CN106992939A - A kind of Satellite IP Network QoS flow control thresholding dynamic learning system and method - Google Patents
A kind of Satellite IP Network QoS flow control thresholding dynamic learning system and method Download PDFInfo
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- CN106992939A CN106992939A CN201710340999.8A CN201710340999A CN106992939A CN 106992939 A CN106992939 A CN 106992939A CN 201710340999 A CN201710340999 A CN 201710340999A CN 106992939 A CN106992939 A CN 106992939A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic control in data switching networks
- H04L47/10—Flow control; Congestion control
- H04L47/24—Traffic characterised by specific attributes, e.g. priority or QoS
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic control in data switching networks
- H04L47/10—Flow control; Congestion control
- H04L47/24—Traffic characterised by specific attributes, e.g. priority or QoS
- H04L47/2441—Traffic characterised by specific attributes, e.g. priority or QoS relying on flow classification, e.g. using integrated services [IntServ]
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic control in data switching networks
- H04L47/10—Flow control; Congestion control
- H04L47/32—Flow control; Congestion control by discarding or delaying data units, e.g. packets or frames
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic control in data switching networks
- H04L47/50—Queue scheduling
- H04L47/62—Queue scheduling characterised by scheduling criteria
- H04L47/6215—Individual queue per QOS, rate or priority
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Abstract
The invention belongs to communication technical field, specifically related to a kind of Satellite IP Network QoS flow control thresholding dynamic learning system, including Qos stream control modules, stream control thresholding dynamic learning module and physical layer, Qos stream control modules include the first data sink, stream control threshold cell and the first data source, stream control thresholding dynamic learning module includes the second data sink, data dissection process device and the second data source, the input of first data sink includes first input end and the second input, the output end of first data source includes the first output end and the second output end, first input end is external input, the output end of first data sink and the input of stream control threshold cell are communicated to connect, the output end and the input of the first data source of stream control threshold cell are communicated to connect, second output end of the first data source and the signal incoming end of physical layer are communicated to connect, it makes full use of broadband resource, and IP messages are avoided by random drop.
Description
Technical field
The invention belongs to communication technical field, and in particular to a kind of Satellite IP Network QoS flow control thresholding dynamic learning system
And method.
Background technology
Satellite communication system realizes that the direction interconnected with ground network is sent out towards building using IP agreement as core
Exhibition.In order to meet the transmission demand of multiple business, IP operation becomes the main application of present satellites communication system.Default situations
Under, IP messages are that " doing one's best " is forwarded, that is to say, that when network over loading or congestion, it is impossible to ensure important service number
Do not postponed or abandoned according to flow.To break through the unreliable service problem that the forwarding principle of IP messages " doing one's best " is brought,
QoS technology is in satellite communication field extensive use, and satellite modem manufacturer is nearly all built-in with QoS module.
QoS module needs a stream control thresholding when schedules message is sent, to determine its overall speed for sending message
Rate, for satellite modem, the value is exactly the outlet bandwidth of satellite channel.If the stream control set by QoS module
Thresholding is higher than actual value, then important message by random drop, will not reach QoS effect；, whereas if less than actual
Value, cannot make full use of bandwidth resources, cause bandwidth waste.
When QoS module sends message, the statistics to transmission rate is the length based on IP messages.When IP messages are from physical layer
When sending, to adapt to the transmission on satellite channel, some header informations can be coupled with.So, if QoS module
IP messages directly are sent according to physical layer rate, the actual information speed transmitted on a physical layer will be united more than QoS module
The speed of meter, because physical layer does not accommodate so much data volume, these IP messages waiting for transmission will be wrapped by random drop
Include important IP messages.
The content of the invention
It is the problem of based on being mentioned in above-mentioned background technology, dynamic the invention provides a kind of Satellite IP Network QoS flow control thresholding
State learning system and method, it, which has, makes full use of broadband resource, and avoids IP messages by the advantage of random drop.
To realize above-mentioned technical purpose, the technical solution adopted by the present invention is as follows：
A kind of Satellite IP Network QoS flow control thresholding dynamic learning system, it is characterised in that：Including Qos stream controls module, stream control
Thresholding dynamic learning module and physical layer, the Qos streams control module include the first data sink, stream control threshold cell and first
Data source, the stream control thresholding dynamic learning module includes the second data sink, data dissection process device and the second number
According to transmitter, the input of first data sink includes first input end and the second input, the first data hair
The output end of emitter includes the first output end and the second output end, and the first input end is external input, first number
Communicated to connect according to the output end and the input of stream control threshold cell of receiver, the output end and first of the stream control threshold cell
The input communication connection of data source, the second output end of first data source and the signal incoming end of physical layer
Communication connection, the first output end of first data source is communicated to connect with the signal input part of the second data sink,
The signal output part of second data sink is connected with the signal input part of data dissection process device, at the data parsing
Manage the output end of device to communicate to connect with the input of the second data source, the second data source output end and stream control door
The control end communication connection of limit.
Using the invention of above-mentioned technical proposal, stream control threshold cell is received by the first input end of the first data sink
Data, then data are carried out prioritization, queuing, speed limit then by data by the first data source by data-signal
The second data sink is sent, the second data connect device and send data-signal to stream control thresholding dynamic learning module, stream control thresholding
Dynamic learning module calculates maximum threshold to data message through row processing, and result then is passed through into the second data source
The first data sink is sent data to, the first data sink receives feedback signal, stream control thresholding by the second input
Unit, which is received, adjusts threshold value after feedback signal, reach and make full use of broadband resource, and avoids IP messages by random drop
Purpose.
Further limit, the data dissection process device includes data parsing arithmetic unit, data parsing controller and parsing
Data storage, the signal input part of the data parsing controller connects the second data sink signal output part, the number
The control end of arithmetic unit is parsed according to the signal output part connection data of parsing controller, the data parse the output end of arithmetic unit
The input of connection parsing data storage, signal output part the second data source signal of connection of the data storage is defeated
Enter end, control data is further easy in such design, and parsing data can be kept in, and is easy to data when making to need
Give for change and understand stream control state by recording threshold value.
Further limit, the stream control threshold cell includes input buffer, the signal input part of the input buffer
It is connected with the output end of the first data sink, the signal input part of the input buffer signal output part and stream control gate cell
Connection, such design, it is to avoid input data is lost in the case of there is emergency episode.
Further limit, output caching is installed between the first output end and physical layer of first data source
Device, such design, it is to avoid when there is emergency episode, causes output data to lose.
A kind of a kind of Satellite IP Network QoS flow control thresholding dynamic study method, Satellite IP Network QoS flow control thresholding is moved
State learning method is used for the maximum for calculating stream control thresholding, and the stream control threshold module changes stream control threshold value according to calculated value,
Comprise the following steps：
Step one, demarcation interval, takes a scope to be divided into N number of interval；
Step 2, message length is obtained, and is obtained and is sent to the IP message lengths of satellite channel, the message for via
Message after QoS flow control resume module；
Step 3, the cycle judges, is interval, and message in measurement period is total accordingly to sorting out IP messages according to length
Number and the interval message total respectively increase 1, Ct=Ct+ 1, Cj=Cj+ 1, wherein CjFor the number of message, C in interval jtFor statistics week
Message total in phase, then judges whether the cycle terminates, and such as cycle does not terminate to return to step one, continues to obtain message；Such as the cycle
Terminate to continue step 4；
Step 4, calculates average length, according to the average length of message in the step 3 counting statistics cycle
Step 5, calculates thresholding, and the maximum of stream control thresholding is calculated according to above-mentioned steps
Step 6, feedback of the information, stream controls thresholding dynamic learning module by maximumFeed back to stream control threshold cell, stream
Threshold cell is controlled according to maximumRegulation stream control threshold value.
Further limit, interval division method is as follows in the step one,
Sj=(j* Δ L+1, (j+1) * Δs L], wherein j=0,1,2 ..., N-1.
Further limit, Δ L value is self-defined by implementing in the step one, can be 10,20.
Further limit, the cycle can be used as week using the time as the cycle, also using message total in the step 3
Phase, and time, message number are simultaneously as the basis for estimation of measurement period.
Further limit, the average length computational methods in the step 4 are,Wherein
Further limit, maximum in the step 5Computational methods are,
The BphyThe bandwidth calculated for physical layer,
LPhyHeaderThe head length of IP messages is encapsulated for physical layer.
Using the invention of the above method, stream control thresholding dynamic learning module receives to flow the data-signal of control threshold cell,
Then sorting-out in statistics is carried out to data-signal, not packet loss, not speed limit, the maximum for receiving data is calculated according to the result of sorting-out in statistics
Threshold value, stream control threshold cell is adjusted according to the maximum at calculating.
Brief description of the drawings
The nonlimiting examples that the present invention can be provided by accompanying drawing are further illustrated；
Fig. 1 is stream control thresholding dynamic in a kind of Satellite IP Network QoS flow control thresholding dynamic study method embodiment of the invention
The workflow schematic diagram of study module；
Fig. 2 is a kind of schematic flow sheet of Satellite IP Network QoS flow control thresholding dynamic learning system embodiment of the invention.
Embodiment
In order that the present invention may be better understood in those skilled in the art, with reference to the accompanying drawings and examples to this hair
Bright technical scheme is further illustrated.
As shown in Figure 1 and Figure 2, a kind of Satellite IP Network QoS flow control thresholding dynamic learning system, it is characterised in that：Including
Qos stream controls module, stream control thresholding dynamic learning module and physical layer, Qos stream control modules include the first data sink, stream control door
Unit and the first data source are limited, stream control thresholding dynamic learning module includes the second data sink, data dissection process device
With the second data source, the input of the first data sink includes first input end and the second input, the first data hair
The output end of emitter includes the first output end and the second output end, and first input end is external input, the first data sink
Output end and the input of stream control threshold cell communicate to connect, output end and the first data source of stream control threshold cell
Input is communicated to connect, and the second output end of the first data source and the signal incoming end of physical layer are communicated to connect, the first number
Communicated to connect according to the first output end of transmitter with the signal input part of the second data sink, the signal of the second data sink
Output end is connected with the signal input part of data dissection process device, output end and the second data source of data dissection process device
Input communication connection, the second data source output end with stream control thresholding control end communicate to connect.
Preferably, data dissection process device includes data parsing arithmetic unit, data parsing controller and parsing data storage
Device, the signal input part of data parsing controller connects the second data sink signal output part, and data parse the letter of controller
Number output end connection data parse the control end of arithmetic unit, the output end connection parsing data storage of data parsing arithmetic unit
Input, signal output part the second data source signal input part of connection of data storage, such design, further just
In control data, and parsing data can be kept in, be easy to giving for change and by recording threshold value for data when making to need
Solution stream control state.In fact, the other structures of data dissection process device can be considered as the case may be.
Preferably, stream control threshold cell includes input buffer, and the signal input part of input buffer connects with the first data
The output end connection of device is received, input buffer signal output part is connected with the signal input part of stream control gate cell, such design,
Input data is lost in the case of avoiding the occurrence of emergency episode.In fact, can consider to avoid input data from losing as the case may be
The other schemes lost.
Preferably, output state is installed between the first output end and physical layer of the first data source, it is such
Design, it is to avoid when there is emergency episode, causes output data to lose in fact, can consider to avoid output data as the case may be
The other schemes lost.
Preferably, Qos streams control module, stream control thresholding dynamic learning module are electrically connected with battery, and such design is kept away
Exempt from burst powering-off state to impact Qos stream controls module, stream control thresholding dynamic learning module.In fact, can be according to specific
It is specific to consider.
A kind of Satellite IP Network QoS flow control thresholding dynamic study method, the maximum for calculating stream control thresholding, stream control door
Limit module and stream control threshold value is changed according to calculated value, comprise the following steps：
Step one, demarcation interval, 1-1500Bytes scopes are divided intoIndividual interval；Respectively
Sj=(j* Δ L+1, (j+1) * Δs L],
Wherein j=0,1,2 ..., N-1；Δ L value 10；
Step 2, message length is obtained, and obtains the IP message lengths for being sent to satellite channel, and message is via QoS
Message after stream control resume module；
Step 3, the cycle judges, is interval, and message in measurement period is total accordingly to sorting out IP messages according to length
Number and the interval message total respectively increase 1, Ct=Ct+ 1, Cj=Cj+ 1, wherein CjFor message, C in interval jtFor in measurement period
Message total, then judges whether the cycle terminates, and such as cycle does not terminate to return to step one, continues to obtain message, such as end cycle
Continue step 4, regulation is used as a cycle in one hour；
Step 4, calculates average length, according to the average length of message in the step 3 counting statistics cycle
Length calculation method is,Wherein
Step 5, calculates thresholding, and the maximum of stream control thresholding is calculated according to above-mentioned steps
Computational methods are,BphyCalculated for physical layer
Bandwidth, LPhyHeaderThe head length of IP messages is encapsulated for physical layer；
Step 6, feedback of the information, stream controls thresholding dynamic learning module by maximumFeed back to stream control threshold cell, stream
Threshold cell is controlled according to maximumRegulation stream control threshold value.
Using the invention of the above method, stream control threshold cell receives number by the first input end of the first data sink
According to then carrying out prioritization, queuing to data, speed limit and then data-signal sent out to data by the first data source
The second data sink is sent, the second data connect device and send data-signal to stream control thresholding dynamic learning module, and stream control thresholding is moved
State study module calculates maximum threshold so to data message through row processing, and result then is passed through into the second data source
The first data sink is sent data to, the first data sink receives feedback signal, stream control thresholding by the second input
Unit receives and threshold value is adjusted after feedback signal, and stream control thresholding dynamic learning module receives to flow the data letter of control threshold cell
Number, sorting-out in statistics then is carried out to data-signal, not packet loss, not speed limit, calculated according to the result of sorting-out in statistics and receive data
Maximum threshold, stream control threshold cell is adjusted according to the maximum at calculating.
Detailed Jie has been carried out to a kind of Satellite IP Network QoS flow control thresholding dynamic learning system that the present invention is provided above
Continue.The explanation of specific embodiment is only intended to the method and its core concept for helping to understand the present invention.It should be pointed out that for this skill
For the those of ordinary skill in art field, under the premise without departing from the principles of the invention, some change can also be carried out to the present invention
Enter and modify, these are improved and modification is also fallen into the protection domain of the claims in the present invention.
Claims (10)
1. a kind of Satellite IP Network QoS flow control thresholding dynamic learning system, it is characterised in that：Including Qos stream controls module, stream control door
Dynamic learning module and physical layer are limited, the Qos streams control module includes the first data sink, stream control threshold cell and the first number
According to transmitter, the stream control thresholding dynamic learning module includes the second data sink, data dissection process device and the second data
Transmitter, the input of first data sink includes first input end and the second input, the first data transmitting
The output end of device includes the first output end and the second output end, and the first input end is external input, first data
The output end of receiver and the input of stream control threshold cell are communicated to connect, output end and the first number of the stream control threshold cell
Communicated to connect according to the input of transmitter, the second output end of first data source and the signal incoming end of physical layer are logical
Letter connection, the first output end of first data source is communicated to connect with the signal input part of the second data sink, institute
The signal output part for stating the second data sink is connected with the signal input part of data dissection process device, the data dissection process
The output end of device and the input of the second data source are communicated to connect, the second data source output end and stream control thresholding
Control end communication connection.
2. a kind of Satellite IP Network QoS flow control thresholding dynamic learning system according to claim 1, it is characterised in that：It is described
Data dissection process device includes data parsing arithmetic unit, data parsing controller and parsing data storage, the data parsing
The signal input part of controller connects the second data sink signal output part, and the data parse the signal output part of controller
Connect the control end that data parse arithmetic unit, the input of the output end connection parsing data storage of the data parsing arithmetic unit
End, the signal output part of the data storage connects the second data source signal input part.
3. a kind of Satellite IP Network QoS flow control thresholding dynamic learning system according to claim 2, it is characterised in that：It is described
Stream control threshold cell includes the output end of input buffer, the signal input part of the input buffer and the first data sink
Connection, the input buffer signal output part is connected with the signal input part of stream control gate cell.
4. a kind of Satellite IP Network QoS flow control thresholding dynamic learning system according to claim 3, it is characterised in that：It is described
Output state is installed between the first output end and physical layer of first data source.
5. a kind of side of Satellite IP Network QoS flow control thresholding dynamic learning system as described in any one in Claims 1 to 4
Method, it is characterised in that：The stream control threshold module changes stream control threshold value according to calculated value, comprises the following steps：
Step one, demarcation interval, takes a scope to be divided into N number of interval；Respectively
Sj=(j* Δ L+1, (j+1) * Δs L],
Wherein j=0,1,2 ..., N-1；
Step 2, message length is obtained, and obtains the IP message lengths for being sent to satellite channel, and the message is via QoS
Message after stream control resume module；
Step 3, the cycle judges, to sorting out IP messages according to length to be corresponding interval, and by message total in measurement period and
The interval message total respectively increases 1, Ct=Ct+ 1, Cj=Cj+ 1, wherein CjFor the number of message, C in interval jtFor in measurement period
Message total, then judges whether the cycle terminates, and such as cycle does not terminate to return to step one, continues to obtain message；Such as end cycle
Continue step 4；
Step 4, calculates average length, according to the average length of message in the step 3 counting statistics cycle
Step 5, calculates thresholding, and the maximum of stream control thresholding is calculated according to above-mentioned steps
Step 6, feedback of the information, stream controls thresholding dynamic learning module by maximumFeed back to stream control threshold cell, stream control door
Unit is limited according to maximumRegulation stream control threshold value.
6. Satellite IP Network QoS flow control thresholding dynamic study method according to claim 5, it is characterised in that the step
Interval division method is as follows in rapid one,
Sj=(j* Δ L+1, (j+1) * Δs L], wherein j=0,1,2 ..., N-1.
7. Satellite IP Network QoS flow control thresholding dynamic study method according to claim 6, it is characterised in that：Δ L's takes
It is worth for 10 or 20.
8. Satellite IP Network QoS flow control thresholding dynamic study method according to claim 7, it is characterised in that：The step
The cycle can simultaneously be made using the time as the cycle, also using message total as cycle, and time, message number in rapid three
For the basis for estimation of measurement period.
9. Satellite IP Network QoS flow control thresholding dynamic study method according to claim 8, it is characterised in that：The step
Average length computational methods in rapid four are,Wherein
10. Satellite IP Network QoS flow control thresholding dynamic study method according to claim 9, it is characterised in that：The step
Maximum in rapid fiveComputational methods are,The BphyFor
The bandwidth that physical layer is calculated, the LPhyHeaderThe head length of IP messages is encapsulated for physical layer.
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Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030133406A1 (en) * | 1998-11-10 | 2003-07-17 | Ayman Fawaz | Method and apparatus to minimize congestion in a packet switched network |
| CN1556629A (en) * | 2004-01-06 | 2004-12-22 | �����ʵ��ѧ | Method for regulating congest window in communication network |
| US7068599B1 (en) * | 2000-07-26 | 2006-06-27 | At&T Corp. | Wireless network having link-condition based proxies for QoS management |
| CN101595679A (en) * | 2007-02-28 | 2009-12-02 | 中兴通讯股份有限公司 | Realize the device and method of Flow Control on the MSTP equipment based on rate limit |
| CN102246473A (en) * | 2008-12-16 | 2011-11-16 | 阿尔卡特朗讯公司 | Method and devices for performing traffic control in telecommunication networks |
| CN102739510A (en) * | 2011-04-15 | 2012-10-17 | 中兴通讯股份有限公司 | Method and device for flow control |
| US20130102343A1 (en) * | 2011-10-25 | 2013-04-25 | At&T Intellectual Property I. L.P. | Dynamic Bearer Management |
| CN103096336A (en) * | 2013-01-15 | 2013-05-08 | 中国人民解放军理工大学 | High-effect cooperative spectrum sensing method based on quality of service (QOS) guarantee in cognitive radio networks |
| CN103209138A (en) * | 2013-05-06 | 2013-07-17 | 山东大学（威海） | Feedback control converging mechanism based on simulated annealing algorithm in optical burst-switched network |
| US20150282003A1 (en) * | 2014-03-31 | 2015-10-01 | Hughes Network Systems, Llc | System and method for congestion management for downlink queues of digital processing satellites for differentiated quality-of-service (qos) |
| WO2016086551A1 (en) * | 2014-12-03 | 2016-06-09 | 深圳市中兴微电子技术有限公司 | Improved wred-based congestion control method and device |
| CN106385386A (en) * | 2016-08-31 | 2017-02-08 | 成都飞鱼星科技股份有限公司 | Application servo-actuated intelligent floe control method |
-
2017
- 2017-05-16 CN CN201710340999.8A patent/CN106992939B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030133406A1 (en) * | 1998-11-10 | 2003-07-17 | Ayman Fawaz | Method and apparatus to minimize congestion in a packet switched network |
| US7068599B1 (en) * | 2000-07-26 | 2006-06-27 | At&T Corp. | Wireless network having link-condition based proxies for QoS management |
| CN1556629A (en) * | 2004-01-06 | 2004-12-22 | �����ʵ��ѧ | Method for regulating congest window in communication network |
| CN101595679A (en) * | 2007-02-28 | 2009-12-02 | 中兴通讯股份有限公司 | Realize the device and method of Flow Control on the MSTP equipment based on rate limit |
| CN102246473A (en) * | 2008-12-16 | 2011-11-16 | 阿尔卡特朗讯公司 | Method and devices for performing traffic control in telecommunication networks |
| CN102739510A (en) * | 2011-04-15 | 2012-10-17 | 中兴通讯股份有限公司 | Method and device for flow control |
| US20130102343A1 (en) * | 2011-10-25 | 2013-04-25 | At&T Intellectual Property I. L.P. | Dynamic Bearer Management |
| CN103096336A (en) * | 2013-01-15 | 2013-05-08 | 中国人民解放军理工大学 | High-effect cooperative spectrum sensing method based on quality of service (QOS) guarantee in cognitive radio networks |
| CN103209138A (en) * | 2013-05-06 | 2013-07-17 | 山东大学（威海） | Feedback control converging mechanism based on simulated annealing algorithm in optical burst-switched network |
| US20150282003A1 (en) * | 2014-03-31 | 2015-10-01 | Hughes Network Systems, Llc | System and method for congestion management for downlink queues of digital processing satellites for differentiated quality-of-service (qos) |
| WO2016086551A1 (en) * | 2014-12-03 | 2016-06-09 | 深圳市中兴微电子技术有限公司 | Improved wred-based congestion control method and device |
| CN106385386A (en) * | 2016-08-31 | 2017-02-08 | 成都飞鱼星科技股份有限公司 | Application servo-actuated intelligent floe control method |
Non-Patent Citations (8)
| Title |
|---|
| 夏文芳等: "协作频谱感知中快速自适应门限策略", 《电子与信息学报》 * |
| 庞斌,高文: "基于状态反馈的网络分布式拥塞管理方案" * |
| 曾菊玲;蒋砺思;: "基于跨层的自适应预留带宽和多重QoS保证的EDCA流接纳控制" * |
| 段中兴,赵煌: "反馈控制的优先级队列公平调度算法" * |
| 王秦立等: "基于底层流量估计的多级拥塞准入控制算法", 《计算机仿真》 * |
| 管剑波等: "IP路由器中流量控制机制的研究", 《计算机工程与科学》 * |
| 肖楠等: "基于分集接收的卫星认知通信动态频谱感知策略", 《中南大学学报(自然科学版)》 * |
| 邓晓衡,陈志刚,王建新,曾志文: "NARED:一种非线性自适应RED拥塞控制机制" * |
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