CN109194577A - A kind of traffic engineering method and device of the Segment routing network based on partial deployment - Google Patents
A kind of traffic engineering method and device of the Segment routing network based on partial deployment Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L45/00—Routing or path finding of packets in data switching networks
- H04L45/02—Topology update or discovery
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H—ELECTRICITY
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- H04L45/00—Routing or path finding of packets in data switching networks
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- H04L45/123—Evaluation of link metrics
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L45/00—Routing or path finding of packets in data switching networks
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- H04L45/124—Shortest path evaluation using a combination of metrics
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04L45/38—Flow based routing
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Abstract
The traffic engineering method and device of this application discloses a kind of Segment routing network based on partial deployment；Above-mentioned traffic engineering method, comprising: obtain the network topology and traffic matrix of Segment routing network；By successive ignition operation, the maximum link utilization of the minimum of Segment routing network is determined；Wherein, in each interative computation, according to network topology and traffic matrix, determine the network link weight matrix and Segment routing node set that this search obtains, the available path for determining in this operation in the maximum link utilization, traffic matrix of the minimum of Segment routing network every stream according to this obtained network link weight matrix of search and Segment routing node set and the optimal split ratio on available path.The application can be realized the maximum link utilization for minimizing Segment routing network.
Description
Technical field
This application involves but be not limited to Technology of Traffic Engineering field, it is espespecially a kind of based on partial deployment Segment routing (SR,
Segment Routing) network traffic engineering method and device.
Background technique
As internet develops rapidly, there is the problems such as network flow explosive growth in internet.In addition, audio-video industry
The continuous development of business also proposes the requirement of service quality to internet.It is limited to routing algorithm and scheduling strategy, network flow
Easily distribution is uneven on the link, declines so as to cause network congestion and network service quality.How limited net is made full use of
Network resource avoids network congestion, while meeting flow reliable transmission and service by rational management to network flow and distribution
The requirement of quality etc. is a urgent problem to be solved.
Traffic engineering (TE, Traffic Engineering) is a kind of technology of optimization network flow distribution, can be to net
The scheduling of network flow optimization reduces congestion, improves the utilization rate of Internet resources to realize network traffic load equilibrium.
In conventional network protocols (IP, Internet Protocol) network, router usually runs OSPF (Open
Shortest Path First, ospf) or IS-IS (Intermediate System to
Intermediate System, Intermediate System-to-Intermediate System) distributed Interior Gateway Protocol.This kind of Routing Protocol, according to
The weight calculation of each of the links goes out the shortest path between any two node, data packet along source point to point of destination shortest path into
Walking along the street by.Network administrator optimizes flow path by the reasonable disposition to link weight, realizes traffic engineering target.However,
Since the routing mode of IP network is too simple, IP network can not provide best solution for traffic engineering.
The appearance of software defined network (Software Define Network, SDN) provides cleverer for traffic engineering
Mode living.The framework of SDN is divided into data plane layer, controls plane layer and three layers of application layer, realizes point of control and forwarding
From.Data plane layer only has the forwarding capability of data packet, and control plane layer is a SDN Centralized Controller, and application layer is one
A little SDN service applications.SDN Centralized Controller establishes connection by southbound interface and data plane layer, and SDN service application is called
The northbound interface that SDN Centralized Controller provides realizes correlation function.The traffic engineering of SDN, which is applied, is located at application layer, passes through SDN collection
Middle controller issues flow table to the interchanger of data plane layer, realizes the control to data plane layer forwarding behavior and flow path
System.However, the flow table number of interchanger is easily more than flow table capacity limit, scalability in the biggish situation of network size
It is poor.
Segment routing (SR, Segment Routing) is a kind of most emerging source routing mechanism, it is only needed to existing
IGP (Interior Gateway Protocol, Interior Gateway Protocol), which carries out simple extension, just can be applicable to IP/MPLS
(Multiprotocol Label Switching, multiprotocol label switching) or IPv6 (Internet Protocol
Version 6, Internet protocol the 6th edition) in network.In SR network, the state of every stream is merely stored in the entrance section in the domain SR
In point, intermediate node does not need the status information of storage stream, therefore has high scalability.It is simple, easy in view of SR
The advantages that disposing, is expansible, the traffic engineering algorithm based on SR has become the hot issue in traffic engineering research.However,
It is difficult or even infeasible for directly migrating to full SR network from Pure IP network.
Summary of the invention
The embodiment of the present application provides a kind of traffic engineering method and device of SR network based on partial deployment, can be most
The maximum link utilization of smallization SR network.
On the one hand, the embodiment of the present application provides a kind of traffic engineering method of Segment routing network based on partial deployment,
It include: the network topology and traffic matrix for obtaining Segment routing network；By successive ignition operation, the Segment routing is determined
The maximum link utilization of the minimum of network；Wherein, it is carried out the following processing respectively in each interative computation: according to the network
Topology, the optimal network link weight matrix searched before and preset resetting ratio determine what this search obtained
Network link weight matrix；The network link weight matrix obtained according to the network topology, the traffic matrix, this search
And the deployment rate of Segment routing node, determine the Segment routing node set of this selection；According to the network topology, described
The Segment routing node set of traffic matrix, the network link weight matrix that this search obtains and this selection, determines this
The maximum link utilization of the minimum of Segment routing network described in secondary operation, every available road flowed in the traffic matrix
Diameter and the optimal split ratio on the available path；When the number of iterations be equal to preset times, then will be in successive ignition operation
The minimum value of obtained maximum link utilization is determined as the maximum link utilization of the minimum of the Segment routing network；When
The number of iterations is less than the preset times, then executes next iteration operation.
On the other hand, the embodiment of the present application provides a kind of traffic engineering dress of Segment routing network based on partial deployment
It sets, comprising: module is obtained, suitable for obtaining the network topology and traffic matrix of Segment routing network；Processing module, suitable for passing through
Successive ignition operation determines the maximum link utilization of the minimum of the Segment routing network；Wherein, the processing module packet
It includes: network link weight matrix search unit, suitable for being carried out the following processing in each interative computation: being opened up according to the network
The optimal network link weight matrix flutter, searched before and preset resetting ratio determine that this searches for obtained net
Network link weight matrix；Segment routing node set selecting unit, suitable for being carried out the following processing in each interative computation: according to
The portion of network link weight matrix and Segment routing node that the network topology, the traffic matrix, this search obtain
Administration's rate determines the Segment routing node set of this selection；Linear programming optimizes unit, suitable for carrying out in each interative computation
Handle below: according to the network topology, the traffic matrix, this obtained network link weight matrix of search and this
The Segment routing node set of selection determines that the maximum link of the minimum of Segment routing network described in this operation utilizes
Every available path flowed and the optimal split ratio on the available path in rate, the traffic matrix；Iteration judgement is single
Member is suitable for being equal to preset times when the number of iterations, then by the minimum value of maximum link utilization obtained in successive ignition operation
It is determined as the maximum link utilization of the minimum of the Segment routing network；When the number of iterations is less than described default time
Number, then notify the network link weight matrix search unit, the Segment routing node set selecting unit and the line
Property plan optimization unit execute next iteration operation.
In another aspect, the embodiment of the present application provides a kind of terminal, comprising: memory and processor, the memory storage
There is the traffic engineering program of the Segment routing network based on partial deployment, when the traffic engineering program is executed by the processor
The step of realizing the traffic engineering method of the above-mentioned Segment routing network based on partial deployment.
In another aspect, the embodiment of the present application provides a kind of computer-readable medium, it is stored with the segmentation based on partial deployment
The traffic engineering program of route network, the traffic engineering program realize above-mentioned point based on partial deployment when being executed by processor
The step of traffic engineering method of section route network.
In the embodiment of the present application, in the SR network of partial deployment, complex optimum network link weight matrix, deployment
Every available path flowed and the optimal split ratio on available path in SR node set, traffic matrix, to minimize
The maximum link utilization of SR network.
Other features and advantage will illustrate in the following description, also, partly become from specification
It obtains it is clear that being understood and implementing the application.The purpose of the application and other advantages can be by specifications, right
Specifically noted structure is achieved and obtained in claim and attached drawing.
Detailed description of the invention
Attached drawing is used to provide to further understand technical scheme, and constitutes part of specification, with this
The embodiment of application is used to explain the technical solution of the application together, does not constitute the limitation to technical scheme.
Fig. 1 is an exemplary diagram of SR routing procedure；
Fig. 2 is the flow chart of the traffic engineering method of the SR network provided by the embodiments of the present application based on partial deployment；
Fig. 3 is the exemplary diagram of the SR network of the partial deployment of spot style deployment；
Fig. 4 is the sample calculation figure of the maximum link utilization of node；
Fig. 5 is the stage schematic diagram of the linear programming optimization algorithm in the present embodiment；
Fig. 6 is the sample calculation figure of the subpath in the present embodiment；
Fig. 7 is the exemplary diagram of the available path in the present embodiment；
Fig. 8 is to apply demonstration effect figure using traffic engineering method provided in this embodiment；
Fig. 9 is the schematic diagram of the traffic engineering device of the SR network provided in this embodiment based on partial deployment；
Figure 10 is the schematic diagram of terminal provided in this embodiment.
Specific embodiment
Embodiments herein is described in detail below in conjunction with attached drawing.It should be noted that in the feelings not conflicted
Under condition, the features in the embodiments and the embodiments of the present application can mutual any combination.
Step shown in the flowchart of the accompanying drawings can be in a computer system such as a set of computer executable instructions
It executes.Also, although logical order is shown in flow charts, and it in some cases, can be to be different from herein suitable
Sequence executes shown or described step.
In SR network, what section represented is topology or a kind of instruction based on service, there is prefix section, node section, adjacent segments
Etc. classifications.Node section is only related in the embodiment of the present application.Logical path end to end can be divided into section by the Ingress node in the domain SR, so
The intermediate node passed through is needed to indicate this paths by a series of afterwards.Fig. 1 is the schematic diagram of an example of SR routing procedure.
Wherein, ingress router is encapsulated into section label stack (such as MPLS label stack) in packet header, to show what data packet need to flow through
Fullpath.What each segment mark label represented here is an intermediate node, and stack top label is effective and is used to refer to data packet
Forward-path.As shown in Figure 1, data packet reaches M along shortest path routing from S point, according to IGP agreement1Point.Reach M1Point
Afterwards, stack top label M1It is ejected, data packet is by reaching next label M2.Final all labels are ejected, and then data packet arrives
Up to egress router D.
Due to from Pure IP network directly migrate to full SR network be it is difficult or even infeasible, using soft migration
Method, i.e., only by some routers in IP network upgrade to support SR router, can greatly improve operation feasibility and
Simplicity.
The embodiment of the present application provides a kind of traffic engineering method and device of SR network based on partial deployment, by portion
In the SR network of administration of branch, complex optimum network link weight matrix, SR node set and flow path reach and minimize SR
The maximum link utilization of network.
Fig. 2 is the flow chart of the process engineering method of the SR network provided by the embodiments of the present application based on partial deployment.This
The traffic engineering method that embodiment provides can be held by the terminal (for example, desktop computer or notebook computer) independently of SR network
Row.However, the application does not limit this.
As shown in Fig. 2, the traffic engineering method of the SR network provided in this embodiment based on partial deployment, including following step
It is rapid:
Step 201, the network topology and traffic matrix for obtaining Segment routing (SR) network；
Then, by successive ignition operation, the maximum link utilization of the minimum of SR network is determined；Wherein, every time repeatedly
It is carried out the following processing respectively in operation:
Step 202, the optimal network link weight matrix searched according to network topology, before and preset resetting
Ratio determines that this searches for obtained network link weight matrix；
Step 203, the network link weight matrix obtained according to network topology, traffic matrix, this search and SR are saved
The deployment rate of point determines the SR node set of this selection；
Step 204, according to network topology, traffic matrix, this obtained network link weight matrix of search and this
The SR node set of selection determines every in the maximum link utilization, traffic matrix of the minimum of the SR network in this operation
The available path of item stream and the optimal split ratio on available path；
Step 205, when the number of iterations be equal to preset times, then by maximum link utilization obtained in successive ignition operation
Minimum value be determined as the SR network minimum maximum link utilization；
When the number of iterations be less than preset times, then execute next iteration operation, i.e. return step 202.
In the present embodiment, the network topology of SR network may include node set V and directed link collection in SR network
Close E.Traffic matrix in SR network indicates the set for the flow demand that network must be handled whithin a period of time；Traffic matrix
In share L item stream, the stream refers to the polymerization traffic between unique source point and point of destination pair.The utilization rate of any link is equal to warp
Cross the ratio between the flow of the link and the capacity of the link.The maximum link utilization of SR network is the utilization of all links in network
Maximum value in rate.
It should be noted that can be searched for based on the network link weight matrix of initialization new in interative computation for the first time
Network link weight matrix.Preset resetting ratio can be the real number between one 0 to 1；The deployment rate of SR node can also
Think the real number between one 0 to 1；Deployment rate about resetting ratio and SR node, which can be determined by experiment, preferably to be taken
Value.However, the application does not limit this.
In an illustrative embodiments, step 202 may include: to calculate and search before by Freud's function
Rope to optimal network link weight matrix under shortest path in SR network between any two node；It is most short according to what is be calculated
Road and traffic matrix calculate the utilization rate of each of the links；By links all in SR network according to utilization rate from big to small suitable
Sequence is ranked up；According to resetting ratio, the link after sequence is divided into three set；Adjust separately the link in three set
Weight determines that this searches for obtained network link weight matrix.
Illustratively, it after all links in SR network being sorted according to the sequence of utilization rate from big to small, can incite somebody to action
Utilization rate is maximum | E | * percentage link is determined as first set；Utilization rate is the smallest | E | * percentage
Link, is determined as second set；Remaining link is determined as third set；Wherein, E is directed link set,
Percentage is resetting ratio.Then, the weight of the link in three set is adjusted respectively.
In an illustrative embodiments, the weight of the link in three set is adjusted separately, may include: by the first collection
The weight of link in conjunction increases a random integer value between [0, x] respectively；The weight of link in second set is distinguished
Reduce a random integer value between [0, x]；By the weight of the link of weight to be reset in third set according to equal probability with
Machine increases a random integer value between [0, x], alternatively, reducing a random integer value between [0, x]；Wherein, x is positive whole
Number；The utilization rate of link in first set is greater than the utilization rate of the link in third set, the benefit of the link in third set
It is greater than the utilization rate of the link in second set with rate.
In an illustrative embodiments, step 203 may include: to calculate and search at this by Freud's function
Shortest path under the network link weight matrix that rope obtains in SR network between any two node；According to the shortest path being calculated with
And traffic matrix, calculate the utilization rate of each of the links；For each node, calculate using the node as the utilization rate of the link of starting point
Maximum value, the maximum link utilization as the node；Node in the SR network is utilized according to respective maximum link
The sequence of rate from big to small is ranked up；According to the maximum link utilization sequence from big to small of node, selection target number
Node be added SR node set, wherein target data be greater than or equal to SR node total number to be disposed, SR node total number to be disposed
It is determined according to the node total number of SR network and the deployment rate of SR node.
In this illustrative embodiments, SR node is selected according to the maximum link utilization of node.Wherein, node
Maximum link utilization refers to using the node as in the link of starting point, the maximum value of the utilization rate of link.
In an illustrative embodiments, step 204 may include: according to network topology, traffic matrix, this searches for
The network link weight matrix arrived and the SR node set of this selection, calculate the available road of every stream in traffic matrix
Diameter；Construct linear programming problem, wherein target be the maximum link utilization for minimizing SR network, and variable is every and flows can
With the split ratio on path；Linear programming problem is solved, optimal split ratio and SR net of the every stream on available path are obtained
The maximum link utilization of the minimum of network.
In an illustrative embodiments, the restrictive condition of linear programming problem may include: the institute by any link
There is flow to be less than or equal to the product of the capacity of the link and the maximum link utilization of the link；Any bar stream can in all
It is greater than or equal to the flow demand size of this stream with the sum of the flow on path；Stream of any bar stream on any available path
Amount is greater than or equal to 0.
In an illustrative embodiments, after step 205, the traffic engineering method of the present embodiment can also include:
In SR node set, traffic matrix corresponding to maximum link utilization using the minimum for obtaining the SR network every stream
Available path and the optimal split ratio on available path optimize the SR network.
In the present embodiment, the maximum link of the minimum of SR network is obtained in traffic engineering method through this embodiment
After utilization rate, every available path flowed corresponding to the maximum link utilization can will be obtained and on available path
Optimal split ratio be supplied to the interchanger in SR network, relevant flow path is stored by interchanger, for subsequent flow
Transmission uses；Furthermore, it is possible to according to SR node set corresponding to the maximum link utilization is obtained, in SR network deployment SR section
Point, to improve network resource utilization.
Below by spot style deployment partial deployment SR network for traffic engineering method provided in this embodiment into
Row explanation.
Fig. 3 is the exemplary diagram of the SR network of the partial deployment of spot style deployment.In the SR of the partial deployment of spot style deployment
In network, only part of nodes supports SR agreement, and the node of SR agreement is supported to dissipate spot distribution in a network, i.e. support SR association
The node of view not necessarily constitutes the connection subgraph of former network topology.As shown in figure 3, the node that dotted line is framed in figure is SR section
Point, i.e. node R2、R4、R6For SR node, remaining node is ordinary node.Flow is from node R1It sets out, first according to ospf protocol
Shortest path is walked to be routed；Reach node R1And R7Between first SR node (i.e. node R on shortest path2) after, flow switchs to
It is routed using the SR of node section；Flow successively passes through SR node R2、R4、R6, routed in section according to IGP agreement and have passed through biography
System node R3、R5；Reach the last one SR node R on path6Afterwards, flow routes according to ospf protocol and reaches destination node
R7。
In the present embodiment, whole network can be abstracted as a digraph G=(V, E), wherein V is node set, and E is
Directed link set.Whole nodes support ospf protocol in network, and part of nodes supports SR agreement, support the node collection of SR agreement
Conjunction can be denoted as SRN (i.e. SR node set), and It is rightC (e) represents the capacity of link e, c (e) > 0；
ω (e) represents the weight of link e, ω (e) ∈ [1,216It -1] and is integer.Traffic matrix in network is known, wherein stream
Moment matrix represents the set for the flow demand that network must be handled whithin a period of time.L item stream is shared in traffic matrix, here
Stream refer to the polymerization traffic between unique source point-point of destination pair.To any stream i, s (i) represents the source node of stream i, t (i) generation
The destination node of surface low i, d (i) represent the flow demand of stream i.It is rightF (e) represents the flow for passing through link e, then link
The utilization rate util (e) of e=f (e)/c (e).The maximum link utilization of network
The optimization aim of traffic engineering method in the present embodiment is the maximum link utilization for minimizing network.Originally showing
In example, the formalized description of the traffic engineering problem of the SR network of partial deployment is as follows:
Min θ formula (1)
Wherein, w represents network link weight matrix,Refer to when network link weight matrix is w, flows i in link e
On flow, In (v) is the link set that terminal is point v, and Out (v) is starting point for the link set of point v.
Formula (1) is the linear programming form description of the traffic engineering problem of the SR network of partial deployment to formula (5).Wherein, θ
For optimization aim, w andFor unknown quantity, surplus is that known quantity (can be true according to network topology and traffic matrix
It is fixed).
Formula (1) is the optimization aim of traffic engineering problem, minimizes the maximum link utilization of network.
Formula (2) is link capacity limitation；Wherein, for each of the links in network, all flow demand i are on link e
Total flow should no more than link e capacity c (e) and maximum link utilization θ product.
Formula (3) is the stream constraint of each node.Wherein, if node v be flow i starting point, flow into the node flow and
The difference for flowing out the flow of the node should be the opposite number of flow demand size；If node v is the terminal for flowing i, the section is flowed into
The difference of the flow of the flow and outflow of the point node should be equal to flow demand size；The flow and stream of remaining situation inflow point v
The flow difference of point v should be 0 out.
Formula (4) is nonnegativity restriction；Wherein, uninterrupted of any flow demand on any path all should be one
A nonnegative number.
Formula (5) is link weight limitation, and the weight of any link all should be [1,216It -1] in the range of and is integer.
In the present embodiment, the traffic engineering method of the SR network based on partial deployment can pass through WA-SRTE (Weight
Adjustment-Segment Routing Traffic Engineering) algorithm realization, wherein the puppet of WA-SRTE algorithm
Code is as follows:
From the foregoing, it will be observed that the input of algorithm WA-SRTE is network topology G and traffic matrix TM, the maximum for minimum is exported
Link utilization θ.Wherein, during initialization, initialization network link weight matrix is W, then by current lattice chain
Road weight matrix and optimal network link weight matrix are all set as W；Then, using Freud's function (i.e. floyd ()),
Calculate the shortest path (i.e. route) in initial network link weight matrix lower network between any two points；Then, according to meter
Obtained shortest path and known traffic matrix obtains current maximum link utilization, and optimal maximum link is sharp
Current maximum link utilization is initialized as with rate.Hereafter, by continuous interative computation until reaching preset times；Wherein, in advance
If number can be preset by user, however, the application does not limit this.In each iteration, weight search is first called
Algorithm search_for_weight, search obtain new network link weight matrix；Then, it according to current network environment, adjusts
Select SR node set (i.e. SRN) with SR node selection algorithm choose_SR_nodes, at this time network link weight matrix and
The deployed position of SR node all has determined；Then, linear programming optimization algorithm optimize_for_SR is called to obtain current
The maximum link utilization of network under deployment conditions；If current maximum link utilization is utilized better than optimal maximum link
Rate then updates the optimal value of maximum link utilization and network link weight matrix.Final maximum link is finally obtained to utilize
The optimal solution θ of rate.
Separately below to link weight searching algorithm search_for_weight, SR node selection algorithm choose_SR_
Nodes and linear programming optimization algorithm optimize_for_SR are further described.
In the present embodiment, the pseudocode of link weight searching algorithm search_for_weight is as follows:
From the foregoing, it will be observed that the input of link weight searching algorithm search_for_weight be network topology G, it is current optimal
Network link weight matrix best_w and resetting ratio percentage, export the new network link obtained for current search
Weight matrix curr_w.In this example, percentage can be the real number between one 0 to 1, and experiment shows percentage
Value to be set as 0.1 more appropriate.Wherein, during initialization, new network link weight matrix curr_w is initialized, by it
Value be assigned to current optimal network link weight matrix best_w；Then, it using Freud's function, calculates current
Network link weight matrix lower network any two points between shortest path (i.e. route)；Then, according to the shortest path being calculated
With known traffic matrix, the utilization rate of current each of the links is obtained；Then, to all links in network, according to link
The sequence of utilization rate from big to small is ranked up link, and all links are divided into following three set: link utilization is most
Big | E | * percentage link is divided into first set E_max；Link utilization is the smallest | E | * percentage chain
Road is divided into second set E_min；Remaining | E | * (1-2*percentage) link is divided into third set E_mid.Hereafter right
The weight of link in three set is adjusted separately.Wherein, it by the weight of the link in first set E_max, rises respectively
A random integer value between high [0, x]；By the weight of the link in second set E_min, one between [0, x] is reduced respectively
Random integer value；Wherein, during algorithm is realized, it is more appropriate that experiment shows that the value of x is set as 2.For third set E_mid
In link, whether be less than the mode of percentage by the random real number value between judgement [0,1], control in third set
The resetting probability of link weight is about percentage, and will need to reset in third set weight link weight by equalization
A random integer value between [0, x] is raised and lowered in probability at random.By aforesaid operations, available new lattice chain right of way
Weight matrix curr_w.In this example, after obtaining new network link weight matrix, it is provided with cut operator, if that is,
To the cryptographic Hash of new network link weight matrix curr_w do not occurred in Hash table, then return to curr_w, otherwise return
Make the return trip empty (null).It should be noted that if cut operator is returned as null, then need to re-search for new net in the manner described above
Network link weight matrix, until obtaining the curr_w that can be returned.
In the present embodiment, SR node is selected according to the maximum link utilization of node.Wherein, the maximum chain of any node
Road utilization rate refers to using the node as in the link of starting point, the maximum value of link utilization.The maximum link utilization of any node
Calculating formula it is as follows:
Fig. 4 is the sample calculation figure of the maximum link utilization of node.Figure link capacity is 10.There are three in network
Flow D1、D2、D3, D1Path be A-D-F-E, D2Path be A-D-F-H, D3Path be A-D-G.The flow demand of three stream
It is 6.Then the load of link A-D is 18, and the load of link D-F is 12, and the load of link F-E, F-H, D-G are 6.Such as Fig. 4
It is shown, it is assumed that the maximum link utilization for wanting calculate node D at this time has D-F, D-G two by the link of starting point of node D, this
The utilization rate of both links is respectively 1.2 and 0.6, then node D maximum link utilization maxu (D)=max util (D-F),
Util (D-G) }=1.2.
In the present embodiment, the pseudocode of SR node selection algorithm choose_SR_nodes is as follows:
From the foregoing, it will be observed that the input of SR node selection algorithm choose_SR_nodes is network topology G, current search arrives
The deployment rate sr_percentage of network link weight matrix curr_w, traffic matrix TM and SR node, wherein sr_
Percentage can be the real number between one 0 to 1, and experiment shows that sr_percentage can be set to 0.3；Output is SR
Node set SRN.Wherein, during initialization, SRN is initialized as empty set, and the number SR_num that will gather interior joint
It is assigned a value of 0.Then, the Betweenness Centrality of any node is initialized as 0 by each of Enumerate network node；Then, it calls
Freud's function is calculated most short between network any two node according to the network link weight matrix currently searched out
Road (i.e. route)；Then, get_util function is called, the utilization rate of each of the links in network is calculated.In Enumerate network
Each node calculates using the node as the maximum value of the link utilization of starting point, has just obtained the maximum of all nodes in network
Link utilization；Then, the node in network is sorted from large to small according to maximum link utilization, and preferentially selects maximum chain
Utilization rate big node deployment in road is SR node；Each of set V node is enumerated respectively, is added it in SRN, until
Interstitial content in SRN is greater than or equal to SR node total number to be disposed；Finally return that last SRN.Wherein, SR to be disposed
Node total number is equal to the deployment rate of SR node and the product of nodes sum.
Fig. 5 is the stage schematic diagram of the linear programming optimization algorithm in the present embodiment.In the present embodiment, linear programming optimization
Algorithm is broadly divided into three phases, as shown in figure 5, first stage is pretreatment stage, this stage can precompute every
Flow all available paths；Second stage is the construction phase of linear programming problem, this stage can construct corresponding SR-TE line
Property planning problem；Three phases are to solve for the stage, solve wherein can be used and solve software CPLEX to problem.Below
These three stages are illustrated respectively.
In the present embodiment, the groundwork of pretreatment stage is to calculate all available paths of every flow demand.Its
In, flow is walked shortest path according to ospf protocol first from source node and is routed, on reaching source point-destination node shortest path
It after one SR point, may be routed using SR, after flow reaches the last one SR point on path, OSPF can be switched to from SR routing
Routing reaches destination node.
As shown in table 1, all available subpaths of a flow can be divided into following three classes:
The first kind is the shortest path on the source node to source node-destination node shortest path of stream between SR point, this kind of sub- road
It is the first stage of routing mode that diameter is corresponding；Flow is Traditional IP routing from this kind of subpath, routing mode, is being passed through
After this kind of subpath, flow just reaches first SR node, and routing mode switchs to SR routing from Traditional IP routing；
Second class is the shortest path in network between any two SR node；Wherein, flow reaches first SR node
Later, " detouring " will be realized by this kind of subpath, thus reach the target of network traffic engineering, on this kind of subpath,
The routing mode of flow is routed using the SR of node section；
Third class is the shortest path that any SR node (or source node) arrives destination node in network；Wherein, flow is from path
On the last one SR node leave after, routing mode switch to Traditional IP routing, pass through this kind of subpath reach destination node.This
Subpath can also can be used to the shortest path of destination node for one by locating source node, then illustrate flow in entire mistake using this subpath
It does not use SR node to be routed in journey, has directly used ospf protocol routing to walk shortest path from source node and reached purpose section
Point.
The available subpath of 1, flow of table
Fig. 6 is a sample calculation figure of the subpath in the present embodiment.Eight nodes of A to H are shared in Fig. 6, wherein SR
Node is node B, D, G, remaining node is ordinary node.Link between node indicates that the number on line represents chain with straight line
Right of way weight.Flow demand is A to H, and the shortest path of A to H is A-B-C-D-E-H, and the SR node on this path is B and D, then flow
All available subpaths are as shown in table 2.
Table 2, subpath calculated result
After having obtained all available subpaths of a flow demand, so that it may which destination node, source node is identical
Two single sub paths be connected in turn, obtain its all available paths.It, generally can be right in view of current commercial routers
The node section number that one paths use is limited, and when constituting available path, can also be limited an available path and be used
Node section (i.e. the second class subpath) number be no more than K.Table 3 is the calculated result of available path.Wherein, in calculating process
In, it limits the node section number that a paths use and is up to 2.Second is classified as subpath sequence corresponding to available path,
Wherein the subpath of overstriking is the node section in SR.Third is classified as Fig. 6 interior joint A corresponding to subpath sequence to node H's
Actual path.Fig. 7 is the exemplary diagram of the available path in the present embodiment.Four available path (P have been marked in Fig. 71It is double using point
Scribing line expression, P2It is indicated using, P3It is indicated using chain-dotted line, P4Adopt and be represented by dashed line), wherein P4To be routed according to OSPF
The shortest path arrived, P1、P2、P3It is all obtained " detouring " path after joined SR routing.
The calculated result of table 3, available path
| All paths A to H in Fig. 7 | Subpath sequence | Actual path |
| A–B–D–G–H | (A,B)(B,D)(D,G)(G,H) | A–B–C–D–G–H |
| A–B–G–D–H | (A,B)(B,G)(G,D)(G,H) | A–B–F–G–D–E–H |
| A–B–G–H | (A,B)(B,G)(G,H) | A–B–F–G–H |
| A–H | (A,H) | A–B–C–D–E–H |
SR has following characteristic: can define multiple sections of lists (i.e. mulitpath) for a flow demand, source node can be by
According to a pre-configured split ratio, flow is shunted to transmission on the mulitpath of definition.The present embodiment utilizes this of SR
A characteristic shunts flow on precalculated mulitpath, to reach the target for alleviating network congestion.Such as
In the example shown in Fig. 7, it is assumed that flow demand 1, the capacity of each of the links are also 1, if flow is without shunting, the road Zhi
Diameter P4Upper routing, then the utilization rate of link A-B, B-C, C-D, D-E, E-H are all 100%；If flow is equal on four roads Tiao Lian
Even shunting, then P1、P2、P3、P40.25 flow is undertaken respectively, and the utilization rate of all links is all 50% in network, and network is most
Big link utilization has dropped half, and Congestion Level SPCC is alleviated significantly.
By above-mentioned preprocessing process, every all available path of stream has been obtained.The present embodiment exists for flow
What kind of on these paths, the problem of proportional diverting capable of just obtaining minimum maximum link utilization according to, construct such as formula (6)
To linear programming problem shown in formula (9).
Min θ formula (6)
Wherein, network topology G=(V, E), V are the node set of network, and E is the directed link set of network；θ is network
Maximum link utilization；C (e) is the capacity of link e；L is the number of flow demand；DiThe flow demand flowed for i-th is big
It is small；PiThe available path set flowed for i-th；P is an available path；fi(p) flow for i-th stream on available path p
Size；SpFor the subpath set for constituting available path p；S is a single sub path；Is,e∈ { 0,1 }, Is,e=0 illustrates subpath s
Include link e, Is,e=1 illustrates that subpath s does not include link e.
Formula (6) is the optimization aim of linear programming problem, that is, minimizes the maximum link utilization of network.
Formula (7) is link capacity limitation；Wherein, for each of the links in network, all flow demand i is enumerated, are enumerated
All available path p of the flow demand, and all subpath s of the available path are enumerated, if the subpath includes link e,
Flow of the flow demand i on the p of path is then added in summing value.Operation in this way has just obtained the institute on link e
There is flow, this summing value should be not more than the product of the capacity c (e) and maximum link utilization θ of link e.
Formula (8) is the flow demand limitation of link.For every stream i, its all path p are enumerated, flow demand i is at it
The sum of flow on all available paths should be not less than flow demand size Di。
Formula (9) is nonnegativity restriction, uninterrupted of any flow demand on any path, all should be one non-negative
Number.
In the above problem, θ is optimization aim, fiIt (p) is variable, surplus is all that known quantity (can be obtained by data
It takes or is calculated in pretreatment stage).The optimization aim of the problem be it is linear, institute's Prescribed Properties are also linear, so
The problem is a linear programming problem, and the continuous value of all variables.This problem can solve in polynomial time.
In the present embodiment, for above-mentioned linear programming problem, such as interior point method, simplex method, Lagrange can be used
Method of relaxation, primal dual method etc. mode are solved.Illustratively, mathematical optimization problem solver can directly be used
CPLEX and its C++ programming interface is solved.
In an application example, following three network topologies: Abilene (America Research and are obtained respectively
Education Network, National Research and Education Network), CERNET (China Education and Research
Network, China Education and Research Network), GEANT (Europe Research and Education Network, European Section
Grind education network).Wherein, the link capacity of network topology is it is known that link weight is initialized as 1.The information of three network topologies can
Referring to table 4.
The information of table 4, network topology
| Topology | # node | # link |
| Abilene | 12 | 30 |
| CERNET | 14 | 32 |
| GEANT | 23 | 74 |
In this application example, three network topologies are had chosen respectively in the data of 24 hours traffic matrixs, to each
Network topology has obtained 288 or 96 traffic matrixs.More intuitively to embody algorithm effect, this example is by the numerical value of traffic matrix
It is standardized, their numerical value equal proportion is zoomed in or out, the maximum link utilization for reaching network before optimizing exists
100%.Wherein, the information of traffic matrix may refer to table 5.
The information of table 5, traffic matrix
| Topology | Measurement interval (minute) | # traffic matrix |
| Abilene | 5 | 288 |
| CERNET | 5 | 288 |
| GEANT | 15 | 96 |
Fig. 8 is the exemplary effect picture of this application.Wherein, Fig. 8 (a) is the effect picture on Abilene；Fig. 8 (b) be
Effect picture on CERNET；Fig. 8 (c) is the effect picture on GEANT.In this application example, network link weight matrix
Search iteration number is set as 1000 times, and it is 1 that number of segment mesh, which limits K,.Horizontal axis in Fig. 8 is the deployment rate of SR node, the longitudinal axis be
The average value of the maximum link utilization of 288 (or 96) a traffic matrixs under current deployment rate.It only disposes as seen from Figure 8
30% SR node can obtain the traffic engineering effect of optimization very close with full SR network.In three network topologies,
Maximum link utilization drops to 80%, 55% and 40% or so from 100% respectively.
Fig. 9 is the schematic diagram of the traffic engineering device of the SR network provided by the embodiments of the present application based on partial deployment.Such as
Shown in Fig. 9, traffic engineering device provided in this embodiment includes: to obtain module 901 and processing module 902；Wherein, processing module
902 include: network link weight matrix search unit 9021, SR node set selecting unit 9022, linear programming optimization unit
9023 and iteration judging unit 9024.
Wherein, module 901 is obtained, suitable for obtaining the network topology and traffic matrix of SR network；Processing module 902 is fitted
In by successive ignition operation, the maximum link utilization of the minimum of the SR network is determined.
Wherein, network link weight matrix search unit 9021, suitable for being carried out the following processing in each interative computation: root
According to network topology, before the optimal network link weight matrix searched and preset resetting ratio, determine this search
Obtained network link weight matrix；SR node set selecting unit 9022 is suitable for carrying out following place in each interative computation
Reason: according to the deployment of network link weight matrix and Segment routing node that network topology, traffic matrix, this search obtain
Rate determines the Segment routing node set of this selection；Linear programming optimize unit 9023, be suitable in each interative computation into
The following processing of row: the network link weight matrix that is obtained according to network topology, traffic matrix, this search and this selection
Segment routing node set determines in this operation every in the maximum link utilization, traffic matrix of the minimum of SR network
The available path of stream and the optimal split ratio on available path；Iteration judging unit 9024, suitable for being equal to when the number of iterations
The minimum value of maximum link utilization obtained in successive ignition operation is then determined as the minimum of the SR network by preset times
Maximum link utilization；When the number of iterations be less than preset times, then notify network link weight matrix search unit 9021, SR
Node set selecting unit 9022 and linear programming optimization unit 9023 execute next iteration operation.
In an illustrative embodiments, network link weight matrix search unit 9021 is suitable for root in the following manner
According to network topology, before the optimal network link weight matrix searched and preset resetting ratio, determine this search
Obtained network link weight matrix: it by Freud's function, calculates in the optimal lattice chain right of way searched before
Shortest path under weight matrix in SR network between any two node；According to the shortest path and the traffic matrix being calculated, meter
Calculate the utilization rate of each of the links；Link in SR network is ranked up according to the sequence of utilization rate from big to small；According to resetting
Link after sequence is divided into three set by ratio；The weight for adjusting separately the link in three set, determines that this is searched for
The network link weight matrix arrived.
In an illustrative embodiments, SR node set selecting unit 9022 is suitable in the following manner according to network
The deployment rate of network link weight matrix and Segment routing node that topology, traffic matrix, this search obtain, determines this
The SR node set of selection: by Freud's function, the SR under the network link weight matrix that this search obtains is calculated
Shortest path in network between any two node；According to the shortest path and traffic matrix being calculated, the benefit of each of the links is calculated
With rate；For each node, the maximum chain using the node as the maximum value of the utilization rate of the link of starting point, as the node is calculated
Road utilization rate；Node in SR network is ranked up according to the sequence of respective maximum link utilization from big to small；According to
SR node set is added in the sequence of the maximum link utilization of node from big to small, selection target number destination node, wherein target
Data are greater than or equal to SR node total number to be disposed, and SR node total number to be disposed is according to the node total number of SR network and SR node
Deployment rate determines.
In an illustrative embodiments, linear programming optimizes unit 9023, suitable for being opened up in the following manner according to network
It flutters, Segment routing node set of traffic matrix, this obtained network link weight matrix of search and this selection, determines
The available path of every stream and available in the maximum link utilization, traffic matrix of the minimum of SR network in this operation
Optimal split ratio on path: the network link weight matrix and sheet obtained according to network topology, traffic matrix, this search
The Segment routing node set of secondary selection calculates the available path of every stream in traffic matrix；Linear programming problem is constructed,
In, target is the maximum link utilization for minimizing SR network, and variable is split ratio of the every stream on available path；Solve line
Property planning problem, the maximum link for obtaining the minimum of every optimal split ratio and SR network of the stream on available path utilizes
Rate.
Related description about traffic engineering device provided in this embodiment is referred to the description of above method embodiment,
Therefore it is repeated no more in this.
Figure 10 is the schematic diagram of terminal provided by the embodiments of the present application.As shown in Figure 10, the embodiment of the present application provides one kind
Terminal 1000, comprising: memory 1001 and processor 1002, memory 1001 are suitable for storing the SR network based on partial deployment
Traffic engineering program, the traffic engineering program are realized provided by the above embodiment based on partial deployment when being executed by processor 1002
SR network traffic engineering method the step of, such as step shown in Fig. 2.It will be understood by those skilled in the art that in Figure 10
The structure shown, only the schematic diagram of part-structure relevant to application scheme, does not constitute and is answered application scheme
With the restriction of terminal 1000 thereon, terminal 1000 may include than more or fewer components as shown in the figure, or combination
Certain components, or with different component layouts.
Wherein, processor 1002 can include but is not limited to microprocessor (MCU, Microcontroller Unit) or can
The processing unit of programmed logic device (FPGA, Field Programmable Gate Array) etc..Memory 1001 can be used for
The software program and module for storing application software, such as the corresponding program instruction of traffic engineering method or mould in the present embodiment
Block, the software program and module that processor 1002 is stored in memory 1001 by operation, is answered thereby executing various functions
With and data processing, for example realize traffic engineering method provided in this embodiment.Memory 1001 may include that high speed is deposited at random
Reservoir may also include nonvolatile memory, such as one or more magnetic storage device, flash memory or other are non-volatile
Solid-state memory.In some instances, memory 1001 may include the memory remotely located relative to processor 1002, these
Remote memory can pass through network connection to terminal 1000.The example of above-mentioned network includes but is not limited to internet, in enterprise
Portion's net, local area network, mobile radio communication and combinations thereof.
In addition, the embodiment of the present application also provides a kind of computer-readable medium, it is stored with the SR network based on partial deployment
Traffic engineering program, which realizes traffic engineering method provided by the above embodiment when being executed by processor
Step, for example, step shown in Fig. 2.
It will appreciated by the skilled person that whole or certain steps, system, dress in method disclosed hereinabove
Functional module/unit in setting may be implemented as software, firmware, hardware and its combination appropriate.In hardware embodiment,
Division between the functional module/unit referred in the above description not necessarily corresponds to the division of physical assemblies；For example, one
Physical assemblies can have multiple functions or a function or step and can be executed by several physical assemblies cooperations.Certain groups
Part or all components may be implemented as by processor, such as the software that digital signal processor or microprocessor execute, or by
It is embodied as hardware, or is implemented as integrated circuit, such as specific integrated circuit.Such software can be distributed in computer-readable
On medium, computer-readable medium may include computer storage medium (or non-transitory medium) and communication media (or temporarily
Property medium).As known to a person of ordinary skill in the art, term computer storage medium is included in for storing information (such as
Computer readable instructions, data structure, program module or other data) any method or technique in the volatibility implemented and non-
Volatibility, removable and nonremovable medium.Computer storage medium include but is not limited to RAM, ROM, EEPROM, flash memory or its
His memory technology, CD-ROM, digital versatile disc (DVD) or other optical disc storages, magnetic holder, tape, disk storage or other
Magnetic memory apparatus or any other medium that can be used for storing desired information and can be accessed by a computer.This
Outside, known to a person of ordinary skill in the art to be, communication media generally comprises computer readable instructions, data structure, program mould
Other data in the modulated data signal of block or such as carrier wave or other transmission mechanisms etc, and may include any information
Delivery media.
The advantages of basic principles and main features and the application of the application have been shown and described above.The application is not by upper
The limitation for stating embodiment, the above embodiments and description only describe the principles of the application, are not departing from the application
Under the premise of spirit and scope, the application be will also have various changes and improvements, these changes and improvements both fall within claimed
Within the scope of the application.
Claims (10)
1. a kind of traffic engineering method of the Segment routing network based on partial deployment characterized by comprising
Obtain the network topology and traffic matrix of Segment routing network；
By successive ignition operation, the maximum link utilization of the minimum of the Segment routing network is determined；Wherein, every time repeatedly
It is carried out the following processing respectively in operation:
According to the network topology, before the optimal network link weight matrix searched and preset resetting ratio, really
Fixed this searches for obtained network link weight matrix；
The network link weight matrix and Segment routing obtained according to the network topology, the traffic matrix, this search
The deployment rate of node determines the Segment routing node set of this selection；
The network link weight matrix obtained according to the network topology, the traffic matrix, this search and this selection
Segment routing node set, determine the maximum link utilization of the minimum of Segment routing network described in this operation, institute
State every available path flowed and the optimal split ratio on the available path in traffic matrix；
When the number of iterations is equal to preset times, then by the minimum value determination of maximum link utilization obtained in successive ignition operation
For the maximum link utilization of the minimum of the Segment routing network；
When the number of iterations be less than the preset times, then execute next iteration operation.
2. the method according to claim 1, wherein described according to the network topology, before search most
Excellent network link weight matrix and preset resetting ratio determine that this searches for obtained network link weight matrix, packet
It includes:
By Freud's function, the Segment routing under the optimal network link weight matrix searched before is calculated
Shortest path in network between any two node；
According to the shortest path and the traffic matrix being calculated, the utilization rate of each of the links is calculated；
Link in the Segment routing network is ranked up according to the sequence of the utilization rate from big to small；
According to the resetting ratio, the link after sequence is divided into three set；
The weight for adjusting separately the link in three set, determines that this searches for obtained network link weight matrix.
3. according to the method described in claim 2, it is characterized in that, the power for adjusting separately the link in three set
Weight, comprising:
The weight of link in first set is increased to a random integer value between [0, x] respectively；
The weight of link in second set is reduced to a random integer value between [0, x] respectively；
One that the weight of the link of weight to be reset in third set is increased between [0, x] at random according to equal probability is random whole
Numerical value, alternatively, reducing a random integer value between [0, x]；
Wherein, x is positive integer；The utilization rate of link in the first set is greater than the utilization of the link in the third set
Rate, the utilization rate of the link in the third set are greater than the utilization rate of the link in the second set.
4. the method according to claim 1, wherein described according to the network topology, the traffic matrix, sheet
The secondary deployment rate for searching for obtained network link weight matrix and Segment routing node, determines the Segment routing section of this selection
Point set, comprising:
By Freud's function, the Segment routing network under the network link weight matrix that this search obtains is calculated
In shortest path between any two node；
According to the shortest path and the traffic matrix being calculated, the utilization rate of each of the links is calculated；
For each node, calculate using the node as the maximum value of the utilization rate of the link of starting point, most as the node
Big link utilization；
Node in the Segment routing network is ranked up according to the sequence of respective maximum link utilization from big to small；
According to the maximum link utilization sequence from big to small of the node, Segment routing is added in selection target number destination node
Node set, wherein the target data is greater than or equal to Segment routing node total number to be disposed, the Segment routing to be disposed
Node total number is determined according to the node total number of the Segment routing network and the deployment rate of the Segment routing node.
5. the method according to claim 1, wherein described according to the network topology, the traffic matrix, sheet
The secondary Segment routing node set for searching for obtained network link weight matrix and this selection, determines described in this operation
In the maximum link utilization of the minimum of Segment routing network, the traffic matrix every stream available path and described
Optimal split ratio on available path, comprising:
The network link weight matrix obtained according to the network topology, the traffic matrix, this search and this selection
Segment routing node set, calculate in the traffic matrix available path of every stream；
Construct linear programming problem, wherein target is the maximum link utilization for minimizing the Segment routing network, and variable is
Split ratio of the every stream on available path；
The linear programming problem is solved, optimal split ratio and the Segment routing net of the every stream on available path are obtained
The maximum link utilization of the minimum of network.
6. according to the method described in claim 5, it is characterized in that, the restrictive condition of the linear programming problem includes:
It is less than or equal to the capacity of the link and the maximum link utilization of the link by all flows of any link
Product；
The sum of the flow of any bar stream on all available paths is greater than or equal to the flow demand size of the stream；
Flow of any bar stream on any available path is greater than or equal to 0.
7. the method according to claim 1, wherein the minimum of the determination Segment routing network is most
After big link utilization, the method also includes:
Segment routing node set corresponding to maximum link utilization using the minimum for obtaining the Segment routing network,
Every available path flowed and the optimal split ratio on the available path, optimize the segmentation road in the traffic matrix
By network.
8. a kind of traffic engineering device of the Segment routing network based on partial deployment characterized by comprising
Module is obtained, suitable for obtaining the network topology and traffic matrix of Segment routing network；
Processing module is suitable for determining that the maximum link of the minimum of the Segment routing network is utilized by successive ignition operation
Rate；
Wherein, the processing module includes:
Network link weight matrix search unit, suitable for being carried out the following processing in each interative computation: being opened up according to the network
The optimal network link weight matrix flutter, searched before and preset resetting ratio determine that this searches for obtained net
Network link weight matrix；
Segment routing node set selecting unit, suitable for being carried out the following processing in each interative computation: being opened up according to the network
It flutters, the deployment rate of network link weight matrix and Segment routing node that the traffic matrix, this search obtain, determines this
The Segment routing node set of secondary selection；
Linear programming optimizes unit, suitable for carrying out the following processing in each interative computation: according to the network topology, the stream
The Segment routing node set of moment matrix, the network link weight matrix that this search obtains and this selection, determines this
The available path of every stream in the maximum link utilization of the minimum of Segment routing network described in operation, the traffic matrix
And the optimal split ratio on the available path；
Iteration judging unit is suitable for being equal to preset times when the number of iterations, then by maximum link obtained in successive ignition operation
The minimum value of utilization rate is determined as the maximum link utilization of the minimum of the Segment routing network；When the number of iterations is small
In the preset times, then notify the network link weight matrix search unit, Segment routing node set selection single
The first and described linear programming optimization unit executes next iteration operation.
9. a kind of terminal characterized by comprising memory and processor, the memory are stored with based on partial deployment
The traffic engineering program of Segment routing network realizes such as claim 1 when the traffic engineering program is executed by the processor
To the Segment routing network described in any one of 7 based on partial deployment traffic engineering method the step of.
10. a kind of computer-readable medium, which is characterized in that be stored with the flow work of the Segment routing network based on partial deployment
Cheng Chengxu, when the traffic engineering program is executed by processor realize as described in any one of claims 1 to 7 based on part
The step of traffic engineering method of the Segment routing network of deployment.
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| CN116055385A (en) * | 2022-12-30 | 2023-05-02 | 中国联合网络通信集团有限公司 | Routing method, management node, routing node and medium |
| WO2023148830A1 (en) * | 2022-02-01 | 2023-08-10 | 日本電信電話株式会社 | Traffic engineering device, traffic engineering method and traffic engineering program |
| WO2024001210A1 (en) * | 2022-06-29 | 2024-01-04 | 中兴通讯股份有限公司 | Path calculation method, controller, and computer readable storage medium |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040165710A1 (en) * | 2003-02-21 | 2004-08-26 | Delhoyo Sergio Jason | Method for scheduling videoconferences |
| CN103685011A (en) * | 2012-09-14 | 2014-03-26 | 华为技术有限公司 | Method and device of determining energy-saving routing |
| CN104270313A (en) * | 2014-09-29 | 2015-01-07 | 清华大学 | Method for adjusting utilization rate of network link |
| US20150117203A1 (en) * | 2013-10-24 | 2015-04-30 | Cisco Technology, Inc. | Segment routing based wide area network orchestration in a network environment |
| US20160294699A1 (en) * | 2015-03-30 | 2016-10-06 | Alcatel-Lucent Usa, Inc. | Traffic oblivious offline optimization for traffic engineering with segment routing |
| CN106161257A (en) * | 2016-08-30 | 2016-11-23 | 杭州电子科技大学 | A kind of adaptive power conservation method for routing based on link utilization towards SDN |
| CN107548545A (en) * | 2015-03-30 | 2018-01-05 | 阿尔卡特朗讯公司 | The offline optimization for traffic engineering with Segment routing |
| CN108429685A (en) * | 2018-04-28 | 2018-08-21 | 电子科技大学 | A kind of service function chain method for searching based on Segment routing technology |
-
2018
- 2018-10-23 CN CN201811234886.0A patent/CN109194577B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040165710A1 (en) * | 2003-02-21 | 2004-08-26 | Delhoyo Sergio Jason | Method for scheduling videoconferences |
| CN103685011A (en) * | 2012-09-14 | 2014-03-26 | 华为技术有限公司 | Method and device of determining energy-saving routing |
| US20150117203A1 (en) * | 2013-10-24 | 2015-04-30 | Cisco Technology, Inc. | Segment routing based wide area network orchestration in a network environment |
| CN104270313A (en) * | 2014-09-29 | 2015-01-07 | 清华大学 | Method for adjusting utilization rate of network link |
| US20160294699A1 (en) * | 2015-03-30 | 2016-10-06 | Alcatel-Lucent Usa, Inc. | Traffic oblivious offline optimization for traffic engineering with segment routing |
| CN107548545A (en) * | 2015-03-30 | 2018-01-05 | 阿尔卡特朗讯公司 | The offline optimization for traffic engineering with Segment routing |
| CN106161257A (en) * | 2016-08-30 | 2016-11-23 | 杭州电子科技大学 | A kind of adaptive power conservation method for routing based on link utilization towards SDN |
| CN108429685A (en) * | 2018-04-28 | 2018-08-21 | 电子科技大学 | A kind of service function chain method for searching based on Segment routing technology |
Non-Patent Citations (2)
| Title |
|---|
| RANDEEPBHATIA等: ""Optimized network traffic engineering using segment routing"", 《IEEE》 * |
| 黄建洋等: ""一种基于分段路由的多路径流传输机制"", 《万方数据库》 * |
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