CN102594693A - Flow control method of space network - Google Patents

Flow control method of space network Download PDF

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CN102594693A
CN102594693A CN2012100551556A CN201210055155A CN102594693A CN 102594693 A CN102594693 A CN 102594693A CN 2012100551556 A CN2012100551556 A CN 2012100551556A CN 201210055155 A CN201210055155 A CN 201210055155A CN 102594693 A CN102594693 A CN 102594693A
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module
network
spatial network
spatial
network capacity
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CN102594693B (en
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黄东
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Abstract

The invention provides a flow control method of a space network, which realizes efficient and reliable transmission of business resources in the space network by establishing corresponding flow control functional modules and algorithms for the space network.

Description

A kind of flow control methods of spatial network
Technical field
The present invention relates to wireless communication technology field, particularly relate to wireless network and Optimum Theory.
Background technology
Along with space mission constantly advances to deep space, traditional space flight measurement and control pattern can not satisfy the needs of message transmission, and the situation that point-to-point in the past transmission means is solely deposited will not exist.Interconnecting between the user's space unit, between the repeater satellite, between user's space unit and the repeater satellite becomes the inexorable trend and the requirement of space information system development; Research and construction comprise that the spatial information transmission system of ground tracking and command network, space-based TT & C network, space network and deep space tracking and command network is imperative, and the structure of spatial network is as shown in Figure 1.
Interspace interconnected (IPN) can be divided into by function: backbone network, Access Network, constellation or formation flight network, low coverage wireless network.
Backbone network is the high-speed wideband network of a responsible message transmission and distribution, mainly is made up of data relay satellite system, ground observing and controlling net, ground data net and deep space net etc.Data, telemetry intelligence (TELINT) and application data etc. are injected in the instruction of negative your the transmission user's space unit of backbone network.Guaranteeing under the prerequisite of fail safe that this network also can provide the interface with the terrestrial interconnection net.
Access Network refers to be used for space cell and the trunk network that each constitutes of establishing with information exchange that just connected.
Constellation or Small Satellite Formation Flying network refer to the to cooperate space cell of flight for example is used for the network that the inter-satellite link of swap data constitutes in constellation or the satellites formation.
In some space missions, need carry out co-ordination to dissimilar space cells, as the manned space station dock with the intersection of airship, release between Mars orbiter, orbital vehicle and the lander and docking.If rely on ground to measure and control fully, will bring great expense in the face of many space cells.The backbone network node only and between one of this task of execution or the minority principal space unit is set up link, accomplishes information exchange.And the network of between principal space unit and other space cells, setting up is referred to as the low coverage wireless network.The characteristics of this network are that operating distance is short, power hungry is low, cost is low, tear down and build conveniently, and route between interspace and data forwarding flow process are shown in Fig. 2 and 3.
Therefore be necessary to design a kind of flow control mechanism efficiently, the stable transfer of implementation space Network.
Summary of the invention
Technical problem to be solved by this invention is: the professional stable transfer problem that solves spatial network.
The present invention solves the problems of the technologies described above the flow control methods that a kind of spatial network is provided, and it is characterized in that:
A, set up the flow-control module of spatial network;
B, using system initialization module obtain the initialization condition and the service condition of spatial network system, then initialization information are sent to network capacity optimized distribution module, and acquisition spatial network capacity is stablized the condition of optimum allocation;
