and/or" describes the association relationship of the associated objects, meaning that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. A is connected with B and can represent: a and B are directly connected and A and B are connected through C. In addition, in the description of the present application, the terms "first," "second," and the like are used for descriptive purposes only and are not intended to indicate or imply relative importance nor order to be construed.
In addition, in the technical scheme of the application, the data acquisition, transmission, use and the like all meet the requirements of relevant national laws and regulations.
The design idea of the application is as follows:
in the related art, a congestion control algorithm GCC or a bandwidth estimation algorithm TCC is used to realize effective detection of network bandwidth, however, the above method still has the following defects:
1) Congestion control algorithm GCC
The congestion control algorithm GCC is a bandwidth detection algorithm based on delay perception and realized by a receiving end, the available bandwidth of a network is estimated through the change of network characteristics such as delay information and the like perceived by the receiving end, and the method needs to frequently perceive the upper limit of the bandwidth of the network due to the time change of the available bandwidth, so that the problems of too low convergence speed and slow response to the step change of the bandwidth exist; meanwhile, the detection result is too sensitive to delay jitter, and delayed false sampling occurs with a high probability under a weak network with large packet loss and jitter, so that misjudgment of available bandwidth is caused, and the finally obtained bandwidth detection result is influenced.
2) Bandwidth estimation algorithm TCC
The bandwidth estimation algorithm TCC is a bandwidth detection algorithm based on delay sensing implemented by a sending end, and estimates the available bandwidth of a network through delay information received by the sending end, because this method requires the receiving end to transmit a large number of feedback packets back to the sending end, a certain network bandwidth is usually occupied, and in a weaker network, the above method easily causes a long estimation time required by the algorithm due to the loss of the feedback packets, thereby affecting the efficiency of bandwidth detection.
In order to improve accuracy and real-time performance of bandwidth detection, the embodiment of the application provides a bandwidth detection method, a bandwidth detection device, electronic equipment and a storage medium, the method is applied to a receiving end of a network to be detected, overload detection is performed on calculated packet cluster intervals through a preset trend line filter, and a corresponding network overload state is obtained, wherein the trend line filter calculates a packet cluster delay gradient of the network by using a least square method, so that the delay trend of the network is rapidly and accurately obtained while the number of feedback packets to be received and sent is reduced, rapid convergence of an algorithm is ensured, further, the corresponding network estimation bandwidth is calculated by using the determined network overload state, and the calculated network estimation bandwidth is dynamically adjusted when the network to be detected is determined to be in a steady state based on a preset steady state condition.
Based on the above technical effects, the preferred embodiments of the present application are described below with reference to the drawings of the specification, it should be understood that the preferred embodiments described herein are only for illustrating and explaining the present application, and are not used to limit the present application, and features in the embodiments and examples of the present application may be combined with each other without conflict.
Referring to fig. 1, a schematic diagram of a possible application scenario provided in an embodiment of the present application is shown, where the application scenario includes: a target client 101 and a server 102. The target client 101 and the server 102 may perform information interaction through a communication network, where the communication mode adopted by the communication network may include: wireless communication and wired communication.
Illustratively, the target client may communicate with the server 102 by accessing the network via cellular Mobile communication technology, including fifth Generation Mobile networks (5 g) technology.
Optionally, the target client 101 may access a network through a short-range Wireless communication mode, and communicate with the server 102, where the short-range Wireless communication mode includes a Wireless Fidelity (Wi-Fi) technology.
In the embodiment of the present application, the number of the above-mentioned devices is not limited at all, and as shown in fig. 1, only one target client 101 and one server 102 are taken as an example for description, and the above-mentioned devices and their respective functions are briefly described below.
The target client 101 may be or operate through a device that provides voice and/or data connectivity to a user, the device comprising: a hand-held terminal device, a vehicle-mounted terminal device, etc. having a wireless connection function.
By way of example, the target client may be or operate through any one or combination of the following devices, including but not limited to a Mobile phone, a tablet computer, a laptop computer, a palmtop computer, a Mobile Internet Device (MID), a wearable Device, a Virtual Reality (VR) Device, an Augmented Reality (AR) Device, a wireless terminal Device in industrial control, a wireless terminal Device in unmanned driving, a wireless terminal Device in a smart grid, a wireless terminal Device in transportation security, a wireless terminal Device in a smart city, or a wireless terminal Device in a smart home, and the like, and the present application is not limited thereto.
