CN115801639B - Bandwidth detection method and device, electronic equipment and storage medium - Google Patents
Bandwidth detection method and device, electronic equipment and storage medium Download PDFInfo
- Publication number
- CN115801639B CN115801639B CN202210913535.2A CN202210913535A CN115801639B CN 115801639 B CN115801639 B CN 115801639B CN 202210913535 A CN202210913535 A CN 202210913535A CN 115801639 B CN115801639 B CN 115801639B
- Authority
- CN
- China
- Prior art keywords
- network
- bandwidth
- state
- overload state
- preset
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000001514 detection method Methods 0.000 title claims abstract description 88
- 238000003860 storage Methods 0.000 title claims abstract description 17
- 238000000034 method Methods 0.000 claims abstract description 34
- 238000009826 distribution Methods 0.000 claims description 16
- 238000004590 computer program Methods 0.000 claims description 13
- 230000009467 reduction Effects 0.000 claims description 10
- 230000004044 response Effects 0.000 claims description 9
- 238000012423 maintenance Methods 0.000 claims description 5
- 239000000523 sample Substances 0.000 claims description 5
- 238000004422 calculation algorithm Methods 0.000 abstract description 25
- 238000004891 communication Methods 0.000 abstract description 19
- 230000005540 biological transmission Effects 0.000 abstract description 18
- 238000010586 diagram Methods 0.000 description 16
- 230000006870 function Effects 0.000 description 11
- 238000012545 processing Methods 0.000 description 9
- 238000005070 sampling Methods 0.000 description 7
- 230000008859 change Effects 0.000 description 6
- 230000000694 effects Effects 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 4
- 230000008569 process Effects 0.000 description 4
- 230000003190 augmentative effect Effects 0.000 description 2
- 230000003139 buffering effect Effects 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 238000010295 mobile communication Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000008447 perception Effects 0.000 description 2
- 230000002411 adverse Effects 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 238000013473 artificial intelligence Methods 0.000 description 1
- 230000001413 cellular effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000005538 encapsulation Methods 0.000 description 1
- 238000009499 grossing Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 230000009191 jumping Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000000737 periodic effect Effects 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Landscapes
- Data Exchanges In Wide-Area Networks (AREA)
Abstract
The embodiment of the application provides a bandwidth detection method, a device, electronic equipment and a storage medium, wherein the method is applied to a receiving end of a network to be detected, and overload detection is carried out on calculated packet cluster intervals through a preset trend line filter to obtain a corresponding network overload state, wherein the trend line filter calculates packet cluster delay gradients of the network by adopting a least square method, so that the delay trend of the network is rapidly and accurately obtained while the number of feedback packets needing to be transmitted and received is reduced, and the rapid convergence of an algorithm is ensured. Further, the determined network overload state is adopted, the corresponding network estimated bandwidth is calculated, and based on the preset steady state condition, when the network to be detected is determined to be in a steady state, the calculated network estimated bandwidth is dynamically adjusted, based on the mode, maintainability and easy iteration of an algorithm are ensured, and further video transmission service quality in real-time communication is ensured.
Description
Technical Field
The present invention relates to the field of bandwidth data detection technologies, and in particular, to a bandwidth detection method, a device, an electronic apparatus, and a storage medium.
Background
In a Real-time communication (Web Real-Time Communications, webRTC) transmission module, a congestion control algorithm (Google Congestion Control, GCC) or a bandwidth estimation algorithm (Transport Congestion Control, TCC) is adopted to effectively and dynamically detect and evaluate the network bandwidth change between a sending end and a receiving end, so that network congestion is identified through detection results, and important effects are played on video transmission service quality (Quality of Service, qoS), user experience and the like in a WebRTC system.
However, the above-described method has the following drawbacks in the related art:
in the first aspect, when the congestion control algorithm GCC is adopted to perform network detection, the available bandwidth of the network is estimated through the change of network characteristics such as delay information perceived by the receiving end, and the available bandwidth is time-varying, so that the upper limit of the bandwidth of the network needs to be frequently perceived, and the problem that the convergence speed is too slow and the response to the step change of the bandwidth is slower exists; meanwhile, the detection result is too sensitive to delay jitter, and delay error sampling occurs at a high probability under a weak network with large packet loss and jitter, so that erroneous judgment of available bandwidth is caused, and finally obtained bandwidth detection result is influenced.
In the second aspect, when the network detection is performed by adopting the bandwidth estimation algorithm TCC, the available bandwidth of the network is estimated by the delay information received by the transmitting end, and because the receiving end is required to transmit a large number of feedback packets back to the transmitting end in this way, a certain network bandwidth is generally occupied, and under a weaker network, the above manner is easy to cause longer estimation time required by the algorithm due to the loss of the feedback packets, thereby affecting the efficiency of bandwidth detection.
Disclosure of Invention
The embodiment of the application provides a bandwidth detection method, a device, electronic equipment and a storage medium, which are used for improving the accuracy and instantaneity 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 adopting a preset trend line filter to carry out overload detection on the packet cluster interval to obtain a corresponding network overload state, wherein the trend line filter adopts a least square method to calculate the packet cluster delay gradient of the network.
And 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 network overload state meeting a preset steady-state condition, 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 apparatus, 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 adopts a least square method to calculate the packet cluster delay gradient of the network.
And 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 the corresponding network estimation bandwidth.
