CN102769806B - Resource assignment method and device of optical transmission net - Google Patents
Resource assignment method and device of optical transmission net Download PDFInfo
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- 239000011159 matrix material Substances 0.000 claims abstract description 38
- 210000000349 chromosome Anatomy 0.000 claims description 54
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Abstract
The invention provides a resource assignment method and a resource assignment device of an optical transmission net. The method comprises the following steps of: acquiring network topology structure information of the optical transmission net, and a static business matrix formed by static businesses loaded by the optical transmission net; acquiring an initial available wavelength loaded by each optical fiber on each link circuit between each two network nodes; and carrying out route and wavelength assignment on each static business in the static business matrix through a genetic algorithm according to the acquired network topology structure information and the acquired initial available wavelength loaded by each optical fiber on each link circuit between each two network nodes. The invention also provides a corresponding device. According to the method and the device, the efficiency of route and wavelength assignment for the optical transmission net can be high.
Description
Technical field
The present invention relates to Resource Allocation in Networks technology, particularly relate to a kind of resource allocation methods and device of optical transfer network, belong to optical-fiber network technical field.
Background technology
The optical transfer network intersected based on light (Optical Transport Network, hereinafter referred to as: OTN), be the passage transmitted as it using different wave length, wavelength available restricted number network.The maximum number of connection end to end that network can provide, and the physical constraint such as tuning capability of wavelength channel interval on optical fiber link, optical transceiver all limits the quantity of available channel.In addition, during to each channel allocation wavelength, the factors such as bandwidth demand amount are not considered, so bandwidth granularity problem limits the bandwidth availability ratio of wavelength channel too.In a word, due to the limiting factor of various physical technique, make optical-fiber network can't provide all physical properties required by us, therefore need to carry out efficiency utilization and resource optimization to existing available resources.
In the OTN intersected based on light, wave length routing has two requirements, and one is wavelength continuity requirement: between business is end-to-end, and the wavelength used must be consistent; Two be with fine must different wave length: the light path of all shared same optical fiber must distribute different wavelength.Existing based on mainly static routing Wavelength Assignment in the OTN of light intersection, namely under static traffic environment, consider wavelength and resource allocation problem.Static traffic flow refer to all nodes between connection request be given in advance and time-independent, namely the annexation of source node and destination node is given constant.After all connection establishments are good, connect and will remain unchanged.Now network can not set up new connection, also can not remove the connection of having built up.For the OTN that intersects based on light, how rationally and effectively to carry out route symmetry extremely important, adopt heuritic approach to carry out route symmetry in prior art, but it is lower to utilize this heuritic approach to carry out the efficiency of route symmetry.
Summary of the invention
The invention provides a kind of resource allocation methods and device of optical transfer network, route symmetry efficiency can be improved.
First aspect of the present invention is to provide a kind of resource allocation methods of optical transfer network, comprising:
Obtain the network topology information of optical transfer network, and the static traffic matrix that the static traffic of described optical transfer network carrying is formed, the network topology information of described optical transfer network comprises the network node information in optical transfer network, link information between each network node, and the link cost of each bar link between network node, each bar link between described network node is two-way link, and described each bar link comprises same root optical fiber;
Obtain the initial wavelength available of each bearing optical fiber on each bar link between network node;
According to the initial wavelength available of each bearing optical fiber on each bar link between the described network topology information obtained and described network node, be that each static traffic in described static traffic matrix carries out route symmetry according to genetic algorithm.
Another aspect of the present invention is to provide a kind of resource allocation device of optical transfer network, comprising:
First acquisition module, for obtaining the network topology information of optical transfer network, and the static traffic matrix that the static traffic of described optical transfer network carrying is formed, the network topology information of described optical transfer network comprises the network node information in optical transfer network, link information between each network node, and the link cost of each bar link between network node, each bar link between described network node is two-way link, and described each bar link comprises identical number of fibers;
Second acquisition module, for obtaining the initial wavelength available of each bearing optical fiber on each bar link between network node;
Wavelength Assignment module, for according to the initial wavelength available of each bearing optical fiber on each bar link between the described network topology information obtained and described network node, be that each static traffic in described static traffic matrix carries out route symmetry according to genetic algorithm.
