CN108696596A - The resource provider method of Services Composition problem in cloud integrated wireless-fiber hybrid access network network - Google Patents
The resource provider method of Services Composition problem in cloud integrated wireless-fiber hybrid access network network Download PDFInfo
- Publication number
- CN108696596A CN108696596A CN201810531169.8A CN201810531169A CN108696596A CN 108696596 A CN108696596 A CN 108696596A CN 201810531169 A CN201810531169 A CN 201810531169A CN 108696596 A CN108696596 A CN 108696596A
- Authority
- CN
- China
- Prior art keywords
- service
- infrastructure
- resource
- facility
- user
- 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.)
- Granted
Links
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/56—Provisioning of proxy services
- H04L67/562—Brokering proxy services
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B10/00—Transmission systems employing electromagnetic waves other than radio-waves, e.g. infrared, visible or ultraviolet light, or employing corpuscular radiation, e.g. quantum communication
- H04B10/25—Arrangements specific to fibre transmission
- H04B10/2575—Radio-over-fibre, e.g. radio frequency signal modulated onto an optical carrier
- H04B10/25752—Optical arrangements for wireless networks
- H04B10/25753—Distribution optical network, e.g. between a base station and a plurality of remote units
- H04B10/25754—Star network topology
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/50—Network service management, e.g. ensuring proper service fulfilment according to agreements
- H04L41/5041—Network service management, e.g. ensuring proper service fulfilment according to agreements characterised by the time relationship between creation and deployment of a service
- H04L41/5051—Service on demand, e.g. definition and deployment of services in real time
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/50—Network service management, e.g. ensuring proper service fulfilment according to agreements
- H04L41/5041—Network service management, e.g. ensuring proper service fulfilment according to agreements characterised by the time relationship between creation and deployment of a service
- H04L41/5054—Automatic deployment of services triggered by the service manager, e.g. service implementation by automatic configuration of network components
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/51—Discovery or management thereof, e.g. service location protocol [SLP] or web services
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/53—Network services using third party service providers
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Physics & Mathematics (AREA)
- Electromagnetism (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses the resource provider methods of Services Composition problem in cloud integrated wireless-fiber hybrid access network network, including three phases.First stage:A variety of infrastructure services are resolved into integrated service request, collect the integrated service request of user, the marked price of each service facility publication and the basis consumption of total resources and basis service, according to market mechanism, auction theory is built by target of user's minimum cost;Second stage:The algorithm based on auction theory is designed, the resource provider case for reaching user's Least-cost and the pricing strategy of corresponding basis service are found out;Phase III:The algorithm of verification design is with the low feature of compatible incentives and time complexity.The interaction of service facility and user are formulated for auction theory by the present invention, so that user is obtained with minimum cost and are serviced, while service facility being allowed to be actively engaged in cloud service after centainly being returned, to more efficiently provide various cloud services to the user.
Description
Technical field
The invention belongs to wireless optical mixed insertion network fields, more particularly to cloud integrated wireless-fiber hybrid access network
The resource provider method of Services Composition problem in network.
Background technology
Access network is commonly called as " last one kilometer " network, is the important foundation framework that terminal user obtains network service.It is existing
Modern access network is broadly divided into cable access network and Radio Access Network two major classes.Optical access network can be provided because of it
Stablize the access bandwidth of high speed and becomes a kind of Wiring access method to have a great attraction, however the deep laying generation of optical fiber
Valence is relatively expensive and is short of flexibility.Radio Access Network can provide immanent network insertion service and it is laid with cost
Relatively low, still, the problems such as range limited and lower network bandwidth, is transmitted in network transmission interference, limits wireless access
The scalability of network.In view of Optical Access Network and the respective advantage and disadvantage of Radio Access Network, two kinds of access networks have been merged
Wireless-light broadband mixed insertion network of technology is just by extensive concern.
Typical optical-fiber wireless mixed insertion network is usually with passive optical network (PON:Passive Optical
Network) it is used as soft exchange rear end simultaneously comprising a wireless sub network as access front end, namely the optical link in PON
Terminal (OLT:Optical Line Terminal) an optical fiber line is connected to by multiple optical network units by photo-fission device
(ONU:Optical Network Unit), each ONU is simultaneously as a radio network gateway via multiple nothings in wireless sub network
Line router services one group of terminal user.Therefore, the request that terminal user is sent out by any service of acquisition must all first pass through
The wireless sub network of multi-hop reaches soft exchange rear end, finally reaches the core net where service provider.
