CN106503832A - Unmanned someone's cooperative information distribution transmission optimization method and system - Google Patents

Abstract

The present invention provides a kind of unmanned someone's cooperative information distribution transmission optimization method and system, and the method includes：Step 1, each information to be distributed is encoded according to the attribute of default coded method and each information to be distributed, obtain each corresponding initial solution of information to be distributed；Step 2, using each obtained initial solution as initial population, the unmanned someone's cooperative information distribution transmission Optimized model for pre-setting is solved using genetic algorithm, so as to obtain optimal solution；Step 3, the optimal case output that the scheme corresponding to the optimal solution is transmitted optimization problem as unmanned someone's cooperative information distribution.Unmanned someone's cooperative information distribution transmission optimization method and system that invention is provided, can effectively improve the accuracy of unmanned someone's cooperative information distribution transmission.

Description

Nobody-someone's cooperative information distribution transmission optimization method and system

Technical field

The present invention relates to unmanned air vehicle technique field, and in particular to a kind of nobody-someone's cooperative information distribution transmission optimization side Method and system.

Background technology

In the implementation procedure of complex task, the high maneuverability of unmanned plane and zero casualty rate with have man-machine fuzzy decision Ability and strong anti-interference ability present very strong complementarity, by nobody-to complete complex task be using existing to someone's collaboration Technical conditions improve a kind of important way and effective way of formation efficiency.Wherein, the instant messaging pair of various information in forming into columns Act on important support in smoothly completing for support mission, therefore how to carry out effectively distribution to relevant information with transmission is Nobody-someone's collaborative processes in key issue.Nobody-someone's cooperative information distribution excellent optimization method of transmission is by rationally choosing The time serieses that information source planning information send are selected, to meet the constraint of network performance, realizes information in unmanned plane and someone Effective distribution between machine.

At present, both at home and abroad for the information distribution problem research under the backgrounds such as real-time traffic, cooperation is more, but specially Door study nobody-someone collaboration background under information distribution optimization problem relatively fewer；Simultaneously for grinding for information distribution problem Study carefully the influence factors such as the bandwidth and the communication distance that mainly consider in communication network, for information distributes transmission in a communication network The correlational study affected by factors such as time delay and time windows is less.

Content of the invention

(1) technical problem for solving

One purpose of the embodiment of the present invention be to provide a kind of nobody-someone's cooperative information distribution transmission optimization method and be System, with improve nobody-someone's cooperative information distribution transmission accuracy.

(2) technical scheme

For reaching above-mentioned purpose, the first aspect of the invention provide nobody-the distribution transmission of someone's cooperative information optimizes Method, including：

In a first aspect, one embodiment of the invention provide a kind of nobody-someone's cooperative information distribution transmission optimization method, bag Include:

Step 1, to be distributed to each according to the attribute of default coded method and each information to be distributed Information is encoded, and obtains each corresponding initial solution of information to be distributed；

Step 2, using each obtained initial solution as initial population, using genetic algorithm to pre-set nobody- Someone's cooperative information distribution transmission Optimized model is solved, so as to obtain optimal solution；

Step 3, using the scheme corresponding to the optimal solution as described nobody-someone's cooperative information distribution transmission optimization ask The optimal case output of topic.

Second aspect, embodiments provide a kind of nobody-someone's cooperative information distribution transmission optimization system, bag Include:

Initial solution generation module, for the attribute according to default coded method and each information to be distributed to every One information to be distributed is encoded, and obtains each corresponding initial solution of information to be distributed；

Optimal solution generation module, for using each obtained initial solution as initial population, using genetic algorithm to pre- First arrange nobody-someone's cooperative information distribution transmission Optimized model solved, so as to obtain optimal solution；

Output module, for using the scheme corresponding to the optimal solution as described nobody-someone's cooperative information distribution pass Pass the optimal case output of optimization problem.

(3) beneficial effect

The present invention provide nobody-someone's cooperative information distribution transmission optimization method and system, can effectively improve nobody- The accuracy of someone's cooperative information distribution transmission.

Description of the drawings

In order to be illustrated more clearly that the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing Accompanying drawing to be used needed for having technology description is briefly described, it should be apparent that, drawings in the following description are only this Some embodiments of invention, for those of ordinary skill in the art, on the premise of not paying creative work, can be with Other accompanying drawings are obtained according to these accompanying drawings.

Fig. 1 for one embodiment of the invention provide nobody-someone's cooperative information distribution transmission optimization method schematic flow sheet；

Fig. 2 provide for one embodiment of the invention nobody-flow process of someone's cooperative information distribution transmission optimization method illustrates A kind of schematic diagram of chromosome coding in figure；

Fig. 3 for using the present invention provides nobody-someone's cooperative information distribution transmit optimization method in the middle part of split flow one Plant the schematic diagram of embodiment；

Fig. 4 for using the present invention provides nobody-someone's cooperative information distribution transmit optimization method in the middle part of split flow one Plant the schematic diagram of embodiment；

Fig. 5 for one embodiment of the invention provide nobody-someone's cooperative information distribution transmission optimization system structural representation.

Specific embodiment

Purpose, technical scheme and advantage for making the embodiment of the present invention is clearer, below in conjunction with the embodiment of the present invention In accompanying drawing, to the embodiment of the present invention in technical scheme be clearly and completely described, it is clear that described embodiment is The a part of embodiment of the present invention, rather than whole embodiments.Embodiment in based on the present invention, those of ordinary skill in the art The every other embodiment obtained under the premise of creative work is not made, belongs to the scope of protection of the invention.

In a first aspect, one embodiment of the invention provide a kind of nobody-someone's cooperative information distribution transmission optimization method, ginseng See that Fig. 1, the method include:

S1, according to default coded method and each information to be distributed attribute to each information to be distributed Encoded, obtained each corresponding initial solution of information to be distributed；

S2, using each obtained initial solution as initial population, using genetic algorithm to pre-set nobody-someone Cooperative information distribution transmission Optimized model is solved, so as to obtain optimal solution；

S3, using the scheme corresponding to the optimal solution as described nobody-someone's cooperative information distribution transmission optimization problem Optimal case output.

The present invention provide nobody-someone's cooperative information distribution transmission optimization method, using genetic algorithm and default nothing People-someone's cooperative information distribution transmission Optimized model is optimized to each corresponding initial solution of information to be distributed and obtains most Excellent scheme output.Can so effectively improve nobody-someone's cooperative information distribution transmission accuracy.

In the specific implementation, here nobody-someone's cooperative information distribution transmission Optimized model object function can have Body is：

And constraints can be specially：

ET_t≤l_t,t∈T；

ET_t≥e_t,t∈T；

ET_t-ST_t≤D,t∈T；

Wherein, E=<i,j>| i, j ∈ V, i ≠ j } oriented line set is represented, wherein<i,j>Represent in communication network topology Directed edge of the node i to node j；

W={ w_ij| i, j ∈ V } represent figure in every directed edge weights set, wherein w_ijRepresent node i to node j it Between Euclidean distance.

B_vThe maximum amount of data that node v can be provided is represented, wherein, v represents any node in communication network topology, v ∈V；

T={ 1,2 ..., n } represents that information aggregate to be distributed, n represent that the number of element in set, t represent that any one is treated Distribution information, t ∈ T；

[e_t,l_t] representing, information t to be distributed needs information sink, e to be reached in this time window_tRepresent earliest arrival time, l_t Represent the time of advent at the latest；

ST_tRepresent that information t to be distributed starts delivery time, ET from information source is actual_tRepresent that information t to be distributed is actually reached The moment of information sink；

SN_tRepresent the actual information source of information t to be distributed, EN_tRepresent the information sink for needing to receive information t to be distributed；

Represent that information t to be distributed is delivered to the propagation delay time of node j generations from node i；

Represent that information t to be distributed is delivered to the propagation delay of node j generations from node i；

D represents acceptable maximum delay in communication network topology；

TW_tRepresent the bandwidth required for information t to be distributed；

NW_ijRepresent directed edge in communication network topology<i,j>The maximum bandwidth that can bear；

Decision variableIt is defined as：

In the specific implementation, step S1 can be specifically included：

S10, using quantity n of information to be distributed as the intragentic quantity of chromosome in genetic algorithm, gene adopts five yuan The mode of group is encoded, and such as following formula is represented；

Gene=(Sflag, Stask_start, Stask_end, Stime_start, Stime_end)

Wherein, Sflag represents whether information to be distributed is distributed, and Stask_start represents the information source of information to be distributed, Stask_end represents that the information sink of information to be distributed, Stime_start represent that information to be distributed starts to distribute from information source is actual Moment, Stime_end represent that information to be distributed is actually reached the moment of information sink.One is described in fig. 2 by 5 gene institutes The chromosome of composition, by taking first gene as an example, (1,1,2,8,9.5) represent first information to be distributed from the letter that numbering is 1 Breath source is sent to the information sink that numbering is 2, and the time that sends is the 8th second to the 9.5th second.

In addition, the computing formula of fitness function is f=D-M, wherein D is a given maximum, and M is current dyeing Corresponding distribution transmission total time under body coding.In view of information to be distributed need to meet nobody-someone's information distribution transmission mould The constraint of the bandwidth of communication network topology, time delay, time window and information source in type, therefore also needs to enter chromosome in row constraint school Test.For the chromosome failed by constraint checking, then increase penalty factor on its target function value so as to fitness function Value diminishes, to remove the chromosome for being unsatisfactory for given constraint.

Be the process that assignment is carried out to each attribute in five-tuple afterwards, referring to Fig. 3, can specifically include：

S11, reads the attribute of n information to be distributed, from information attribute table to be distributed if all information to be distributed all may be used To be distributed transmission, even the value of the Sflag of n gene is 1 in chromosome；Unit in information attribute table to be distributed have Stask_id, Datavolume, Timewindow_start, Timewindow_end, Stime_end, wherein Stask_id tables Show the sequence number of information to be distributed, Datavolume represents the data volume of information to be distributed, Timewindow_start is represented and treated point The starting point of photos and sending messages time window, Timewindow_end represent the time window terminal of information to be distributed, and Stime_end is represented and treated point The information sink of photos and sending messages)；

S12, generates the Stask_start of each information to be distributed at random, and judges whether that needs are forwarded, if needed Then to turn S13, otherwise, by Stask_start records in the node path table that information distributes transmission, turn S14；Wherein, node Routing table is used for record information and distributes the node sequence that is passed through in transmission；

S13, the random number of times and corresponding relay equipment for generating forwarding, and the number record by relay equipment In the node path table that information distributes transmission, turn S14；

S14, reads the time window attribute of each information to be distributed and the node path table of information distribution transmission, calculating of retrodicting Go out each information to be distributed to send the time earliest and send the time at the latest, and randomly generate a Stask_ within the time period Start, then forwards calculates Stime_end, turns S15；

S15, reads the information sink attribute Stask_end of n information to be distributed, by Sflag, Stask_start, Stask_ End, Stime_start, Stime_end are recorded in initial solution.

In certain embodiments, step S2 can be executed in various ways, such as：

An initial population can be obtained after initial solution generation method is executed POPSIZE time, then using roulette Mode carries out initial population selection.Population after to selection carries out crossover operation by the way of single-point intersection, that is, randomly generate One cross point, and the part by two neighboring chromosome coding in current population after the point is exchanged with each other successively, so as to Generate two new chromosomes.Then according to mutation probability, by the way of 0-1 variations, to chromogene in Sflag enter Row variation is operated.Population after to variation is arranged by the descending of fitness function value, SonNum chromosome before taking out, with When parent population is arranged by the ascending order of fitness function value, FatherNum chromosome after taking-up is two-part by this Population of the chromosome set into a new generation.Aforesaid operations are repeated, until exceeding to maximum iteration time and exporting optimal solution.

Referring to Fig. 4, the above-mentioned mode for referring to specifically can be carried out in accordance with the following steps：

S21, can obtain an initial population after the initial solution generation method is executed predetermined number time；Initially will plant Group is designated as POP (1), and initializes t=1, turns S22；

S22, to each chromosome pop in colony POP (t)_εT () calculates its fitness function Wherein D is a maximum,For target function value, turn S23；

S23, judges whether to meet end condition t ＞=MAX_ITERATION；Wherein, MAX_ITERATION represents maximum Iterationses), if being unsatisfactory for, S24 is executed, otherwise turns S29；

S24, using roulette method from t for population POP (t) in select POPSIZE chromosome, so as to produce One new population NEWPOP (t), records now best solution, turns S25；

S25, to t for population NEWPOP (t) in chromosome carry out single-point crossover operation, that is, randomly generate an intersection Two neighboring chromosome in population is located at the part after the point and is exchanged with each other, generates two new chromosomes by point successively, The now best solution of record, turns STEP 6；

S26, is made a variation using 0-1 for the gene of chromosome in population NEWPOP (t) to t, i.e., whether task is performed (Sflag) enter row variation, give a mutation probability Pm, in [0,1], produce a random number, if random number is general less than variation Rate, then enter row variation to the gene, otherwise, does not enter row variation, and records now best solution, turn S27；

S27, carries out constraint checking, the i.e. feasibility to being solved to t for population NEWPOP (t) and judges, mainly include The constraint of time windows constraints, delay constraint, bandwidth constraint and information source.When chromosome is unsatisfactory for arbitrary constraint therein, then in target Plus a very big integer as punishment on functional value so as to which fitness function value diminishes, and will be eliminated in selection operation, Turn S28；

S28, is updated operation to t for population NEWPOP (t), i.e., carries out by the descending of fitness function value by population Arrangement, SonNum chromosome before taking out, while parent population is arranged by the ascending order of fitness function value, after taking-up FatherNum chromosome, by this two-part chromosome set into the population of a new generation, turns S29

S29, is updated operation to t generations variation population NEWPOP (t), forms new population, and POP (t+1) makes t=t + 1, turn S22；

S210, exports optimal solution, and algorithm terminates.

Further, above-mentioned step S24 can be specifically included：

Step S241, by formulaT is calculated for the ε chromosome pop in population POP (t)_ε(t) Be genetic to probability of future generation

Step S242, by formulaT is calculated for the ε chromosome pop in population POP (t)_ε(t) Cumulative probability

Step S243, produces a random number r between [0,1] using random function, judges cumulative probabilityWith r, IfThen the ε chromosome pop_εT () is selected.

The embodiment of the present invention by set up nobody-someone's cooperative information distribution transmission Optimized model, from information distribution pass Total time for passing, minimum angle formulated distribution transmission scheme, improves the efficiency of information distribution transmission, quickly and easily obtains Information distribution transmission scheme.

In addition the embodiment of the present invention devises formal similarity with reference to the application background of problem, makes the solution of problem more directly perceived, Be easy to the understanding of people, the demand to problem solving can be more met than traditional 0-1 codings and real coding.

In addition the embodiment of the present invention according to nobody-generation of the Process Design initial solution of someone's cooperative information distribution transmission Method, substantially increases the feasibility of initial solution, advantageously reduces the iterationses of genetic algorithm, reduces the time of program operation, The result that solve quickly is obtained.

In addition the embodiment of the present invention is solved to problem using genetic algorithm, and genetic algorithm is that one kind passes through to simulate nature The method that evolutionary process searches for optimal solution, with higher search efficiency, the ability of global optimization and preferable robustness etc. Advantage, can help our fast searchs to optimal solution.

Second aspect, the invention provides a kind of nobody-someone's cooperative information distribution transmission optimization system, referring to Fig. 5, bag Include:

Initial solution generation module 51, for the attribute pair according to default coded method and each information to be distributed Each information to be distributed is encoded, and obtains each corresponding initial solution of information to be distributed；

Optimal solution generation module 52, for using each obtained initial solution as initial population, using genetic algorithm pair Pre-set nobody-someone's cooperative information distribution transmission Optimized model solved, so as to obtain optimal solution；

Output module 53, for using the scheme corresponding to the optimal solution as described nobody-someone's cooperative information distribution The optimal case output of transmission optimization problem.

Further, described nobody-someone's cooperative information distribution transmission Optimized model object function be：

Constraints is：

ET_t≤l_t,t∈T；

ET_t≥e_t,t∈T；

ET_t-ST_t≤D,t∈T；

Wherein, E=<i,j>| i, j ∈ V, i ≠ j } oriented line set is represented, wherein<i,j>Represent in communication network topology Directed edge of the node i to node j；

W={ w_ij| i, j ∈ V } represent figure in every directed edge weights set, wherein w_ijRepresent node i to node j it Between Euclidean distance；

B_vThe maximum amount of data that node v can be provided is represented, wherein, v represents any node in communication network topology, v ∈V；

T={ 1,2 ..., n } represents that information aggregate to be distributed, n represent that the number of element in set, t represent that any one is treated Distribution information, t ∈ T；

[e_t,l_t] representing, information t to be distributed needs information sink, e to be reached in this time window_tRepresent earliest arrival time, l_t Represent the time of advent at the latest；

ST_tRepresent that information t to be distributed starts delivery time, ET from information source is actual_tRepresent that information t to be distributed is actually reached The moment of information sink；

SN_tRepresent the actual information source of information t to be distributed, EN_tRepresent the information sink for needing to receive information t to be distributed；

Represent that information t to be distributed is delivered to the propagation delay time of node j generations from node i；

Represent that information t to be distributed is delivered to the propagation delay of node j generations from node i；

D represents acceptable maximum delay in communication network topology；

TW_tRepresent the bandwidth required for information t to be distributed；

NW_ijRepresent directed edge in communication network topology<i,j>The maximum bandwidth that can bear；

Decision variableIt is defined as：

Further, the initial solution generation module 51 is specifically for executing：

S10, using quantity n of information to be distributed as the intragentic quantity of chromosome in genetic algorithm, gene adopts five yuan The mode of group is encoded, and such as following formula is represented；

Gene=(Sflag, Stask_start, Stask_end, Stime_start, Stime_end)

Wherein, Sflag represents whether information to be distributed is distributed, and Stask_start represents the information source of information to be distributed, Stask_end represents that the information sink of information to be distributed, Stime_start represent that information to be distributed starts to distribute from information source is actual Moment, Stime_end represent that information to be distributed is actually reached the moment of information sink；

S11, reads the attribute of n information to be distributed, from information attribute table to be distributed if all information to be distributed all may be used To be distributed transmission, even the value of the Sflag of n gene is 1 in chromosome；Unit in information attribute table to be distributed have Stask_id, Datavolume, Timewindow_start, Timewindow_end, Stime_end, wherein Stask_id tables Show the sequence number of information to be distributed, Datavolume represents the data volume of information to be distributed, Timewindow_start is represented and treated point The starting point of photos and sending messages time window, Timewindow_end represent the time window terminal of information to be distributed, and Stime_end is represented and treated point The information sink of photos and sending messages)；

S12, generates the Stask_start of each information to be distributed at random, and judges whether that needs are forwarded, if needed Then to turn S13, otherwise, by Stask_start records in the node path table that information distributes transmission, turn S14；Wherein, node Routing table is used for record information and distributes the node sequence that is passed through in transmission；

S13, the random number of times and corresponding relay equipment for generating forwarding, and the number record by relay equipment In the node path table that information distributes transmission, turn S14；

S14, reads the time window attribute of each information to be distributed and the node path table of information distribution transmission, calculates each Individual information to be distributed sends the time earliest and sends the time at the latest, and randomly generates a Stask_start within the time period, Forwards calculates Stime_end again, turns S15；

S15, reads the information sink attribute Stask_end of n information to be distributed, by Sflag, Stask_start, Stask_ End, Stime_start, Stime_end are recorded in initial solution.

Further, the optimal solution generation module 52, specifically for executing：

S21, can obtain an initial population after the initial solution generation method is executed predetermined number time；Initially will plant Group is designated as POP (1), and initializes t=1, turns S22；

S22, to each chromosome pop in colony POP (t)_εT () calculates its fitness function Wherein D is a maximum,For target function value, turn S23；

S23, judges whether to meet end condition t ＞=MAX_ITERATION；Wherein, MAX_ITERATION represents maximum Iterationses), if being unsatisfactory for, S24 is executed, otherwise turns S29；

S24, using roulette method from t for population POP (t) in select POPSIZE chromosome, so as to produce One new population NEWPOP (t), records now best solution, turns S25；

S25, to t for population NEWPOP (t) in chromosome carry out single-point crossover operation, that is, randomly generate an intersection Two neighboring chromosome in population is located at the part after the point and is exchanged with each other, generates two new chromosomes by point successively, The now best solution of record, turns STEP 6；

S26, is made a variation using 0-1 for the gene of chromosome in population NEWPOP (t) to t, i.e., whether task is performed (Sflag) enter row variation, give a mutation probability Pm, in [0,1], produce a random number, if random number is general less than variation Rate, then enter row variation to the gene, otherwise, does not enter row variation, and records now best solution, turn S27；

S27, carries out constraint checking, the i.e. feasibility to being solved to t for population NEWPOP (t) and judges, mainly include The constraint of time windows constraints, delay constraint, bandwidth constraint and information source；When chromosome is unsatisfactory for arbitrary constraint therein, then in target Plus a very big integer as punishment on functional value so as to which fitness function value diminishes, and will be eliminated in selection operation, Turn S28；

S28, is updated operation to t for population NEWPOP (t), i.e., carries out by the descending of fitness function value by population Arrangement, SonNum chromosome before taking out, while parent population is arranged by the ascending order of fitness function value, after taking-up FatherNum chromosome, by this two-part chromosome set into the population of a new generation, turns S29；

S29, is updated operation to t generations variation population NEWPOP (t), forms new population, and POP (t+1) makes t=t + 1, turn S22；

S210, exports optimal solution.

Further, step S24 includes：

Step S241, by formulaT is calculated for the ε chromosome pop in population POP (t)_ε(t) Be genetic to probability of future generation

Step S242, by formulaT is calculated for the ε chromosome pop in population POP (t)_ε(t) Cumulative probability

Step S243, produces a random number r between [0,1] using random function, judges cumulative probabilityWith r, IfThen the ε chromosome pop_εT () is selected.

Understandable be introduced due to above-mentioned second aspect nobody-the distribution transmission of someone's cooperative information optimizes system Unite for can execute in the embodiment of the present invention nobody-system of someone's cooperative information distribution transmission optimization method, so be based on Described in the embodiment of the present invention nobody-someone's cooperative information distribution transmission optimize method, those skilled in the art Will appreciate that the present embodiment nobody-someone's cooperative information distribution transmission optimization system specific embodiment and its various change Change form, thus here for this nobody-someone's cooperative information distribution transmission optimization system how to realize in the embodiment of the present invention Nobody-someone's cooperative information distribution transmission optimization method be no longer discussed in detail.As long as those skilled in the art implement this In inventive embodiments nobody-system that adopted of method that optimizes of someone's cooperative information distribution transmission, belong to the application and be intended to The scope of protection.

Through the above description of the embodiments, those skilled in the art can be understood that each embodiment can Mode by software plus required general hardware platform is realizing.Be based on such understanding, above-mentioned technical proposal substantially or Person says that the part contributed by prior art can be embodied in the form of software product, and the computer software product can be with In a computer-readable storage medium, such as ROM/RAM, magnetic disc, CD etc. are used including some instructions so that a calculating for storage Machine equipment (can be personal computer, server, or network equipment etc.) executes some of each embodiment or embodiment Method described in part.

In description mentioned herein, a large amount of details are illustrated.It is to be appreciated, however, that the enforcement of the present invention Example can be put into practice in the case where not having these details.In some instances, known method, structure are not been shown in detail And technology, so as not to obscure the understanding of this description.

Similarly, it will be appreciated that in order to simplify open and help to understand one or more in each inventive aspect, upper In the face of the present invention exemplary embodiment description in, the present invention each feature be grouped together into sometimes single embodiment, In figure or descriptions thereof.However, should not be construed to reflect following intention by the method for the disclosure：I.e. claimed The more features of the feature that is expressly recited in each claim of application claims ratio.More precisely, as following As claims are reflected, inventive aspect is all features less than single embodiment disclosed above.Therefore, abide by Thus the claims for following specific embodiment are expressly incorporated in the specific embodiment, wherein each claim itself Separate embodiments as the present invention.

Those skilled in the art be appreciated that can to embodiment in equipment in module carry out adaptively Change and they are arranged in one or more equipment different from the embodiment.Can be the module in embodiment or list Unit or component are combined into a module or unit or component, and can be divided in addition multiple submodule or subelement or Sub-component.In addition at least some in such feature and/or process or unit is excluded each other, can adopt any Combination is disclosed to all features disclosed in this specification (including adjoint claim, summary and accompanying drawing) and so to appoint Where all processes or unit of method or equipment are combined.Unless expressly stated otherwise, this specification (includes adjoint power Profit is required, summary and accompanying drawing) disclosed in each feature can identical by offers, be equal to or the alternative features of similar purpose carry out generation Replace.

Although additionally, it will be appreciated by those of skill in the art that some embodiments in this include institute in other embodiments Including some features rather than further feature, but the combination of the feature of different embodiment means in the scope of the present invention Within and form different embodiments.For example, in the following claims, embodiment required for protection any it One can in any combination mode using.

It should be noted that above-described embodiment the present invention will be described rather than limits the invention, and ability Field technique personnel can design alternative embodiment without departing from the scope of the appended claims.In the claims, Any reference markss being located between bracket should not be configured to limitations on claims.Word "comprising" is not excluded the presence of not Element listed in the claims or step.Word "a" or "an" before being located at element does not exclude the presence of multiple such Element.The present invention can come real by means of the hardware for including some different elements and by means of properly programmed computer Existing.If in the unit claim for listing equipment for drying, several in these devices can be by same hardware branch To embody.The use of word first, second, and third does not indicate that any order.These words can be explained and be run after fame Claim.

Finally it should be noted that：Above example only in order to technical scheme to be described, rather than a limitation；Although With reference to the foregoing embodiments the present invention has been described in detail, it will be understood by those within the art that：Which still may be used To modify to the technical scheme described in foregoing embodiments, or equivalent is carried out to which part technical characteristic； And these modification or replace, do not make appropriate technical solution essence depart from various embodiments of the present invention technical scheme spirit and Scope.

Claims (10)

1. a kind of nobody-someone's cooperative information distribution transmission optimization method, it is characterized in that, including:

Step 1, according to default coded method and each information to be distributed attribute to each information to be distributed Encoded, obtained each corresponding initial solution of information to be distributed；

Step 2, using each obtained initial solution as initial population, using genetic algorithm to pre-set nobody-someone Cooperative information distribution transmission Optimized model is solved, so as to obtain optimal solution；

Step 3, using the scheme corresponding to the optimal solution as described nobody-someone cooperative information distribution transmission optimization problem Optimal case is exported.

2. according to claim 1 nobody-someone's cooperative information distribution transmission optimization method, it is characterized in that, described nobody-have The object function of Optimized model is transmitted in the distribution of people's cooperative information：

$\min M=\underset{t\&Element;T}{\&Sigma;}\underset{i,j\&Element;V}{\&Sigma;}(x_{ij}^t\&CenterDot;{\mathrm{ct}}_{ij}^t+x_{ij}^t\&CenterDot;{\mathrm{ft}}_{ij}^t)$

Constraints is：

${\mathrm{ET}}_t={\mathrm{ST}}_t+\underset{i,j\&Element;V}{\&Sigma;}({\mathrm{ct}}_{ij}^t+{\mathrm{ft}}_{ij}^t),t\&Element;T;$

ET_t≤l_t,t∈T；

ET_t≥e_t,t∈T；

ET_t-ST_t≤D,t∈T；

$\underset{t}{\&Sigma;}{x}_{ij}^t{W}_t\&le;{\mathrm{NW}}_{ij},i,j\&Element;V,t\&Element;T;$

$\underset{j}{\&Sigma;}\underset{t}{\&Sigma;}(x_{vj}^t\&CenterDot;{\mathrm{TW}}_t)\&le;B_v,v\&Element;V;$

$\underset{j}{\&Sigma;}{x}_{{\mathrm{SN}}_{t}j}^t=1,t\&Element;T;$

$\underset{i}{\&Sigma;}{x}_{{\mathrm{iEN}}_t}^t=1,t\&Element;T;$

$\underset{j}{\&Sigma;}{x}_{vj}^t\&le;1,t\&Element;T,v\&Element;V;$

$x_{ij}^t=1or0;$

Wherein, E=<i,j>| i, j ∈ V, i ≠ j } oriented line set is represented, wherein<i,j>Represent communication network topology interior joint Directed edges of the i to node j；

W={ w_ij| i, j ∈ V } represent figure in every directed edge weights set, wherein w_ijRepresent node i to the Europe between node j Formula distance；

B_vThe maximum amount of data that node v can be provided is represented, wherein, v represents any node in communication network topology, v ∈ V；

T={ 1,2 ..., n } represents that information aggregate to be distributed, n represent that the number of element in set, t represent that any one is to be distributed Information, t ∈ T；

[e_t,l_t] representing, information t to be distributed needs information sink, e to be reached in this time window_tRepresent earliest arrival time, l_tRepresent Time of advent at the latest；

ST_tRepresent that information t to be distributed starts delivery time, ET from information source is actual_tRepresent that information t to be distributed is actually reached information The moment of place；

SN_tRepresent the actual information source of information t to be distributed, EN_tRepresent the information sink for needing to receive information t to be distributed；

Represent that information t to be distributed is delivered to the propagation delay time of node j generations from node i；

Represent that information t to be distributed is delivered to the propagation delay of node j generations from node i；

D represents acceptable maximum delay in communication network topology；

TW_tRepresent the bandwidth required for information t to be distributed；

NW_ijRepresent directed edge in communication network topology<i,j>The maximum bandwidth that can bear；

Decision variableIt is defined as：

3. according to claim 1 nobody-someone's cooperative information distribution transmission optimization method, it is characterized in that, the step 1 Including：

S10, using quantity n of information to be distributed as the intragentic quantity of chromosome in genetic algorithm, gene is using five-tuple Mode is encoded, and such as following formula is represented；

Gene=(Sflag, Stask_start, Stask_end, Stime_start, Stime_end)

Wherein, Sflag represents whether information to be distributed is distributed, and Stask_start represents the information source of information to be distributed, Stask_end represents that the information sink of information to be distributed, Stime_start represent that information to be distributed starts to distribute from information source is actual Moment, Stime_end represent that information to be distributed is actually reached the moment of information sink；

S11, reads the attribute of n information to be distributed from information attribute table to be distributed, if all information to be distributed can be by Distribution transmission, even the value of the Sflag of n gene is 1 in chromosome；Unit in information attribute table to be distributed have Stask_ Id, Datavolume, Timewindow_start, Timewindow_end, Stime_end, wherein Stask_id are represented and are treated point The sequence number of photos and sending messages, Datavolume represent that the data volume of information to be distributed, Timewindow_start represent information to be distributed The starting point of time window, Timewindow_end represent that the time window terminal of information to be distributed, Stime_end represent information to be distributed Information sink)；

S12, generates the Stask_start of each information to be distributed at random, and judges whether that needs are forwarded, if necessary Turn S13, otherwise, by Stask_start records in the node path table that information distributes transmission, turn S14；Wherein, node path Table is used for record information and distributes the node sequence that is passed through in transmission；

S13, the random number of times and corresponding relay equipment for generating forwarding, and by the number record of relay equipment in letter In the node path table of breath distribution transmission, turn S14；

S14, reads the time window attribute of each information to be distributed and the node path table of information distribution transmission, calculates each and treat Distribution information sends the time earliest and sends the time at the latest, and randomly generates a Stask_start within the time period, then suitable Push away and calculate Stime_end, turn S15；

S15, reads the information sink attribute Stask_end of n information to be distributed, by Sflag, Stask_start, Stask_end, Stime_start, Stime_end are recorded in initial solution.

4. according to claim 1 nobody-someone's cooperative information distribution transmission optimization method, it is characterized in that, the step 2 Including：

Initial population is designated as POP (1), and initializes t=1, turns S22 by S21；

S22, to each chromosome pop in colony POP (t)_εT () calculates its fitness function Wherein D is a maximum,For target function value, turn S23；

S23, judges whether to meet end condition t ＞=MAX_ITERATION；Wherein, MAX_ITERATION represents greatest iteration Number of times), if being unsatisfactory for, S24 is executed, otherwise turns S29；

S24, using roulette method from t for population POP (t) in select POPSIZE chromosome, so as to produce one New population NEWPOP (t), records now best solution, turns S25；

S25, to t for population NEWPOP (t) in chromosome carry out single-point crossover operation, that is, randomly generate a cross point, Two neighboring chromosome in population is located at the part after the point successively to be exchanged with each other, two new chromosomes, note is generated The now best solution of record, turns STEP 6；

S26, is made a variation using 0-1 for the gene of chromosome in population NEWPOP (t) to t, i.e., whether task is performed (Sflag) enter row variation, give a mutation probability Pm, in [0,1], produce a random number, if random number is general less than variation Rate, then enter row variation to the gene, otherwise, does not enter row variation, and records now best solution, turn S27；

S27, carries out constraint checking, the i.e. feasibility to being solved to t for population NEWPOP (t) and judges, mainly include the time The constraint of window constraint, delay constraint, bandwidth constraint and information source；When chromosome is unsatisfactory for arbitrary constraint therein, then in object function Plus a very big integer as punishment in value so as to which fitness function value diminishes, and will be eliminated in selection operation, turn S28；

S28, is updated operation to t for population NEWPOP (t), i.e., is arranged by the descending of fitness function value by population Row, SonNum chromosome before taking out, while parent population is arranged by the ascending order of fitness function value, after taking-up FatherNum chromosome, by this two-part chromosome set into the population of a new generation, turns S29；

S29, is updated operation to t generations variation population NEWPOP (t), forms new population, and POP (t+1) makes t=t+1, Turn S22；

S210, exports optimal solution.

5. according to claim 4 nobody-someone's cooperative information distribution transmission optimization method, it is characterized in that, the step S24 includes：

Step S241, by formulaT is calculated for the ε chromosome pop in population POP (t)_εThe something lost of (t) Pass to probability of future generation

Step S242, by formulaT is calculated for the ε chromosome pop in population POP (t)_εThe accumulation of (t) Probability

Step S243, produces a random number r between [0,1] using random function, judges cumulative probabilityWith r, ifThen the ε chromosome pop_εT () is selected.

6. a kind of nobody-someone's cooperative information distribution transmission optimization system, it is characterized in that, including:

Initial solution generation module, for the attribute according to default coded method and each information to be distributed to each Information to be distributed is encoded, and obtains each corresponding initial solution of information to be distributed；

Optimal solution generation module, for using each obtained initial solution as initial population, using genetic algorithm to setting in advance Put nobody-someone's cooperative information distribution transmission Optimized model solved, so as to obtain optimal solution；

Output module, for using the scheme corresponding to the optimal solution as described nobody-someone's cooperative information distribution transmission excellent The optimal case output of change problem.

7. according to claim 6 nobody-someone's cooperative information distribution transmission optimization system, it is characterized in that, described nobody-have The object function of Optimized model is transmitted in the distribution of people's cooperative information：

$\min M=\underset{t\&Element;T}{\&Sigma;}\underset{i,j\&Element;V}{\&Sigma;}(x_{ij}^t\&CenterDot;{\mathrm{ct}}_{ij}^t+x_{ij}^t\&CenterDot;{\mathrm{ft}}_{ij}^t)$

Constraints is：

${\mathrm{ET}}_t={\mathrm{ST}}_t+\underset{i,j\&Element;V}{\&Sigma;}({\mathrm{ct}}_{ij}^t+{\mathrm{ft}}_{ij}^t),t\&Element;T;$

ET_t≤l_t,t∈T；

ET_t≥e_t,t∈T；

ET_t-ST_t≤D,t∈T；

$\underset{t}{\&Sigma;}{x}_{ij}^t{W}_t\&le;{\mathrm{NW}}_{ij},i,j\&Element;V,t\&Element;T;$

$\underset{j}{\&Sigma;}\underset{t}{\&Sigma;}(x_{vj}^t\&CenterDot;{\mathrm{TW}}_t)\&le;B_v,v\&Element;V;$

$\underset{j}{\&Sigma;}{x}_{{\mathrm{SN}}_{t}j}^t=1,t\&Element;T;$

$\underset{i}{\&Sigma;}{x}_{{\mathrm{iEN}}_t}^t=1,t\&Element;T;$

$\underset{j}{\&Sigma;}{x}_{vj}^t\&le;1,t\&Element;T,v\&Element;V;$

$x_{ij}^t=1or0;$

Wherein, E=<i,j>| i, j ∈ V, i ≠ j } oriented line set is represented, wherein<i,j>Represent communication network topology interior joint Directed edges of the i to node j；

W={ w_ij| i, j ∈ V } represent figure in every directed edge weights set, wherein w_ijRepresent node i to the Europe between node j Formula distance；

B_vThe maximum amount of data that node v can be provided is represented, wherein, v represents any node in communication network topology, v ∈ V；

T={ 1,2 ..., n } represents that information aggregate to be distributed, n represent that the number of element in set, t represent that any one is to be distributed Information, t ∈ T；

[e_t,l_t] representing, information t to be distributed needs information sink, e to be reached in this time window_tRepresent earliest arrival time, l_tRepresent Time of advent at the latest；

ST_tRepresent that information t to be distributed starts delivery time, ET from information source is actual_tRepresent that information t to be distributed is actually reached information The moment of place；

SN_tRepresent the actual information source of information t to be distributed, EN_tRepresent the information sink for needing to receive information t to be distributed；

Represent that information t to be distributed is delivered to the propagation delay time of node j generations from node i；

Represent that information t to be distributed is delivered to the propagation delay of node j generations from node i；

D represents acceptable maximum delay in communication network topology；

TW_tRepresent the bandwidth required for information t to be distributed；

NW_ijRepresent directed edge in communication network topology<i,j>The maximum bandwidth that can bear；

Decision variableIt is defined as：

8. according to claim 6 nobody-someone's cooperative information distribution transmission optimization system, it is characterized in that, described initial Solution generation module is specifically for executing：

S10, using quantity n of information to be distributed as the intragentic quantity of chromosome in genetic algorithm, gene is using five-tuple Mode is encoded, and such as following formula is represented；

Gene=(Sflag, Stask_start, Stask_end, Stime_start, Stime_end)

Wherein, Sflag represents whether information to be distributed is distributed, and Stask_start represents the information source of information to be distributed, Stask_end represents that the information sink of information to be distributed, Stime_start represent that information to be distributed starts to distribute from information source is actual Moment, Stime_end represent that information to be distributed is actually reached the moment of information sink；

S11, reads the attribute of n information to be distributed from information attribute table to be distributed, if all information to be distributed can be by Distribution transmission, even the value of the Sflag of n gene is 1 in chromosome；Unit in information attribute table to be distributed have Stask_ Id, Datavolume, Timewindow_start, Timewindow_end, Stime_end, wherein Stask_id are represented and are treated point The sequence number of photos and sending messages, Datavolume represent that the data volume of information to be distributed, Timewindow_start represent information to be distributed The starting point of time window, Timewindow_end represent that the time window terminal of information to be distributed, Stime_end represent information to be distributed Information sink)；

S12, generates the Stask_start of each information to be distributed at random, and judges whether that needs are forwarded, if necessary Turn S13, otherwise, by Stask_start records in the node path table that information distributes transmission, turn S14；Wherein, node path Table is used for record information and distributes the node sequence that is passed through in transmission；

S13, the random number of times and corresponding relay equipment for generating forwarding, and by the number record of relay equipment in letter In the node path table of breath distribution transmission, turn S14；

S14, reads the time window attribute of each information to be distributed and the node path table of information distribution transmission, calculates each and treat Distribution information sends the time earliest and sends the time at the latest, and randomly generates a Stask_start within the time period, then suitable Push away and calculate Stime_end, turn S15；

S15, reads the information sink attribute Stask_end of n information to be distributed, by Sflag, Stask_start, Stask_end, Stime_start, Stime_end are recorded in initial solution.

9. according to claim 6 nobody-someone's cooperative information distribution transmission optimization system, it is characterized in that, the optimum Solution generation module, specifically for executing：

Initial population is designated as POP (1), and initializes t=1, turns S22 by S21；

S22, to each chromosome pop in colony POP (t)_εT () calculates its fitness function Wherein D is a maximum,For target function value, turn S23；

S23, judges whether to meet end condition t ＞=MAX_ITERATION；Wherein, MAX_ITERATION represents greatest iteration Number of times), if being unsatisfactory for, S24 is executed, otherwise turns S29；

S24, using roulette method from t for population POP (t) in select POPSIZE chromosome, so as to produce one New population NEWPOP (t), records now best solution, turns S25；

S25, to t for population NEWPOP (t) in chromosome carry out single-point crossover operation, that is, randomly generate a cross point, Two neighboring chromosome in population is located at the part after the point successively to be exchanged with each other, two new chromosomes, note is generated The now best solution of record, turns STEP 6；

S26, is made a variation using 0-1 for the gene of chromosome in population NEWPOP (t) to t, i.e., whether task is performed (Sflag) enter row variation, give a mutation probability Pm, in [0,1], produce a random number, if random number is general less than variation Rate, then enter row variation to the gene, otherwise, does not enter row variation, and records now best solution, turn S27；

S27, carries out constraint checking, the i.e. feasibility to being solved to t for population NEWPOP (t) and judges, mainly include the time The constraint of window constraint, delay constraint, bandwidth constraint and information source；When chromosome is unsatisfactory for arbitrary constraint therein, then in object function Plus a very big integer as punishment in value so as to which fitness function value diminishes, and will be eliminated in selection operation, turn S28；

S28, is updated operation to t for population NEWPOP (t), i.e., is arranged by the descending of fitness function value by population Row, SonNum chromosome before taking out, while parent population is arranged by the ascending order of fitness function value, after taking-up FatherNum chromosome, by this two-part chromosome set into the population of a new generation, turns S29；

S29, is updated operation to t generations variation population NEWPOP (t), forms new population, and POP (t+1) makes t=t+1, Turn S22；

S210, exports optimal solution.

10. according to claim 9 nobody-someone's cooperative information distribution transmission optimization system, it is characterized in that, the step S24 includes：

Step S241, by formulaT is calculated for the ε chromosome pop in population POP (t)_εThe something lost of (t) Pass to probability of future generation

Step S242, by formulaT is calculated for the ε chromosome pop in population POP (t)_εThe accumulation of (t) Probability

Step S243, produces a random number r between [0,1] using random function, judges cumulative probabilityWith r, ifThen the ε chromosome pop_εT () is selected.