And the adjusting module is used for dynamically adjusting the estimated bandwidth of the network to obtain a corresponding bandwidth detection result in response to the network overload state meeting a preset steady-state condition.
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 for each audio and video data packet: judging whether a first sending time stamp carried by one audio/video data packet is larger than a second sending time stamp carried by an audio/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/video data packet in the audio/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, the one audio/video data packet is used as a detection data packet for the network.
Based on the determined individual probe data packets, packet cluster intervals of the network are calculated.
In an optional embodiment, the overload detection is performed on the packet cluster interval by using a preset trend line filter, so as 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 general 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 estimating module is specifically configured to perform bandwidth estimation on the receiving code rate of the receiving end based on the network overload state, calculate a corresponding network estimated bandwidth, and:
If the network overload state is the underload state, adopting a maintenance control state to carry out bandwidth estimation on the receiving code rate of the receiving end, 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 carry out bandwidth estimation on the receiving code rate of the receiving end and calculating a corresponding network estimation bandwidth, wherein the reduction control state controls the reduction of the receiving code rate of the receiving end.
If the network overload state is a common state, carrying out state promotion on the current control state of the receiving code rate based on a preset state control rule, carrying out bandwidth estimation on the receiving code rate of the receiving end by adopting the promoted corresponding target control state, and calculating the corresponding network estimation bandwidth.
In an alternative embodiment, the network overload condition is an underload condition or a normal condition,
The response to the network overload state meeting a preset steady-state condition dynamically adjusts the network estimated bandwidth to obtain a corresponding bandwidth prediction result, and the adjustment module is specifically configured to:
Acquiring a historical overload state histogram of the network, wherein the historical overload state histogram at least comprises: and the network records the respective probability distribution value of at least one historical overload state in a preset historical time range.
And responding to the fact that the sum of probability distribution values of corresponding ordinary states and underload states 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, improving the bandwidth critical point of the network, and adopting the improved 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 bandwidth estimation is performed on the receiving code rate of the receiving end, and after the corresponding network estimated bandwidth is calculated, the adjusting module is further configured to:
Based on the network overload state, the bandwidth critical point of the network is linearly adjusted according to the recorded historical critical point, and the adjusted bandwidth critical point is adopted to dynamically adjust the estimated bandwidth of the network, so that a corresponding bandwidth detection result is obtained.
In an alternative embodiment, the network overload condition is a severe overload condition,
The bandwidth estimation is performed on the receiving code rate of the receiving end, and after the corresponding network estimated bandwidth is calculated, 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 provided, which comprises a processor and a memory, wherein the memory stores program code that, when executed by the processor, causes the processor to perform the steps of the bandwidth detection method according to the first aspect.
In a fourth aspect, a computer readable storage medium is proposed, comprising program code for causing an electronic device to perform the steps of the bandwidth detection method according to the first aspect described above, when said program code is run 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 device, electronic equipment and a storage medium, wherein the method is applied to a receiving end of a network to be detected, and overload detection is carried out on calculated packet cluster intervals through a preset trend line filter to obtain a corresponding network overload state, wherein the trend line filter calculates packet cluster delay gradients of the network by adopting a least square method, so that the delay trend of the network is rapidly and accurately obtained while the number of feedback packets needing to be transmitted and received is reduced, and the rapid convergence of an algorithm is ensured.
Further, the determined network overload state is adopted, the corresponding network estimated bandwidth is calculated, and based on the preset steady state condition, when the network to be detected is determined to be in a steady state, the calculated network estimated bandwidth is dynamically adjusted, based on the mode, the calculated network estimated bandwidth is adjusted to be more accurate under the steady state condition, meanwhile, the bandwidth detection mode based on the receiving end is adopted, the maintainability and the easy iteration of an algorithm are ensured, and the video transmission service quality in real-time communication is further ensured.
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 application;
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 application;
fig. 5 is a schematic diagram of packet cluster intervals according to an embodiment of the present application;
FIG. 6 is a historical overload state histogram provided by an embodiment of the present application;
FIG. 7 is a schematic diagram of overload buffering according to an embodiment of the present application;
Fig. 8 is a schematic diagram of an actual application scenario provided in an embodiment of the present application;
fig. 9 is a schematic structural diagram of a bandwidth detecting device according to an embodiment of the present application;
fig. 10 is a schematic diagram of an electronic device according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
In the description of the present application, "a plurality of" means "at least two". "and/or", describes an association relationship of an association object, and indicates that there may be three relationships, for example, a and/or B, and may indicate: a exists alone, A and B exist together, and B exists alone. A is connected with B, and can be represented as follows: both cases of direct connection of A and B and connection of A and B through C. In addition, in the description of the present application, the words "first," "second," and the like are used merely for distinguishing between the descriptions and not be construed as indicating or implying a relative importance or order.
In addition, in the technical scheme of the application, the data is collected, transmitted, used and the like, and all meet the requirements of national relevant laws and regulations.
The design idea of the application is as follows:
in the related art, the congestion control algorithm GCC or the bandwidth estimation algorithm TCC is adopted to realize effective detection of the network bandwidth, however, the following defects still exist in the above manner:
1) Congestion control algorithm GCC
The congestion control algorithm GCC is a bandwidth detection algorithm based on delay perception, which is realized by a receiving end, and the available bandwidth of a network is estimated through the change of network characteristics such as delay information perceived by the receiving end; meanwhile, the detection result is too sensitive to delay jitter, and delay error sampling occurs at a high probability under a weak network with large packet loss and jitter, so that erroneous judgment of available bandwidth is caused, and 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 perception, which is implemented by a transmitting end, and estimates the available bandwidth of a network through delay information received by the transmitting end.