With the application and development of various clouds, various specific services are dissolved into from the aspect of bandwidth and delay
Network internal is accessed, it will be on the distributed each network node being deployed in access network of service facility.The service that user sends out
Request does not have to go to long-range core net and directly can be obtained response in access network internal.
The service (such as online voice, video flowing, online game) of all terminal users shows complicated and diversified
Development trend designs single service type and has been difficult to meet the various demands of user, and increases hardware cost.It can essentially
By a complicated service abstraction at the integrated service formed by multiple single services, and the various combination meeting of each single service
Different integrated services is generated, the integrated service demand of various complexity can be completed with assembled arrangement by each single service, it can
It is isolated with the flexible deployment and service of realizing service, and the cost of infrastructure can be saved.
Therefore service provider is in advance in the good a certain number of service facilities of optical-fiber wireless mixed insertion network On-premise,
Then the service of oneself demand is sent to control node by terminal user, is taken the service decomposition at multiple bases by control node
Business, executes completion (as shown in Figure 1) on different service facilities respectively.And it is directed to a certain infrastructure service, network internal has more
A service facility can provide resource to complete service request for it, and suitable resource how to be selected to provide from multiple service facilities
Person can meet the needs of users but also so that user the Least-cost paid, be main problem needed to be considered.
In fact, the minimum of pursuit user's cost simply, lacks certain incentive measure, the service of may result in is set
It applies because the income for failing to obtain satisfaction is unwilling that providing resource to the user completes service request.By suitable incentive mechanism,
It allows user suitably to pay to Service Source supplier (service facility), each service facility is encouraged to provide resource for user service,
Under the premise of minimizing user charges cost, meet the service request of user.
Invention content
In order to solve the technical issues of above-mentioned background technology proposes, the present invention is intended to provide cloud integrated wireless-fiber mix
Interaction between service facility and user is formulated for an auction by the resource provider method for accessing Services Composition problem in network
Model, and then user is made to obtain service with minimum cost, while service facility can actively be led after centainly being returned
Cloud service is participated in dynamicly, to more efficiently provide various cloud services for terminal user.
In order to achieve the above technical purposes, the technical scheme is that:
The resource provider method of Services Composition problem in a kind of cloud integrated wireless-fiber hybrid access network network, including as follows
Three phases:
First stage:Each service facility publication provides time paid needed for unit resource for different infrastructure services on it
Report, that is, mark the price;When user needs certain integrated service, integrated service request is resolved into a variety of infrastructure services by control node,
The role for taking on auction intermediary simultaneously collects the integrated service request of user, the marked price of each service facility publication and total resources
And the basis consumption of basis service builds auction theory, selection according to market mechanism by target of user's minimum cost
Suitable service facility provides specific infrastructure service;
Second stage:Design the algorithm based on auction theory, find out the resource provider case for reaching user's Least-cost and
The pricing strategy of corresponding basis service;
Phase III:The algorithm based on auction theory of verification design is with the low spy of compatible incentives and time complexity
Sign.
Further, in the first phase, be located at disposed in cloud integrated wireless-fiber hybrid access network network can be eventually
End subscriber provides the set C=[ of the service facility of resource;c1,c2,…,cm], wherein ciIndicate i-th of service facility, i=1,
2 ..., m, the infrastructure service type being capable of providing are n, respectively T=[t1,t2,…,tn], wherein tjIndicate jth class basis clothes
Business, j=1,2 ..., n, each service facility are capable of providing needed for resource situation of all infrastructure services only according to its own
Cost it is different;If i-th of service facility ciFor jth kind infrastructure service tjThe quotation for providing resource is bij, enable B=
{bij}1≤i≤m,1≤j≤n;The resource that each service facility possesses simultaneously is limited, and the resource of basis service consumption is also not
With, if the total type of resource that all infrastructure services need is A kinds, define i-th of service facility ciThe total resources possessed
For REi=[Ri1,Ri2,…,RiA], 1≤i≤m, orderDefine jth kind infrastructure service t simultaneouslyjRequired consumption
Resource is rej=[rj1,rj2,…,rjA], 1≤j≤n, orderThe integrated service for defining a certain terminal user is S=
{[t1,k2t2,…,kn tn], d }, indicate that the integrated service can resolve into k1The infrastructure service t of a unit1,k2The base of a unit
Plinth services t2, until knThe infrastructure service t of a unitn, d indicates the maximum transmitted cost that this service can allow for, defines D=
[d1,d2,…,dm]Indicate that the integrated service S of terminal user obtains different service facilities and provides the transmission paid needed for resource for it
Cost, wherein diThe transmission cost paid needed for resource is provided for i-th of service facility;On this basis, service facility is set
Auction theory is built according to market mechanism for seller, terminal user buyer.