The resource allocation methods of optical transfer network provided by the invention and device, first the network topology information of optical transfer network is obtained, and the static traffic matrix that the static traffic of described optical transfer network carrying is formed, obtain the initial wavelength available of each bearing optical fiber on each bar link between network node simultaneously, then be that each static traffic in static traffic matrix carries out route symmetry according to genetic algorithm, what can make full use of that genetic algorithm has can parallel computation and the advantage of separating more, rises to the efficiency that optical transfer network carries out route symmetry.
Accompanying drawing explanation
Fig. 1 is the schematic flow sheet of the resource allocation methods of optical transfer network in the embodiment of the present invention;
Fig. 2 is network node schematic diagram in the embodiment of the present invention;
Fig. 3 is the principle schematic of crossover operator in the embodiment of the present invention;
Fig. 4 is the principle schematic of mutation operator in the embodiment of the present invention;
Fig. 5 is the structural representation of the resource allocation device of optical transfer network in the embodiment of the present invention;
Fig. 6 is the structural representation of medium wavelength distribution module embodiment illustrated in fig. 5.
Embodiment
The invention provides a kind of resource allocation methods of optical transfer network, Fig. 1 is the schematic flow sheet of the resource allocation methods of optical transfer network in the embodiment of the present invention, as shown in Figure 1, comprises following step:
The network topology information of step 101, acquisition optical transfer network, and the static traffic matrix that the static traffic of described optical transfer network carrying is formed, the network topology information of described optical transfer network comprises the network node information in optical transfer network, link information between each network node, and the link cost of each bar link between network node, each bar link between described network node is two-way link, and described each bar link comprises same root optical fiber;
The initial wavelength available of each bearing optical fiber on each bar link between step 102, acquisition network node;
Step 103, according to the initial wavelength available of each bearing optical fiber on each bar link between the described network topology information obtained and described network node, be that each static traffic in described static traffic matrix carries out route symmetry according to genetic algorithm.
In the above embodiment of the present invention, first the network topology information of optical transfer network is obtained, and the static traffic matrix that the static traffic of described optical transfer network carrying is formed, obtain the initial wavelength available of each bearing optical fiber on each bar link between network node simultaneously, then be that each static traffic in static traffic matrix carries out route symmetry according to genetic algorithm, what can make full use of that genetic algorithm has can parallel computation and the advantage of separating more, rises to the efficiency that optical transfer network carries out route symmetry.
In the above embodiment of the present invention, wherein step 103 can be specially:
According to the initial wavelength available of each bearing optical fiber on each bar link between the described network topology information obtained and described network node, structure comprises more than one chromosomal initial population, each chromosome comprises the genome encoding corresponding with each static traffic in described static traffic matrix, it is the link that this static traffic distributes between network node that described genome encoding is included according to network topology information, each bar link is the optical fiber of this static traffic distribution, and be the wavelength of this static traffic distribution in each bar optical fiber, the wavelength distributed for this static traffic is one in the initial wavelength available of described each bearing optical fiber,
Calculate each chromosomal fitness function average in initial population, and according to described initial population, and genetic operator obtains progeny population, described progeny population comprises the chromosome identical with described initial population, calculates each chromosomal fitness function average in progeny population;
Obtaining fitness function average in initial population and progeny population is the chromosome of zero.
As above, chromosome in the embodiment of the present invention comprises the genome encoding corresponding with each static traffic in described static traffic matrix, it is the link that this static traffic distributes between network node that described genome encoding is included according to network topology information, each bar link is the optical fiber of this static traffic distribution, and be the wavelength that this static traffic distributes in each bar optical fiber, each chromosome can be presented as the route symmetry situation that each static traffic in static traffic matrix carries out.