In order to improve accuracy and instantaneity of bandwidth detection, the embodiment of the application provides a bandwidth detection method, a device, electronic equipment and a storage medium, which are 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 to obtain a corresponding network overload state, wherein the trend line filter adopts a least square method to calculate a packet cluster delay gradient of the network, so that delay trend of the network is rapidly and accurately obtained while the number of feedback packets needing to be transmitted and received is reduced, rapid convergence of an algorithm is ensured, further, the determined network overload state is adopted to calculate a corresponding network estimation bandwidth, dynamic adjustment is carried out on the calculated network estimation bandwidth based on a preset steady state condition when the network to be detected is determined to be in a steady state, the calculated network estimation bandwidth is adjusted to be more accurate under the steady state condition based on the mode, and simultaneously, the bandwidth detection mode based on the receiving end is adopted, maintainability and iterative performance of the algorithm are ensured, and video transmission service quality in real time is further ensured.
Based on the technical effects described above, preferred embodiments of the present application will be described below with reference to the accompanying drawings of the specification, it should be understood that the preferred embodiments described herein are for illustrating and explaining the present application only, are not intended to limit the present application, and the embodiments of the present application and features in the embodiments 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 includes: a target client 101 and a server 102. The information interaction between the target client 101 and the server 102 may be performed through a communication network, where a communication manner adopted by the communication network may include: wireless communication and wired communication.
Illustratively, the target client may access the network and communicate with the server 102 via cellular mobile communication technology, including fifth generation mobile communication (5th Generation Mobile Networks,5G) technology.
Alternatively, the target client 101 may access the network for communication with the server 102 via a short-range wireless communication means, including wireless fidelity (WIRELESS FIDELITY, wi-Fi) technology.
The number of the devices is not limited in this embodiment of the present application, and as shown in fig. 1, only one target client 101 and one server 102 are described as an example, and each device and its respective functions are briefly described below.
The target client 101 may be or operate by a device providing voice and/or data connectivity to a user, the device comprising: a handheld terminal device with a wireless connection function, a vehicle-mounted terminal device, and the like.
The target client may be, by way of example, or operate with any one or a combination of the following devices, including, but not limited to, a cell phone, tablet, notebook, palm, mobile internet device (Mobile INTERNET DEVICE, MID), wearable device, virtual Reality (VR) device, augmented Reality (Augmented Reality, AR) device, wireless terminal device in industrial control, wireless terminal device in unmanned driving, wireless terminal device in smart grid, wireless terminal device in transportation security, wireless terminal device in smart city, wireless terminal device in smart home, etc., to which the present application is not limited.
Further, in the embodiment of the present application, the target client 101 may use an audio/video data packet according to a Real-time transmission protocol (Real-time Transport Protocol, RTP), trigger the server 102 to enter bandwidth detection, and receive a receiver bandwidth estimation data packet (RECEIVER ESTIMATED Max Bitrate, REMB) according to a Real-time transmission control protocol (Realtime Transport Control Protocol, RTCP) from periodic feedback of the server 102, determine a bandwidth detection result of the server 102 as a receiver, and in a subsequent process, the target client 101 may perform rate control of the sender 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 that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, a content delivery network (Content Delivery Network, CDN), and basic cloud computing services such as big data and an artificial intelligence platform.
In an exemplary embodiment of the present application, the server 102 may be a background server for providing WebRTC, and referring to fig. 2, the server 102 may be configured with a bandwidth detection module, and specifically, the bandwidth detection module may be configured with a time filter 201, a trend line filter 202, and an AIMD (add-multiply-subtract) code rate adjustment module 203, and when receiving each audio/video data packet sent from the target client 101, the server 102 may implement relevant functions of the bandwidth detection method provided in the embodiment of the present application based on the bandwidth detection module 202.
Based on the application scenario, the bandwidth detection method provided by the embodiment of the present application will be further described and illustrated with reference to the accompanying drawings, where the method may be applied to a receiving end of a network to be detected, for example, may be applied to a server end 102 in the 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 the packet cluster interval of the network.
Specifically, in the real-time communication WebRTC, a transmitting end adopts a real-time transmission protocol RTP to transmit an audio/video data packet conforming to the protocol to a receiving end to be detected, the receiving end responds to the received audio/video data packet, and based on a preset sampling time, each audio/video data packet received in a unit sampling time forms a corresponding audio/video data packet cluster, and the corresponding audio/video data packet cluster is used as a data unit 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/video data packet clusters.
In an exemplary embodiment of the present application, the received audio and video data packets from the target client 101 are formed into corresponding audio and video data packet clusters by using a preset sampling time (e.g., 5 ms), and the packet cluster interval of the network is calculated based on the respective receiving time of each audio and video data packet cluster.
In an alternative embodiment, to avoid the disorder of receiving between the audio and video data packet clusters caused by network jitter, and to eliminate the influence of noise generated by network jitter on the bandwidth detection result, the calculating the packet cluster interval of the network may include:
S3011: 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 cluster:
S30111: judging whether a first sending time stamp carried by one audio/video data packet is larger than a second sending time stamp carried by an audio/video data packet cluster of adjacent receiving time.