Further, in the first phase, as follows using user's minimum cost as target structure auction theory:
s.t.
Wherein, variable xijIndicate i-th of service facility ciFor jth kind infrastructure service tjX is providedijA unit resource.
Further, in second stage, the designed algorithm based on auction theory is divided into successfully bid arithmetic and most
Post-paid determines algorithm;The success bid arithmetic is determined based on greedy algorithm final competing using user's minimum cost as target
Successful bidding price is marked, that is, determines which service facility provides how many a unit resources for which kind of infrastructure service;Finally pay
Determine that algorithm is to determine the corresponding basis that the successful service facility of competitive bidding finally obtains on the basis of success bidding algorithm result
The unit income of service.
Further, in success bid arithmetic, remove those transmission costs first allows transmission cost more than user
Then marked price decomposites in all infrastructure services come from user service and the infrastructure service having the call is selected to exist at first
It is disposed in each service facility, the principle disposed to infrastructure service is that ask a price minimum service facility of selection is disposed, and
It determines the units disposed on the service facility, the surplus resources number of the service facility is changed after deployment success, if should
Service facility resource abundance then can be by the infrastructure service whole deployment success, if on the service facility on the service facility
Resource it is limited, then a part for the infrastructure service can only be disposed on the service facility, and by remaining service need
The amount of asking is deployed on other qualified service facilities, and no matter all deployment or partial deployment, are required for changing the service
The surplus yield of facility;After the infrastructure service whole successful deployment of greatest requirements, then from remaining infrastructure service, selection
The infrastructure service having the call is disposed, until all infrastructure services deployment finishes.
Further, in last payment determines algorithm, according to success bid arithmetic as a result, determining that competitive bidding successfully takes
Business facility be finally the unit price paid of specific infrastructure service be all service facilities be in infrastructure service bid the
Two at a low price.
Further, in the phase III, when the algorithm based on auction theory for verifying design has compatible incentives feature,
It is honest that the algorithm of design, which only need to be verified, and that is, marked price that the person that do not take part in auction goes out is its true valuation to the commodity.
The advantageous effect brought using above-mentioned technical proposal:
The present invention is according to the design feature for converging into wireless optical fiber mixed insertion network, it is proposed that one kind having excitation consciousness
The resource provider method for user's integrated service request, by between the service request and service facility of user terminal,
Auction theory is built based on market mechanism so that user can be with minimum cost in the case of ensureing the certain income of service facility acquisition
Obtain the resource that service facility provides.
The present invention provides resource to problem for the first time and is introduced into the wireless optical fiber mixed insertion network converged, and designs and swash
Encouraging compatible auction mechanism makes the aggressive participation resource of service facility for accessing network internal provide, while minimizing use
Family cost makes to effectively improve the quality to user service in cloud integrated access network and reduces service delay.
Description of the drawings
Fig. 1 provides resource schematic diagram to converge into wireless optical fiber mixed insertion network for user service;
Fig. 2 is the three phase flow figures of the present invention;
Fig. 3 is success bid arithmetic flow chart in the present invention;
Fig. 4 is finally to pay to determine algorithm flow chart in the present invention;
Fig. 5 is authenticity verification result figure of the present invention, is included (a), (b) two width subgraph;
Fig. 6 is resource provider case of the present invention and optimal resource provider case income and elapsed time comparison diagram, including
(a), (b) two width subgraph.
Specific implementation mode
Below with reference to attached drawing, technical scheme of the present invention is described in detail.
The present invention provides a kind of resource of Services Composition problem in converging into wireless optical fiber hybrid network based on auction
Providing method, this method are formulated for one according to market mechanism, by interaction of service provider's (service facility) between user
Auction theory, and then user is made to obtain service with minimum cost, while service provider's (service facility) being allowed to obtain centainly
Aggressive cloud service can be participated in after return, various cloud services are provided for terminal user to more efficient.
