CN101404660B - Service flow distribution system and method for multi-module cooperation communication - Google Patents
Service flow distribution system and method for multi-module cooperation communication Download PDFInfo
- Publication number
- CN101404660B CN101404660B CN2008102266042A CN200810226604A CN101404660B CN 101404660 B CN101404660 B CN 101404660B CN 2008102266042 A CN2008102266042 A CN 2008102266042A CN 200810226604 A CN200810226604 A CN 200810226604A CN 101404660 B CN101404660 B CN 101404660B
- Authority
- CN
- China
- Prior art keywords
- network
- module
- priority
- available
- information
- 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
Images
Abstract
The invention relates to the technical field of heterogeneous network communication, and provides a system for distributing traffic flow of multimode coordinating communication and a method thereof. The system comprises a perception module, a judge module, a target module and a decision-making module, wherein the perception module is used for perceiving the status of connected network link and acquiring network information and traffic flow information; the judge module is used for determining the priority level of the traffic flow and filtering an available network according to the received network information and traffic flow information; the target module is used for converting user requirement into a decision-making object which can be measured according to relative nearness; the decision-making module is used for acquiring the nearness of the available network and an optimal network and determining the optimal network fulfilling each traffic flow by using a multiparameter weighing self-generating algorithm and a TOPSIS multiattribute decision-making method. According to the invention, important traffic flow can be ensured to have the priority for using the network when the most suitable distribution network is selected for the traffic flow; weighing corresponding to each network parameter impacting the traffic flow distribution decision making can be automatically determined, thereby reducing the burden of users.
Description
Technical field
The present invention relates to the computer technical field of heterogeneous network communication, more specifically, the present invention relates to the service flow distribution system and the method for multi-module cooperation communication on a kind of heterogeneous network.
Background technology
In recent years, along with the continuous increase to mobile access demand with people that develops rapidly of wireless communication technology, various Radio Access Networks emerge in large numbers one after another, and the isomerism of future network is more outstanding.People reach common understanding to the composition of next generation mobile networks: next generation mobile networks must be the heterogeneous network that multiple access technology merges mutually.
Be accompanied by the development of heterogeneous network, in order to make the user can enjoy convenient, fast, the seamless access experience that heterogeneous network brings to the full, the multi-module mobile terminal of integrating multi network interface is universal day by day, and the technology that makes multi-module mobile terminal utilize a plurality of interfaces to communicate simultaneously is referred to as multi-module cooperation communication.Multi-module cooperation communication makes following situation become possibility: when the Business Stream that number of different types is arranged on the terminal need be transmitted, can to different access networks, transmit each bar distribution of traffic flows according to the current link circuit condition of dissimilar Business Stream characteristics, different access networks, the factors such as hobby of different user, on the basis that ensures each bar traffic stream service quality, obtain minimum communications cost and maximum resource utilance; In addition, when no longer available or service quality obviously reduces when certain access network, also can in time make a response, loaded service stream on this network seamlessly be switched on other available networks transmit.
Multi-module cooperation communication needs a system stable operation on multimode terminal, carries out the real-time measurement of network link situation automatically, and perception current business stream type is set up mapping relations automatically between Business Stream and each access network interface automatically.At present, network link situation line Measurement Technique and type of service cognition technology be comparative maturity all, multi-module mobile terminal can obtain the signal strength signal intensity and the available bandwidth of current each access network at an easy rate, also can tell the traffic flow types of concurrent running on this machine easily, therefore the key of problem is to lack a kind of distribution of traffic flows method, can automatically between Business Stream and each network interface, set up mapping relations according to the type of each the bar Business Stream that is transmitting on the network link situation of real-time measurement and the multi-module mobile terminal.Existing heterogeneous network multi-module mobile terminal distribution of traffic flows method, there are following three problems: 1) be difficult to distinguish dissimilar Business Streams, and be difficult to determine only transmission network and guarantee that important business has the priority of using the networking according to the feature of Business Stream; 2) be difficult to automatic under the situation that need not user's participation, rational each parameter weight of network of determining to influence the distribution of traffic flows decision-making; 3) be difficult to the distribution of traffic flows problem of multi-module mobile terminal in the heterogeneous network is summarized and Business Stream is instructed.
Summary of the invention
For overcome on the active computer heterogeneous network that type in the distribution of traffic flows is difficult to distinguish and preferentially distribution be difficult to the defective that guarantees and be difficult to determine automatically the distribution of traffic flows weight, the present invention proposes a kind of service flow distribution system and method for multi-module cooperation communication.