Specifically, each audio and video data packet may carry a first transmission time stamp indicating a corresponding transmission time, and when the server receives each audio and video data packet from the transmitting end, the server may perform out-of-order determination for the received audio and video data packet based on the carried first transmission time stamp.
S30112: and when the first sending time stamp is determined to be larger than the second sending time stamp, taking an audio/video data packet as a detection data packet of the network.
In an alternative embodiment, in order to avoid the influence of noise generated by network jitter on the bandwidth detection result, the maximum timestamp representing the latest transmission time of each corresponding audio/video data packet cluster in the audio/video data packet cluster corresponding to the adjacent receiving time (i.e., the last received audio/video data packet cluster) of the currently received audio/video data packet is used as the second transmission timestamp carried by the audio/video data packet cluster of the adjacent receiving time, so that when the first transmission timestamp carried by the currently received audio/video data packet is determined to be greater than the second transmission timestamp carried by the corresponding last received audio/video data packet cluster, the one audio/video data packet is determined to be ordered.
In an exemplary embodiment of the present application, when it is determined that the first transmission time stamp carried by the current audio/video data packet is greater than the second transmission time stamp carried by the 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 probe data packet of the network.
S3012: based on the determined individual probe data packets, packet cluster intervals of the network are calculated.
Therefore, based on the above manner, the embodiment of the application performs denoising processing on each received audio and video data packet, so that based on each detected data packet determined after processing, the corresponding packet cluster of each audio and video data packet and the packet cluster interval of the network are redetermined, thereby avoiding adverse effects on bandwidth detection results caused by network jitter and the like, and effectively ensuring the accuracy of the finally obtained bandwidth detection results.
S302: and adopting a preset trend line filter to carry out overload detection on the packet cluster interval to obtain a corresponding network overload state.
Further, the calculated packet cluster intervals are input into a preset trend line filter, and 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 reflected rapidly and accurately under fewer samples.
For example, referring to fig. 4, in the embodiment of the present application, a preset trend line filter is used to input a plurality of calculated packet cluster intervals, and a least square method is adopted to calculate a packet cluster delay gradient of a network, further, the calculated packet cluster delay gradient is mapped to each preset gradient interval, and thus, a network overload state of the network to be detected is determined.
It should be noted that, the actual calculation formula of the trend line filter may be shown as the trend line filter in the bandwidth estimation algorithm TCC, and in actual situations, the actual calculation formula may also be adaptively modified by a person skilled in the art according to an actual service scenario, which is not described herein.
Further, in the embodiment of the present application, the network overload state to be determined is defined as: the underload state, the normal state, the general overload state and the serious overload state, and corresponding gradient intervals are respectively set according to the network overload states, as shown in fig. 4, packet cluster delay gradients calculated based on a trend line filter are mapped to a preset gradient interval (such as a preset first gradient interval, a preset second gradient interval, a preset third gradient interval and a preset fourth gradient interval), so that the network overload state of the network to be detected is determined, and respective packet cluster intervals of the network overload states are shown in fig. 5.
S303: and based on the network overload state, performing bandwidth estimation on the receiving code rate of the receiving end, and calculating corresponding network estimation bandwidth.
Further, in the embodiment of the present application, for an AIMD (addition, multiplication, and subtraction) code rate adjustment module, the following code rate control states are defined for the module: the control state is maintained, the control state is reduced, and the control state is improved, which correspond to the code rate maintenance, the code rate reduction, and the code rate improvement of the current receiving end respectively, and based on the calculated network overload state, the code rate control state of the module is adjusted, and the corresponding network estimated bandwidth is calculated, as follows:
In an alternative embodiment, if the calculated network overload state is an underload state, the method enters a maintenance control state, performs bandwidth estimation on a receiving code rate of a receiving end, and calculates a corresponding network estimated bandwidth.
In an alternative embodiment, if the calculated network overload state is a general overload state or a severe overload state, the method enters a reduced control state, performs bandwidth estimation on a receiving code rate of the receiving end, and calculates a corresponding network estimated bandwidth, where in the reduced control state, the receiving code rate of the receiving end is reduced multiplicatively.
In an alternative embodiment, if the calculated network overload state is a normal state, based on a preset state control rule, performing state promotion on the current control state of the received code rate, and performing bandwidth estimation on the received code rate of the receiving end by adopting the promoted corresponding target control state, so as 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 holding control state, performing state promotion on the current control state, performing bandwidth estimation on the receiving code rate of the receiving end by adopting a corresponding promotion control state, and calculating a corresponding network estimation bandwidth, wherein in the promotion control state, the receiving code rate of the receiving end is additively and slowly promoted.
For another example, if the network overload state is a normal state and the current control state of the receiving code rate is a reduced control state, the current control state is promoted, the corresponding maintaining control state is adopted, the bandwidth estimation is performed on the receiving code rate of the receiving end, and the corresponding network estimated bandwidth is calculated.
In the embodiment of the present application, the specific implementation manner of the bandwidth estimation may be performed with reference to the bandwidth estimation manner in the related art, for example, the estimated channel capacity is used to obtain the corresponding estimated bandwidth of the network, which is not limited in the present application.
