CN102186208A - Terminal system difference based heterogeneous network load distribution method - Google Patents
Terminal system difference based heterogeneous network load distribution method Download PDFInfo
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Abstract
The invention discloses a heterogeneous network load distribution algorithm based on an evolutionary game theory and in consideration of terminal differences. A subscriber strategy is adjusted dynamically according to the idea of the evolutionary game theory; the acquisition of improved utility serves as an evolutionary force for the strategy adjustment; and the difference between terminal systems and various limits to subscriber switching between heterogeneous networks due to the difference are taken into consideration while the subscriber strategy is adjusted. Terminal subscribers of the heterogeneous network and a network provider form subjects of a game, wherein the subscribers expect to get higher service quality and pay lower cost, and the provider expects to provide service for more subscribers and consume less network resources. The difference between terminals is sufficiently taken into consideration in heterogeneous network load balancing algorithm based on the evolutionary game theory in the invention, so that the algorithm is more practical.
Description
Technical field
The present invention relates to the RRM field of wireless network, relate in particular to the load-balancing method in the heterogeneous wireless network.
Background technology
The great demand of radio multimedium data service and wireless access the Internet has promoted developing rapidly of wireless communication technology, and different wireless communication technologys will provide various service for the user.This indicating following wireless communication system will merge multiple different Radio Access Network (Radio Access Network, RAN), for example radio honeycomb communication system, IEEE802.16/20 and short haul connection WLAN, satellite communication network etc.Under the framework of multiple heterogeneous network, the user can select the specific different business of RAN carrying according to certain standard or individual's preference, as the residing environment of user, the load state of current RAN, the active user position is under the covering of which RAN, and QoS requirement and network tolling etc. all will influence the user and select which kind of network and distribution service how.The balanced a kind of optimal control technology that under this background, proposes exactly of the combined loading of heterogeneous wireless network at the heterogeneous network resource, effectively implementing of this mechanism helps improve the entire system utilization ratio of wireless resources, dynamically adjust offered load, increase the network in general capacity.
A kind of existing load-balancing algorithm application scenarios is that under the situation that the UMTS network can be used, user priority is selected the UMTS network under the situation of UMTS and GSM coexistence, and the GSM network is option in support.The user selects the GSM network when UMTS is unavailable.Also considered simultaneously the difference of terminal, i.e. the backward compatible GSM standard of the terminal of UMTS standard, but the terminal of GSM standard can not upward-compatible UMTS standard.During load balancing under this scene, the terminal of UMTS standard can shift to adjacent UMTS sub-district and GSM sub-district, but the terminal of GSM standard can only shift to adjacent GSM sub-district, can not shift to adjacent UMTS sub-district.The advantage of this algorithm is simple, feasible, and the influence when having considered that the terminal standard is switched in the sub-district.Weak point is to be, can not satisfy in the heterogeneous network, and diversified type service, requiring of speed and QoS is different, only applies mechanically the diversified demand that this method is not enough to tackle following user under the environment of heterogeneous network.
The method of evolutionary game theory of utilizing another kind of existing algorithm realizes the server selection in the distributed computer network, and this algorithm has provided an effective evolution explicit model.On this basis, evolutionary game theory can be incorporated in the problem of load balancing of heterogeneous network, the heterogeneous-network service assignment problem is summed up as an Evolutionary Game process, utilize the self study mechanism dynamic evolution of Evolutionary Game to realize the target of professional reasonable distribution.The application scenarios of this algorithm is, the zone at user place is the zone under the overlapping covering of three kinds of heterogeneous networks (for example cellular network, WLAN, WiMAX), the user produces at random, user's terminal is supported three kinds of different network formats, and any one user can freely be switched under three kinds of networks.The advantage of algorithm is, can adjust the distribution that the parameter that influences load balancing is optimized the business load of heterogeneous network flexibly, and shortcoming is that model is too desirable, and the standard of terminal need support simultaneously that the heterogeneous network more than three kinds or three kinds is to be difficult for realizing.
Summary of the invention
At the shortcoming of above-mentioned prior art, the present invention proposes a kind ofly to take into account the heterogeneous network load sharing algorithm of terminal otherness simultaneously based on evolutionary game theory, and this method has realized the load balancing of heterogeneous network from the angle of practicality based on evolutionary game theory.
A kind of heterogeneous network load sharing algorithm based on terminal standard difference may further comprise the steps:
The first step: the line module initialization takes into full account the terminal otherness during initialization.Definition user number UE_num produces UE_num user at random.Define network formats N1, N2, N3 that three kinds of user terminals are supported, network 1 is supported N1, and network 2 is supported N2, and network 3 is supported N3.And network 1, network 2, network 3 cover mutually.Definition user's terminal type, A, B, C, D.Category-A type terminal is supported N1 and N2; Category-B type terminal is supported N2 and N3; The C type terminals is supported N1 and N3; The D type terminals is supported N1, N2 and N3.For avoiding extreme case, the quantity that defines four types of A, B, C, D is more or less the same.Provide distribution X=(x at random simultaneously
1, x
2, x
3) initial value.x
iFor the user's number in the Ni network accounts for the percentage of total user's number, x
1+ x
2+ x
3=1, the terminal type that comprises in the N1 network is A, C, D, and the terminal type that comprises in the N2 network is A, B, D, and the terminal type that comprises in the N3 network is B, C, D.
Second step: the network parameter initialization, by relatively determining the network parameter initial value between heterogeneous network in twos, determine utility matrix U0.Cycle-index is set.The value of U0 is promptly represented three kinds of network states and resource situation.Initialization evolution matrix G.
The 3rd step: the beginning that circulates, fixedly utility matrix scrambling, whether the detection module detection of evolution should evolve and adjust the item of evolving automatically.Calculate N1, N2, the fitness under each comfortable current network parameter configuration of N3 network, and average fitness.Owing to considered the otherness of terminal and used the thought of evolutionary game theory, here need to compare respectively N1, N2, the size of the fitness of N3 and average fitness, so that to the big network of fitness, promptly select the individuality of fitness maximum to replace minimum individuality from the little network transitions of fitness.Result relatively is divided into six kinds of situations.If the fitness of N1 network is f1, the fitness of N2 network is f2, and the fitness of N3 network is f3, and the Pingdu fitness is f_mean.Then six kinds of comparative results are respectively
f1＜f_mean，f2＞f_mean，f3＞f_mean；
f1＜f_mean，f2＞f_mean，f3＜f_mean；
f1＜f_mean，f2＜f_mean，f3＞f_mean；
f1＞f_mean，f2＜f_mean，f3＞f_mean；
f1＞f_mean，f2＜f_mean，f3＜f_mean；
f1＞f_mean，f2＞f_mean，f3＜f_mean；
The 4th step: the evolution thought in the utilization evolutionary game theory, evolve according to duplicating kinetic equation, calculate at first respectively
Judge that respectively whether stop condition satisfies, if do not satisfy stop condition (
Level off to 0), then the rate of increase in the dynamics of evolution equation is converted into concrete user's number,, determines that each network changes over to or produces according to the sign symbol of rate of increase, dynamically adjust the number of users of each network, thus the number of times upper limit of circulation in providing.
The 5th step: stability and precision judge that the judgement of stability can be judged by Liapunov (A.M.Lyapunov) stability of a system theorem.The precision decision condition is by the stop condition decision in the 4th step.Obtain equiblibrium mass distribution and the average value of utility of user in three networks.If do not satisfy, reenter the loop body in the 3rd step.
Description of drawings
Fig. 1 is a kind of heterogeneous network load sharing algorithm flow chart based on terminal standard difference of the present invention;
Fig. 2 is the flow chart of evolution module 1 of the present invention;
Fig. 3 is the flow chart of evolution module 2 of the present invention;
Fig. 4 is the flow chart of evolution module 3 of the present invention;
Fig. 5 is the flow chart of evolution module 4 of the present invention;
Fig. 6 is the flow chart of evolution module 5 of the present invention;
Fig. 7 is the flow chart of evolution module 6 of the present invention;
Embodiment
Below in conjunction with accompanying drawing and instantiation the present invention is described in further details.
Fig. 1 example illustrates the load-balancing method flow chart of multistage cooperation in the heterogeneous wireless network of the present invention, may further comprise the steps:
In step 101, detect network state and User Status, and collection network parameter and customer parameter.
In step 102, customer parameter is carried out initialization, definition user number UE_num produces UE_num user at random.Definition user's terminal type, A, B, C, D.The category-A type is supported N1 and N2; The category-B type is supported N2 and N3; The C type is supported N1 and N3; The D type is supported N1, N2 and N3.For avoiding extreme case, the quantity that defines four types of A, B, C, D is more or less the same.
In step 103, network parameter is carried out initialization, provide at random distribution X=(x1, x2, initial value x3).Xi is the percentage that the user's number in the Ni network accounts for total user's number, and x1+x2+x3=1, the terminal type that comprises in the N1 network are A, C, D, and the terminal type that comprises in the N2 network is A, B, D, and the terminal type that comprises in the N3 network is B, C, D.
In step 104, Control Parameter is carried out initialization, set observation variable, the variate-value of being convenient to observe in the simulation process and being followed the tracks of.These observation variables comprise, user's effectiveness in the network 1, user's effectiveness in the network 2, user's effectiveness in the network 3, the average utility of three networks, evolutionary rate control variables, fixedly utility matrix initial value.
In step 105, cycle controller is set cycle-index.
In step 106, system added make an uproar, produce additive white Gaussian noise at random and system is added make an uproar.
In step 107, produce evolution matrix G.Evolution function of the present invention is:
X wherein
kWith
Be directly proportional, promptly
I, j=1,2,3.
In step 108, calculate and the comparison fitness
Suppose that strategy set is described as S={s
1, s
2..., s
N, with each tactful s
iThe fitness that is associated is f
i, x
iThe expression individual in population is selected pure strategy s
iProbability, also be evolutionary system selects pure strategy s in moment in this colony
iIndividuality account for the percentage of individual sum, vector X=(x
1, x
2..., x
N) represented the population state.The fitness that the pure strategy distribution is corresponding and the average fitness of colony of mixed strategy correspondence are respectively
f1＜f_mean，f2＞f_mean，f3＞f_mean；
f1＜f_mean，f2＞f_mean，f3＜f_mean；
f1＜f_mean，f2＜f_mean，f3＞f_mean；
f1＞f_mean，f2＜f_mean，f3＞f_mean；
f1＞f_mean，f2＜f_mean，f3＜f_mean；
f1＞f_mean，f2＞f_mean，f3＜f_mean；
In step 109, determine each network under the demand of evolving, the number of users that should shift or receive.Evolve according to duplicating kinetic equation, calculate at first respectively
Judge that respectively whether stop condition satisfies, if do not satisfy stop condition (
Level off to 0), then the rate of increase in the dynamics of evolution equation is converted into concrete user's number,, determines that each network changes over to or produces according to the sign symbol of rate of increase, dynamically adjust the number of users of each network, thus the number of times upper limit of circulation in providing.
In step 110, carry out scene judgement, stored all possible result who relatively produces by in the step 108 in this module, below identify this six kinds of situations respectively with A-F.
(A)f1＜f_mean，f2＞f_mean，f3＞f_mean；
The effectiveness that is network 1 is less than average utility, thus the satisfactory user in the network 1 can be in network 2 and network 3 transferring user.
(B)f1＜f_mean，f2＞f_mean，f3＜f_mean；
The effectiveness that is network 1 and network 3 is less than average utility, thus the satisfactory user in network 1 and the network 3 can be in network 2 transferring user.
(C)f1＜f_mean，f2＜f_mean，f3＞f_mean；
The effectiveness that is network 1 and network 2 is less than average utility, thus the satisfactory user in network 1 and the network 2 can be in network 3 transferring user.
(D)f1＞f_mean，f2＜f_mean，f3＞f_mean；
The effectiveness that is network 2 is less than average utility, thus the satisfactory user in the network 2 can be in network 1 and network 3 transferring user.
(E)f1＞f_mean，f2＜f_mean，f3＜f_mean；
The effectiveness that is network 2 and network 3 is less than average utility, thus the satisfactory user in network 2 and the network 3 can be in network 2 transferring user.
(F)f1＞f_mean，f2＞f_mean，f3＜f_mean；
The effectiveness that is network 3 is less than average utility, thus the satisfactory user in the network 3 can be in network 1 and network 2 transferring user.
In step 111, carry out matching detection, utilize switch function, the function of the module 1 of selecting whether to realize to evolve.If scenario A then jumps to step 201 and continues to carry out.
In step 112, carry out matching detection, utilize switch function, the function of the module 2 of selecting whether to realize to evolve.If scenario B then jumps to step 301 and continues to carry out.
In step 113, carry out matching detection, utilize switch function, the function of the module 3 of selecting whether to realize to evolve.If scene C then jumps to step 401 and continues to carry out.
In step 114, carry out matching detection, utilize switch function, the function of the module 4 of selecting whether to realize to evolve.If scene D then jumps to step 501 and continues to carry out.
In step 115, carry out matching detection, utilize switch function, the function of the module 5 of selecting whether to realize to evolve.If scene E then jumps to step 601 and continues to carry out.
In step 116, carry out matching detection, utilize switch function, the function of the module 6 of selecting whether to realize to evolve.If scene F then jumps to step 701 and continues to carry out.
In step 117,, just need stability and precision determination module when duplicate the evolution function executing once the time at every turn.If scenario A then jumps to step 201 and continues to carry out.
In step 118, cycling condition detects.If reach precision and stability requirement then jump out circulation.
In step 119, output and drawing.User's effectiveness variation diagram in the output network 1, user's effectiveness variation diagram in the network 2, user's effectiveness variation diagram in the network 3, the average utility variation diagram of three networks, the variation diagram of number of users in the network 1, the variation diagram of number of users in the network 2, the variation diagram of number of users in the network 3, and the comparison diagram that changes of the number of users in three kinds of networks and the effectiveness of three kinds of networks change comparison diagram.
In step 120, finish the distribution of user in three kinds of networks in 4, and make that average utility is the highest.
Fig. 2 example illustrates the algorithm flow chart of evolution module 1 of the present invention.May further comprise the steps:
In step 201, carry out matching detection, because may have A, C, three types of users of D in the network 1, the user that network 2 support A, B, D are three types, the user that network 3 support B, C, D are three types, under this kind love scape, network 1 has proposed transfer request so, and network 2,3 has been accepted request.Exceed in network 1, to appoint with the number of users that needs in the step 109 to change so and get a user,, jump to step 202 if this user type is A; If this user type is C, jump to step 203; If this user type is D, jump to step 204.
In step 202,, switch to the network 2 from net 1 so carry out this category-A type user because network 2 is supported the user of A standard.
In step 203,, switch to the network 3 from net 1 so carry out this C type of user because network 3 is supported the user of C standard.
In step 204, the D type of user is best because of its multiple display modes compatible, so during the select target handover network, need adjudicate, the foundation of judgement is that the value of utility of comparison object handover network selects the bigger target handover network of value of utility to switch.(method herein has autgmentability, if the number of target handover network, can be set up an objective network tabulation greater than two, sorts by value of utility order from big to small, gets switching of value of utility maximum.) if the effectiveness of network 2 is less than the effectiveness of network 3, jumps to step 205 so; If the effectiveness of network 2 jumps to step 206 greater than the effectiveness of network 3.
In step 205, carry out this D type of user and switch to network 3 from network 1.
In step 206, carry out this D type of user and switch to network 3 from network 2.
Fig. 3 example illustrates the algorithm flow chart of evolution module 2 of the present invention.May further comprise the steps:
In step 301, carry out matching detection, because may have B, C, three types of users of D in the network 3, may have A, C, three types of users of D in the network 1, target handover network is a network 2, the user that network 2 support A, B, D are three types, so under this kind love scape, network 1,3 has proposed transfer request, and network 2 has been accepted request.In network 1 or network 3, exceed to appoint so and get a user,, jump to step 302 if this user type is A with the number of users that needs in the step 109 to change; If this user type is B, jump to step 303; If this user type is D, jump to step 304; If this user's type is C, jump to step 305 so.
In step 302,, switch in the network 2 so carry out this category-A type users from networks 1 because network 2 is supported the user of A standard.
In step 303,, switch in the network 2 so carry out this category-B type users from networks 3 because network 2 is supported the user of B standard.
In step 304, the D type of user is best because of its multiple display modes compatible, and no matter this D type of user place network is network 1 or network 3, all is directly switch in the network 2
In step 305, because of network 2 is not supported the user of C type, thus if the C type of user that is taken as, so directly redirect would be returned step 301 and is continued to carry out.
Fig. 4 example illustrates the algorithm flow chart of evolution module 3 of the present invention.May further comprise the steps:
In step 401, carry out matching detection, because may have A, B, three types of users of D in the network 2, may have A, C, three types of users of D in the network 1, target handover network is a network 3, the user that network 3 support B, C, D are three types, so under this kind love scape, network 1,2 has proposed transfer request, and network 3 has been accepted request.In network 1 or network 2, exceed to appoint so and get a user,, jump to step 402 if this user type is B with the number of users that needs in the step 109 to change; If this user type is C, jump to step 403; If this user type is D, jump to step 404; If this user's type is A, jump to step 405 so.
In step 402,, switch in the network 3 so carry out this category-B type users from networks 2 because network 2 is supported the user of B standard.
In step 403,, switch to the network 3 from network 1 so carry out this C type of user because network 1 is supported the user of C standard.
In step 404, the D type of user is best because of its multiple display modes compatible, and no matter this D type of user place network is network 1 or network 2, all is directly switch in the network 3.
In step 405, because of network 3 is not supported the user of category-A type, thus if the category-A type user that is taken as, so directly redirect would be returned step 401 and is continued to carry out.
Fig. 5 example illustrates the algorithm flow chart of evolution module 4 of the present invention.May further comprise the steps:
In step 501, carry out matching detection, because may have A, B, three types of users of D in the network 2, the user that network 1 support A, C, D are three types, the user that network 3 support B, C, D are three types, under this kind love scape, network 2 has proposed transfer request so, and network 1,3 has been accepted request.Exceed in network 2, to appoint with the number of users that needs in the step 109 to change so and get a user,, jump to step 502 if this user type is A; If this user type is B, jump to step 503; If this user type is D, jump to step 504.
In step 502,, switch to the network 1 from net 2 so carry out this category-A type user because network 1 is supported the user of A standard.
In step 503,, switch to the network 3 from net 2 so carry out this category-B type user because network 3 is supported the user of B standard.
In step 504, the D type of user is best because of its multiple display modes compatible, so during the select target handover network, need adjudicate, the foundation of judgement is that the value of utility of comparison object handover network selects the bigger target handover network of value of utility to switch.(method herein has autgmentability, if the number of target handover network, can be set up an objective network tabulation greater than two, sorts by value of utility order from big to small, gets switching of value of utility maximum.) if the effectiveness of network 3 is less than the effectiveness of network 1, jumps to step 505 so; If the effectiveness of network 3 jumps to step 506 greater than the effectiveness of network 1.
In step 505, carry out this D type of user and switch to network 3 from network 2.
In step 506, carry out this D type of user and switch to network 1 from network 2.
Fig. 6 example illustrates the algorithm flow chart of evolution module 5 of the present invention.May further comprise the steps:
In step 601, carry out matching detection, because may have A, B, three types of users of D in the network 2, may have B, C, three types of users of D in the network 3, target handover network is a network 1, the user that network 1 support A, C, D are three types, so under this kind love scape, network 2,3 has proposed transfer request, and network 1 has been accepted request.In network 2 or network 3, exceed to appoint so and get a user,, jump to step 602 if this user type is A with the number of users that needs in the step 109 to change; If this user type is C, jump to step 603; If this user type is D, jump to step 604; If this user's type is B, jump to step 605 so.
In step 602,, switch in the network 1 so carry out this category-A type users from networks 2 because network 1 is supported the user of A standard.
In step 603,, switch to the network 1 from network 3 so carry out this C type of user because network 1 is supported the user of C standard.
In step 604, the D type of user is best because of its multiple display modes compatible, and no matter this D type of user place network is network 2 or network 3, all is directly switch in the network 1.
In step 605, because of network 1 is not supported the user of category-B type, thus if the category-B type user that is taken as, so directly redirect would be returned step 601 and is continued to carry out.
Fig. 7 example illustrates the algorithm flow chart of evolution module 6 of the present invention.May further comprise the steps:
In step 701, carry out matching detection, because may have B, C, three types of users of D in the network 3, the user that network 2 support A, B, D are three types, the user that network 1 support A, C, D are three types, under this kind love scape, network 3 has proposed transfer request so, and network 1,2 has been accepted request.Exceed in network 3, to appoint with the number of users that needs in the step 109 to change so and get a user,, jump to step 702 if this user type is B; If this user type is C, jump to step 703; If this user type is D, jump to step 704.
In step 702,, switch in the network 2 so carry out this category-B type users from networks 3 because network 2 is supported the user of B standard.
In step 703,, switch to the network 1 from net 3 so carry out this C type of user because network 1 is supported the user of C standard.
In step 704, the D type of user is best because of its multiple display modes compatible, so during the select target handover network, need adjudicate, the foundation of judgement is that the value of utility of comparison object handover network selects the bigger target handover network of value of utility to switch.(method herein has autgmentability, if the number of target handover network, can be set up an objective network tabulation greater than two, sorts by value of utility order from big to small, gets switching of value of utility maximum.) if the effectiveness of network 1 is less than the effectiveness of network 2, jumps to step 705 so; If the effectiveness of network 2 jumps to step 706 greater than the effectiveness of network 2.
In step 705, carry out this D type of user and switch to network 2 from network 3.
In step 706, carry out this D type of user and switch to network 1 from network 3.
It more than is detailed introduction based on the heterogeneous network load sharing algorithm of terminal standard difference to being proposed among the present invention, used specific embodiment herein principle of the present invention and execution mode have been carried out elaboration, the explanation of above implementation method just is used for helping to understand method of the present invention and core concept thereof; Simultaneously,,, all can change in specific embodiments and applications and point out, all have suitable change part in specific embodiments and applications according to thought of the present invention for one of ordinary skill in the art.In sum, this description should not be construed as limitation of the present invention.
Claims (9)
1. the heterogeneous network load sharing algorithm based on terminal standard difference is characterized in that comprising the following steps:
The first step: the line module initialization, definition user number UE_num produces UE_num user at random.Define network formats N1, N2, N3 that four kinds of user terminals are supported, network 1 is supported N1, and network 2 is supported N2, and network 3 is supported N3.And network 1, network 2, network 3 cover mutually.Definition user's terminal type, A, B, C, D.Category-A type terminal is supported N1 and N2; Category-B type terminal is supported N2 and N3; The C type terminals is supported N1 and N3; The D type terminals is supported N1, N2 and N3.For avoiding extreme case, the quantity that defines four types of A, B, C, D is more or less the same.Provide distribution X=(x at random simultaneously
1, x
2, x
3) initial value.x
iFor the user's number in the Ni network accounts for the percentage of total user's number, x
1+ x
2+ x
3=1, the terminal type that comprises in the N1 network is A, C, D, and the terminal type that comprises in the N2 network is A, B, D, and the terminal type that comprises in the N3 network is B, C, D.
Second step: the network parameter initialization, by relatively determining the network parameter initial value between heterogeneous network in twos, determine utility matrix U0.Cycle-index is set.
The 3rd step: the circulation beginning, N1 is calculated in fixedly utility matrix scrambling, N2, the fitness under each comfortable current network parameter configuration of N3 network, and average fitness.Owing to considered the otherness of terminal, need respectively relatively N1 here, N2, the size of the fitness of N3 and average fitness so that from the little network transitions of fitness to the big network of fitness, promptly select the individuality of fitness maximum to replace minimum individuality.Result relatively is divided into six kinds of situations.If the fitness of N1 network is f1, the fitness of N2 network is f2, and the fitness of N3 network is f3, and the Pingdu fitness is f_mean.Then six kinds of comparative results are respectively
f1＜f_mean，f2＞f_mean，f3＞f_mean；
f1＜f_mean，f2＞f_mean，f3＜f_mean；
f1＜f_mean，f2＜f_mean，f3＞f_mean；
f1＞f_mean，f2＜f_mean，f3＞f_mean；
f1＞f_mean，f2＜f_mean，f3＜f_mean；
f1＞f_mean，f2＞f_mean，f3＜f_mean；
The 4th step: evolve according to duplicating kinetic equation, calculate at first respectively
Judge that respectively whether stop condition satisfies, if do not satisfy stop condition (
Level off to 0), then the rate of increase in the dynamics of evolution equation is converted into concrete user's number,, determines that each network changes over to or produces according to the sign symbol of rate of increase, dynamically adjust the number of users of each network, thus the number of times upper limit of circulation in providing.
The 5th step: stability and precision judge that the judgement of stability can be judged by Liapunov (A.M.LYApunov) stability of a system theorem.The precision decision condition is by the stop condition decision in the 4th step.Obtain equiblibrium mass distribution and the average value of utility of user in three networks.If do not satisfy, reenter the loop body in the 3rd step.
2. method according to claim 1 is characterized in that user's producing method is for producing at random in the described first step.
3. method according to claim 1 is characterized in that defined 4 kinds of terminal types and 3 kinds of network formats only are examples in the described first step, and this method can be derived to the terminal type of each quantity and the network formats kind of each quantity.
4. method according to claim 1, the quantity that it is characterized in that defining in the described first step four types of A, B, C, D is more or less the same.
5. method according to claim 1 is characterized in that providing in the described first step distribution X=(x at random
1, x
2, x
3) initial value.x
iFor the user's number in the Ni network accounts for the percentage of total user's number, x
1+ x
2+ x
3=1, the terminal type that comprises in the N1 network is A, C, D, and the terminal type that comprises in the N2 network is A, B, D, and the terminal type that comprises in the N3 network is B, C, D.
6. method according to claim 1 is characterized in that in described second step, by relatively determining the network parameter initial value between heterogeneous network in twos, determined utility matrix U0.Cycle-index is set.
7. method according to claim 1, it is characterized in that having considered in described the 3rd step otherness of terminal, here need to compare respectively N1, N2, the size of the fitness of N3 and average fitness, so that to the big network of fitness, promptly select the individuality of fitness maximum to replace minimum individuality from the little network transitions of fitness.Used the thought of the game of evolutionary game theory herein, result relatively is divided into six kinds of situations, and is as follows:
f1＜f_mean，f2＞f_mean，f3＞f_mean；
f1＜f_mean，f2＞f_mean，f3＜f_mean；
f1＜f_mean，f2＜f_mean，f3＞f_mean；
f1＞f_mean，f2＜f_mean，f3＞f_mean；
f1＞f_mean，f2＜f_mean，f3＜f_mean；
f1＞f_mean，f2＞f_mean，f3＜f_mean。
8. method according to claim 1, it is characterized in that having used idea of evolution in the evolutionary game theory in described the 4th step, rate of increase in the dynamics of evolution equation is converted into concrete user's number, sign symbol according to rate of increase, determine that each network changes over to or produces, dynamically adjust the number of users of each network, thus the number of times upper limit of circulation in providing.
9. method according to claim 1 is characterized in that the judgement of stability in described the 5th step can be judged by Liapunov (A.M.LYApunov) stability of a system theorem.The precision decision condition is by the stop condition decision in the 4th step.Obtain equiblibrium mass distribution and the average value of utility of user in three networks.
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| CN104754646A (en) * | 2013-12-27 | 2015-07-01 | 中兴通讯股份有限公司 | Heterogeneous network load balancing method and device |
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