In the above embodiment of the present invention, the chromosome that fitness function average is zero if get from initial population and progeny population, then think in this network topology structure, on each bar link when between given network node when the number of the initial wavelength available of each bearing optical fiber, route symmetry can be realized.Therefore, can be further, rebuild initial population, and according to the initial population rebuild, and genetic operator obtains new progeny population, described new progeny population comprises the chromosome identical with the described initial population rebuild, and obtaining fitness function average in the initial population and new progeny population rebuild is the chromosome of zero.If also got the chromosome that fitness function average is zero, then illustrate after by the decreased number one of initial wavelength available, still achieve route symmetry, reduce the number of wavelength available always, under just can obtaining this network topology structure, it is the minimum wavelength number that every root optical fiber that each static traffic in static traffic matrix carries out needed for route symmetry carries.In the above embodiment of the present invention, wherein the physical topological structure information of optical transfer network can by three element complex G(N, L, C) represent, wherein, N={N
1, N
2, N
3... N
krepresenting the set of network node, K is the number of network node; L={L
1, L
2, L
3... L
mrepresenting the set of link in network, M is the number of link between network node, and above-mentioned each link is two-way link, every each direction of bar link comprises L bar optical fiber, all can carry the wavelength of identical number in every bar optical fiber; C
i, jrepresentative link cost between i-th network node and a jth network node;
In the OTN network intersected based on light, for the rouing and wavelength assignment under static traffic model, its target function can be defined as:
f=min(λ)
The implication of this formula is under static traffic matrix prerequisite, asks minimum wavelength number required when meeting this all traffic assignments route for this static traffic matrix, the several restrictions with giving demand fulfillment following:
A, in the OTN network intersected based on light, each network node comprises termination function and routing function, and so-called termination function can be launched or receiving optical signals exactly, namely realizes/lower road the function of setting out on a journey of business; And routing function is exactly by light signal from source-end networks node-routing to destination network node, namely realize the cross connect function of light signal;
The contrary one-way optical fiber in a pair direction or a bidirectional optical fiber is all comprised between B, the network node that is connected between any two;
C, under static traffic environment, the request granularity of each static traffic be wavelength level other, each static traffic is assigned with a wavelength;
D, consider Wavelength continuity constraint, be the connection that each static traffic is set up, all to meet its route process link on there is identical free wavelength channel.
In the specific embodiment of the invention, wherein genetic algorithm can the content of following several part:
The first, chromosomal coding is determined.
In the embodiment of the present invention, genome encoding, based on business, can use T={T
1, T
2, T
3..., T
wrepresent the set of all static traffics in OTN network, wherein, W is the total number of business in this set.For any one static traffic T in network
i, have a genome encoding t
icorrespond, this genome encoding t
ican be expressed as:
t
i={p
i,f
i,λ
i}
As can be seen from above-mentioned, a genome encoding comprises three elements, wherein p
irepresent the route corresponding to this static traffic Ti, p
istatic traffic T
ia certain bar route in the alternate routing set comprised; f
irepresent this static traffic T
icorresponding optical fiber numbering, λ
irepresent this static traffic T
ithe wavelength numbering used, owing to considering Wavelength continuity constraint, therefore static traffic T
ithe link of its process must use identical wavelength, λ
iwavelength set { λ
1, λ
2, λ
3... λ
win some wavelength.
Be static traffic T
iwhen setting up alternate routing set, can with reference to the following two kinds router-level topology strategy:
Strategy 1: based on the alternate routing calculative strategy of K bar shortest path
Based on source node and the destination node of static traffic, use K bar shortest path (K Shortest Paths, hereinafter referred to as: KSP) strategy, can calculate K bar alternate routing for static traffic, relevant between this K bar alternate routing, but its weighted value is ascending carries out arranging.As shown in Figure 2, suppose that all link weight weight values are identical, then between network node S and network node D, find K bar route, shortest route can be network node S, network node 1 and network node D, secondary short circuit is by being network node S, network node 2, network node 1 and network node D, short circuit is by being meshed network S, node 2, network node 3, network node 1 and network node D again, and these three routes are relevant each other.
Strategy 2: based on the alternate routing calculative strategy of D-algorithm
The source node based on static traffic and destination node equally, repeat to call D-algorithm, before the N time is called D-algorithm, previous used link is deleted from network topology, like this, also can calculate K bar alternate routing for static traffic, but this K bar alternate routing is what it doesn't matter each other, equally, its weighted value is also ascending arranges.Same as Fig. 2, K bar route is found between network node S and network node D, shortest route can be network node S, network node 1 and node D, longest path by being network node S, network node 2, network node 3, network node 4 and network node D, incoherent between these two routes.
Chromosome P
igenome corresponding to all static traffics formed, and can be expressed as:
P
i={t
1,t
2,t
3...,t
W}
In formula is above-mentioned, W represents the maximum number of static traffic.Can know that, because a genome encoding is made up of 3 bit address space, therefore, the address space shared by each chromosome is 3 × W by above-mentioned formula.
The second, fitness function value is calculated
In embodiments of the present invention, different fitness function values is proposed for genome encoding and chromosome.For some static traffic T
icorresponding genome encoding t
i, can f (t be used
i) represent its fitness function, f (t
i) represent static traffic T
iwith the conflict spectrum of other static traffics in network.Such as, static traffic T
iwith static traffic T
jbetween there is conflict on route and wavelength, then f (t
i)=f (t
j)=1, the fitness function value of each genome encoding is one.
For any one chromosome P
i, its fitness function F (P
i) can be expressed as:
Wherein, W represents in individual chromosome, and namely the number of genome encoding equals the number of static traffic in static traffic matrix.As can be seen from above-mentioned formula, chromosomal fitness function value is less, represents in this chromosome, and the mutual conflict spectrum between each genome encoding is less.
Three, initial population is generated
Initial population needs to ensure randomness, in order to avoid whole genetic algorithm is absorbed in locally optimal solution too early.In the genetic algorithm that the embodiment of the present invention proposes, its optimization aim is to meet static traffic requests all in network with minimum wavelength number, and considers specific Wavelength continuity constraint in OTN network simultaneously.
Initial population must be made up of the chromosome of some, initial population G
initcan be expressed as:
G
0=G
init={P
0,P
1,P
2...,P
M-1}
Wherein M represents chromosomal number in initial population.In initial population, chromosomal quantity can not very few can not be too much, the effect of the following race evolution of impact of crossing that I haven't seen you for ages, can not get the optimal solution space of the overall situation, and too much greatly can improve the time complexity of whole algorithm, affect the efficiency of algorithm simulating, preferably, in initial population, chromosomal number can be 6-10.
Each chromosome p in initial population
iinitialization be all made up of genome encoding, such as, at chromosome p
iin, for some genome encoding t
i={ p
i, f
i, λ
i, p
ifrom static traffic T
ithe a certain bar route of Stochastic choice in the alternate routing set comprised; f
ithe optical fiber set { f from link
1, f
2, f
3... f
fmiddle Stochastic choice optical fiber; And λ
ifrom wavelength set { λ
1, λ
2, λ
3... λ
wmiddle Stochastic choice wavelength.
Four, genetic operator is utilized to obtain progeny population
In a particular embodiment of the present invention, three kinds of following different genetic operators are provided selective:
1, selection opertor
Selection course is exactly according to each chromosomal fitness function value, according to certain principle or method, from t for colony G
tsome excellent individual inheritances are selected to G of future generation in (comprising initial population)
t+1in.In genetic algorithm, this step is also called selection opertor.Its effect be from current group, select some more excellent individual replicate in the next generation.Selection opertor used in the present embodiment can be ratio selection opertor, refers to that chromosome body is selected and the fitness function average size being genetic to probability and this chromosome body gone in colony of future generation is inversely proportional to.
Ratio selection opertor is also called disk and selects, by whole disk according to chromosomal fitness function average each in this population inversely proportional be divided into several sectors, if this chromosomal fitness function average is less, central angle then corresponding to this sector is larger, the following possibility of this sector of selecting is larger, and the central angle of this sector determines this chromosome by the probability be genetic in the next generation.
2, crossover operator
So-called intersection is exactly the partial segments in exchange two chromosomes.In fact, the intersection of broad sense not only refers to the exchange of segment, and can be reconfiguring of two chromosomal arbitrary characteristics.By in proposed scheme in step one, each chromosomal length equals 3 times of all static traffic numbers in network, therefore the genome corresponding to any one static traffic is all be made up of the basi gene of 3 in chromosome, for such chromosome, iff exchanging their partial segments simply, the numeral of repetition may be had in the new chromosome then generated, no longer legal chromosome, therefore in the process of carrying out chiasma, preferably whole genome entirety is intersected, instead of the basi gene in each genome is intersected.
As shown in Figure 3, two chromosomes are supposed
with
to crossing operation be carried out, wherein m<n<W, and
represent i-th chromosome P
iin m genome, the genome namely corresponding to m static traffic.Conveniently, by each chromosome, m genome t
mwith the n-th genome t
n(comprise t
mand t
n) between all genomes be all called middle genome, and other genome is called margin gene group, Fig. 3 gives the result schematic diagram of intermediate interdigitated and intersect edge, for two to four genomic codings (0, 0, 1) (1, 1, 0) (2, 1, 0) (1, 1, 2) and (1, 2, 0) (2, 2, 1) (0, 1, 0) (0, 2, 1), intermediate interdigitated is adopted to obtain (0, 0, 1) (2, 2, 1) (0, 1, 0) (1, 1, 2) and (1, 2, 0) (1, 1, 0) (2, 1, 0) (0, 2, 1), intersect edge is adopted to obtain (1, 2, 0) (1, 1, 0) (2, 1, 0) (0, 2, 1) and (0, 0, 1) (2, 2, 1) (0, 1, 0) (1, 1, 2).
3, mutation operator
Mutation process just refers to and to change some genes of individual chromosome in genetic algorithm, and in embodiments of the present invention, because chromosome is made up of genome, therefore, above-mentioned variation is genomic variation mainly.Consider if only simply changed chromosomal some genome encodings, newly-generated chromosome is easy to repeat mutually with other chromosomes in population, therefore, in the present embodiment, the mutation operator adopted comprises two kinds of operators: commutating operator and upset operator.
For i-th chromosome P in population
i={ t
1, t
2, t
3..., t
w, can at [0, W-1] by different integer i and j of Stochastic choice two, the genome corresponding to it is t
iand t
j.
Wherein, commutating operator refers to and exchanges genome t
iand t
jposition; Upset operator upset genome t
iand t
j(comprise t
iand t
j) between all genomic orders; Specifically as shown in Figure 4, for continuous print four genomic codings (0,0,1) (1,1,0) (2,1,0) (1,1,2), commutating operator is adopted to obtain (0,0,1) (2,1,0) (1,1,0) (1,1,2), adopt upset operator to obtain (1,1,2) (2,1,0) (1,1,0) (0,0,1).
Five, genetic algorithm end condition
The race evolution process of genetic algorithm is an iterative process being cycled to repeat calculating, during evolution, likely finds optimal solution space, also likely can not find optimal solution space, therefore, in embodiments of the present invention, each genetic algorithm can terminate in the following two kinds situation:
One is that in this population, some chromosomal fitness function averages are 0 when algorithm evolution is to certain generation population, then think algorithm for all static traffics in static traffic matrix have found suitable route and wavelength, can terminate genetic algorithm; Two are, when genetic algorithm evolves to certain generation population, still not meeting chromosomal fitness function average is the situation of 0, and in this population, all chromosomal average fitness functional values still shake at a certain nonzero value, then think and cannot find optimal solution space, terminate genetic algorithm.
Fig. 5 is the structural representation of the resource allocation device of optical transfer network in the embodiment of the present invention, as shown in Figure 5, this device comprises the first acquisition module 11, second acquisition module 12 and Wavelength Assignment module 13, wherein the first acquisition module 11 is for obtaining the network topology information of optical transfer network, and the static traffic matrix that the static traffic of described optical transfer network carrying is formed, the network topology information of described optical transfer network comprises the network node information in optical transfer network, link information between each network node, and the link cost of each bar link between network node, each bar link between described network node is two-way link, and described each bar link comprises identical number of fibers, second acquisition module 12 is for obtaining the initial wavelength available of each bearing optical fiber on each bar link between network node, Wavelength Assignment module 13 for according to the initial wavelength available of each bearing optical fiber on each bar link between the described network topology information obtained and described network node, is that each static traffic in described static traffic matrix carries out route symmetry according to genetic algorithm.
First the network topology information of optical transfer network is obtained, and the static traffic matrix that the static traffic of described optical transfer network carrying is formed, obtain the initial wavelength available of each bearing optical fiber on each bar link between network node simultaneously, then be that each static traffic in static traffic matrix carries out route symmetry according to genetic algorithm, what can make full use of that genetic algorithm has can parallel computation and the advantage of separating more, rises to the efficiency that optical transfer network carries out route symmetry.
In addition, as shown in Figure 6, the Wavelength Assignment module in the above embodiment of the present invention comprises initial population construction unit 131, genetic computation unit 132, fitness function value computing unit 133 and chromosome acquiring unit 134.Wherein initial population construction unit 131 is for the initial wavelength available according to each bearing optical fiber on each bar link between the described network topology information obtained and described network node, structure comprises more than one chromosomal initial population, each chromosome comprises the genome encoding corresponding with each static traffic in described static traffic matrix, it is the link that this static traffic distributes between network node that described genome encoding is included according to network topology information, each bar link is the optical fiber of this static traffic distribution, and be the wavelength of this static traffic distribution in each bar optical fiber, the wavelength distributed for this static traffic is one in the initial wavelength available of described each bearing optical fiber, genetic computation unit 132 is for according to described initial population, and genetic operator obtains progeny population, and described progeny population comprises the chromosome identical with described initial population, fitness function value computing unit 133 is for calculating initial population, and each chromosomal fitness function average in progeny population, chromosome acquiring unit 134 is the chromosome of zero for obtaining fitness function average in initial population and progeny population.
In the above embodiment of the present invention, intrachromosomal fitness function average is wherein the mean value of the fitness function value of the genome encoding that in this chromosome, each static traffic is corresponding, when the route of distributing for other static traffic volumes in described static traffic distribution route and wavelength and static traffic matrix and Wavelength conflict, the fitness function value of the genome encoding that described static traffic is corresponding is one, when the route of distributing for other static traffics in described static traffic distribution route and wavelength and static traffic matrix and Wavelength conflict, the fitness function value of the genome encoding that described static traffic is corresponding is zero.
In the above embodiment of the present invention, genetic computation unit 132 is specifically for according to initial population, and selection opertor, crossover operator or mutation operator obtain progeny population.
One of ordinary skill in the art will appreciate that: all or part of step realizing above-mentioned each embodiment of the method can have been come by the hardware that program command is relevant.Aforesaid program can be stored in a computer read/write memory medium.This program, when performing, performs the step comprising above-mentioned each embodiment of the method; And aforesaid storage medium comprises: ROM, RAM, magnetic disc or CD etc. various can be program code stored medium.
Last it is noted that above each embodiment is only in order to illustrate technical scheme of the present invention, be not intended to limit; Although with reference to foregoing embodiments to invention has been detailed description, those of ordinary skill in the art is to be understood that: it still can be modified to the technical scheme described in foregoing embodiments, or carries out equivalent replacement to wherein some or all of technical characteristic; And these amendments or replacement, do not make the essence of appropriate technical solution depart from the scope of various embodiments of the present invention technical scheme.
Claims (6)
1. a resource allocation methods for optical transfer network, is characterized in that, comprising:
Obtain the network topology information of optical transfer network, and the static traffic matrix that the static traffic of described optical transfer network carrying is formed, the network topology information of described optical transfer network comprises the network node information in optical transfer network, link information between each network node, and the link cost of each bar link between network node, each bar link between described network node is two-way link, and described each bar link comprises same root optical fiber;
Obtain the initial wavelength available of each bearing optical fiber on each bar link between network node;
According to the initial wavelength available of each bearing optical fiber on each bar link between the described network topology information obtained and described network node, be that each static traffic in described static traffic matrix carries out route symmetry according to genetic algorithm;
The initial wavelength available of each bearing optical fiber on each bar link between described described network topology information according to obtaining and described network node is that each static traffic in described static traffic matrix carries out route symmetry and comprises according to genetic algorithm:
According to the initial wavelength available of each bearing optical fiber on each bar link between the described network topology information obtained and described network node, structure comprises more than one chromosomal initial population, each chromosome comprises the genome encoding corresponding with each static traffic in described static traffic matrix, it is the link that this static traffic distributes between network node that described genome encoding is included according to network topology information, each bar link is the optical fiber of this static traffic distribution, and be the wavelength of this static traffic distribution in each bar optical fiber, the wavelength distributed for this static traffic is one in the initial wavelength available of described each bearing optical fiber,
Calculate each chromosomal fitness function average in initial population, and according to described initial population, and genetic operator obtains progeny population, calculates each chromosomal fitness function average in progeny population;
Obtaining fitness function average in initial population and progeny population is the chromosome of zero;
After to get fitness function average from initial population and progeny population be the chromosome of zero, by the decreased number one of the initial wavelength available of each bearing optical fiber on each bar link between described network node, rebuild initial population, and according to the initial population rebuild, and genetic operator obtains new progeny population, described new progeny population comprises the chromosome identical with the described initial population rebuild, and obtaining fitness function average in the initial population and new progeny population rebuild is the chromosome of zero.
2. the resource allocation methods of optical transfer network according to claim 1, it is characterized in that, described intrachromosomal fitness function average is the mean value of the fitness function value of the genome encoding that in this chromosome, each static traffic is corresponding, when the route of distributing for other static traffic volumes in described static traffic distribution route and wavelength and static traffic matrix and Wavelength conflict, the fitness function value of the genome encoding that described static traffic is corresponding is one, when distributing route that route and wavelength and other static traffics in static traffic matrix distribute for described static traffic and wavelength does not conflict, the fitness function value of the genome encoding that described static traffic is corresponding is zero.
3. the resource allocation methods of optical transfer network according to claim 1, is characterized in that, described according to initial population, and genetic operator acquisition progeny population comprises:
According to initial population, and selection opertor, crossover operator or mutation operator obtain progeny population.
4. a resource allocation device for optical transfer network, is characterized in that, comprising:
First acquisition module, for obtaining the network topology information of optical transfer network, and the static traffic matrix that the static traffic of described optical transfer network carrying is formed, the network topology information of described optical transfer network comprises the network node information in optical transfer network, link information between each network node, and the link cost of each bar link between network node, each bar link between described network node is two-way link, and described each bar link comprises identical number of fibers;
Second acquisition module, for obtaining the initial wavelength available of each bearing optical fiber on each bar link between network node;
Wavelength Assignment module, for according to the initial wavelength available of each bearing optical fiber on each bar link between the described network topology information obtained and described network node, be that each static traffic in described static traffic matrix carries out route symmetry according to genetic algorithm;
Described Wavelength Assignment module comprises:
Initial population construction unit, for the initial wavelength available according to each bearing optical fiber on each bar link between the described network topology information obtained and described network node, structure comprises more than one chromosomal initial population, each chromosome comprises the genome encoding corresponding with each static traffic in described static traffic matrix, it is the link that this static traffic distributes between network node that described genome encoding is included according to network topology information, each bar link is the optical fiber of this static traffic distribution, and be the wavelength of this static traffic distribution in each bar optical fiber, the wavelength distributed for this static traffic is one in the initial wavelength available of described each bearing optical fiber,
Genetic computation unit, for according to described initial population, and genetic operator obtains progeny population;
Fitness function value computing unit, for calculating initial population, and each chromosomal fitness function average in progeny population;
Chromosome acquiring unit is the chromosome of zero for obtaining fitness function average in initial population and progeny population;
3rd acquisition module, for after to get fitness function average from initial population and progeny population be the chromosome of zero, by the decreased number one of the initial wavelength available of each bearing optical fiber on each bar link between described network node; Described initial population construction unit is further used for rebuilding initial population, described genetic computation unit is further used for the initial population according to rebuilding, and genetic operator obtains new progeny population, described new progeny population comprises the chromosome identical with the described initial population rebuild, and it is the chromosome of zero that described chromosome acquiring unit is further used for obtaining fitness function average in the initial population and new progeny population rebuild.
5. the resource allocation device of optical transfer network according to claim 4, it is characterized in that, described intrachromosomal fitness function average is the mean value of the fitness function value of the genome encoding that in this chromosome, each static traffic is corresponding, when the route of distributing for other static traffic volumes in described static traffic distribution route and wavelength and static traffic matrix and Wavelength conflict, the fitness function value of the genome encoding that described static traffic is corresponding is one, when the route of distributing for other static traffics in described static traffic distribution route and wavelength and static traffic matrix and Wavelength conflict, the fitness function value of the genome encoding that described static traffic is corresponding is zero.
6. the resource allocation device of optical transfer network according to claim 4, is characterized in that, described genetic computation unit is specifically for according to initial population, and selection opertor, crossover operator or mutation operator obtain progeny population.
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| CN109429117B (en) * | 2017-08-30 | 2021-12-07 | 中国移动通信集团设计院有限公司 | Routing method and device |
| CN107566926B (en) * | 2017-09-21 | 2019-08-13 | 烽火通信科技股份有限公司 | The calculation method of relay resource is distributed in a kind of planning of optical transport network |
| CN111131032B (en) * | 2018-10-31 | 2021-12-28 | 中兴通讯股份有限公司 | Network path optimization method and device, computer equipment and storage medium |
| CN112367572B (en) * | 2020-10-27 | 2021-07-06 | 西安电子科技大学 | Multi-target RSCA method based on fiber core variability in elastic optical network |
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