S304: and responding to the network overload state to meet the preset steady-state condition, dynamically adjusting the network estimated bandwidth, and obtaining 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 fault test process of a critical point, and in the embodiment of the application, in order to reduce the influence of jitter under a weak network and avoid the critical point from greatly jumping caused by inaccurate delay sampling, a historical overload state histogram is adopted to carry out smoothing on the critical point of the bandwidth of the network, specifically, based on the historical overload state histogram, whether the network overload state meets a preset steady-state condition is determined, wherein the historical overload state histogram at least comprises: the network records respective probability distribution values of at least one historical overload state in a preset historical time range.
As an example, referring to fig. 6, a graphical historical overload state histogram is adopted, and the probability distribution value of each at least one historical overload state in a preset historical time range is counted by the network, where if the sum of the probability distribution values of the corresponding normal state and the underload 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, further, in response to the network meeting the steady-state condition, the bandwidth critical point of the current network is raised to the currently calculated network estimated bandwidth, and the raised bandwidth critical point is adopted to dynamically adjust the network estimated bandwidth, so as to obtain a corresponding bandwidth detection result.
In an alternative embodiment, if the calculated network overload state is a general overload state, in S303, after calculating the corresponding estimated bandwidth of the network, the historical critical point is considered to be unnecessary to be updated based on the general overload state, and then the bandwidth critical point of the network is adjusted linearly according to the recorded historical critical point, so as to dynamically adjust the estimated bandwidth of the network, and obtain the corresponding bandwidth detection result.
In an alternative embodiment, if the calculated network overload state is a severe overload state, in S303, after calculating the corresponding network estimated bandwidth, the historical critical point may be updated based on the severe overload state, and the bandwidth critical point may be 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 above manner, in the embodiment of the present application, through the historical overload state histogram in the steady state and the overload buffering for the bandwidth critical point of the network, the too fast change of the code rate in the weak network is prevented, and the error sampling in the weak network is avoided, so that the accuracy of the bandwidth detection is further improved.
For easy understanding, referring to fig. 8, a schematic diagram of a bandwidth detection method under an actual application is provided in an embodiment of the present application, in the actual application, a server side adopts a Janus-based SFU, and encapsulates a congestion control module encapsulation C interface of WebRTC source code into library. And in libbe. So, deleting the overload detection module based on Kalman filter such as OveruseEstimator, overuseDetector of GCC, and adding trend line filter TrendlineEstimator in TCC. Furthermore, a Histogram object is added in the AIMD code rate adjustment module and is used for counting an overload state, and a critical point buffer algorithm under the overload state is added, so that the convergence speed 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 application also provides a bandwidth detection device, which can be used for realizing the above-mentioned method flow of the embodiment of the 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:
and the receiving module 901 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 902 is configured to perform overload detection on the packet cluster interval by using a preset trend line filter, so as to obtain a corresponding network overload state, where the trend line filter uses a least square method to calculate a packet cluster delay gradient of the network.
The estimating module 903 is configured to perform bandwidth estimation on the receiving code rate of the receiving end based on the network overload state, and calculate a corresponding network estimated bandwidth.
And the adjusting module 904 is configured to dynamically adjust the estimated bandwidth of the network in response to the network overload condition meeting a preset steady-state condition, so as to obtain a corresponding bandwidth detection result.
In an optional embodiment, the calculating, in response to each audio/video data packet received in real time, a packet cluster interval of the network, the receiving module 901 is specifically configured to:
Responding to each audio and video data packet received in real time, and respectively executing the following operations for each audio and video data packet: judging whether a first sending time stamp carried by one audio/video data packet is larger than a second sending time stamp carried by an audio/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/video data packet in the audio/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, the one audio/video data packet is used as a detection data packet for the network.
Based on the determined individual probe data packets, packet cluster intervals of the network are calculated.
In an alternative embodiment, the overload detection is performed on the packet cluster interval by using a preset trend line filter, so as 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 general 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 estimating module 903 is configured to perform bandwidth estimation on the receiving code rate of the receiving end based on the network overload state, calculate a corresponding network estimated bandwidth, and specifically:
If the network overload state is the underload state, adopting a maintenance control state to carry out bandwidth estimation on the receiving code rate of the receiving end, 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 carry out bandwidth estimation on the receiving code rate of the receiving end and calculating a corresponding network estimation bandwidth, wherein the reduction control state controls the reduction of the receiving code rate of the receiving end.
If the network overload state is a common state, carrying out state promotion on the current control state of the receiving code rate based on a preset state control rule, carrying out bandwidth estimation on the receiving code rate of the receiving end by adopting the promoted corresponding target control state, and calculating the corresponding network estimation bandwidth.
In an alternative embodiment, the network overload condition is an underload condition or a normal condition,
The response to the network overload condition meeting a preset steady-state condition dynamically adjusts the estimated bandwidth of the network to obtain a corresponding bandwidth prediction result, and the adjustment module 904 is specifically configured to:
Acquiring a historical overload state histogram of the network, wherein the historical overload state histogram at least comprises: and the network records the respective probability distribution value of at least one historical overload state in a preset historical time range.
And responding to the fact that the sum of probability distribution values of corresponding ordinary states and underload states 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, improving the bandwidth critical point of the network, and adopting the improved 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 904 is further configured to perform bandwidth estimation on the receiving code rate of the receiving end, calculate a corresponding network estimated bandwidth, and then:
Based on the network overload state, the bandwidth critical point of the network is linearly adjusted according to the recorded historical critical point, and the adjusted bandwidth critical point is adopted to dynamically adjust the estimated bandwidth of the network, so that a corresponding bandwidth detection result is obtained.
In an alternative embodiment, the network overload condition is a severe overload condition,
The bandwidth estimation is performed on the receiving code rate of the receiving end, and after the corresponding network estimated bandwidth is calculated, 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.
Based on the same inventive concept as the above-mentioned application embodiments, an electronic device is further provided in the embodiments of the present application, where 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, including a memory 1001, a communication interface 1003, and one or more processors 1002.
Memory 1001 for storing computer programs for execution by processor 1002. The memory 1001 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, a program required for running an instant communication function, and the like; the storage data area can store various instant messaging information, operation instruction sets and the like.
The memory 1001 may be a volatile memory (RAM) such as a random-access memory (RAM); the memory 1001 may also be a nonvolatile memory (non-volatile memory), such as a read-only memory, a flash memory (flash memory), a hard disk (HARD DISK DRIVE, HDD) or a solid state disk (solid-STATE DRIVE, SSD), or the memory 1001 is any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited thereto. Memory 1001 may be a combination of the above.
The processor 1002 may include one or more central processing units (Central Processing Unit, CPU) or digital processing units, or the like. A processor 1002 for implementing the above bandwidth detection method when calling a computer program stored in the memory 1001.
The communication interface 1003 is used for communication with a terminal device and other servers.
The specific connection medium between the memory 1001, the communication interface 1003, and the processor 1002 is not limited in the embodiment of the present application. In the embodiment of the present application, the memory 1001 and the processor 1002 are connected by a bus 1004 in fig. 10, where the bus 1004 is shown by a thick line in fig. 10, and the connection manner between other components is only schematically illustrated, and is not limited thereto. 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 not only one bus or one type of bus.
Based on the same inventive concept, the embodiments of the present application also provide a storage medium storing computer instructions that, when executed on a computer, cause the computer to perform a bandwidth detection method as previously discussed.
The embodiment of the application provides a bandwidth detection method, a device, electronic equipment and a storage medium, wherein the method is applied to a receiving end of a network to be detected, and overload detection is carried out on calculated packet cluster intervals through a preset trend line filter to obtain a corresponding network overload state, wherein the trend line filter calculates packet cluster delay gradients of the network by adopting a least square method, so that the delay trend of the network is rapidly and accurately obtained while the number of feedback packets needing to be transmitted and received is reduced, and the rapid convergence of an algorithm is ensured.
Further, the determined network overload state is adopted, the corresponding network estimated bandwidth is calculated, and based on the preset steady state condition, when the network to be detected is determined to be in a steady state, the calculated network estimated bandwidth is dynamically adjusted, based on the mode, the calculated network estimated bandwidth is adjusted to be more accurate under the steady state condition, meanwhile, the bandwidth detection mode based on the receiving end is adopted, the maintainability and the easy iteration of an algorithm are ensured, and the video transmission service quality in real-time communication is further ensured.
It should be noted that although several units or sub-units of the apparatus are mentioned in the above detailed description, such a division is merely exemplary and not mandatory. Indeed, the features and functions of two or more of the elements described above may be embodied in one element in accordance with embodiments of the present application. Conversely, the features and functions of one unit described above may be further divided into a plurality of units to be embodied.
Furthermore, although the operations of the methods of the present application are depicted in the drawings in a particular order, this is not required or suggested that these operations must be performed in this particular order or that all of the illustrated operations must be performed in order to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step to perform, and/or one step decomposed into multiple steps to perform.
It will be appreciated by those skilled in the art that 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 flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations 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's computing device, partly on the user's equipment, as a stand-alone software package, partly on the user's computing device, 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., connected over 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 modifications and variations can be made to the present application without departing from the spirit or scope of the application. Thus, it is intended that the present application also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (9)
1. The bandwidth detection method is characterized by being applied to a receiving end of a network to be detected and comprising the following steps:
responding to each audio and video data packet received in real time, and calculating packet cluster intervals of the network;
calculating a packet cluster delay gradient of the network based on the packet cluster interval by adopting a preset trend line filter; the trend line filter calculates a packet cluster delay gradient of the network by adopting a least square method;
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;
based on the network overload state, performing bandwidth estimation on the receiving code rate of the receiving end, and calculating corresponding network estimation bandwidth;
If the network overload state is an underload state or a common state, acquiring a historical overload state histogram of the network, wherein the historical overload state histogram at least comprises: the network records respective probability distribution values of at least one historical overload state in a preset historical time range;
responding to the fact that the sum of probability distribution values of corresponding ordinary states and underload states 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, improving the bandwidth critical point of the network, and adopting the improved bandwidth critical point to dynamically adjust the estimated bandwidth of the network to obtain a corresponding bandwidth detection result.
2. The method of claim 1, wherein said calculating packet cluster intervals for the network in response to each audio-video data packet received in real-time comprises:
responding to each audio and video data packet received in real time, and respectively executing the following operations for each audio and video data packet:
Judging whether a first sending time stamp carried by an audio/video data packet is larger than a second sending time stamp carried by an audio/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/video data packet in the audio/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, the audio-video data packet is used as a detection data packet for the network;
Based on the determined individual probe data packets, packet cluster intervals of the network are calculated.