Further, in this embodiment of the present application, the target client 101 may use an audio/video data packet conforming to a Real-time Transport Protocol (RTP), trigger the server 102 to enter bandwidth detection, receive a Receiver bandwidth estimation data packet (REMB) conforming to a Real-time Transport Control Protocol (RTCP) and periodically fed back from the server 102, and determine a bandwidth detection result of the server 102 as a Receiver, and in a subsequent process, the target client 101 may perform code rate Control of a transmitter based on the bandwidth detection result to adapt to network jitter in the above scenario.
Further, the server 102 may be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server providing basic cloud computing services such as a cloud service, a cloud database, cloud computing, a cloud function, cloud storage, a Network service, cloud communication, a middleware service, a domain name service, a security service, a Content Delivery Network (CDN), a big data and artificial intelligence platform, and the like.
For example, in this embodiment of the present application, the server 102 may be a background server for providing a real-time communication service WebRTC, and referring to fig. 2, the server 102 may be deployed with a bandwidth detection module, specifically, the bandwidth detection module may be composed of a time filter 201, a trend line filter 202, and an AIMD (increase, multiply, decrease) code rate adjustment module 203, and when receiving each audio/video data packet sent from the target client 101, the server 102 may implement the relevant function of the bandwidth detection method provided in the embodiment of the present application based on the bandwidth detection module 202.
Based on the above application scenario, referring to the accompanying drawings, the bandwidth detection method provided in the embodiment of the present application will be further described and explained, where the method may be applied to a receiving end of a network to be detected, for example, the method may be applied to a server 102 in the above application scenario, and referring to fig. 3, the method specifically includes:
s301: and responding to each audio and video data packet received in real time, and calculating packet cluster intervals of the network.
Specifically, in real-time communication WebRTC, a transmitting end adopts a real-time transmission protocol RTP to transmit audio and video data packets conforming to the protocol to a receiving end to be detected, the receiving end responds to the received audio and video data packets and forms corresponding audio and video data packet clusters by using each audio and video data packet received in unit sampling time based on preset sampling time, the audio and video data packet clusters are used as data units processed by an algorithm, and the state change condition of a network to be detected is analyzed through the calculated receiving interval between each audio and video data packet cluster.
Illustratively, in the embodiment of the present application, the audio/video data packets received from the target client 101 are sampled at preset sampling time (e.g., 5 ms) to form corresponding audio/video data packet clusters, and packet cluster intervals of the network are calculated based on the respective receiving time of each audio/video data packet cluster.
In an optional embodiment, to avoid receiving disorder among each audio/video data packet cluster caused by network jitter, and to eliminate the influence of noise on the bandwidth detection result caused by network jitter, the following method may be adopted to calculate the packet cluster interval of the network, including:
s3011: responding to each audio and video data packet received in real time, and aiming at each audio and video data packet cluster, respectively executing the following operations:
s30111: and judging whether the first sending time stamp carried by one audio and video data packet is greater than the second sending time stamp carried by the audio and video data packet cluster of the adjacent receiving time.
Specifically, each audio/video data packet may carry a first sending time stamp indicating its corresponding sending time, and when receiving each audio/video data packet from the sending end, the server may perform disorder judgment on the received audio/video data packet based on each carried first sending time stamp.
S30112: and when the first sending time stamp is determined to be larger than the second sending time stamp, taking an audio and video data packet as a detection data packet of the network.
In an optional embodiment, in order to avoid the influence of noise generated by network jitter on the bandwidth detection result, a maximum timestamp representing the latest transmission time of each corresponding audio/video data packet cluster in an audio/video data packet cluster of adjacent reception time corresponding to a currently received audio/video data packet (i.e., the audio/video data packet cluster received last time) is used as a second transmission timestamp carried by the audio/video data packet cluster of the adjacent reception time, so that when it is determined that a first transmission timestamp carried by a currently received audio/video data packet is greater than a second transmission timestamp carried by the corresponding audio/video data packet cluster received last time, the audio/video data packet is determined to be ordered.
Illustratively, in the embodiment of the application, when it is determined that a first sending timestamp carried by a current audio/video data packet is greater than a second sending timestamp carried by an adjacent audio/video data packet cluster, it is determined that the current audio/video data packet is ordered, and the current audio/video data packet is used as a detection data packet of a network.
S3012: based on the determined individual probe packets, packet cluster intervals of the network are calculated.
Therefore, based on the manner, the embodiment of the application performs denoising processing on each received audio and video data packet, and determines each corresponding audio and video data packet cluster and the packet cluster interval of the network again based on each detected data packet determined after processing, thereby avoiding adverse effects on bandwidth detection results caused by network jitter and the like, and effectively ensuring the accuracy of finally obtained bandwidth detection results.
S302: and (4) carrying out overload detection on the packet cluster intervals by adopting a preset trend line filter to obtain a corresponding network overload state.
And further, inputting the calculated packet cluster interval into a preset trend line filter, wherein the trend line filter calculates the packet cluster delay gradient of the network by adopting a least square method, so that the delay trend of the network is quickly and accurately reflected under the condition of less sampling.
For example, referring to fig. 4, in the embodiment of the present application, a preset trend line filter is used to take a calculated interval between a plurality of packet clusters as an input, and a least square method is used to calculate a packet cluster delay gradient of a network, and further, the calculated packet cluster delay gradient is mapped to each preset gradient interval, so as to determine a network overload state of the network to be detected.
It should be noted that the actual calculation formula of the trend line filter may be shown as a trend line filter in a bandwidth estimation algorithm TCC, and in an actual situation, the trend line filter may also be adaptively modified by a person skilled in the art according to an actual service scenario, which is not described herein again.
Further, in the embodiment of the present application, the network overload state to be determined is defined as: an underload state, a normal state, a general overload state, and a severe overload state, and corresponding gradient intervals are respectively set according to the network overload states, as shown in fig. 4, a packet cluster delay gradient calculated based on a trend line filter is mapped to a preset certain gradient interval (e.g., a preset first gradient interval, a preset second gradient interval, a preset third gradient interval, and a preset fourth gradient interval) to determine a network overload state of a network to be detected, and a packet cluster interval of each network overload state is shown in fig. 5.
S303: and based on the network overload state, carrying out bandwidth estimation on the receiving code rate of the receiving end, and calculating the corresponding network estimated bandwidth.
Further, in the embodiment of the present application, for an AIMD (increase, multiply, decrease) code rate adjustment module, the following code rate control states are defined: the control state keeping, the control state reducing and the control state improving respectively correspond to the code rate keeping, the code rate reducing and the code rate improving of the current receiving end, and based on the calculated network overload state, the code rate control state of the module is adjusted, and the corresponding network estimation bandwidth is calculated, as follows:
in an optional embodiment, if the calculated network overload state is an underload state, the state enters a control-maintaining state, bandwidth estimation is performed on a receiving code rate of a receiving end, and a corresponding network estimated bandwidth is calculated.
In an optional embodiment, if the calculated network overload state is a general overload state or a severe overload state, entering a reduction control state, performing bandwidth estimation on a receiving code rate of a receiving end, and calculating a corresponding network estimated bandwidth, wherein in the reduction control state, multiplicatively and rapidly reducing the receiving code rate of the receiving end.
In an optional embodiment, if the calculated network overload state is a normal state, the current control state of the receiving bit rate is subjected to state promotion based on a preset state control rule, and the receiving bit rate of the receiving end is subjected to bandwidth estimation by adopting a promoted corresponding target control state to calculate a corresponding network estimation bandwidth.
For example, if the network overload state is a normal state and the current control state of the receiving code rate is a control-maintaining state, the current control state is subjected to state promotion, and the corresponding promotion control state is adopted to perform bandwidth estimation on the receiving code rate of the receiving end and calculate the corresponding network estimated bandwidth, wherein in the promotion control state, the receiving code rate of the receiving end is subjected to additive slow promotion.
For another example, if the network overload state is a normal state and the current control state of the receiving bit rate is a reduced control state, the current control state is subjected to state promotion, and a corresponding control maintaining state is adopted to perform bandwidth estimation on the receiving bit rate of the receiving end and calculate a corresponding network estimation bandwidth.
In the embodiment of the present application, a specific implementation manner of the bandwidth estimation may refer to a bandwidth estimation manner in the related art, for example, a corresponding network estimated bandwidth is obtained through the estimated channel capacity, which is not limited in the present application.
S304: and responding to the condition that the network overload state meets the preset steady state condition, and dynamically adjusting the network estimated bandwidth to obtain a corresponding bandwidth detection result.
Specifically, on the premise that the available bandwidth needs to be fully utilized, the detection process of the maximum available bandwidth is actually a trial-and-error process of the critical point, in the embodiment of the present application, in order to reduce the influence of jitter under the weak network and avoid large jump of the critical point caused by inaccurate delay sampling, a historical overload state histogram is adopted to smooth the critical point of the bandwidth of the network, specifically, whether the network overload state meets a preset steady state condition is determined based on the historical overload state histogram, where the historical overload state histogram at least includes: and recording the probability distribution value of each of at least one historical overload state in a preset historical time range by the network.
For example, referring to fig. 6, with reference to the historical overload state histogram shown in the drawing, the probability distribution value of each of at least one historical overload state in a preset historical time range of the network is counted, wherein if the sum of the probability distribution values of the corresponding normal state and the underloaded state in the historical overload state histogram meets a preset distribution threshold (e.g., 98%), it may be determined that the network meets a preset steady-state condition, and further, in response to the network meeting the steady-state condition, the bandwidth critical point of the current network is promoted to the currently calculated network estimated bandwidth, and the promoted bandwidth critical point is adopted to dynamically adjust the network estimated bandwidth, so as to obtain a corresponding bandwidth detection result.
In an optional embodiment, if the calculated network overload state is a general overload state, in the above step S303, after the corresponding network estimated bandwidth is calculated, based on the general overload state, it is considered that the historical critical point does not need to be updated, and then the bandwidth critical point of the network is slowly and linearly adjusted according to the recorded historical critical point, so as to dynamically adjust the network estimated bandwidth, and obtain the corresponding bandwidth detection result.
In an optional embodiment, if the calculated network overload state is a severe overload state, in the above step S303, after the corresponding network estimated bandwidth is calculated, the historical critical point may be updated based on the severe overload state, and the bandwidth critical point is rapidly reduced to the calculated network estimated bandwidth, so as to dynamically adjust the network estimated bandwidth, and obtain the corresponding bandwidth detection result.
Referring to fig. 7, based on the foregoing manner, in the embodiment of the present application, through a history overload state histogram in a steady state and overload buffering for a bandwidth critical point of a network, a code rate under a weak network is prevented from changing too fast, and erroneous sampling under a weak network is avoided, so that accuracy of bandwidth detection is further improved.
For convenience of understanding, refer to fig. 8, which is a schematic diagram of a bandwidth detection method in practical application provided in the embodiment of the present application, in the practical application, a server uses an SFU based on Janus, and packages a congestion control module package C interface of a WebRTC source code into librbe. In libbe, deleting overload detection modules based on Kalman filters, such as original OveruseEstimators, overuseDetectors and the like of GCC, and adding trendline Estimators in TCC. Furthermore, a Histogram object is added in the AIMD code rate adjusting module for counting the overload state, and a critical point buffer algorithm under the overload state is added, so that the convergence rate of the algorithm and the accuracy of the output bandwidth detection result are effectively improved based on the mode.
Further, based on the same technical concept, the embodiment of the present application further provides a bandwidth detection device, which can be used to implement the above method flow of the embodiment of the present application. Referring to fig. 9, the apparatus includes: a receiving module 901, a detecting module 902, an estimating module 903 and an adjusting module 904, wherein:
a receiving module 901, configured to calculate a packet cluster interval of the network in response to each audio/video data packet received in real time.
A detecting module 902, configured to perform overload detection on the packet cluster interval by using a preset trend line filter to obtain a corresponding network overload state, where the trend line filter calculates a packet cluster delay gradient of the network by using a least square method.
An estimating module 903, configured to perform bandwidth estimation on the receiving bit rate of the receiving end based on the network overload state, and calculate a corresponding network estimated bandwidth.
An adjusting module 904, configured to dynamically adjust the network estimated bandwidth in response to that the network overload state meets a preset steady-state condition, so as to obtain a corresponding bandwidth detection result.
In an optional embodiment, in response to each audio/video data packet received in real time, the receiving module 901 is specifically configured to calculate a packet cluster interval of the network:
responding to each audio and video data packet received in real time, and respectively executing the following operations aiming at each audio and video data packet: and judging whether a first sending time stamp carried by one audio and video data packet is greater than a second sending time stamp carried by an audio and video data packet cluster of adjacent receiving time, wherein the second sending time stamp is used for indicating the latest sending time of each audio and video data packet in the audio and video data packet cluster of the adjacent receiving time. And when the first sending time stamp is determined to be larger than the second sending time stamp, taking the audio and video data packet as a detection data packet aiming at the network.
Calculating packet cluster intervals for the network based on the determined respective probe packets.
In an optional embodiment, the packet cluster interval is subjected to overload detection by using a preset trend line filter to obtain a corresponding network overload state, and the detection module 902 is specifically configured to:
and calculating the packet cluster delay gradient of the network based on the packet cluster interval by adopting a preset trend line filter.
And if the packet cluster delay gradient belongs to a preset first gradient interval, determining that the network overload state is an underload state.
And if the packet cluster delay gradient belongs to a preset second gradient interval, determining that the network overload state is a common state.
And if the packet cluster delay gradient belongs to a preset third gradient interval, determining that the network overload state is a common overload state.
And if the packet cluster delay gradient belongs to a preset fourth gradient interval, determining that the network overload state is a serious overload state.
In an optional embodiment, the bandwidth estimation is performed on the receiving code rate of the receiving end based on the network overload state, and a corresponding network estimated bandwidth is calculated, where the estimating module 903 is specifically configured to:
and if the network overload state is an underload state, performing bandwidth estimation on the receiving code rate of the receiving end by adopting a control-keeping state, and calculating the corresponding network estimation bandwidth.
And if the network overload state is a general overload state or a serious overload state, adopting a reduction control state to estimate the bandwidth of the receiving code rate of the receiving end and calculate the corresponding network estimation bandwidth, wherein the reduction control state controls multiplicative reduction of the receiving code rate of the receiving end.
And if the network overload state is a common state, performing state promotion on the current control state of the receiving code rate based on a preset state control rule, performing bandwidth estimation on the receiving code rate of the receiving end by adopting a promoted corresponding target control state, and calculating a corresponding network estimation bandwidth.
In an alternative embodiment, the network overload condition is an underrun condition or a normal condition,
the adjusting module 904 is specifically configured to, in response to the network overload state meeting a preset steady-state condition, dynamically adjust the network estimated bandwidth to obtain a corresponding bandwidth prediction result:
obtaining a historical overload state histogram of the network, wherein the historical overload state histogram at least comprises: and recording the probability distribution value of at least one historical overload state in a preset historical time range by the network.
And responding to the fact that the sum of the probability distribution values of the corresponding common state and the underload state in the historical overload state histogram meets a preset distribution threshold value, and determining that the network overload state meets a preset steady-state condition.
And based on the network overload state, promoting a bandwidth critical point of the network, and adopting the promoted bandwidth critical point to dynamically adjust the estimated bandwidth of the network to obtain a corresponding bandwidth detection result.
In an alternative embodiment, the network overload condition is a general overload condition,
then, after performing bandwidth estimation on the receiving bit rate of the receiving end and calculating the corresponding network estimated bandwidth, the adjusting module 904 is further configured to:
and based on the network overload state, linearly adjusting the bandwidth critical point of the network according to the recorded historical critical point, and dynamically adjusting the estimated bandwidth of the network by adopting the adjusted bandwidth critical point to obtain a corresponding bandwidth detection result.
In an alternative embodiment, the network overload condition is a severe overload condition,
the adjusting module is further configured to, after performing bandwidth estimation on the receiving bit rate of the receiving end and calculating a corresponding network estimated bandwidth, perform:
and reducing the bandwidth critical point of the network based on the network overload state, and dynamically adjusting the estimated bandwidth of the network by adopting the reduced bandwidth critical point to obtain a corresponding bandwidth detection result.
Based on the same inventive concept as the above application embodiments, the application embodiments further provide an electronic device, and the electronic device may be used for bandwidth detection. In one embodiment, the electronic device may be a server, a terminal device, or other electronic device. In this embodiment, the electronic device may be configured as shown in fig. 10, and include a memory 1001, a communication interface 1003, and one or more processors 1002.
A memory 1001 for storing computer programs executed by the processor 1002. The memory 1001 may mainly include a storage program area and a storage data area, where the storage program area may store an operating system, a program required for running an instant messaging function, and the like; the storage data area can store various instant messaging information, operation instruction sets and the like.
The processor 1002 may include one or more Central Processing Units (CPUs), a digital Processing Unit, and the like. The processor 1002 is configured to implement the bandwidth detection method when calling the computer program stored in the memory 1001.
The communication interface 1003 is used for communicating with a terminal device and other servers.
The embodiment of the present application does not limit the specific connection medium among the memory 1001, the communication interface 1003, and the processor 1002. In the embodiment of the present application, the memory 1001 and the processor 1002 are connected through the bus 1004 in fig. 10, the bus 1004 is represented by a thick line in fig. 10, and the connection manner between other components is only schematically illustrated and not limited. The bus 1004 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in FIG. 10, but this is not intended to represent only one bus or type of bus.
Based on the same inventive concept, embodiments of the present application further provide a storage medium storing computer instructions, which when executed on a computer, cause the computer to perform a bandwidth detection method as discussed above.
The embodiment of the application provides a bandwidth detection method, a bandwidth detection device, electronic equipment and a storage medium, the method is applied to a receiving end of a network to be detected, overload detection is carried out on calculated packet cluster intervals through a preset trend line filter, and a corresponding network overload state is obtained, wherein the trend line filter calculates packet cluster delay gradient of the network by adopting a least square method, so that the number of feedback packets needing to be received and sent is reduced, meanwhile, the delay trend of the network is rapidly and accurately obtained, and rapid convergence of an algorithm is guaranteed.
Further, the determined network overload state is adopted to calculate the corresponding network estimated bandwidth, and the calculated network estimated bandwidth is dynamically adjusted when the network to be detected is determined to be in a steady state based on the preset steady state condition.
It should be noted that although in the above detailed description several units or sub-units of the apparatus are mentioned, such a division is merely exemplary and not mandatory. Indeed, the features and functions of two or more units described above may be embodied in one unit, according to embodiments of the application. Conversely, the features and functions of one unit described above may be further divided into embodiments by a plurality of units.
Further, while the operations of the methods of the present application are depicted in the drawings in a particular order, this does not require or imply that these operations must be performed in this particular order, or that all of the illustrated operations must be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a server, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Program code for carrying out operations of the present application may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user computing device, partly on the user equipment, as a stand-alone software package, partly on the user computing device and partly on a remote computing device, or entirely on the remote computing device or server.
In the case of remote computing devices, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.
Claims (10)
1. A bandwidth detection method is characterized in that the bandwidth detection method is applied to a receiving end of a network to be detected, and comprises the following steps:
responding to each audio and video data packet received in real time, and calculating packet cluster intervals of the network;
performing overload detection on the packet cluster intervals by adopting a preset trend line filter to obtain a corresponding network overload state, wherein the trend line filter calculates packet cluster delay gradient of the network by adopting a least square method;
based on the network overload state, performing bandwidth estimation on the receiving code rate of the receiving end, and calculating corresponding network estimation bandwidth;
and responding to the condition that the network overload state meets a preset steady state condition, and dynamically adjusting the network estimated bandwidth to obtain a corresponding bandwidth detection result.
2. The method of claim 1, wherein said computing packet cluster intervals for said network in response to individual audio-visual data packets received in real-time comprises:
responding to each audio and video data packet received in real time, and respectively executing the following operations aiming at each audio and video data packet:
judging whether a first sending time stamp carried by one audio and video data packet is greater than a second sending time stamp carried by an audio and video data packet cluster of adjacent receiving time, wherein the second sending time stamp is used for indicating the latest sending time of each audio and video data packet in the audio and video data packet cluster of the adjacent receiving time;
when the first sending time stamp is determined to be larger than the second sending time stamp, taking the audio and video data packet as a detection data packet aiming at the network;
calculating packet cluster intervals for the network based on the determined respective probe packets.
3. The method according to claim 1 or 2, wherein the detecting overload of the packet cluster interval by using a preset trend line filter to obtain a corresponding network overload state comprises:
calculating a packet cluster delay gradient of the network based on the packet cluster interval by adopting a preset trend line filter;
if the packet cluster delay gradient belongs to a preset first gradient interval, determining that the network overload state is an underload state;
if the packet cluster delay gradient belongs to a preset second gradient interval, determining that the network overload state is a common state;
if the packet cluster delay gradient belongs to a preset third gradient interval, determining that the network overload state is a common overload state;
and if the packet cluster delay gradient belongs to a preset fourth gradient interval, determining that the network overload state is a serious overload state.
4. The method as claimed in claim 3, wherein said performing bandwidth estimation for the receiving code rate of the receiving end based on the network overload status, and calculating the corresponding network estimated bandwidth comprises:
if the network overload state is an underload state, performing bandwidth estimation on the receiving code rate of the receiving end by adopting a control-keeping state, and calculating corresponding network estimation bandwidth;
if the network overload state is a general overload state or a serious overload state, adopting a reduction control state to carry out bandwidth estimation on the receiving code rate of the receiving end and calculate the corresponding network estimation bandwidth, wherein the reduction control state controls multiplicative reduction of the receiving code rate of the receiving end;
and if the network overload state is a common state, performing state promotion on the current control state of the receiving code rate based on a preset state control rule, performing bandwidth estimation on the receiving code rate of the receiving end by adopting a promoted corresponding target control state, and calculating a corresponding network estimation bandwidth.
5. The method of claim 4, wherein the network overload state is an underrun state or a normal state,
the dynamically adjusting the network estimated bandwidth in response to the network overload state meeting a preset steady-state condition to obtain a corresponding bandwidth prediction result includes:
obtaining a historical overload state histogram of the network, wherein the historical overload state histogram at least comprises: recording the probability distribution value of at least one historical overload state in a preset historical time range by the network;
responding to the historical overload state histogram, wherein the sum of the probability distribution values of the corresponding common state and the underload state meets a preset distribution threshold value, and determining that the network overload state meets a preset steady-state condition;
and based on the network overload state, promoting a bandwidth critical point of the network, and dynamically adjusting the estimated bandwidth of the network by adopting the promoted bandwidth critical point to obtain a corresponding bandwidth detection result.
6. The method of claim 4 or 5, wherein the network overload condition is a general overload condition,
the estimating the bandwidth of the receiving code rate of the receiving end, and after calculating the corresponding network estimated bandwidth, further includes:
and based on the network overload state, linearly adjusting the bandwidth critical point of the network according to the recorded historical critical point, and dynamically adjusting the estimated bandwidth of the network by adopting the adjusted bandwidth critical point to obtain a corresponding bandwidth detection result.
7. The method of claim 4 or 5, wherein the network overload condition is a severe overload condition,
after the bandwidth estimation is performed on the receiving bit rate of the receiving end and the corresponding network estimated bandwidth is calculated, the method further includes:
and reducing the bandwidth critical point of the network based on the network overload state, and dynamically adjusting the estimated bandwidth of the network by adopting the reduced bandwidth critical point to obtain a corresponding bandwidth detection result.
8. A bandwidth detection device, which is applied to a receiving end of a network to be detected, includes:
the receiving module is used for responding to each audio and video data packet cluster received in real time and calculating the packet cluster interval of the network;
the detection module is used for carrying out overload detection on the packet cluster intervals by adopting a preset trend line filter to obtain a corresponding network overload state, wherein the trend line filter calculates the packet cluster delay gradient of the network by adopting a least square method;
the estimation module is used for carrying out bandwidth estimation on the receiving code rate of the receiving end based on the network overload state and calculating corresponding network estimation bandwidth;
and the adjusting module is used for responding to the condition that the network overload state meets the preset steady state condition, dynamically adjusting the network estimated bandwidth and obtaining a corresponding bandwidth detection result.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1-7 when executing the computer program.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.
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