This method is divided into three implementation phases, as shown in Figure 2.First stage, that is, auction theory structure, second stage design actual base
In the execution algorithm of auction mechanism;In the phase III, the algorithm of main verification design has some basic characteristics, such as encourages phase
Hold, time complexity it is low etc..Detailed process is as follows.
First stage, it is assumed that is disposed in the wireless optical fiber mixed insertion network converged can provide for terminal user
The service facility of resource has m C=[c1,c2,…,cm], the infrastructure service type being capable of providing is n, respectively T=[t1,
t2,…,tn].Each service facility is capable of providing the cost needed for resource situation of all infrastructure services only according to its own
It is different.Assuming that i-th of service facility ciFor jth kind infrastructure service tjThe quotation for providing resource is bij, enable B=
{bij}1≤i≤m,1≤j≤n.The resource that each service facility possesses simultaneously is limited, and the resource of basis service consumption is also not
With.Assuming that the total type of resource that all infrastructure services need is A kinds.So, we define i-th of service facility ciPossess
Total resources be REi=[Ri1,Ri2,…,RiA](1≤i≤m) is enabledDefine jth kind infrastructure service simultaneously
tjThe resource of required consumption is rej=[rj1,rj2,…,rjA](1≤j≤n) is enabledThe synthesis of a certain terminal user
Service be expressed as S=;t1,k2t2,…,kn tn], d }, indicate that the integrated service is decomposed into k1The infrastructure service t of a unit1,
k2The infrastructure service t of a unit2, and so on, in addition, d indicates the maximum transmitted cost that this service can allow for, when such as transmitting
Prolong.Meanwhile using D=[d1,d2,…,dm]Indicate that the integrated service S of terminal user obtains different service facilities to provide resource institute
The transmission cost that need to be paid.
In order to build auction theory, defined variable xijIndicate i-th of service facility ciFor jth kind infrastructure service tjX is providedij
A unit resource, according to the parameter setting of front, it is known that the minimum cost that user pays is such as shown in (1):
Shown in its relevant constraint such as formula (2) (3) (4) (5):
Wherein, formula (2) indicates variable xijValue can not possibly be more than user to the demand of respective service;And formula (3)
It indicates to work as certain service facility ciTo the transmission cost d of active useriMore than the transmission cost d that the user allows, the then service facility
ciWill not be that user base services tjAny resource is provided;The number of resources for the jth kind service that all service facilities of formula (4) provide
Amount just meets demand of the user to jth kind service;And formula (5) illustrates all services that each service facility can be provided
The resource consumed is no more than the number of resources that the service facility possesses.
Second stage, above-mentioned auction theory can be reduced to more knapsack problems by relaxed constraints condition, and it is well known that more
Knapsack problem is a NP-hard problem, it follows that it is also a NP-hard problem that the resource, which provides problem, i.e., multinomial
It is difficult to find optimal solution in the formula time.In order to perform effectively auction algorithm, devises one and find approximation in polynomial time
The resource provider method based on auction mechanism of optimal solution.The resource provider method is divided into two steps, success bid arithmetic and
It finally pays and determines algorithm.
First step success bid arithmetic, removing those transmission costs first allows the marked price of transmission cost more than user, so
Afterwards, being decomposited from user service in all infrastructure services come selects the infrastructure service having the call to be set at first in each service
Middle deployment is applied, the principle disposed to infrastructure service is that the minimum service facility of selection charge is disposed, and is determined at this
The units disposed on service facility will change the surplus resources number of the service facility after deployment success, if the service facility
Resource abundance then can be by the infrastructure service whole deployment success, if the resource on the service facility has on the service facility
Limit, then can only dispose the infrastructure service part on the service facility, and remaining demand for services amount is deployed to
On other eligible service facilities, no matter all deployment or partial deployment, we are required for changing the surplus of the service facility
Remaining stock number;After the infrastructure service whole successful deployment of the greatest requirements, then from remaining infrastructure service, demand is selected
Maximum infrastructure service is disposed, and so on, detail is shown in Fig. 3, therefore the algorithm is a greedy algorithm.
Second step, which is finally paid, determines algorithm, is provided to encourage each service facility to participate in resource, close based on the second price
Envelope auction (being called Wei Kerui auctions) strategy devises a true auction mechanism.I.e. competing buyer is only equally in the form of sealing
Vertical bid, commodity are also sold to highest tender person.But victor's payment is second high in all tender prices
Valence, so it is referred to as the auction of the second price sealed.If executing this program, the optimal strategy of each bidder is exactly to make mark
Valence is equal to true valuation of the himself to this part commodity, in other words, honest at this time to be only best auction strategy.In the algorithm
In, according to success bid arithmetic as a result, it is that specific infrastructure service is paid to determine the final successful service facility of competitive bidding finally
Unit price be all service facilities be in infrastructure service bid second at a low price (i.e. time low price).Specific algorithm details
See Fig. 4.
Phase III needs to prove that this method has the characteristics that compatible incentives (or honest), Algorithms T-cbmplexity are low.It is first
First, compatible incentives are the important features of auction algorithm, and this feature encourages seller's (i.e. each service facility) to play an active part in auction machine
In system, and the optimal strategy based on each bidder of the second price sealed auction (being called Wei Kerui auctions) strategy is exactly to make mark
Valence is equal to true valuation of the himself to this part commodity.Therefore, it was demonstrated that compatible incentives feature, only need to prove algorithm be it is honest,
The marked price that the person that i.e. do not take part in auction goes out is its true valuation to the commodity.
Assuming that certain service facility ciFor certain infrastructure service tjCompetitive bidding is marked the price as bij, separately define vijFor service facility ciNeedle
To infrastructure service tjTrue valuation.Assuming that service facility ciFor certain infrastructure service tjCompetitive bidding success, and final transaction value is
pij, then service facility ciFrom infrastructure service tjThe income u of upper acquisitionij=xij(pij-vij) income.First, it is assumed that bij=
vij, according to algorithm bid successfully marked price bijIt is that all service facilities are directed to infrastructure service tjThe lowest price gone out, and pij
It is time low price in Any and All Bid, then, uij> 0.If marking the price bij< vij< pij, then, service facility ciWith the b that marks the priceijGinseng
With competitive bidding also can competitive bidding success, and profit with true valuation vijCompetitive bidding has no difference as obtained income of marking the price;
If bij> pij> vij, then service facility ciWith the b that marks the priceijCompetitive bidding fails, income 0, because of marked price b at this timeijNo longer it is most
At a low price.Experimental result is with reference to (a) figure in figure 5.If service facility ciFor certain infrastructure service tjMark the price bij=vijIt bids mistake
It loses, then uij=0, and another service facilityWith marked priceCompetitive bidding success, at this timeService facility ciNeedle
To infrastructure service tjDirectly with a new marked priceCompetitive bidding is participated in, then service facility ciSubstitutionCompetitive bidding success, this
When low bid be bijAnd secondary low bid isIncome is obtained at this timeIncome uij< 0 loses.Service
Facility ciFor infrastructure service tjDirectly with marked priceIt participates in competitive bidding and still competes failure, income 0, experimental result reference
(b) in Fig. 5.Therefore, the desired principle for obtaining maximum return of certain service facility is to maintain honesty, i.e. its marked price sent out is
Its true valuation to commodity, if dishonest very likely competition failure, without income;Competing successfully its income not
It can exceed that the income of acquisition when honest bid, or even loss.Fig. 5 gives us for algorithm authenticity (compatible incentives
Feature) verification experimental result, this group experiment in, be arranged converge WOBAN access network in, the number of service facility is
3 (m=3), can provide 8 kinds of infrastructure services (n=8), and the sum of all resource categories are 3 (A=3).(a) in Fig. 5 provides certain
Service facility is with true valuation (vij=0.369) in the case that competitive bidding can succeed competitive bidding, maximum return u can be obtainedij=0.528,
The income trend that the modification marked price service facility obtains;(b) in Fig. 5 provides certain service facility with true valuation (vij=
0.635) competitive bidding can competitive bidding failure in the case of, income 0, modification mark the price the service facility obtain income trend, work as marked price
When less than 0.36, i.e., success competitive bidding when marked price is less than the minimum marked price that all service facilities provide, but last traded price at this time
Lattice are 0.419, so, ultimate yield is negative, loss.
It about the time complexity of algorithm, is modeled according to problem, even if it is also that a NP-hard is asked that this problem, which simplifies,
Topic, it is impossible to optimal solution is obtained in polynomial time, therefore, the algorithm of design is a near-optimization algorithm, allows it more
Approximate optimal solution is found in the item formula time.Pass through the successful bid arithmetic (abbreviation algorithm 1) of Fig. 3, it is known that the algorithm is to n kinds basis
Service is handled one by one from big to small according to volume of services, and is directed to each infrastructure service, and needs to select one from m service facility
A service facility provides service for it, also to change its all kinds of resources left quantity one by one after determining service facility, therefore calculate
The time complexity of method 1 is O (nmA), and the last payment of Fig. 4 determines algorithm (abbreviation algorithm 2), it is necessary first to according to success portion
Affix one's name to matrix Xm*n, corresponding concluded price is determined for each element in matrix, so needing to find from m service facility secondary
At a low price, it is finally still modification surplus yield, therefore the time complexity of algorithm 2 is O (m2nA).The time of algorithm 1 and algorithm 2
Complexity is all to be completed in polynomial time, therefore the resource provider method of the present invention can also be completed in polynomial time, right
Answer experimental result Fig. 6.In order to illustrate the time complexity of algorithm, one group of experiment is devised herein, m=80, n in group experiment
=10, A=3 ask the number of users of service to be incremented to 80 from 10.Fig. 6 give the present invention resource provider case with it is optimal
(a) and (b) of the resource provider method in comparison of both service facility total revenue and time loss, difference corresponding diagram 6, from
(a) in Fig. 6 it is found that the total revenue that the method for the present invention obtains is slightly below optimal case, but by (b) in Fig. 6 it is found that
The present invention program runs the time loss that institute elapsed time is far below optimal case, and jump is brighter when number of users is more
It is aobvious.
Above example is merely illustrative of the invention's technical idea, and protection scope of the present invention cannot be limited with this, every
According to technological thought proposed by the present invention, any change done on the basis of technical solution each falls within the scope of the present invention
Within.
Claims (7)
1. the resource provider method of Services Composition problem in a kind of cloud integrated wireless-fiber hybrid access network network, which is characterized in that
Including the following three stage:
First stage:Each service facility publication provides the return paid needed for unit resource for different infrastructure services on it,
Mark the price;When user needs certain integrated service, integrated service request is resolved into a variety of infrastructure services by control node, simultaneously
Take on auction intermediary role, collect user integrated service request, each service facility publication marked price and total resources and
The basis consumption of basis service builds auction theory, selection is suitable according to market mechanism by target of user's minimum cost
Service facility specific infrastructure service is provided;
Second stage:The algorithm based on auction theory is designed, the resource provider case for reaching user's Least-cost and corresponding is found out
Basis service pricing strategy;
Phase III:The algorithm based on auction theory of verification design is with the low feature of compatible incentives and time complexity.
2. according to claim 1 in cloud integrated wireless-fiber hybrid access network network Services Composition problem resource provider
Method, which is characterized in that in the first phase, it can be terminal to be located at disposed in cloud integrated wireless-fiber hybrid access network network
User provides the set C=[ of the service facility of resource;c1,c2,…,cm], wherein ciIndicate i-th of service facility, i=1,
2 ..., m, the infrastructure service type being capable of providing are n, respectively T=[t1,t2,…,tn], wherein tjIndicate jth class basis clothes
Business, j=1,2 ..., n, each service facility are capable of providing needed for resource situation of all infrastructure services only according to its own
Cost it is different;If i-th of service facility ciFor jth kind infrastructure service tjThe quotation for providing resource is bij, enable B=
{bij}1≤i≤m,1≤j≤n;The resource that each service facility possesses simultaneously is limited, and the resource of basis service consumption is also not
With, if the total type of resource that all infrastructure services need is A kinds, define i-th of service facility ciThe total resources possessed
For REi=[Ri1,Ri2,…,RiA], 1≤i≤m, orderDefine jth kind infrastructure service t simultaneouslyjRequired consumption
Resource is rej=[rj1,rj2,…,rjA], 1≤j≤n, orderThe integrated service for defining a certain terminal user is S=
{[t1,k2t2,…,kntn], d }, indicate that the integrated service can resolve into k1The infrastructure service t of a unit1,k2The base of a unit
Plinth services t2, until knThe infrastructure service t of a unitn, d indicates the maximum transmitted cost that this service can allow for, defines D=
[d1,d2,…,dm]Indicate that the integrated service S of terminal user obtains different service facilities and provides the transmission paid needed for resource for it
Cost, wherein diThe transmission cost paid needed for resource is provided for i-th of service facility;On this basis, service facility is set
Auction theory is built according to market mechanism for seller, terminal user buyer.
3. according to claim 2 in cloud integrated wireless-fiber hybrid access network network Services Composition problem resource provider
Method, which is characterized in that in the first phase, it is as follows to build auction theory using user's minimum cost as target:
s.t.