C, use the balanced new Business Stream of dynamic subscriber's balance point module, and the professional Control Parameter through the Business Stream adjustment network capacity optimum allocation that calculates;
D, the condition that the flow control of spatial network finishes is set.
In the said steps A, the flow-control module of spatial network by transmission time re-computation module, system initialization module, network capacity optimized distribution module, dynamic subscriber's balance point module, the check balance point whether restrains module and the punishment strategy module is formed.
Among the said step B, order
Figure 237650DEST_PATH_IMAGE001
; Wherein
Figure 624769DEST_PATH_IMAGE002
is penalty factor;
Figure 994570DEST_PATH_IMAGE003
;
Figure 354008DEST_PATH_IMAGE004
makes the point of spatial network capacity optimum allocation do
Figure 151062DEST_PATH_IMAGE005
; is the capacity of direct connected link
Figure 933391DEST_PATH_IMAGE007
;
Figure 412914DEST_PATH_IMAGE008
is the Business Stream of link
Figure 380870DEST_PATH_IMAGE009
;
Figure 477001DEST_PATH_IMAGE010
is weight coefficient, and total flow process is as shown in Figure 4.
Among the said step B, the spatial network capacity is stablized the optimum allocation condition provides the optimized point set for the network capacity optimal module.Work as condition
Figure 188606DEST_PATH_IMAGE011
is when satisfying; The spatial network capacity realizes stablizing optimum allocation; Wherein
Figure 771903DEST_PATH_IMAGE012
is Lagrange multiplier; is spatial network capacity utilance function;
Figure 494188DEST_PATH_IMAGE014
is physical link
Figure 212745DEST_PATH_IMAGE015
capacity;
Figure 198019DEST_PATH_IMAGE013
is the increasing function of
Figure 507777DEST_PATH_IMAGE016
;
Figure 578502DEST_PATH_IMAGE017
is the route set of spatial network;
Figure 100750DEST_PATH_IMAGE018
is the physical link set of spatial network; And use genetic algorithm to obtain optimal solution, as shown in Figure 5.
Among the said step C; When step B accomplishes; Obtain current dynamic subscriber's equilibrium state information, divide timing, use the initialization information of current dynamic subscriber's equilibrium state information as next network capacity optimal module running status when next user is carried out network capacity.
Figure 940530DEST_PATH_IMAGE019
;
Figure 421190DEST_PATH_IMAGE018
is the Business Stream vector;
Figure 182472DEST_PATH_IMAGE020
is the data signal vector in the network, and
Figure 39570DEST_PATH_IMAGE021
is and the corresponding data signal vector of Business Stream.
Among the said step D; The condition
Figure 733856DEST_PATH_IMAGE022
that flow control finishes is set; Wherein
Figure 385418DEST_PATH_IMAGE023
is the time interval of professional deviated from network;
Figure 273477DEST_PATH_IMAGE024
is that transmitting terminal and receiving terminal are right; is Route Distinguisher;
Figure 624004DEST_PATH_IMAGE025
is transmitting terminal and the route set of receiving terminal to being used in
Figure 430155DEST_PATH_IMAGE024
;
Figure 697188DEST_PATH_IMAGE026
is the collection of services on the route in the time interval
Figure 896088DEST_PATH_IMAGE023
;
Figure 27172DEST_PATH_IMAGE027
be in the time interval the professional transmission time on the route
Figure 518513DEST_PATH_IMAGE002
;
Figure 41899DEST_PATH_IMAGE028
be in the time interval
Figure 940585DEST_PATH_IMAGE023
transmitting terminal and receiving terminal to in all Business Streams, be in the time interval
Figure 100805DEST_PATH_IMAGE023
transmitting terminal and receiving terminal to
Figure 904812DEST_PATH_IMAGE024
in shortest path by transmission time.
Beneficial effect of the present invention is: a kind of flow control methods of spatial network is provided, through setting up corresponding flow control function module of spatial network and algorithm, has realized the high efficient and reliable transmission of service resources in spatial network.
Description of drawings
Fig. 1 is the structural representation of spatial network;
Figure 633734DEST_PATH_IMAGE030
ground base station wherein;
Figure 712548DEST_PATH_IMAGE031
is communication truck;
Figure 210526DEST_PATH_IMAGE032
is mobile node, and is circumterrestrial satellite.
Figure 650920DEST_PATH_IMAGE034
is the satellite around Mars;
Fig. 2 is the route sketch map between interspace;
Fig. 3 is that the business between interspace is transmitted sketch map;
Fig. 4 is total workflow sketch map;
Fig. 5 obtains the optimal solution schematic flow sheet for using genetic algorithm.

Claims (6)

1. the flow control methods of a spatial network solves the professional stable transfer problem of spatial network, comprises the steps:
A, set up the flow-control module of spatial network;
B, system initialization module are obtained the initialization condition and the service condition of spatial network system, then initialization information are sent to network capacity optimized distribution module, and acquisition spatial network capacity is stablized the condition of optimum allocation;
C, use the balanced new Business Stream of dynamic subscriber's balance point module, and the professional Control Parameter through the Business Stream adjustment network capacity optimum allocation that calculates;
D, the condition that the flow control of spatial network finishes is set.
2. according to the method for claim 1, it is characterized in that for said steps A: the flow-control module of spatial network by transmission time re-computation module, system initialization module, network capacity optimized distribution module, dynamic subscriber's balance point module, the check balance point whether restrains module and the punishment strategy module is formed.
3. according to the method for claim 1, it is characterized in that: order for said step B
Figure 420788DEST_PATH_IMAGE001
; Wherein
Figure 337928DEST_PATH_IMAGE002
is penalty factor;
Figure 117666DEST_PATH_IMAGE003
;
Figure 512875DEST_PATH_IMAGE004
makes the point of spatial network capacity optimum allocation do
Figure 796089DEST_PATH_IMAGE005
;
Figure 618551DEST_PATH_IMAGE006
is the capacity of direct connected link
Figure 885584DEST_PATH_IMAGE007
;
Figure 802594DEST_PATH_IMAGE008
is the Business Stream of link , and
Figure 589470DEST_PATH_IMAGE010
is weight coefficient.
4. according to the method for claim 1, it is characterized in that for said step B: the spatial network capacity is stablized the optimum allocation condition provides the optimized point set for the network capacity optimal module, works as condition
is when satisfying; The spatial network capacity realizes stablizing optimum allocation; Wherein
Figure 80811DEST_PATH_IMAGE012
is Lagrange multiplier;
Figure 73038DEST_PATH_IMAGE013
is spatial network capacity utilance function;
Figure 502882DEST_PATH_IMAGE014
is physical link
Figure 744508DEST_PATH_IMAGE015
capacity;
Figure 19631DEST_PATH_IMAGE013
is the increasing function of ;
Figure 467110DEST_PATH_IMAGE017
is the route set of spatial network; is the physical link set of spatial network, and uses genetic algorithm to obtain optimal solution.
5. according to the method for claim 1; It is characterized in that for said step C: when step B accomplishes; Obtain current dynamic subscriber's equilibrium state information; When being carried out network capacity, next user divides timing; Use the initialization information of current dynamic subscriber's equilibrium state information as next network capacity optimal module running status;
Figure 274846DEST_PATH_IMAGE019
;
Figure 241665DEST_PATH_IMAGE018
is the Business Stream vector;
Figure 13312DEST_PATH_IMAGE020
is the data signal vector in the network, and
Figure 963951DEST_PATH_IMAGE021
is and the corresponding data signal vector of Business Stream.
6. according to the method for claim 1; It is characterized in that for said step D: the condition
Figure 846456DEST_PATH_IMAGE022
that flow control finishes is set; Wherein
Figure 917049DEST_PATH_IMAGE023
is the time interval of professional deviated from network; is that transmitting terminal and receiving terminal are right;
Figure 297532DEST_PATH_IMAGE002
is Route Distinguisher;
Figure 186990DEST_PATH_IMAGE025
is transmitting terminal and the route set of receiving terminal to being used in
Figure 659560DEST_PATH_IMAGE024
;
Figure 773010DEST_PATH_IMAGE026
is the collection of services on the route
Figure 391390DEST_PATH_IMAGE002
in the time interval
Figure 698240DEST_PATH_IMAGE023
;
Figure 452887DEST_PATH_IMAGE027
be in the time interval the professional transmission time on the route
Figure 149764DEST_PATH_IMAGE002
; be in the time interval
Figure 828187DEST_PATH_IMAGE023
transmitting terminal and receiving terminal to
Figure 17860DEST_PATH_IMAGE024
in all Business Streams,
Figure 917683DEST_PATH_IMAGE029
be in the time interval transmitting terminal and receiving terminal to
Figure 503571DEST_PATH_IMAGE024
Nei shortest path by transmission time.
CN201210055155.6A 2012-03-05 2012-03-05 Flow control method of space network Expired - Fee Related CN102594693B (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106059960A (en) * 2016-05-24 2016-10-26 北京交通大学 Software defined network-based space network QoS guarantee method and management center

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102186072A (en) * 2011-04-20 2011-09-14 上海交通大学 Optimized transmission method of multi-rate multicast communication for scalable video stream

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102186072A (en) * 2011-04-20 2011-09-14 上海交通大学 Optimized transmission method of multi-rate multicast communication for scalable video stream

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
李可维: "基于网络效用最大化的无线mesh网络跨层优化算法研究", 《中国博士学位论文全文数据库》 *
林闯等: "《计算机网络服务质量优化方法研究综述》", 《计算机学报》 *
黄昭文: "无线mesh网络资源调度算法与Qos保障机制研究", 《中国博士学位论文全文数据库》 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106059960A (en) * 2016-05-24 2016-10-26 北京交通大学 Software defined network-based space network QoS guarantee method and management center
CN106059960B (en) * 2016-05-24 2019-06-04 北京交通大学 A kind of spatial network QoS assurance and administrative center based on software defined network

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