According to an aspect of the present invention, proposed a kind of service flow distribution system of multi-module cooperation communication, having comprised:
Sensing module is used for the link circuit condition of the network that perception connects, and obtains the network information and Business Stream information;
Judge module is used for determining Business Stream priority and filtering out available network according to the described network information and the Business Stream information that receive;
Object module is used for user's request is converted into the decision objective that can weigh according to relative approach degree;
Decision-making module, according to receiving from the usable network information of described judge module with from the decision objective information of described object module, use multi-parameter weight self-generating algorithm and TOPSIS multiple attributive decision making method, obtain the approach degree of described available network and theoretical optimal network, determine to satisfy the optimal network of each Business Stream.
Wherein, described sensing module is according to the network online measurement technology, and the current link circuit condition of each network that perception connected comprises available bandwidth, signal strength signal intensity and time delay, shake, the packet loss of network; And according to the type of service cognition technology, perception needs serviced traffic flow types.
Wherein, described judge module is determined Business Stream priority and formed priority query according to following principle: the priority of real time business is higher than non-real-time service, and interactive service priority is higher than the non-interactive type business, and service switchover priority is higher than new access service.
Wherein, described judge module is chosen the available network collection that satisfies this Business Stream requirement according to the network qualifications of highest priority traffic stream.
Wherein, in the described object module, described relative approach degree be restricted to be used to weigh available network and theoretical optimal network press close to degree and with the variable of the poorest network of theory away from degree.
Wherein, described decision-making module uses existing multi-parameter weight self-generating algorithm according to described usable network information, generates the weight of network parameters correspondence; Described decision-making module is according to described usable network information and described network parameters respective weights, uses the TOPSIS multiple attributive decision making method, calculates the relative approach degree of each available network and desirable optimal network.
Wherein, described TOPSIS multiple attributive decision making method comprises: by the theoretical optimal network and the poorest network of theory of structure evaluating network, and with near optimal network with away from the degree of poor network, calculate available network and come available network is sorted, select optimum available network with the relative approach degree of desirable optimal network.
According to a further aspect in the invention, proposed a kind of distribution of traffic flows method of multi-module cooperation communication, having comprised:
The link circuit condition of step 10), network that perception connected obtains the network information and Business Stream information;
Step 20), according to the described network information and the Business Stream information that receive, determine Business Stream priority and filter out available network;
Step 30), user's request is converted into the decision objective that can weigh according to relative approach degree;
Step 40), according to the described usable network information and the described decision objective information that receive, use multi-parameter weight self-generating algorithm and TOPSIS multiple attributive decision making method, obtain the approach degree of described available network and theoretical optimal network, determine to satisfy the optimal network of each Business Stream.
Wherein, step 10) also comprises: according to the network online measurement technology, the current link circuit condition of each network that perception connected comprises available bandwidth, signal strength signal intensity and time delay, shake, the packet loss of network; And according to the type of service cognition technology, perception needs serviced traffic flow types.
Wherein, step 20) comprise that also determine Business Stream priority and form priority query according to following principle: the priority of real time business is higher than non-real-time service, and interactive service priority is higher than the non-interactive type business, and service switchover priority is higher than new access service.
Wherein, step 20) also comprise:, choose the available network collection that satisfies described Business Stream requirement according to the network qualifications of highest priority traffic stream.
Wherein, step 30) in, described relative approach degree be restricted to be used to weigh available network and theoretical optimal network press close to degree and with the variable of the poorest network of theory away from degree.
Wherein, step 40) also comprise: according to described usable network information, use existing multi-parameter weight self-generating algorithm, generate the weight of network parameters correspondence; According to described usable network information and described network parameters respective weights, use the TOPSIS multiple attributive decision making method, calculate the relative approach degree of each available network and theoretical optimal network.
Wherein, step 40) in, described TOPSIS multiple attributive decision making method comprises: by the theoretical optimal network and the poorest network of theory of structure evaluating network, and with near optimal network with away from the degree of poor network, calculate available network and come available network is sorted, select optimum available network with the relative approach degree of desirable optimal network.
According to the present invention,,, guarantee that when selecting only distributing network important Business Stream has the priority of using network for Business Stream for each bar Business Stream is given different service priority based on the feature of different kinds of business stream; The present invention introduces multi-parameter weight self-generating algorithm, is used for definite automatically weight that influences every network parameter correspondence of distribution of traffic flows decision-making, alleviates burden for users.
Description of drawings
Fig. 1 is multi-module cooperation communication typical scene figure in the heterogeneous network;
Fig. 2 is based on the multi-module cooperation communication service flow distribution system schematic diagram of priority and weight self-generating;
Fig. 3 is based on the multi-module cooperation communication distribution of traffic flows method flow diagram of priority and weight self-generating.
Embodiment
Be described in detail below in conjunction with the service flow distribution system and the method for the drawings and specific embodiments a kind of multi-module cooperation communication provided by the invention.
Fig. 1 as shown in the figure, provides the composition topology example of next generation mobile networks for multi-module cooperation communication typical scene figure in the existing heterogeneous network, and next generation mobile networks is a heterogeneous network that plurality of access modes merges mutually.Various wireless access technologys differ from one another, multiple access network coexistence, and for example: high bandwidth can be provided in the focus covering but coverage is little; Big but the limited bandwidth of the coverage that honeycomb covers; Even same type overlay network, the difference of realization technology or operator also can have influence on user's access and select.Therefore be difficult to replace other all access technology with single access technology, various wireless access ways are with long-term co-existence.The target of next generation mobile networks is exactly well to merge these different Radio Access Networks, allows their have complementary advantages, thereby provides the most perfect experience for the mobile subscriber.
In addition, Fig. 1 also illustrates the typical scene of multimode terminal collaboration communication in the heterogeneous network.When having dissimilar Business Streams to transmit on the multimode terminal, can each bar distribution of traffic flows be transmitted to different network interfaces according to the feature of different kinds of business stream, the factors such as current link circuit condition of heterogeneous networks, on the basis that ensures the traffic stream service quality, obtain minimum communications cost and maximum resource utilization; In addition, when no longer available or service quality obviously reduced when certain access network, multimode terminal can in time be made a response, and loaded service stream on this network is seamlessly switched on other networks that satisfy traffic flow requirements transmit.As shown in Figure 1, this multimode terminal is equipped with multiple interfaces, can directly link to each other with cellular network, focus overlay network, and supposing can 3 kinds of sessions of concurrent running---speech, video and file transfer on the multimode terminal.3 kinds of sessions have different service features and QoS requirement, and desirable transmission plan is: voice service, because relatively more responsive, should select the good cellular network transmission of service quality to time delay, shake; Video traffic, data volume is big, delay requirement is general, preferably select focus overlay network transmission, but the user move and cause focus overlay network time spent no longer, should transmit just seamlessly switching on the honeycomb overlay network that satisfies the demands as much as possible at serviced Business Stream; The file transfer business, data volume is big, to the time delay no requirement (NR), should select the focus overlay network to transmit as far as possible, and the zone that does not have focus to cover can be transmitted under the prerequisite that does not influence the transmission of other types Business Stream.
Fig. 2 illustrates according to an embodiment of the invention the multi-module cooperation communication service flow distribution system based on priority and weight self-generating.According to existing Multiple Attribute Decision Making Theory, in conjunction with service priority notion and weight self-generating algorithm, propose a kind of multi-module cooperation communication service flow distribution system according to embodiments of the invention, comprise sensing module, judge module, decision-making module and object module based on priority and weight self-generating.
Sensing module, on the one hand according to existing network online measurement technology, the current link circuit condition of each network that perception connected, comprise two time-varying parameters (available bandwidth, signal strength signal intensity) and three service quality measurement indexs (time delay, shake, packet loss) of network, form the current collection of network Y={y that exists
1, y
2, y
3... y
m, m ∈ N, each network y
iAll use one group of parameter to characterize y
i={ y
I, 1, y
I, 2, y
I, 3... y
I, k, k ∈ N, wherein y
I, jJ parameter representing i network.On the other hand, according to existing type of service cognition technology, perception needs serviced traffic flow types, comprises that this Business Stream to the demand of bandwidth, signal strength signal intensity with to the tolerance limit of time delay, shake, packet loss, forms the Business Stream set X={x of concurrent running on the multi-module mobile terminal
1, x
2, x
3... x
n, n ∈ N, final sensing module passes to judge module with the network information and the Business Stream information that perception obtains.
Judge module, on the one hand according to the Business Stream feature, for each the bar Business Stream that receives is determined a priority, and Business Stream set is adjusted according to priority, form a priority query, in the formation each is represented Business Stream to be distributed such as, and formation is according to the priority descending, the Business Stream X of head of the queue
iBe the object of decision-making distribution next time.In general, the Business Stream Determination of priority is followed following rules: the priority of real time business is higher than non-real-time service, and interactive service priority is higher than the non-interactive type business, and service switchover priority is higher than new access service.On the other hand, judge module is according to head of the queue Business Stream X
iQualifications at aspects such as bandwidth, time delay, shake and packet loss screens collection of network, is met m available network of distribution of traffic flows, constitutes available network set Y={y
1, y
2, y
3... y
m.Available network must satisfy the demand of Business Stream on bandwidth and signal strength signal intensity, and is dropping on the features such as time delay, shake and packet loss within the limit that Business Stream can tolerate.Final judge module passes to decision-making module with judged result (usable network information).
The effect of object module is exactly that demand with the user changes into the target that can weigh comparison by certain mathematical method.In the middle of the heterogeneous network environment in future, the user wishes to obtain convenient, fast, seamless access most and experiences.Promptly when having dissimilar Business Streams to transmit on the multimode terminal, can each bar distribution of traffic flows be transmitted to different network interfaces according to the feature of different kinds of business stream, the factors such as current link circuit condition of heterogeneous networks; In addition, when no longer available or service quality obviously reduced when certain access network, multimode terminal can in time be made a response, and loaded service stream on this network is seamlessly switched on other networks that satisfy traffic flow requirements transmit.The present invention defines relative approach degree N
jFor weigh available network and theoretical optimal network press close to degree and with the variable of the poorest network of theory away from degree, the big more explanation scheme of its value is excellent more, thereby the optimal network selection problem of Business Stream is exactly the N to all available networks
jSort and choose N
jThe network that the maximum network of value transmits as Business Stream.
Approach degree is by constructing the positive ideal solution C of a problem relatively
+(
) and negative ideal solution C
-(
), calculate each available network i and theoretical optimal solution C
+The poorest C that separates
-Distance
With
Finally by formula
Calculate.Wherein, c
iA certain parameter of expression network, as: bandwidth, time delay, shake etc.The span of approach degree is [0,1] relatively.Decision-making module receives from the usable network information that satisfies this distribution of traffic flows of judge module with from the decision objective of object module, uses existing multiple attribute decision making (MADM) analytical method, realizes the distribution decision-making of Business Stream.When estimating a plurality of available networks good and bad, must determine to influence the weight of every network parameter of distribution of traffic flows decision-making, Chang Yong method was by user's specified weight in the past, for reducing burden for users, the present invention has introduced multi-parameter weight self-generating algorithm, in the present embodiment, select for use lagrange's method of multipliers to find the solution the weight of each parameter.Therefore, decision-making module uses existing multi-parameter weight self-generating algorithm at first according to usable network information, generates the weights W={ w of network parameters correspondence
1, w
2, w
3... w
n, suppose that at this each network all described by n parameter.At last, decision-making module is according to usable network information and network parameters respective weights, use TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) multiple attributive decision making method, by calculating the relative approach degree N of each available network and desirable optimal network
j, N
jThe big more network of selection that shows of value approach desirable optimal network more, thereby find the optimal network that satisfies this distribution of traffic flows, and this distribution of traffic flows is transmitted in selected optimal network.The TOPSIS method is classical multiple attributive decision making method, it is widely used in numerous areas such as management, industrial production, its basic thought is the positive ideal solution and the negative ideal solution of structure evaluation problem, and with close positive ideal solution with away from the degree of bearing ideal solution, come each scheme is sorted to the relative approach degree of ideal scheme by calculating each alternative, thereby select optimal case.Article " Inter-companycomparison using modified TOPSIS with objective weights " is asked for an interview in the detailed introduction of this method.(H.Deng，C.H.Yeh?and?R.J?Willis，“Computers?&?Operations?Research”Volume?27，Number10，September?2000，pp.963-973)
Fig. 3 illustrates the multi-module cooperation communication distribution of traffic flows method based on priority and weight self-generating according to another embodiment of the invention, comprising:
S1: for better differentiated service, guarantee that important service has the priority of using network, introduced the notion of priority based on the multi-module cooperation communication distribution of traffic flows algorithm of priority and weight self-generating, each Business Stream is endowed a priority, in general, the definite of service priority can abide by following rules: the priority of real time business is higher than non-real-time service, the priority of interactive service is higher than the non-interactive type business, and the priority of service switchover is higher than the business of new access.On each terminal, algorithm of the present invention is being safeguarded a priority query, in the formation each is represented Business Stream to be distributed such as, and formation is according to the descending of Business Stream priority, and the Business Stream that comes the formation head has the priority of using network than the Business Stream of afterbody.
S2:, measure the current link circuit condition of each network according to existing network measure method.Want two time-varying parameters of Measurement Network on the one hand: network remaining bandwidth and current demand signal intensity; We adopt the definition of International Telecommunications Union to QoS on the other hand, weigh with time-delay, shake and three indexs of packet loss, therefore want the current time-delay of Measurement Network, shake and packet loss.
S3: conventional algorithm of the present invention at first takes out each bar Business Stream successively from the formation head of each terminal and distributes decision-making.
S4: the distribution of traffic flows decision process is divided into two stages, at first according to the qualifications of current business flow at aspects such as bandwidth, time delay, shake and packet loss, set is screened to current network, the available network that obtains must satisfy the bandwidth demand of Business Stream, and features such as time delay, shake and packet loss drop within the limit that Business Stream can tolerate.The feasible solution space of available network being formed this distribution of traffic flows.
S5: judge whether the feasible solution space is empty.If the feasible solution space is empty, enter the S9 adjustment algorithm; Otherwise, enter the second stage that S6 distributes decision process.
S6: each network is all described by a plurality of parameters, can compare mutually in order to make between the dissimilar parameters, need to carry out normalization according to the characteristics of parameter earlier it is carried out nondimensional standardization processing, thereby obtain normalized feasible solution space.In general, according to the value characteristics of different parameters it is divided into cost shape parameter, benefit shape parameter, threshold type parameter and fuzzy shape parameter, dissimilar parameter correspondences different processing rules and normalization formula.
● the cost shape parameter
The value of this class parameter is the smaller the better, typically as communication cost, transmission power consumption etc., uses following formula to carry out normalization for this class parameter:
● the benefit shape parameter
The value of this class parameter is the bigger the better, and is typical in network coverage, uses following formula to carry out normalization for this class parameter:
● the threshold type parameter
Professional value to this class parameter has mandatory, promptly must be more than or equal to (perhaps smaller or equal to) some threshold value t, and typical in bandwidth demand, use following formula to carry out normalization for this class parameter:
● fuzzy shape parameter
This class parameter is inconvenient to use accurate numerical value to describe usually, but can be " fine ", " generally ", " poor " etc. with the language variable description, typical in internet security, reliability, stability etc., for this class parameter, can be by the instrument of fuzzy mathematics, adopt methods such as gravity model appoach, maximin method with its de-fuzzy, be converted into concrete numerical value.
S7: when estimating a plurality of alternative network qualities, must at first determine to influence the weight of the network parameters of distribution of traffic flows decision-making.Method commonly used at present is by the user-specified parameters weight, and this is a job that is difficult to finish to the domestic consumer that lacks background knowledge, has also increased user's burden simultaneously.The present invention introduces multi-parameter weight self-generating algorithm, can effectively address the above problem, and is the weight of normalized feasible solution space automatic generating network parameters correspondence.
S8: the feasible solution space of satisfying this distribution of traffic flows and the S7 automatic network parameters weight that generate definite according to S6, the present invention introduces TOPSIS (Technique for Order Performance bySimilarity to Ideal Solution) multiple attributive decision making method, for this Business Stream is found out optimal solution in the feasible solution space, and this distribution of traffic flows transmitted in selected optimal network, turn back to the distribution decision-making that S2 carries out next Business Stream simultaneously.The basic thought of TOPSIS is: by the positive ideal solution and the negative ideal solution of structure evaluation problem, and with close positive ideal solution with away from the degree of bearing ideal solution, calculate each alternative and come each scheme is sorted, thereby select optimal case to the relative approach degree of ideal scheme.Step S3-S8 is a conventional algorithm flow process of the present invention, realizes distribution of traffic flows decision-making generally speaking.
S9: the feasible solution space is empty, can't realize distribution of traffic flows, thereby enter into adjustment algorithm of the present invention.Adjustment algorithm still according to professional priority, is supposed the business that stops a low priority on this terminal, recomputates the available bandwidth of network, is about to the bandwidth that low priority traffice takies and joins in the middle of the network availability bandwidth.Be not the transmission that really stops low priority traffice this moment, and the bandwidth of just utilizing low priority traffice to take recomputates the available bandwidth of each network.
S10: the collection of network to available bandwidth recomputates, according to the qualifications of current business flow at aspects such as bandwidth, time delay, shake and packet loss, calculate the feasible solution space of satisfying this distribution of traffic flows once more.
Whether S11: rejudging the feasible solution space is empty.If the feasible solution space still is empty, enter S12; Otherwise, enter into S13.
S12: current can't the distribution and fail for this Business Stream finds suitable transmission network.This Business Stream is removed, turned back to the distribution decision-making that S2 carries out next Business Stream simultaneously.
S13: feasible solution space non-NULL, nondimensional standardization processing is carried out in the feasible solution space of new composition, principle is with step S6.
S14: use the weight self-generating algorithm of step S7, be the weight of normalized feasible solution space automatic generating network parameters correspondence.
S15: by the TOPSIS multiple attributive decision making method of step S8, in the feasible solution space, find out optimal solution, and distribution of traffic flows is transmitted in this optimal network.
S16: stop the transmission of previous chosen low priority traffice stream, it is put back into etc. in the middle of the Business Stream priority query to be distributed, turn back to the distribution decision-making that S2 carries out next Business Stream simultaneously.Step S9-S16 is under the situation that Business Stream can't be realized distributing for the first time, the adjustment algorithm that the present invention carries out.
The present invention makes following situation become possibility: in following heterogeneous network, when having dissimilar Business Streams to transmit on the multi-module mobile terminal, can each bar distribution of traffic flows be transmitted to different network interfaces according to factors such as Link States before the net of the feature of different kinds of business stream, heterogeneous networks, on the basis that guarantees the traffic stream service quality, obtain minimum communications cost and maximum resource utilization; In addition, when no longer available or service quality obviously reduced when certain access network, multi-module mobile terminal can in time be made a response, and loaded service stream on this network is seamlessly switched on other networks that satisfy the distribution of traffic flows demand transmit.
It should be noted that at last, above embodiment is only in order to describe technical scheme of the present invention rather than the present technique method is limited, the present invention can extend to other modification, variation, application and embodiment on using, and therefore thinks that all such modifications, variation, application, embodiment are in spirit of the present invention and teachings.
Claims (12)
1. the service flow distribution system of a multi-module cooperation communication comprises:
Sensing module is used for the link circuit condition of the network that perception connects, and obtains the network information and Business Stream information;
Judge module is used for determining Business Stream priority and filtering out available network according to the described network information and the Business Stream information that receive;
Object module is used for user's request is converted into measurable decision objective information according to relative approach degree;
Decision-making module, according to receiving from the usable network information of described judge module with from the decision objective information of described object module, use multi-parameter weight self-generating algorithm and TOPSIS multiple attributive decision making method, the theoretical optimal network of structure evaluating network, obtain the relative approach degree of described available network and theoretical optimal network, from described available network, determine to satisfy the optimal network of described Business Stream;
Wherein said relative approach degree is pressed close to the variable of degree for weighing available network and theoretical optimal network.
2. the system of claim 1, wherein, described sensing module is according to the network online measurement technology, and the current link circuit condition of each network that perception connected comprises available bandwidth, signal strength signal intensity and time delay, shake, the packet loss of network; And according to the type of service cognition technology, perception needs serviced traffic flow types.
3. the system of claim 1, wherein, described judge module is determined Business Stream priority and formed priority query according to following principle: the priority of real time business is higher than non-real-time service, and interactive service priority is higher than the non-interactive type business, and service switchover priority is higher than new access service.
4. the system of claim 3, wherein, described judge module is chosen the available network collection that satisfies described Business Stream according to the network qualifications of highest priority traffic stream.
5. the system of claim 1, wherein, described decision-making module uses multi-parameter weight self-generating algorithm according to described usable network information, generates the weight of network parameters correspondence; Described decision-making module is according to described usable network information and described network parameters respective weights, uses the TOPSIS multiple attributive decision making method, calculates the relative approach degree of each available network and theoretical optimal network.
6. the system of claim 5, wherein, described TOPSIS multiple attributive decision making method comprises: by the theoretical optimal network and the poorest network of theory of structure evaluating network, and with near theoretical optimal network with away from the theory degree of poor network, calculate available network and theoretical optimal network and theory the most relative approach degree of poor network come available network is sorted, from described available network, select optimal network; Wherein, described relative approach degree also is used to weigh available network and the poorest network of theory away from degree.
7. the distribution of traffic flows method of a multi-module cooperation communication comprises:
The link circuit condition of step 10), network that perception connected obtains the network information and Business Stream information;
Step 20), according to the described network information and the Business Stream information that receive, determine Business Stream priority and filter out available network;
Step 30), user's request is converted into measurable decision objective information according to relative approach degree;
Step 40), according to the described usable network information and the described decision objective information that receive, use multi-parameter weight self-generating algorithm and TOPSIS multiple attributive decision making method, the theoretical optimal network of structure evaluating network, obtain the approach degree of described available network and theoretical optimal network, from described available network, determine to satisfy the optimal network of described Business Stream;
Wherein said relative approach degree is pressed close to the variable of degree for weighing available network and theoretical optimal network.
8. the method for claim 7, wherein, step 10) also comprises: according to the network online measurement technology, the current link circuit condition of each network that perception connected comprises available bandwidth, signal strength signal intensity and time delay, shake, the packet loss of network; And according to the type of service cognition technology, perception needs serviced traffic flow types.
9. the method for claim 7, wherein, step 20) comprise that also determine Business Stream priority and form priority query according to following principle: the priority of real time business is higher than non-real-time service, interactive service priority is higher than the non-interactive type business, and service switchover priority is higher than new access service.
10. the method for claim 9, wherein, step 20) also comprise: according to the network qualifications of highest priority traffic stream, choose the available network collection that satisfies described Business Stream.
11. the method for claim 8, wherein, step 40) also comprise: according to described usable network information, use multi-parameter weight self-generating algorithm, generate the weight of network parameters correspondence; According to described usable network information and described network parameters respective weights, use the TOPSIS multiple attributive decision making method, calculate the relative approach degree of each available network and theoretical optimal network.
12. the method for claim 11, wherein, step 40) in, described TOPSIS multiple attributive decision making method comprises: by the theoretical optimal network and the poorest network of theory of structure evaluating network, and with near optimal network with away from the degree of poor network, calculate available network and theoretical optimal network and theory the most relative approach degree of poor network come available network is sorted, from described available network, select optimum available network; Wherein, described relative approach degree also is used to weigh available network and the poorest network of theory away from degree.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2008102266042A CN101404660B (en) | 2008-11-17 | 2008-11-17 | Service flow distribution system and method for multi-module cooperation communication |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2008102266042A CN101404660B (en) | 2008-11-17 | 2008-11-17 | Service flow distribution system and method for multi-module cooperation communication |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN101404660A CN101404660A (en) | 2009-04-08 |
| CN101404660B true CN101404660B (en) | 2011-09-07 |
Family
ID=40538528
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN2008102266042A Active CN101404660B (en) | 2008-11-17 | 2008-11-17 | Service flow distribution system and method for multi-module cooperation communication |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN101404660B (en) |
Families Citing this family (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101631124A (en) * | 2009-06-16 | 2010-01-20 | 中兴通讯股份有限公司 | Method and device for downloading data |
| WO2010148542A1 (en) * | 2009-06-26 | 2010-12-29 | 中国科学院计算技术研究所 | Multi-mode mobile terminal and method for automatic allocation of service flows |
| CN102075521A (en) * | 2010-12-21 | 2011-05-25 | 云浮长佳数字科技有限公司 | Multi-netstat interactive service oriented method for forming and distributing traffic streams |
| CN102811465B (en) * | 2012-07-11 | 2015-07-22 | 北京邮电大学 | Service shunting system and method based on feedback information under heterogeneous network |
| CN103036802A (en) * | 2013-01-08 | 2013-04-10 | 中国科学院计算技术研究所 | Traffic unloading method and system |
| CN103747512B (en) * | 2014-01-21 | 2017-11-17 | 宇龙计算机通信科技(深圳)有限公司 | Processing method, processing system and the terminal of data service |
| CN104185221A (en) * | 2014-02-19 | 2014-12-03 | 上海物联网有限公司 | Vertical network switching method based on self-adaptive weight adjustment |
| CN103957267A (en) * | 2014-05-08 | 2014-07-30 | 中国人民解放军总参谋部气象水文空间天气总站 | Multi-network multi-task multi-node data distribution method |
| CN105792330A (en) * | 2014-12-25 | 2016-07-20 | 中国移动通信集团公司 | Method and device for mobile terminal to access to network |
| CN106686687B (en) * | 2016-12-29 | 2020-12-08 | 努比亚技术有限公司 | Access control method and device |
| CN111542073B (en) * | 2020-04-16 | 2023-03-24 | 全球能源互联网研究院有限公司 | Heterogeneous network selection method and system for power service and network adaptation |
| CN112260950B (en) * | 2020-10-19 | 2022-05-06 | 桂林电子科技大学 | Cloud storage network multicast stream scheduling method based on service priority differentiation |
| CN112312504A (en) * | 2020-11-16 | 2021-02-02 | 中国电子科技集团公司第七研究所 | Cross-domain fusion switching method for heterogeneous network |
| CN112822725B (en) * | 2020-12-30 | 2023-03-31 | 国网甘肃省电力公司信息通信公司 | Wireless heterogeneous network multilink data distribution method based on service priority |
| CN115484645A (en) * | 2021-05-31 | 2022-12-16 | 中国移动通信集团重庆有限公司 | Method, device and equipment for determining voice fallback frequency point and computer storage medium |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101179839A (en) * | 2006-11-07 | 2008-05-14 | 华为技术有限公司 | Isomerized network switch method, system, terminal and network |
| CN101198128A (en) * | 2007-12-28 | 2008-06-11 | 中国科学院计算技术研究所 | Multi-module equipment and its service stream switching method |
-
2008
- 2008-11-17 CN CN2008102266042A patent/CN101404660B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101179839A (en) * | 2006-11-07 | 2008-05-14 | 华为技术有限公司 | Isomerized network switch method, system, terminal and network |
| CN101198128A (en) * | 2007-12-28 | 2008-06-11 | 中国科学院计算技术研究所 | Multi-module equipment and its service stream switching method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN101404660A (en) | 2009-04-08 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN101404660B (en) | Service flow distribution system and method for multi-module cooperation communication | |
| Zhang et al. | A hierarchical game framework for resource management in fog computing | |
| Zekri et al. | Context aware vertical handover decision making in heterogeneous wireless networks | |
| CN102802204B (en) | Network selection method based on user experience QoE | |
| CN105075184B (en) | For indicating load variations to the method and system of the influence of service disconnection on multilink | |
| CN111510879B (en) | Heterogeneous Internet of vehicles network selection method and system based on multi-constraint utility function | |
| CN102769551B (en) | Network quality evaluation and test and the method and system of the network optimization | |
| Piamrat et al. | QoE-aware vertical handover in wireless heterogeneous networks | |
| CN102415059A (en) | Bus control device | |
| Loganathan et al. | A novel multi-criteria channel decision in co-operative cognitive radio network using E-TOPSIS | |
| CN106413015A (en) | Network access switching method and device | |
| CN111614754A (en) | Fog-calculation-oriented cost-efficiency optimized dynamic self-adaptive task scheduling method | |
| CN109640330A (en) | Spectrum management system, blank frequency spectrum cognitive method and blank frequency spectrum distribution method | |
| CN101815317B (en) | Method and system for measuring sensor nodes and sensor network | |
| CN109982385A (en) | Network intelligence equalization methods and device based on LTE type of service feature | |
| CN107889195A (en) | A kind of self study heterogeneous wireless network access selection method of differentiated service | |
| Awathankar et al. | To mitigate with trusted channel selection using MOORA algorithm in cognitive radio network | |
| Chai et al. | Utility-based bandwidth allocation algorithm for heterogeneous wireless networks | |
| CN111083724A (en) | OCWG-TOPSIS-based user association method in fog computing network | |
| Asuquo et al. | Analytic hierarchy process for QoS evaluation of mobile data networks | |
| CN107484208A (en) | The load-balancing algorithm and system of a kind of heterogeneous network | |
| González et al. | Dynamic access control and slice allocation algorithm for diverse traffic demand over 5G heterogeneous networks | |
| Fontana et al. | SMASH: a SMArt Slicing Heterogeneous 5G network selection algorithm | |
| Vithalani et al. | Application of combined TOPSIS and AHP method for spectrum selection in cognitive radio by channel characteristic evaluation | |
| CN109495315B (en) | Metropolitan area network analysis and prediction method under big data environment and readable storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| ASS | Succession or assignment of patent right |
Owner name: HANGZHOU EWELL TECHNOLOGY CO., LTD. Free format text: FORMER OWNER: INSTITUTE OF COMPUTING TECHNOLOGY, CHINESE ACADEMY OF SCIENCES Effective date: 20140114 |
|
| C41 | Transfer of patent application or patent right or utility model | ||
| COR | Change of bibliographic data |
Free format text: CORRECT: ADDRESS; FROM: 100190 HAIDIAN, BEIJING TO: 310053 HANGZHOU, ZHEJIANG PROVINCE |
|
| TR01 | Transfer of patent right |
Effective date of registration: 20140114 Address after: Hangzhou City, Zhejiang province 310053 Binjiang District Dongxin Road No. 66 East communication city D, 2 floor Patentee after: Hangzhou Medical Technology Co., Ltd. Address before: 100190 Haidian District, Zhongguancun Academy of Sciences, South Road, No. 6, No. Patentee before: Institute of Computing Technology, Chinese Academy of Sciences |
|
| C56 | Change in the name or address of the patentee | ||
| CP01 | Change in the name or title of a patent holder |
Address after: Hangzhou City, Zhejiang province 310053 Binjiang District Dongxin Road No. 66 East communication city D, 2 floor Patentee after: Medical Technology Co., Ltd. Address before: Hangzhou City, Zhejiang province 310053 Binjiang District Dongxin Road No. 66 East communication city D, 2 floor Patentee before: Hangzhou Medical Technology Co., Ltd. |
|
| PE01 | Entry into force of the registration of the contract for pledge of patent right |
Denomination of invention: Service flow distribution system and method for multi-module cooperation communication Effective date of registration: 20160218 Granted publication date: 20110907 Pledgee: Bank of Hangzhou Limited by Share Ltd science and Technology Branch Pledgor: Medical Technology Co., Ltd. Registration number: 2016330000007 |
|
| PLDC | Enforcement, change and cancellation of contracts on pledge of patent right or utility model |