Wherein, variable xijIndicate i-th of service facility ciFor jth kind infrastructure service tjX is providedijA unit resource.
4. according to Services Composition problem in any one of the claim 1-3 cloud integrated wireless-fiber hybrid access network networks
Resource provider method, which is characterized in that in second stage, the designed algorithm based on auction theory is divided into successfully competitive bidding
Algorithm and last payment determine algorithm;The success bid arithmetic is that it is true to be based on greedy algorithm using user's minimum cost as target
The fixed final successful bidding price of competitive bidding determines which service facility provides how many a unit resources for which kind of infrastructure service;
It finally pays and determines that algorithm is to determine what the successful service facility of competitive bidding finally obtained on the basis of success bidding algorithm result
The unit income of corresponding infrastructure service.
5. according to claim 4 in cloud integrated wireless-fiber hybrid access network network Services Composition problem resource provider
Method, which is characterized in that in success bid arithmetic, removing those transmission costs first allows the mark of transmission cost more than user
Then valence decomposites in all infrastructure services come from user service and selects the infrastructure service having the call at first each
It is disposed in service facility, the principle disposed to infrastructure service is that ask a price minimum service facility of selection is disposed, and really
It is scheduled on the units disposed on the service facility, the surplus resources number of the service facility is changed after deployment success, if the clothes
Facility resource abundance of being engaged in then can be by the infrastructure service whole deployment success, if on the service facility on the service facility
Resource is limited, then can only dispose a part for the infrastructure service on the service facility, and by remaining demand for services
No matter all amount is deployed on other qualified service facilities, deployment or partial deployment, is required for changing the service and is set
The surplus yield applied;After the infrastructure service whole successful deployment of greatest requirements, then from remaining infrastructure service, selection needs
The maximum infrastructure service of the amount of asking is disposed, until all infrastructure services deployment finishes.
6. according to claim 4 in cloud integrated wireless-fiber hybrid access network network Services Composition problem resource provider
Method, which is characterized in that in last payment determines algorithm, according to success bid arithmetic as a result, determining that competitive bidding successfully services
Facility be finally the unit price paid of specific infrastructure service be all service facilities be in infrastructure service bid second
At a low price.
7. according to claim 1 in cloud integrated wireless-fiber hybrid access network network Services Composition problem resource provider
Method, which is characterized in that in the phase III, when the algorithm based on auction theory for verifying design has compatible incentives feature, only
It is honest that the algorithm of design, which need to be verified, and that is, marked price that the person that do not take part in auction goes out is its true valuation to the commodity.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810531169.8A CN108696596B (en) | 2018-05-29 | 2018-05-29 | Resource providing method for service combination problem in cloud integrated wireless-optical fiber hybrid access network |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810531169.8A CN108696596B (en) | 2018-05-29 | 2018-05-29 | Resource providing method for service combination problem in cloud integrated wireless-optical fiber hybrid access network |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108696596A true CN108696596A (en) | 2018-10-23 |
| CN108696596B CN108696596B (en) | 2021-03-02 |
Family
ID=63848074
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810531169.8A Active CN108696596B (en) | 2018-05-29 | 2018-05-29 | Resource providing method for service combination problem in cloud integrated wireless-optical fiber hybrid access network |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108696596B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116485477A (en) * | 2023-06-19 | 2023-07-25 | 北京大学 | Advertisement valuation processing method and device and electronic equipment |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050197877A1 (en) * | 2004-03-08 | 2005-09-08 | Ken Kalinoski | System and method for scheduling heterogeneous resources |
| CN101170549A (en) * | 2007-06-15 | 2008-04-30 | 西安电子科技大学 | CBP packet frame structure and auction resource distribution method based on IEEE802.22 protocol |
| CN101969475A (en) * | 2010-11-15 | 2011-02-09 | 张军 | Business data controllable distribution and fusion application system based on cloud computing |