3. The method as recited in claim 1, further comprising:
if the packet cluster delay gradient belongs to a preset third gradient interval, determining that the network overload state is a general 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 of claim 3, wherein the calculating the corresponding network estimated bandwidth by estimating the bandwidth of the receiving code rate of the receiving end based on the network overload state comprises:
If the network overload state is the underload state, adopting a maintenance control state to carry out bandwidth estimation on the receiving code rate of the receiving end, and calculating a 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 calculating a corresponding network estimation bandwidth, wherein the reduction control state controls the reduction of the receiving code rate multiplicative performance of the receiving end;
If the network overload state is a common state, carrying out state promotion on the current control state of the receiving code rate based on a preset state control rule, carrying out bandwidth estimation on the receiving code rate of the receiving end by adopting the promoted corresponding target control state, and calculating the corresponding network estimation bandwidth.
5. The method of claim 4, wherein the network overload condition is a general overload condition,
The step of estimating the bandwidth of the receiving code rate of the receiving end, after calculating the corresponding estimated bandwidth of the network, further comprises:
Based on the network overload state, the bandwidth critical point of the network is linearly adjusted according to the recorded historical critical point, and the adjusted bandwidth critical point is adopted to dynamically adjust the estimated bandwidth of the network, so that a corresponding bandwidth detection result is obtained.
6. The method of claim 4, wherein the network overload condition is a severe overload condition,
The step of estimating the bandwidth of the receiving code rate of the receiving end, after calculating the corresponding estimated bandwidth of the network, further comprises:
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.
7. A bandwidth probing apparatus, applied to a receiving end of a network to be probed, comprising:
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 calculating the packet cluster delay gradient of the network based on the packet cluster interval by adopting a preset trend line filter; the trend line filter calculates a packet cluster delay gradient of the network by adopting a least square method;
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;
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 estimated bandwidth;
the adjusting module is configured to obtain a historical overload state histogram of the network if the network overload state is an underload state or a normal state, where the historical overload state histogram at least includes: the network records respective probability distribution values of at least one historical overload state in a preset historical time range;
responding to the fact that the sum of probability distribution values of corresponding ordinary states and underload states 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, improving the bandwidth critical point of the network, and adopting the improved bandwidth critical point to dynamically adjust the estimated bandwidth of the network to obtain a corresponding bandwidth detection result.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any of claims 1-6 when executing the computer program.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method according to any of claims 1-6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210913535.2A CN115801639B (en) | 2022-08-01 | 2022-08-01 | Bandwidth detection method and device, electronic equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210913535.2A CN115801639B (en) | 2022-08-01 | 2022-08-01 | Bandwidth detection method and device, electronic equipment and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115801639A CN115801639A (en) | 2023-03-14 |
| CN115801639B true CN115801639B (en) | 2024-06-07 |
Family
ID=85431424
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210913535.2A Active CN115801639B (en) | 2022-08-01 | 2022-08-01 | Bandwidth detection method and device, electronic equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115801639B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116260799B (en) * | 2023-05-16 | 2023-07-21 | 北京庭宇科技有限公司 | Method for adjusting network state and electronic equipment |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2006053817A2 (en) * | 2004-11-18 | 2006-05-26 | Nokia Siemens Networks Gmbh & Co. Kg | Estimation of bandwidth requirements in a communications network with access controls |
| WO2012079236A1 (en) * | 2010-12-16 | 2012-06-21 | 北京航空航天大学 | Transmission control method of video-stream based on dual time scale |
| CN107438031A (en) * | 2017-08-07 | 2017-12-05 | 成都三零凯天通信实业有限公司 | The audio/video flow transfer control method and system of multichannel network bandwidth adaptive |
| CN109743600A (en) * | 2019-01-15 | 2019-05-10 | 国网河南省电力公司 | Based on wearable live O&M adaptive video stream transmission rate control |
| CN110493658A (en) * | 2019-08-20 | 2019-11-22 | 武汉兴图新科电子股份有限公司 | A kind of network bandwidth method for detecting, equipment and storage equipment |
| CN110515103A (en) * | 2019-07-24 | 2019-11-29 | 西安空间无线电技术研究所 | A kind of low rail navigation enhancing PPP-RTK tropospheric delay product generation method |
| WO2020125716A1 (en) * | 2018-12-21 | 2020-06-25 | 中兴通讯股份有限公司 | Method for realizing network optimization and related device |
| CN111615006A (en) * | 2020-05-29 | 2020-09-01 | 高小翎 | Video code conversion transmission control system based on network state self-evaluation |
| CN111726301A (en) * | 2020-05-15 | 2020-09-29 | 北京理工大学 | Congestion control method and system for guaranteeing video quality in real-time video |
| CN113453045A (en) * | 2021-06-28 | 2021-09-28 | 苏州科达科技股份有限公司 | Network bandwidth prediction method, system, device and storage medium |
| CN114422443A (en) * | 2022-01-24 | 2022-04-29 | 西安电子科技大学 | Satellite network TCP congestion control method based on bandwidth estimation and congestion prediction |
| CN114629797A (en) * | 2022-03-11 | 2022-06-14 | 阿里巴巴（中国）有限公司 | Bandwidth prediction method, model generation method and equipment |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR100640492B1 (en) * | 2004-08-31 | 2006-10-30 | 삼성전자주식회사 | Method for estimating available bandwidth of network |
| US7558202B2 (en) * | 2006-03-16 | 2009-07-07 | Microsoft Corporation | Estimating available bandwidth with multiple overloading streams |
| US8026762B2 (en) * | 2009-06-18 | 2011-09-27 | Alcatel Lucent | High efficiency transmitter for wireless communication |
| CN108024156B (en) * | 2017-12-14 | 2020-04-14 | 四川大学 | Partially reliable video transmission method based on hidden Markov model |
-
2022
- 2022-08-01 CN CN202210913535.2A patent/CN115801639B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2006053817A2 (en) * | 2004-11-18 | 2006-05-26 | Nokia Siemens Networks Gmbh & Co. Kg | Estimation of bandwidth requirements in a communications network with access controls |
| WO2012079236A1 (en) * | 2010-12-16 | 2012-06-21 | 北京航空航天大学 | Transmission control method of video-stream based on dual time scale |
| CN107438031A (en) * | 2017-08-07 | 2017-12-05 | 成都三零凯天通信实业有限公司 | The audio/video flow transfer control method and system of multichannel network bandwidth adaptive |
| WO2020125716A1 (en) * | 2018-12-21 | 2020-06-25 | 中兴通讯股份有限公司 | Method for realizing network optimization and related device |
| CN109743600A (en) * | 2019-01-15 | 2019-05-10 | 国网河南省电力公司 | Based on wearable live O&M adaptive video stream transmission rate control |
| CN110515103A (en) * | 2019-07-24 | 2019-11-29 | 西安空间无线电技术研究所 | A kind of low rail navigation enhancing PPP-RTK tropospheric delay product generation method |
| CN110493658A (en) * | 2019-08-20 | 2019-11-22 | 武汉兴图新科电子股份有限公司 | A kind of network bandwidth method for detecting, equipment and storage equipment |
| CN111726301A (en) * | 2020-05-15 | 2020-09-29 | 北京理工大学 | Congestion control method and system for guaranteeing video quality in real-time video |
| CN111615006A (en) * | 2020-05-29 | 2020-09-01 | 高小翎 | Video code conversion transmission control system based on network state self-evaluation |
| CN113453045A (en) * | 2021-06-28 | 2021-09-28 | 苏州科达科技股份有限公司 | Network bandwidth prediction method, system, device and storage medium |
| CN114422443A (en) * | 2022-01-24 | 2022-04-29 | 西安电子科技大学 | Satellite network TCP congestion control method based on bandwidth estimation and congestion prediction |
| CN114629797A (en) * | 2022-03-11 | 2022-06-14 | 阿里巴巴（中国）有限公司 | Bandwidth prediction method, model generation method and equipment |
Non-Patent Citations (3)
| Title |
|---|
| Adaptive Energy-Aware Algorithms for Minimizing Energy Consumption and SLA Violation in Cloud Computing;R. Yadav, et al.;《IEEE Access》;20181002;全文 * |
| 基于物理主机过载检测的虚拟机动态整合方法研究;闫成雨;《中国优秀硕士论文电子期刊网》;20180215;全文 * |
| 新一代大地测量VLBI关键技术及应用研究;范昊鹏;《中国博士学位论文电子期刊网》;20200215;全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115801639A (en) | 2023-03-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11778006B2 (en) | Data transmission method and apparatus | |
| US10880226B2 (en) | Scheduled transmission of data | |
| CN109981225B (en) | Code rate estimation method, device, equipment and storage medium | |
| CN101636945B (en) | Method of transmitting data in a communication system | |
| CN109660467B (en) | Method and apparatus for controlling flow | |
| US11677639B2 (en) | Connection management between applications and service resources | |
| CN110012324B (en) | Code rate self-adaption method, WIFI camera, control device and code rate self-adaption system for embedded wireless video transmission | |
| CN115801639B (en) | Bandwidth detection method and device, electronic equipment and storage medium | |
| WO2020026018A1 (en) | Method for downloading file, device, apparatus/terminal/ server, and storage medium | |
| CN113453045A (en) | Network bandwidth prediction method, system, device and storage medium | |
| US9326161B2 (en) | Application-driven control of wireless networking settings | |
| US20170163509A1 (en) | Inter-node distance metric method and system | |
| US11088960B2 (en) | Information processing apparatus and verification system | |
| CN115499230A (en) | Network attack detection method and device, equipment and storage medium | |
| CN112737940A (en) | Data transmission method and device | |
| US11190430B2 (en) | Determining the bandwidth of a communication link | |
| US20140294379A1 (en) | Method and apparatus for using credits to determine cable length | |
| US9437205B2 (en) | Method, application, and device for audio signal transmission | |
| CN114143271B (en) | Bandwidth estimation method and device based on congestion detection | |
| JP2014112779A (en) | Data transmission controller, data transmission control method, and computer program | |
| US9882751B2 (en) | Communication system, communication controller, communication control method, and medium | |
| CN111966510B (en) | Method, system, device and medium for calculating data stream | |
| CN115037696B (en) | Data transmission method, device, electronic equipment and storage medium | |
| CN117319752A (en) | Audio and video processing method and device, electronic equipment and storage medium | |
| US20230125350A1 (en) | Video stream transmission control method and apparatus, device, and medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant |