CN107395426A - A kind of communication network architecture optimization method that probability is used based on node - Google Patents
A kind of communication network architecture optimization method that probability is used based on node Download PDFInfo
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- CN107395426A CN107395426A CN201710662420.XA CN201710662420A CN107395426A CN 107395426 A CN107395426 A CN 107395426A CN 201710662420 A CN201710662420 A CN 201710662420A CN 107395426 A CN107395426 A CN 107395426A
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- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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- H04L41/12—Discovery or management of network topologies
Abstract
The present invention relates to a kind of communication network architecture optimization method that probability is used based on node, passes through the index C of hereditary reconnection side optimization method reduction communication networkmax, obtain the solution of approximate global optimum.Wherein, hereditary reconnection side optimization process following steps：S1, coding and the initial parameter that genetic optimization process is set；S2, initialization network individual；S3, selection remain into follow-on individual；S4, mating obtain new individual；S5, variation obtain the new individual that makes a variation；S6, the fitness index for calculating M network individual, iterative step S3 S5, until meeting end condition, export CmaxMinimum network individual, optimization terminate.The present invention can improve the communications performance of network to greatest extent on the premise of ensureing communications efficiency and need not increase extra communication transmission media or port.
Description
Technical field
The present invention relates to the technical field of the network optimization, more particularly to a kind of communication network that probability is used based on node
Structural optimization method.
Background technology
Computer and communications network system are one of mostly important infrastructure of today's society.Wherein, internet
(Internet) technological breakthrough of high speed development and cordless communication network is to the life style of people and the leather of industry
Newly bring far-reaching influence.
With the high speed development of social demand, communication network and Internet scale and data transfer loads constantly increase
Greatly.But communication network and Internet be while transmission bulk information amount is carry, the problem of traffic congestion but all the time without
Method avoids.Traffic congestion first occurs at the local nodes of communication network, is gradually diffused into other nodes of network, and passes through level
Connection effect causes the local paralysis of communication network.Therefore, the efficiency of transmission and effectively of data in communication network how is improved
Alleviate network congestion and have become one of great difficult problem of Nowadays communication networks industrial quarters.
Internet be one be made up of numerous computers, router, communication transmission media, other communication equipments it is huge
Network, information reach another computer in network from a computer via multiple routers and transmission medium.
Internet network structure is broadly divided into route (router), subnet (subnet), domain (domain) and autonomous system
(autonomous system, abbreviation AS) four-layer structure.For each Rotating fields, Internet can be abstracted as by one group
The network system that the company side connected each other between node and node is formed.Past research have shown that Internet and communication network
There is network etc. worldlet and uncalibrated visual servo characteristic, Faloutsos et al. to find Internet degree series (degree sequence)
Power-law distribution is obeyed in distribution, and there are some researches show the topological structure of the information transmission performance of communication network and network has very
Big correlation.
In past research, the transmittability for improving communication network and the method for alleviating network congestion are broadly divided into " hard side
Method " and " soft method " two class." soft method " refers to design effective routing algorithm on the basis of network topology structure is not changed,
And " hard method " is then to improve the transmission performance of network by changing the topological structure of network.Wherein improve network transmission performance
" hard method " two classes can be classified as, be " active " strategy respectively and " passive " tactful." active " strategy is generally used for as network
System design has the network topology structure of high-transmission characteristic.R.Guimera's et al. researchs and proposes, when the information of communication network
When transmission quantity is very big, the topological structure of network should be designed as uniform, isotropic (homogeneous-isotropic)
Network structure；On the contrary, when the transinformation of communication network is smaller, network should be designed as star (star-like) net
Network structure." passive " strategy be generally used for being adjusted the structure of existing communication network with improve the transmission performance of network and
Alleviate transmission congestion, including delete while dilatation and increase while dilatation strategy.Side dilatation strategy is deleted by removing between magnanimous node
Company side alleviate network congestion situation, and increase small to reduce when dilatation strategy is then by increasing even between small degree node
The information transfer distance spent between node, so as to improve information transfer efficiency and alleviate the congestion situation of network.
But " active " strategy for improving network transmission performance at present is only to be provided for design communication network topology structure
Qualitatively instruct, be not provided with specific method be used for design obey the network that specific degree series are distributed.And delete side dilatation plan
Slightly while the congestion situation of existing network is alleviated, the transmission range between nodes and node can be increased, cause letter
Ceasing efficiency of transmission reduces.Use increasing side dilatation strategy then needs for communication to improve the transmittability of network and alleviate congestion situation
Network additionally increases communication transmission media or transmission port, but in most cases the port number of nodes is fixed
Limited, therefore need extra cost using this policy optimization network.
Above-mentioned deletes the dilatation strategy in dilatation and increasing, occurs that reduction communications efficiency and needs increase are extra respectively
Communication transmission media or the defects of port, and be all not used to the high transformation property net that specific degree series distribution is obeyed in design
Network.
The content of the invention
It is an object of the invention to overcome the deficiencies of the prior art and provide one kind to ensure communications efficiency and need not increase
Can be improved to greatest extent on the premise of adding extra communication transmission media or port the communications performance of network based on section
Point uses the communication network architecture optimization method of probability.
To achieve the above object, technical scheme provided by the present invention is as follows：
When transinformation increase in network, a transformation temperature be present so that network is changed into congestion shape from unimpeded state
State.The communications load of network can be weighed with packet generation rate λ, be embodied as in the unit interval average each section
Number of data packets caused by point.Define the critical data bag generation rate λ when network is changed into congestion state by unimpeded statecFor
The message transmission capability of the network.As λ ＜ λcWhen, network is in unimpeded state；As λ ＞ λ, network is in congestion state.Separately
One index of transmission performance for being used for weighing communication network is information transfer efficiency, can use the flat of nodes and node
Equal distanceTo represent.When the average distance of networkWhen excessive, information from a main frame be sent to another main frame when, it is necessary to
By multiple routers, thus the information transfer efficiency of network is low.However, in most cases, the information for improving network passes
The information transfer efficiency of network can be had influence on while Movement Capabilities to a certain degree, vice versa.Propose and be based on for this this programme
The transmission performance optimization index C that node is derived from using probabilitymax, when using the index optimization communication network, can examine simultaneously
Consider the transmittability and efficiency of transmission of network.
Understand that node is using probability U (i) expression formula：
Critical data bag generation rate λcIt is expressed as：
Wherein, V be network in all nodes set, if node i in node u and node w routed path, σuw
(i)=1, conversely, σuw(i)=0, routing algorithm here is considered most basic shortest path first；Defining C (i) in addition is
Number in path in network between any two node Jing Guo node i：
C (i)=∑u,w∈V,u≠w≠iσuw(i)；
If CmaxFor the maximum in the C (i) of all nodes.It can be derived from formula above, the index of communication network
CmaxAnd average distanceAnd critical data bag generation rate λcIt is respectively present below equation relation：
From derivation result, the λ of network capacity is characterizedcWith CmaxIt is inversely proportional, and average distanceAnd maximum node
Use probability UmaxProduct and CmaxIt is directly proportional.CmaxReduction can makeReduce, increase so as to suppress the average distance of network
Greatly, therefore this programme is by reducing the C of communication networkmaxIndex improves the transmittability of network while ensures efficiency of transmission not
It is impacted.
Further, in order to improve network transmittability while, keep the information transfer efficiency of network substantially not
Optimizing index C impacted, that this programme is derived based on node using probabilitymax, reduced by hereditary reconnection side optimization method logical
The index C of communication networkmax, obtain the solution of approximate global optimum.
Further, the hereditary reconnection side optimization method reduces the index C of communication networkmax, obtain approximate global optimum
Solution, process is：
S1, coding and the initial parameter that genetic optimization process is set：
The network for company's side composition communication network being abstracted between a group node and node and node, according to network
Figure establishes communications model, using all even sides of network as the coding of a network plan, sets genetic algorithm optimization mistake
The initial parameter of journey, including the gene dosage N of population scale M, chromosome, mating rate P, aberration rate Q.
S2, initialization network individual：
More opposite side of a network are randomly selected, to each opposite side eijAnd ekl, the connection side of two side interior joints of exchange
Formula, two sides are e after obtaining reconnectionilAnd ekj, and judge whether the network behind reconnection side meets constraints；
The constraints for needing to meet has two：
1) network behind reconnection side remains as connected graph；
2) when repetition is not present in two pairs of nodes of the reconnection after.
Connected graph refers to that arbitrary two nodes in network are all reachable, by using Depth Priority Algorithm
(DFS) node in traverses network, so as to judge whether the network behind reconnection side meets the constraints of connected graph.
If the network behind reconnection side is unsatisfactory for two above constraints, reconnection side operation is cancelled, again random choosing
Two are selected to operate when swapping.For one in the network that number is N, it is necessary to operated when performing the random reconnection of N/2 times, obtain
To a network individual scheme.
Assuming that each node in network stores the global Topological Structure information of network, then net can be calculated
The routed path of any two node in network.A plurality of routed path is there may be between any two node, it is assumed that two nodes
Between all packets transmission all only can pass through a specific routed path., can be with by taking shortest route routing algorithm as an example
The shortest route path of any two node is calculated by dijkstra's algorithm, so as to which the C (i) of each node be calculated
Value.Choose C of maximum C (i) values as networkmax, with 1/CmaxAs fitness function Cmax, bigger, network-adaptive degree is got over
It is small.Initialize the fitness of M network plan.
S3, selection remain into follow-on individual：
Using roulette strategy, the ratio that individual adaptation degree accounts for colony's fitness summation is calculated, takes the random number of [0,1],
The bound determination for comparing cumulative frequency section is chosen to follow-on individual, and fitness is bigger, and the selected probability of individual is got over
Greatly.
S4, mating obtain new individual：
Random pair is carried out to the individual in population according to mating rate, to two individuals of pairing, randomly selects two
The coding site of body swaps；The individual after coding site is exchanged as new individual, retains the individual before exchanging；And exchange
Latter two new individual of position must is fulfilled for the constraints of network, otherwise cancels the operation.Obtained new network individual adds
To among population.
S5, variation obtain the new individual that makes a variation：
The number of variation individual is drawn according to aberration rate, after the step that mates, individual is randomly selected and enters row variation, and judge
Whether network meets constraints after variation, if being unsatisfactory for constraints, re-executes the operation of reconnection side.One network
The degree of variation of the gene code of individual can specifically determine according to the scale of network.
Variation detailed process be：More opposite side of a network are randomly selected, to each opposite side eijAnd ekl, exchange two sides
The connected mode of interior joint, two sides are e after obtaining reconnectionilAnd ekj。
Obtained variation new individual is inserted into colony.
S6, the fitness index for calculating M network individual, iterative step S3-S5, until meeting end condition, export Cmax
Minimum network individual, optimization terminate.
Compared with prior art, this programme principle and advantage is as follows：
1. by using genetic algorithm, ensure communication network after topological structure optimization, the topological structure of network is approximate
Global optimum, so as to improve the communications ability of communication network to greatest extent.
2. the optimizing index C derived based on node using probabilitymax, reduce communication network by way of reconnection side
Index Cmax, while the transmittability of network is improved the information transfer efficiency of network can be kept to be substantially unaffected.
3. the physical port quantity of the router and main frame in communication network is fixed, therefore is each saved in communication network
The degree of point can not arbitrarily change, and reconnection side optimisation strategy can ensure communication network after topological structure optimization, every in network
The degree of individual node all keeps constant, meets constraints of the communication network in actual scene.
4. topological structure optimization is carried out to communication network using reconnection side optimisation strategy, the degree series of network point before and after optimization
Cloth keeps constant, can be used to optimize different types of network topology structure.
Brief description of the drawings
Fig. 1 is the flow chart of heredity reconnection of embodiment of the present invention side optimization；
Schematic diagram when Fig. 2 is network reconnection of heredity of the embodiment of the present invention reconnection in optimization；
Fig. 3 is roulette strategy schematic diagram in the optimization of heredity reconnection of embodiment of the present invention side；
Fig. 4 is to exchange position coding gene process schematic in the optimization of heredity reconnection of embodiment of the present invention side；
Fig. 5 is communications ability comparison diagram before and after the network optimization.
Embodiment
With reference to specific embodiment, the invention will be further described：
A kind of communication network architecture optimization method that probability is used based on node described in the present embodiment, passes through hereditary reconnection
C in side optimization networkmaxIndex, it is tended to be minimum, ensure transmission while the transmittability of network so as to improve to greatest extent
Efficiency is not influenceed by excessive.
Referring to shown in accompanying drawing 1, hereditary reconnection side optimization method reduces the index C of communication networkmax, obtain the approximate overall situation most
Excellent solution, process are：
S1, coding and the initial parameter that genetic optimization process is set：
The network for company's side composition communication network being abstracted between a group node and node and node, according to network
Figure establishes communications model, using all even sides of network as the coding of a network plan, sets genetic algorithm optimization mistake
The initial parameter of journey, including the gene dosage N of population scale M, chromosome, mating rate P, aberration rate Q.
S2, initialization network individual：
As shown in Fig. 2 more opposite side of a network are randomly selected, to each opposite side eijAnd ekl, exchange two side interior joints
Connected mode, two sides are e after obtaining reconnectionilAnd ekj, and it is following two to judge whether the network behind reconnection side meets
Constraints：
1) network behind reconnection side remains as connected graph；
2) when repetition is not present in two pairs of nodes of the reconnection after.
If the network behind reconnection side is unsatisfactory for two above constraints, reconnection side operation is cancelled, again random choosing
Two are selected to operate when swapping.For one in the network that number is N, it is necessary to operated when performing the random reconnection of N/2 times, obtain
To a network individual scheme.
The shortest route path of any two node is calculated by dijkstra's algorithm, so as to which each section be calculated
C (i) values of point.Choose C of maximum C (i) values as networkmax, with 1/CmaxAs fitness function Cmax, bigger, network is fitted
Response is smaller.Initialize the fitness of M network plan.
S3, selection remain into follow-on individual：
Using roulette strategy, the ratio that individual adaptation degree accounts for colony's fitness summation is calculated, takes the random number of [0,1],
The bound determination for comparing cumulative frequency section is chosen to follow-on individual, and fitness is bigger, and the selected probability of individual is got over
Greatly.Specially：
(1 calculates fitness f (i)=1/C of each network planmax, it is genetic to down so as to calculate each network plan
The probability of a generation：
(2 calculate each individual cumulative probability：
(3 take the random number of [0,1], and the bound for comparing cumulative frequency section determines to be chosen to follow-on network side
Case, as shown in Figure 3.One network plan may be selected multiple times, but be genetic to follow-on individual and only occurred once.
S4, mating obtain new individual：
Random pair is carried out to the individual in population according to mating rate, to two individuals of pairing, randomly selects two
The coding site of body swaps；The individual after coding site is exchanged as new individual, retains the individual before exchanging；And exchange
Latter two new individual of position must is fulfilled for the constraints of network, otherwise cancels the operation.Specially：
(1) randomly select two individuals according to mating rate to be matched, mating rate is about between 0.6-1.Such as Fig. 4 institutes
Show, for network A and network B, a line e is randomly selected from network AijIf side eijExist in network B, then in network A
In randomly select another a line again, until this edge is not present in network B；
(2) another a line e is chosen in network Alk, disconnect side eijWith side elk, reconnection e when obtainingilAnd ekj, and judge
Whether network meets connected graph and without two, side constraints is repeated, and is unsatisfactory for constraints and then re-executes the operation；
(3) node i and node j two neighbor node u and node v are randomly selected respectively in network B, disconnects side eiuWith
Side ejv, reconnection e when obtainingijAnd euv, and judge whether network meets connected graph and without two, side constraints is repeated, it is discontented with
Sufficient constraints then re-executes the operation；
(4) after above two steps, network A and network B have exchanged position coding gene, obtain two new nets
Network scheme individual, new network individual is added among population.
Between two networks exchange position coding gene number can specifically be determined according to the scale of network, mated
Journey can ensure the ability of global search solution so that the search to solution is intended to preferably region.
S5, variation obtain the new individual that makes a variation：
The number of variation individual is drawn according to aberration rate, after the step that mates, individual is randomly selected and enters row variation, and judge
Whether network meets constraints after variation, if being unsatisfactory for constraints, re-executes the operation of reconnection side.One network
The degree of variation of the gene code of individual can specifically determine according to the scale of network.
Variation detailed process be：More opposite side of a network are randomly selected, to each opposite side eijAnd ekl, exchange two sides
The connected mode of interior joint, two sides are e after obtaining reconnectionilAnd ekj。
Obtained variation new individual is inserted into colony.
S6, the fitness index for calculating M network individual, iterative step S3-S5, until meeting end condition, export Cmax
Minimum network individual, optimization terminate.
End condition in the present embodiment is：When the maximum value of the fitness of optimization program search keeps subsequent iteration number
K does not change.
As shown in figure 5, compared with the network of original state, after optimizing by the present embodiment, Internet AS layer networks
It is respectively increased with the communications ability of BA scales-free networks as original 510% and 360%.Absolutely prove the heredity of the present invention
Reconnection side optimisation strategy can increase substantially the communications performance of network.
Examples of implementation described above are only the preferred embodiments of the invention, and the implementation model of the present invention is not limited with this
Enclose, therefore the change that all shape, principles according to the present invention are made, it all should cover within the scope of the present invention.
Claims (7)
- A kind of 1. communication network architecture optimization method that probability is used based on node, it is characterised in that：It is excellent by hereditary reconnection side Change C in networkmaxIndex, it is tended to be minimum, ensure efficiency of transmission while the transmittability of network so as to improve to greatest extent Do not influenceed by excessive.
- 2. a kind of communication network architecture optimization method that probability is used based on node according to claim 1, its feature are existed In：C in the hereditary reconnection side optimization networkmaxIndex, it is tended to be minimum, comprise the following steps that：S1, coding and the initial parameter that genetic optimization process is set；S2, initialization network individual；S3, selection remain into follow-on individual；S4, mating obtain new individual；S5, variation obtain the new individual that makes a variation；S6, the fitness index for calculating M network individual, iterative step S3-S5, until meeting end condition, export CmaxIt is minimum Network individual, optimization terminates.
- 3. a kind of communication network architecture optimization method that probability is used based on node according to claim 2, its feature are existed In：The step S1 is specially：The net for company's side composition communication network being abstracted between a group node and node and node Network figure, communications model is established according to network, using all even sides of network as the coding of a network plan, set and lose The initial parameter of propagation algorithm optimization process, including the gene dosage N of population scale M, chromosome, mating rate P, aberration rate Q.
- 4. a kind of communication network architecture optimization method that probability is used based on node according to claim 2, its feature are existed In：The step S2 is specially：More opposite side of a network are randomly selected, to each opposite side eijAnd ekl, exchange and saved in two sides The connected mode of point, two sides are e after obtaining reconnectionilAnd ekj, and judge whether network meets to constrain bar behind reconnection side Part；If not satisfied, then cancel reconnection side operation；M network individual scheme, meter are generated using the method on above-mentioned random reconnection side Calculate the index C of M initial networkmax, 1/CmaxAs fitness function, CmaxBigger, fitness is smaller.
- 5. a kind of communication network architecture optimization method that probability is used based on node according to claim 2, its feature are existed In：The step S3 is specially：Using roulette strategy, the ratio that individual adaptation degree accounts for colony's fitness summation is calculated, take [0, 1] random number, the bound determination for comparing cumulative frequency section are chosen to follow-on individual, and fitness is bigger, individual quilt Choose probability bigger.
- 6. a kind of communication network architecture optimization method that probability is used based on node according to claim 2, its feature are existed In：The step S4 is specially：Random pair is carried out to the individual in population according to mating rate, to two individuals of pairing, with Machine is chosen two individual coding sites and swapped；The individual after coding site is exchanged as new individual, is retained before exchanging Individual；And the constraints that latter two new individual of position must is fulfilled for network is exchanged, otherwise cancel the operation；What is obtained is new Network individual is added among population.
- 7. a kind of communication network architecture optimization method that probability is used based on node according to claim 2, its feature are existed In：The step S5 is specially：The number of variation individual is drawn according to aberration rate, after the step that mates, individual is randomly selected and enters Row variation, and judge whether network meets constraints after variation, if being unsatisfactory for constraints, re-execute reconnection side Operation；Variation detailed process be：More opposite side of a network are randomly selected, to each opposite side eijAnd ekl, exchange two side interior joints Connected mode, two sides are e after obtaining reconnectionilAnd ekj；Obtained variation new individual is inserted into colony.
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| CN109508779A (en) * | 2018-11-09 | 2019-03-22 | 重庆化工职业学院 | A kind of energy-saving control method of municipal road lamp |
| CN109746918A (en) * | 2019-02-14 | 2019-05-14 | 中山大学 | A kind of optimization method of the cloud robot system delay of combined optimization |
| CN110491456A (en) * | 2019-08-27 | 2019-11-22 | 中南大学 | A kind of medical data transmission method and equipment |
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