| CN102143087A (en) * | 2011-04-29 | 2011-08-03 | 北京交通大学 | Resource-oriented service composition selection method |
| CN103533037A (en) * | 2013-09-29 | 2014-01-22 | 浙江工商大学 | Resource scheduling method in forwarding and control separation network based on economic model |
| CN106357796A (en) * | 2016-10-12 | 2017-01-25 | 四川用联信息技术有限公司 | Optimal service allocation algorithm for mobile applications under mobile cloud computing |
| CN106612323A (en) * | 2016-08-08 | 2017-05-03 | 四川用联信息技术有限公司 | Service resource integration optimization algorithm in cloud manufacturing |
| CN107332913A (en) * | 2017-07-04 | 2017-11-07 | 电子科技大学 | A kind of Optimization deployment method of service function chain in 5G mobile networks |
-
2018
- 2018-05-29 CN CN201810531169.8A patent/CN108696596B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050197877A1 (en) * | 2004-03-08 | 2005-09-08 | Ken Kalinoski | System and method for scheduling heterogeneous resources |
| CN101170549A (en) * | 2007-06-15 | 2008-04-30 | 西安电子科技大学 | CBP packet frame structure and auction resource distribution method based on IEEE802.22 protocol |
| CN101969475A (en) * | 2010-11-15 | 2011-02-09 | 张军 | Business data controllable distribution and fusion application system based on cloud computing |
| CN102143087A (en) * | 2011-04-29 | 2011-08-03 | 北京交通大学 | Resource-oriented service composition selection method |
| CN103533037A (en) * | 2013-09-29 | 2014-01-22 | 浙江工商大学 | Resource scheduling method in forwarding and control separation network based on economic model |
| CN106612323A (en) * | 2016-08-08 | 2017-05-03 | 四川用联信息技术有限公司 | Service resource integration optimization algorithm in cloud manufacturing |
| CN106357796A (en) * | 2016-10-12 | 2017-01-25 | 四川用联信息技术有限公司 | Optimal service allocation algorithm for mobile applications under mobile cloud computing |
| CN107332913A (en) * | 2017-07-04 | 2017-11-07 | 电子科技大学 | A kind of Optimization deployment method of service function chain in 5G mobile networks |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116485477A (en) * | 2023-06-19 | 2023-07-25 | 北京大学 | Advertisement valuation processing method and device and electronic equipment |
| CN116485477B (en) * | 2023-06-19 | 2023-11-10 | 北京大学 | Advertisement valuation processing method and device and electronic equipment |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108696596B (en) | 2021-03-02 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Johari | Efficiency loss in market mechanisms for resource allocation | |
| US20110238494A1 (en) | Auction system for maximizing advertising efficiency by exposing advertisements through internet media and method of operating the same | |
| CN101841539A (en) | Method, device and system for grid resource allocation based on trust | |
| Ni et al. | Spectrum Allocation Based on Game Theory in Cognitive Radio Networks. | |
| Dramitinos et al. | An auction mechanism for allocating the bandwidth of networks to their users | |
| Singh | Information technology as an engine of broad-based growth in India | |
| Li et al. | Pricing in combinatorial double auction-based grid allocation model | |
| Liu et al. | Reverse auction based incentive mechanism for location-aware sensing in mobile crowd sensing | |
| Hosseinalipour et al. | Options-based sequential auctions for dynamic cloud resource allocation | |
| Qiu et al. | Auction method to prevent bid-rigging strategies in mobile blockchain edge computing resource allocation | |
| Yue et al. | A double auction-based approach for multi-user resource allocation in mobile edge computing | |
| Li et al. | Double Auction‐Based Two‐Level Resource Allocation Mechanism for Computation Offloading in Mobile Blockchain Application | |
| CN108696596A (en) | The resource provider method of Services Composition problem in cloud integrated wireless-fiber hybrid access network network | |
| Chen et al. | Bayesian mechanism design for blockchain transaction fee allocation | |
| CN111401943A (en) | Multi-source advertisement bidding system and method | |
| Parkes | Computational mechanism design | |
| Wu et al. | Impression allocation and policy search in display advertising | |
| Zheng et al. | AEGIS: an unknown combinatorial auction mechanism framework for heterogeneous spectrum redistribution in noncooperative wireless networks | |
| Beltrán et al. | Multiple equilibria in symmetric strategies for simultaneous auctions in next-generation bandwidth markets | |
| Lepler et al. | Resource pricing under a market-based reservation protocol | |
| Chu et al. | Spectrum trading in cognitive radio network: An agent-based model under demand uncertainty | |
| Beltran et al. | Achieving an efficient equilibrium when simultaneously bidding on multiple, divisible-item auctions | |
| Bessler et al. | A network provisioning scheme based on decentralized bandwidth auctions | |
| Zhang | Optimal Mechanism Design with Aftermarket Interactions | |
| Calzolari et al. | Regulating a multi-utility firm |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |