CN105682176B - Node activations method based on dealing model and bilevel optimization - Google Patents
Node activations method based on dealing model and bilevel optimization Download PDFInfo
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- H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
- H04W40/22—Communication route or path selection, e.g. power-based or shortest path routing using selective relaying for reaching a BTS [Base Transceiver Station] or an access point
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Abstract
The invention discloses the node activations methods based on dealing model and bilevel optimization, this method sets the communication scenes of wireless general Multi net voting at ambient, multiple terminals first, there are the very high node s of business demand rate, the neighbouring dormant network cell sets of node s are as follows: Γ={ k in congested network cell A1,k2,…,km, corresponding access point set is D={ d1,d2,…,dm, wherein m represents dormant network number of cells, kiThe corresponding relay node of ∈ Γ integrates as Ri={ ri1,ri2,…,rin}.The characteristics of ubiquitous environment Ubiquitous Network of this method combining wireless, ubiquitous terminal, constructs the dealing model between business demand node and relay node according to wireless communications environment, realizes the purpose of excitation relay node cooperation forwarding；On the basis of motivating relay node, the target that business demand node meets with minimum incentive price its service rate requirement is reached by bi-level optimization model.
Description
Technical field
The present invention relates to the wireless general node activations methods based on dealing model and bilevel optimization at ambient, belong to more matchmakers
Body communication technical field.
Background technique
With the continuous development of wireless communication technology, for coverage area, number of users, type of service and service quality
(QoS) different requirements, have been researched and developed at present including various cellular communications networks, WLAN (WLAN), wireless personal area
Various wireless communication network including net (WPAN) and satellite communication network, and more new wireless networks are also continuing to bring out.
These networks are supplemented each other using different network technologies, are existed jointly, and ubiquitous Multi net voting multi-service is constituted
The wireless ubiquitous environment of fusion.However, causing to gather around due to the unbalanced characteristic of wireless general network flow each at ambient and load
The very high user node of business demand rate can not obtain the network service of this cell in plug network cell, can be by nearby
User node business demand rate is balanced by service distributing and polymerization technique into ambient idle network cell after node.So
And the terminal node in isomorphism or heterogeneous network can show different degrees of forwarding wish in cooperation forwarding message process,
Especially when the resources such as the caching of terminal node, the energy content of battery, bandwidth are limited, such as node is refused to save limited resource
Receive and forward the data of other nodes absolutely, this is the main source of Node selfishness.This selfishness behavior will substantially reduce net
The routing performance of network, still, if a large amount of message forwarding task is added to a certain part of nodes without doing some volumes to it
Outer compensation, these nodes will be exitted network due to depleted of energy.Node activations mechanism based on ideal money can be with " branch
Pay-compensation " mode motivate node cooperation forward behavior, however, the mechanism often merely in the form of ideal money compensate
The resource of relay node consumption, does not establish careful reasonable trading rules, in addition, the excitation center of gravity of the mechanism is simply placed at
On relay node, without doing more researchs in the incentive cost for saving business demand node.With wireless ubiquitous environment
Become increasingly popular, for promote internode collaboration forwarding mechanism research more and more attention has been paid to.
Now, the research under wireless ubiquitous environment for node activations mechanism and algorithm is broadly divided into three directions: being based on
Prestige is based on ideal money (including auction mechanism), the motivational techniques based on game theory.And the mechanism conduct based on ideal money
The research direction of node cooperation is motivated, it is rationally effective that Major Difficulties are how to utilize on the basis of node is respectively bid
Mathematical model determines that the final conclusion of the business between node is fixed a price, while how user node selects optimal set of relay nodes to carry out
Cooperation forwarding.This patent provides a kind of node activations based on dealing model and bilevel optimization for the characteristics of wireless ubiquitous environment
Method can effectively promote the cooperation forwarding of relay node.
Summary of the invention
It is a kind of based on dealing model and bilevel optimization present invention aims in view of the above shortcomings of the prior art, proposing
Node activations method, the characteristics of the ubiquitous environment Ubiquitous Network of this method combining wireless, ubiquitous terminal, according to wireless communications environment
The dealing model between business demand node and relay node is constructed, realizes the purpose of excitation relay node cooperation forwarding；Swashing
On the basis of encouraging relay node, business demand node is reached by bi-level optimization model, its business speed is met with minimum incentive price
The target that rate requires.
The technical scheme adopted by the invention to solve the technical problem is that: a kind of section based on dealing model and bilevel optimization
Point motivational techniques, this method set the communication scenes of wireless general Multi net voting at ambient, multiple terminals, congested network cell first
There are the very high node s of business demand rate, the neighbouring dormant network cell sets of node s are as follows: Γ={ k in A1,k2,…,km, it is right
The access point set answered is D={ d1,d2,…,dm, wherein m represents dormant network number of cells, kiThe corresponding relay node of ∈ Γ
Integrate as Ri={ ri1,ri2,…,rin}。
Method flow:
Step 1: using environment perception technology obtain each relay node to its correspond to dormant network cell access point letter
Channel state information obtains relay node to the letter between the link gain relay node and access point of access point
Independent additive white Gaussian noise power spectral density N at road bandwidth access points0And other relay nodes interference and initialize relay node rijTransmission power meet whereinDepending on actual conditions.
Step 2: node s is according to relay node rijBusiness forwarding rateUtilize incremental concave functionBid Ys, in
After node rijUsing the non-linear increasing function of its transmission power and transmission signal signal interference ratioBidNode
S and relay node rijThe price of both sides' node is determined according to Agreement for Sale and PurchaseOr the failure that strikes a bargain, it obtains by the relaying of all conclusions of the business
The R of node compositioniCandidate relay node set: CRi={ rih|rih reached a deal with s∩rih∈RiAnd
Corresponding price set:With business forwarding rate setNode s with
Relay node rijBetween Agreement for Sale and Purchase expression formula it is as follows:
Wherein θminAnd θmax(0 < θmin< θmax) it is two non-negative critical values, ζ is non-negative growth factor, for adjustingFunction curve shape, λ is Dynamic gene, for meeting relay node rijSignal interference ratio SIR and service quality QoS want
It asking, α and β are non-negative weight factors,It is relay node rijBusiness forwarding rate, characterize relay node rijIt is corresponding
Network cell can carry the ability of node s business demand rate,Indicate relay node rijSignal reaches access point di's
Signal interference ratio,Indicate access point diRequired minimum signal interference ratio.
Step 3: establishing CRiIn all relay nodes cost performance optimal model, obtain cost performance highest relaying section
Point ri', the above optimal model is established to the corresponding candidate relay node collection of all-network cell in Γ, obtains node s most
Excellent relay node collection: ORs={ r1',r2',…,r'mAnd corresponding price setTurn with business
Send out rate setAbove-mentioned cost performance optimal model is as follows, it may be assumed that
WhereinIndicate relay node cost performance, the i.e. ratio of business forwarding rate and the price that strikes a bargain, ri' indicate CRiIn
The highest relay node of cost performance.
Step 4: comparing ORsIn all relay nodes the sum of business forwarding rate ν and node s business demand rate
νreqIf ν < νreqThen this cooperation Fail Transaction；Otherwise following second layer optimal model is established from ORsMiddle selection business
Forwarding rate summation is greater than νreqAnd the smallest subset τ of total price*:
Wherein τ indicates ORsRandom subset, νreqIndicate the business demand rate of node s.
Step 5: by after above-mentioned bilevel optimization process, node s utilizes high-speed WiFi direct-connecting technology by own service
Demand rate is distributed to τ*In each optimal relay node, each optimal relay node is connected to phase using Multi-Homing technology
Network cell is answered, to realize that overall transmission rate meets the service rate requirement of node s.
The utility model has the advantages that
1, the present invention is the node activations method based on dealing model and bilevel optimization, according to wireless general different at ambient
Incremental concave function relationship between the bid of the radio communication channel rate and node s of network and different terminals node gives egress s
Bid, and using the non-linear increasing function based on relay node transmission power and signal interference ratio obtain relay node bid, so
The dealing model for establishing node s and relay node afterwards provides final arm's length pricing, realizes the purpose of excitation relay node cooperation.
2, the present invention reaches business demand node by bi-level optimization model on the basis of motivating relay node with minimum
Incentive price meets the target of its service rate requirement.
3, the node activations method based on dealing model and bilevel optimization that the present invention generates, this method is simple, is easy to real
It is existing, it has a good application prospect.
Detailed description of the invention
Fig. 1 is flow chart of the method for the present invention.
Fig. 2 is dynamic programming algorithm father formula and minor dependence graph.
Specific embodiment
Innovation and creation are described in further detail with reference to the accompanying drawings of the specification.
The invention proposes a kind of novel node activations method based on dealing model and bilevel optimization, this method settings
There are the Radio Access Networks such as cellular base station, Wi-Fi hotspot and WiMAX, present invention settings under wireless ubiquitous communication environment
The very high node s of business demand rate, which is within the scope of cellular base station A, in the traffic model connects base station network, near node s
Dormant network cell set are as follows: Γ={ k1,k2,…,km, corresponding access point set is D={ d1,d2,…,dm, wherein m represents sky
Not busy network cell number, kiThe corresponding relay node of ∈ Γ integrates as Ri={ ri1,ri2,…,rin}.Then node s can use
Multi-Homing technology is based on double bounce forwarding by relay node and distributes into Γ own service demand rate to each free time
Network cell access point.By node s and relay node rij(rij∈Ri, i ∈ { 1,2 ..., m }) between cooperation repeating process take out
As for two people's transactions, wherein s is buyer, rijFor the seller, r is bought in the s currency of paymentijForwarding service.In order to more efficient
Motivate relay node on ground, and both parties are traded with practical consumable currency, and the payment process of currency is by actual operation
Quotient's processing.
As buyer, node s is under the very high situation of business demand rate, and purchase is relay node rijIt provides
Business forwarding rateThat is relay node rijWith dormant network cell access point d where itiBetween channel speed.This hair
It is bright to be obtained according to wireless communications environment characteristic in access point diPlace is received from relay node rijSignal and signal interference ratio are as follows:
Formula (1)
Formula (2)
WhereinIndicate relay node rijTransmission power, x indicate relay node rijThe signal at place,Indicate signal
X is from relay node rijTo access point diLink gain,Indicate access point diThe independent additive white Gaussian noise (AWGN) at place,
Its mean value is 0, and variance is The interference for indicating all adjacent relay nodes, according to central-limit theorem, due to rij's
Adjacent relay node number is larger, thenObedience mean value is 0, variance isGaussian Profile.According to Shannon's theorems, in
After node rijTransmission power beNode rijWith access node diBetween channel width beWhen, business forwarding speed
RateAre as follows:
Formula (3)
The present invention is according to the incremental concave function relationship between relay node business forwarding rate and node s bidIt gives
The bid of egress s,A kind of concrete form it is as follows:
Formula (4)
Wherein ζ is non-negative growth factor, for adjustingFunction curve shape.
As the seller, relay node rijBid function be transmission power and transmission signal signal interference ratio non-linear increasing letter
NumberA kind of concrete form that the present invention sets the abstract function is as follows:
Formula (5)
Wherein λ is node rijDynamic gene, for meeting the signal interference ratio SIR and service quality QoS requirements, α and β of node
It is non-negative weight factor,Indicate access node diReceive rijRelaying signal bandwidth.N0Indicate access node diEnd
Channel additive Gaussian noise power spectral density.If target cell access point diRequired minimum signal interference ratio is
Indicate relay node rijSignal reach diSignal interference ratio, expression formula obtains by formula (2), then relay node rijSignal reach
diNeed to meet its signal interference ratio requirement, asThus it can acquireLower limit:
Formula (6)
If relay node rijThe maximum value of transmission power is i.e. relay node rijTransmission power meets
Node s and relay node rijIt is utilized respectively (4) and (5) formula obtains bid YsWithIfThen both sides
Node reaches conclusion of the business common recognition, price?On the basis of according to node s and relay node rijGo out price differential
Determine increasing degree:
Formula (7)
IfThen introduce two non-negative critical value θminAnd θmax(0 < θmin< θmax), if
Illustrate node s and relay node rijBid it is very close, it is specified thatThe mesh of excitation relay node is also functioned to simultaneously
's；IfIllustrate relay node rijOverbid egress s it is excessive, strike a bargain failure；IfBetween θmin
And θmaxBetween, for the sake of justice, enableIn conclusion the present invention sets node s and relay node rij's
Agreement for Sale and Purchase expression formula is as follows:
Formula (8)
To Ri={ r1,r2,…,rn, in (i=1,2 ..., m) all relay nodes with formula (8) Agreement for Sale and Purchase calculate with
The relay node of price between node s, all conclusions of the business forms RiCandidate relay node set: CRi={ rih|rih
reached a deal with s∩rih∈RiAnd corresponding price set:Turn with business
Send out rate set
The present invention sets relay node cost performanceIt is the ratio of its business forwarding rate and the price that strikes a bargain, expression formula is such as
Under:
Formula (9)
Establish CRiIn all relay nodes cost performance optimal model, obtain the highest relay node r of cost performancei', it is right
The corresponding candidate relay node collection of all-network cell establishes the above optimal model in Γ, obtains the optimal relaying section of node s
Point set: ORs={ r1',r2',…,r'mAnd corresponding price setWith business forwarding rate collection
It closesAbove-mentioned cost performance optimal model is as follows:
Formula (10)
Compare ORsIn all relay nodes the sum of business forwarding rate ν and node s business demand rate νreqIf
ν < νreqThen this cooperation Fail Transaction；Otherwise following second layer optimal model is established from ORsMiddle selection business forwarding rate
Summation is greater than νreqAnd the smallest subset τ of total price*:
Formula (11)
Wherein τ indicates ORsRandom subset, νreqIndicate the business demand rate of node s.
Subset τ * is solved according to (11) formula, that is, is directed to ORsFind a m member vectorWhereini
∈ 1,2 ..., and m } makeAndMinimum, therefore formula (11) is converted to following Zero-one integer programming
Problem, it may be assumed that
Formula (12)
xi∈{0,1}
Due toI.e. each optimal relay node only selects and does not select two kinds of selections, therefore the present invention examines first
Consider and use the method for exhaustion, all possible m member vector is listed one by one, calculates separately out the sum of the sum of price business forwarding rate,
Then more all prices for meeting node s business demand rate requirement therefrom select the corresponding m member vector of lowest price, i.e.,
Optimal solution.The algorithm shares 2mA m member vector calculates the total 2m meter of the sum of the sum of price business forwarding rate to each vector
It calculates, thus the time complexity of the algorithm is O (2m2m) namely O (m2m+1).Therefore, method of exhaustion thinking is very simple, but real
Now but it is difficult, especially when m is very big, calculation amount will be very huge.
The present invention is solved with the method for Dynamic Programming below, and key is following two ideas:
(1) ifIt is father's formula (12) optimal solution, then1≤i < m must be following minor (note
For Δi) optimal solution:
Formula (13)
xk∈{0,1}
It proves as follows, it is assumed thatIt is not the optimal solution of formula (12), and (y1,y2,…,yi) it is its optimal solution,
Obviously have:
Formula (14)
And
First inequality both sides is same to be added:
Formula (15)
Above formula explanationIt is the optimal solution of formula (12), with optimal solutionLance
Shield.(2) recursive calculation.According to the above-mentioned characteristic of optimal solution, the optimal solution of calculating formula (12) can be by calculating its minor Δm-1
It obtains, equally, calculates Δm-1Optimal solution can be by calculating Δm-2Formula obtains, and is finally attributed to calculating Δ1Formula.Obtaining Δ1Formula
After optimal solution, gradually recurrence, finally obtains formula (12) optimal solution.
Based on both the above idea, the dynamic programming algorithm for seeking formula (12) optimal solution is given below.
If formula (12) optimal value is Pr (m, νreq), expression node s business demand rate is νreq, selectable optimal relaying
Node is r1', r2' ..., rm' m when lowest price.If only considering node r'mTactful xm(0 or 1), then be converted into and only relate to
And the problem of preceding m-1 node:
If 1) xm=0, then problem is converted into " from { r1',r2',…,r'm-1In selection a subset meet node s's
Business demand rate νreq, while node s price is minimum."
If 2) xm=1, then problem is converted into " from { r1',r2',…,r'm-1In selection a subset meet the industry of node s
Business demand rateNode s price is minimum simultaneously."
Pr (m, ν can be obtained by the above analytic processreq) recursion it is as follows:
Formula (16)
Wherein
Formula (17)
Formula (18)
The dependence of father's formula and minor according to Fig.2, the calculating of father's formula need to use minor in different business demand
A variety of possible calculated results under rate, therefore the present invention is by node s business demand rate νreqIt is equally divided into as unit of pSection, enables j=hp (h=1,2 ..., q).Generally, the stepping type of Pr (i, j) is as follows:
Formula (19)
The Pr (i, j) in above-mentioned calculating process is saved with two-dimensional array, then, the minimum price found out according to above-mentioned algorithm
Table itself contains the information of former Optimum Solution,Compare Pr (m-1, ν according to formula (16)req) andSize obtain,After determination,It is obtained according to formula (17) or formula (18),By formula (19)
It obtains, finally obtains total optimization solution
The present invention illustrates the solution procedure of dynamic programming algorithm with a simple examples below, wherein m=6, νreq=
10Mbps, p=1Mbps so q=10.Table 1 is node data table:
1 node data table of table
It is as follows that by dynamic programming algorithm Pr (i, j) bivariate table is calculated in the present invention:
Table 2 Pr (i, j) bivariate table
According to table 2, which is Pr (6,10)=13, and optimal solution is included in path P r (6,10) → Pr (5,5)
In → Pr (4,5) → Pr (3,1), i.e., ifThen xi=1, otherwise xi=0.Therefore, should
Example optimal solution is (0,0,1,1,0,1).
Dynamic programming algorithm can be analyzed by upper example and calculate Pr (i, j) bivariate table needs to calculate the time for O (mq), i.e. according to Pr (i, j) bivariate table show that optimal solution needs to calculate time O (m), therefore algorithm overall time complexity will determine for the choice of the method for exhaustion and dynamic programming algorithm according to the size of m, enableIt solvesTherefore, whenWhen, it is high-efficient using dynamic programming algorithm, on the contrary selection exhaustion
Method.
The present invention is the specific flow chart of node activations method based on dealing model and bilevel optimization as shown in Figure 1, reality
It is existing that steps are as follows:
Step 1: using environment perception technology obtain each relay node to its correspond to dormant network cell access point letter
Channel state information obtains relay node to the letter between the link gain relay node and access point of access point
Independent additive white Gaussian noise power spectral density N at road bandwidth access points0And other relay nodes interference and initialize relay node rijTransmission power meet whereinDepending on actual conditions.
Step 2: node s with relay node is utilized respectively formula (4), formula (5) obtains the Y that respectively bidssWith and then according to
Formula (8) determines the price of both sides' node or the failure that strikes a bargain, and obtains the R being made of the relay node of all conclusions of the businessiCandidate relay
Node set: CRi={ rih|rih reached a deal with s∩rih∈RiAnd corresponding price set:With business forwarding rate set:
Step 3: establishing CR according to formula (10)iIn all relay nodes cost performance optimal model, obtain cost performance most
High relay node ri', the above optimal model is established to the corresponding candidate relay node collection of all-network cell in Γ, is obtained
The optimal relay node collection of node s: ORs={ r1',r2',…,r'mAnd corresponding price setWith business forwarding rate set
Step 4: comparing ORsIn all relay nodes the sum of business forwarding rate ν and node s business demand rate
νreqIf ν < νreqThen this cooperation Fail Transaction；Otherwise according to formula (12) second layer optimal model is established and according to m
Size selection the method for exhaustion or dynamic programming algorithm solve ORsMiddle business forwarding rate summation is greater than νreqAnd the smallest son of total price
Collect τ*。
Step 5: by after above-mentioned bilevel optimization process, node s utilizes high-speed WiFi direct-connecting technology by own service
Demand rate is distributed to τ*In each optimal relay node, each optimal relay node is connected to phase using Multi-Homing technology
Network cell is answered, realizes that overall transmission rate meets the service rate requirement of node s.
It is provided for the embodiments of the invention a kind of novel node activations based on dealing model and bilevel optimization above
Method is described in detail, and for those of ordinary skill in the art, thought according to an embodiment of the present invention is being embodied
There will be changes in mode and application range, in conclusion the contents of this specification are not to be construed as limiting the invention.
Claims (3)
1. a kind of node activations method based on dealing model and bilevel optimization, which is characterized in that the method is based on wireless general
The communication scenes of Multi net voting, multiple terminals at ambient, there are the very high node s of business demand rate in congested network cell A,
Nearby dormant network cell set is Γ={ k to node s1,k2,…,km, corresponding access point set is D={ d1,d2,…,dm,
Middle m represents dormant network number of cells, idle district kiThe corresponding set of relay nodes of ∈ Γ is Ri={ ri1,ri2,…,rin,
This method comprises the following steps:
Step 1: using environment perception technology obtain each relay node to its correspond to dormant network cell access point channel shape
State information obtains relay node rij∈RiWith access point diLink gain between ∈ DAnd channel widthAccess point
The independent additive white Gaussian noise power spectral density N at place0And the interference of other relay nodesAnd initialize relaying section
Point rijTransmission powerMeetWherein transmitting power lower limit Indicate access point diRequired minimum signal interference ratio, upper limit of emission powerDepending on actual conditions；
Step 2: node s is according to relay node rijBusiness forwarding rateUtilize incremental concave functionBid Ys, relaying section
Point rijAccording to own transmission powerAccess point d is reached with self transmission signaliSignal interference ratioUtilize non-linear increasing letter
NumberBidNode s and relay node rijThe price of both sides' node is determined according to Agreement for Sale and PurchaseOr it strikes a bargain
Failure, thus obtains RiThe candidate relay node set CR of the relay node composition of interior all conclusions of the businessi={ rih|rih reached
a deal with s∩rih∈Ri, corresponding price setCorresponding business forwarding rate collection
It closes
Step 3: establishing CRiIn all relay nodes cost performance optimal model, that is, first layer optimal model, obtain CRiIt is interior
The highest relay node r ' of cost performancei, step 2 is performed both by all-network cell in Γ and obtains corresponding candidate relay node collection
And first layer optimal model is established respectively, thus obtain the optimal relay node collection OR of node ss={ r '1,r′2,…,r′m}、
Corresponding price setWith corresponding business forwarding rate setIt is above-mentioned
First layer optimal model is expressed as follows:
WhereinIndicate relay node cost performance, i.e. business forwarding rateIt fixes a price with striking a bargainRatio, r 'iIndicate CRiIt is interior
The highest relay node of cost performance；
Step 4: comparing ORsIn all relay nodes the sum of business forwarding rate ν and node s business demand rate νreq, such as
Fruit ν < νreqThen this cooperation transmitted transaction failure, otherwise establishes second layer optimal model from ORsMiddle selection business forwarding speed
Rate summation is greater than νreqAnd the smallest optimal subset τ of total price*, above-mentioned second layer optimal model is expressed as follows:
Wherein τ indicates ORsRandom subset, νreqIndicate the business demand rate of node s；
Step 5: by after above-mentioned bilevel optimization, node s utilizes high-speed WiFi direct-connecting technology by own service demand rate
It distributes to τ*In each optimal relay node, it is small that each optimal relay node using Multi-Homing technology is connected to corresponding network
Area, to realize that overall transmission rate meets the service rate requirement of node s.
2. a kind of node activations method based on dealing model and bilevel optimization according to claim 1, which is characterized in that
The step 2 interior joint s and relay node rijBetween Agreement for Sale and Purchase expression formula, comprising:
Wherein θminAnd θmaxIt is two non-negative critical values, meets 0 < θmin< θmax, π is pi constant, ζ be non-negative regulator because
Son is used for adjustment functionCurve shape, e be natural Exponents constant, λ is Dynamic gene, for meeting relay node rij
Signal interference ratio SIR and service quality QoS requirements, α and β are non-negative weight factors.
3. the node activations method according to claim 1 based on dealing model and bilevel optimization, which is characterized in that described
Method be applied to it is wireless it is general at ambient.
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