CN114679730A - Software defined network switching node layout method and device - Google Patents
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Abstract
The invention provides a method and a device for arranging switching nodes of a software defined network, wherein the method comprises the following steps: initializing the switching nodes in the network to be distributed into a plurality of clusters according to the topological structure of the network to be distributed; calculating the distance between each cluster, and merging the two clusters with the minimum distance to obtain a clustering result; if the number of the current clusters is larger than the preset value, returning to the step of calculating the distance between the clusters and combining the two clusters with the minimum distance to obtain a clustering result, and determining the current clustering result as a final clustering result until the number of the current clusters is smaller than or equal to the preset value; decomposing the network to be laid into a plurality of sub-networks according to the final clustering result; and respectively simulating the optimal layout position in each sub-network, and replacing the switching node at the optimal layout position in each sub-network with the software-defined network switching node to form the software-defined network layout network. The invention ensures effective traffic engineering, improves network operation performance and improves network function stability.
Description
Technical Field
The invention relates to the technical field of wireless networks, in particular to a software defined network switching node layout method and device.
Background
With the continuous development of informatization of the power industry and the maturity of technologies such as cloud computing, data warehouse, data mining and virtualization, the traditional data center network has the problems of complex management, operation and maintenance, unreasonable network resource allocation, serious virtualization degree and the like, and cannot adapt to the development of network applications such as cloud computing, data warehouse, data mining and virtualization in the future. The appearance of Software Defined Networking (SDN) realizes the separation of network control and forwarding, is beneficial to improving the automatic control and management capability of the network, and provides a new direction for solving the current network problems. The SDN network technology is applied to a power industry data center, particularly in a power SCADA system.
SDN employs a more robust, cost-effective telecommunications infrastructure with dynamic traffic engineering, depending on the network and application. The SDN controller performs different operations for each network setting depending on size and topology type, transitioning to a pure SDN solution is a progressive process that is still not feasible in the short term due to economic, organizational and technical challenges.
The placement of SDN switching nodes will provide convenient and efficient traffic engineering, thereby improving network performance. Due to limited budgets and network operational stability prerequisites, the full deployment of the SDN wide area network SD-WAN (i.e. all nodes on the network are SDN enabled) cannot be done directly within a reduced period. A limited number of legacy switching nodes may be replaced by SDN enabled switching nodes, which is often referred to as hybrid SDN solutions at a certain optimal domain and location, how to more reasonably determine the layout location of SDN switching nodes is an urgent issue to be solved.
Disclosure of Invention
Therefore, the technical problem to be solved by the present invention is to overcome the defect in the prior art that the layout position of the SDN switching node is not reasonable, thereby providing a software defined network switching node layout method and apparatus.
The first aspect of the present invention provides a software defined network switching node layout method, including: initializing switching nodes in the network to be distributed into a plurality of clusters according to the topological structure of the network to be distributed; calculating the distance between each cluster, and combining the two clusters with the minimum distance to obtain a clustering result; if the number of the current clusters is larger than a preset value, repeatedly executing the step of calculating the distance between the clusters, combining the two clusters with the minimum distance to obtain a clustering result, and determining the current clustering result as a final clustering result until the number of the current clusters is smaller than or equal to the preset value; decomposing the network to be laid into a plurality of sub-networks according to the final clustering result; and respectively simulating the optimal layout position in each sub-network, and replacing the switching node at the optimal layout position in each sub-network with the software-defined network switching node to form the software-defined network layout network.
Optionally, in the software defined network switching node layout method provided in the present invention, after the step of determining that the number of current clusters is less than or equal to the preset value, before the step of determining the current clustering result as the final clustering result, the method further includes: calculating the Dunn index of the current clustering result; and if the Dunn index is larger than or equal to the preset value, judging the current clustering result as the final clustering result.
Optionally, in the software-defined network switching node layout method provided in the present invention, the method further includes: if the Dunn index of the current clustering result is smaller than the preset value, changing the preset value; and returning to the step of initializing the switching nodes in the network to be distributed into a plurality of clusters according to the topological structure of the network to be distributed until the Dunn index of the current clustering result is greater than or equal to a preset value, and judging the current clustering result as the final clustering result.
Optionally, in the software-defined network switching node layout method provided by the present invention, the Dunn index of the current clustering result is calculated by the following formula:
where d (x, y) denotes the dissimilarity of the clusters, dis (G)i,Gj) Represents the minimum difference between the two clusters, dia (G)l) Representing the maximum difference between the two clusters.
A second aspect of the present invention provides a software-defined network switching node placement apparatus, including: the data initialization module is used for initializing the switching nodes in the network to be distributed into a plurality of clusters according to the topological structure of the network to be distributed; the cluster merging module is used for calculating the distance between the clusters and merging the two clusters with the minimum distance to obtain a clustering result; the clustering module is used for repeatedly calculating the distance between the clusters if the number of the current clusters is larger than a preset value, combining the two clusters with the smallest distance to obtain a clustering result, and determining the current clustering result as a final clustering result until the number of the current clusters is smaller than or equal to the preset value; the network decomposition submodule is used for decomposing the network to be laid into a plurality of sub-networks according to the final clustering result; and the switching node replacing module is used for respectively simulating the optimal layout positions in each sub-network, replacing the switching nodes at the optimal layout positions in each sub-network with the software-defined network switching nodes, and forming the software-defined network layout network.
Optionally, in the software-defined network switching node placement apparatus provided in the present invention, further includes: the Dunn index calculation module is used for calculating the Dunn index of the current clustering result; and the clustering result evaluation module is used for judging the current clustering result as the final clustering result if the Dunn index is greater than or equal to the preset value.
Optionally, in the software-defined network switching node placement apparatus provided in the present invention, further include: and the cluster threshold changing module is used for changing the preset value if the Dunn index of the current clustering result is smaller than the preset value, returning to the step of initializing the exchange nodes in the network to be distributed into a plurality of clusters according to the topological structure of the network to be distributed until the Dunn index of the current clustering result is larger than or equal to the preset value, and judging the current clustering result as the final clustering result.
Optionally, in the software-defined network switching node placement apparatus provided in the present invention, the Dunn index of the current clustering result is calculated by the following formula:
where d (x, y) denotes the dissimilarity of the clusters, dis (G)i,Gj) Represents the minimum difference between the two clusters, dia (G)l) Representing the maximum difference between the two clusters.
An embodiment of the present invention provides a computer device, including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to perform the software defined network switching node placement method as provided by the first aspect of the invention.
An embodiment of the present invention provides a computer-readable storage medium, which stores computer instructions for causing a computer to execute the software-defined network switching node layout method according to the first aspect of the present invention.
The technical scheme of the invention has the following advantages:
the invention provides a software defined network switching node layout method and device, which solve the problems of SD-WAN partition and switching node layout in a network to be laid by adopting an AHC algorithm.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of a specific example of a method for laying out switching nodes of a software-defined network according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a single-strand process in an embodiment of the present invention;
FIG. 3 is a schematic diagram of a full-chain process in an embodiment of the present invention;
FIG. 4 is a schematic diagram of a homologation process in an embodiment of the present invention;
fig. 5 is a schematic block diagram of a specific example of a software defined network switching node placement apparatus in an embodiment of the present invention;
FIG. 6 is a functional block diagram of a specific example of a computer device in an embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it should be noted that the technical features related to the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.
The embodiment of the invention provides a software defined network switching node layout method, as shown in fig. 1, including:
Step S11: and initializing the switching nodes in the network to be distributed into a plurality of clusters according to the topological structure of the network to be distributed.
In the embodiment of the present invention, the switching node is a conventional switching node, and in order to improve the automation control and management capability of the Network to be provisioned, it is necessary to replace some conventional switching nodes in the Network to be provisioned with Software Defined Network (SDN) switching nodes.
In an alternative embodiment, one or more switching nodes are included in a cluster.
Step S12: and calculating the distance between the clusters, and combining the two clusters with the minimum distance to obtain a clustering result.
In the present embodiment, if GpAnd GqThe distance between the two is minimum, G ispAnd GqMerge into a new cluster GrIn (2), the element of the new cluster Gr is GP∪GqAt this point, the cluster reserves are reduced by 1: c ═ C-1.
Since the clusters are continuously merged to obtain the final clustering result when the switching node is clustered in the embodiment of the present invention, a larger number of clusters can be set when the switching node is initialized to a plurality of clusters in step S11.
In an alternative embodiment, the distance between clusters may be calculated by cosine similarity, euclidean distance, single chain method, full chain method, uniform chain method, or the like.
And judging whether the number of the current clusters is larger than a preset value, if so, returning to the step S12 until the number of the current clusters is smaller than or equal to the preset value, and executing the step S13.
Step S13: and determining the current clustering result as a final clustering result.
Step S14: and decomposing the network to be laid into a plurality of sub-networks according to the final clustering result.
In the embodiment of the invention, the switching nodes belonging to the same cluster in the final clustering result belong to the same sub-network.
Step S15: and respectively simulating the optimal layout position in each sub-network, and replacing the switching node at the optimal layout position in each sub-network with the software-defined network switching node to form the software-defined network layout network.
In an optional embodiment, Mininet can be adopted to simulate the optimal deployment position of each sub-network SDN switching node by simulating each sub-network, and finally, the switching node supporting the SDN mechanism is arranged in the hybrid SD-WAN to replace the traditional switching node at the optimal deployment position.
The software defined network switching node layout method provided by the embodiment of the invention adopts an AHC algorithm to solve the problems of SD-WAN partition and switching node layout in a network to be laid out.
In an optional embodiment, in the software-defined network switching node placement method provided in the embodiment of the present invention, after the step of determining that the number of current clusters is less than or equal to the preset value, before performing step S13, the method further includes:
first, Dunn index of the clustering result is calculated.
The Dunn index is considered one of the suitable cluster effectiveness metrics to evaluate the network data cluster partition. This approach helps to compute the required clusters because it handles the data density by focusing on the maximum spacing between data objects and the minimum spacing between clusters. The Dunn index is used to evaluate the partition quality and then determine the "best" clear partition of n objects, specifically, the node with the largest distance to the centroid and the updated centroid is selected as the initial center for the next partition, and the process is repeated until the network is divided into k subnetworks.
And if the Dunn index is larger than or equal to the preset value, judging the current clustering result as the final clustering result.
Otherwise, if the Dunn index of the current clustering result is smaller than the preset value, the preset value is changed, the step S11 is returned, the clustering process is repeatedly executed until the Dunn index of the current clustering result is larger than or equal to the preset value, and the current clustering result is determined as the final clustering result.
In an optional embodiment, different preset values may be set, and the above steps S11 to S13 are performed respectively to form a plurality of different clustering results, then Dunn indexes of the clustering results are calculated respectively, and the clustering result with the largest Dunn index is determined as the final clustering result.
In an alternative embodiment, the Dunn index of the current clustering result is calculated by the following formula:
where d (x, y) represents the dissimilarity of the clusters, dis (G)i,Gj) Represents the minimum difference between the two clusters, dia (G)l) Representing the maximum difference between the two clusters.
In an alternative embodiment, in step S12, the distance between each cluster may be calculated by using an inter-point distance calculation method:
there are 2 n-dimensional vector data points A, B, a ═ a1,A2,...,An}，B＝{B1,B2,...,Bn}。
Cosine similarity. Cosine similarity measures the similarity between two vectors by utilizing cosine values, and the cosine similarity measures the size of an included angle between the two vectors by using the following calculation formula:
the euclidean distance. The euclidean distance, also called the euclidean distance, is used to measure the absolute distance between two vectors. The calculation formula is as follows:
the inter-cluster-like distance calculation mode is as follows:
The current commonly used measuring methods among clusters include a single-chain method, a full-chain method and a chain-sharing method.
Single strand method: as shown in fig. 2, the single-chain calculation method is to use the distance between two closest data points of two combined data points as the distance between the two combined data points, and thus is easily affected by noise points. The inter-cluster-like distance calculation formula of the single-chain method is as follows:
the full-chain method comprises the following steps: as shown in fig. 3, the full-strand method is opposite to the single-strand method in that the distance between two farthest data points among two cluster-like data points is taken as the inter-cluster distance. The inter-cluster-like distance calculation formula of the full-chain method is as follows:
the chain sharing method comprises the following steps: as shown in fig. 4, the average chain method is to calculate the distance between each data point in the two clusters and all other data points, and then calculate the average value of the distances as the distance between the two clusters. The embodiment of the invention adopts a chain-sharing method, and the inter-cluster-distance calculation formula of the chain-sharing method is as follows:
in a specific embodiment, comparing the network delay and the throughput generated by the method provided by the embodiment of the present invention and the K-means algorithm, it can be found that not only the network delay is greatly reduced, the average delay is reduced by 15%, but also the throughput is significantly improved, and the throughput is improved by 13%, which has significant social and economic benefits.
An embodiment of the present invention provides a software-defined network switching node layout apparatus, as shown in fig. 5, including:
the data initializing module 21 is configured to initialize the switching nodes in the network to be configured into a plurality of clusters according to the topology structure of the network to be configured, for details, refer to the description of step S11 in the foregoing embodiment, and details are not described herein again.
The cluster merging module 22 is configured to calculate distances between the clusters, and merge two clusters with the smallest distance to obtain a clustering result, for details, refer to the description of step S12 in the foregoing embodiment, and details are not repeated here.
If the number of the current clusters is greater than the preset value, the clustering module 23 repeatedly performs the step of calculating the distance between the clusters, and merges the two clusters with the smallest distance to obtain a clustering result, until the number of the current clusters is less than or equal to the preset value, and the clustering module determines the current clustering result as the final clustering result, for details, reference is made to the description of step S13 in the above embodiment, and details are not repeated here.
The network decomposition submodule 24 is configured to decompose the network to be distributed into a plurality of sub-networks according to the final clustering result, for details, refer to the description of step S14 in the foregoing embodiment, and details are not described herein again.
A switching node replacing module 25, configured to respectively simulate an optimal layout position in each sub-network, and replace the switching node at the optimal layout position in each sub-network with a software-defined network switching node to form a software-defined network layout network, for details, refer to the description of step S15 in the foregoing embodiment, and details are not described here again.
In an optional embodiment, the software-defined network switching node placement apparatus provided in the embodiment of the present invention further includes:
and the Dunn index calculation module is used for calculating the Dunn index of the current clustering result, and the details are referred to the description in the above method embodiment and are not repeated herein.
And if the Dunn index is greater than or equal to the preset value, the clustering result evaluation module is configured to determine the current clustering result as the final clustering result, for details, reference is made to the description in the foregoing method embodiment, and details are not repeated here.
In an optional embodiment, the software-defined network switching node placement apparatus provided in the embodiment of the present invention further includes:
and the cluster threshold changing module is used for changing the preset value if the Dunn index of the current clustering result is smaller than the preset value, returning to the step of initializing the switching nodes in the network to be distributed into a plurality of clusters according to the topological structure of the network to be distributed until the Dunn index of the current clustering result is greater than or equal to the preset value, and judging the current clustering result as the final clustering result, wherein the detailed contents are described in the embodiment of the method and are not repeated herein.
In an optional embodiment, in the software-defined network switching node layout apparatus provided in the embodiment of the present invention, the Dunn index of the current clustering result is calculated by the following formula:
where d (x, y) represents the dissimilarity of the clusters, dis (G)i,Gj) Represents the minimum difference between the two clusters, dia (G)l) Representing the maximum difference between the two clusters.
An embodiment of the present invention provides a computer device, as shown in fig. 6, the computer device mainly includes one or more processors 31 and a memory 32, and one processor 31 is taken as an example in fig. 6.
The computer device may further include: an input device 33 and an output device 34.
The processor 31, the memory 32, the input device 33 and the output device 34 may be connected by a bus or other means, and fig. 6 illustrates the connection by a bus as an example.
The processor 31 may be a Central Processing Unit (CPU). The Processor 31 may also be other general purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, or combinations thereof. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The memory 32 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created from use of the software defined network switching node placement apparatus, and the like. Further, the memory 32 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory 32 may optionally include memory located remotely from the processor 31, and these remote memories may be connected to the software defined network switching node placement apparatus via a network. The input device 33 may receive user input of a computation request (or other numeric or character information) and generate key signal inputs associated with the software defined network switching node placement device. The output device 34 may include a display device such as a display screen for outputting the calculation result.
Embodiments of the present invention provide a computer-readable storage medium storing computer instructions, where the computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions may execute the software-defined network switching node layout method in any of the above method embodiments. The storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a Flash Memory (Flash Memory), a Hard Disk (Hard Disk Drive, abbreviated as HDD) or a Solid State Drive (SSD), etc.; the storage medium may also comprise a combination of memories of the kind described above.
It should be understood that the above examples are only for clarity of illustration and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. And obvious variations or modifications therefrom are within the scope of the invention.
Claims (10)
1. A method for software-defined network switching node placement, comprising:
Initializing the switching nodes in the network to be distributed into a plurality of clusters according to the topological structure of the network to be distributed;
calculating the distance between each cluster, and combining the two clusters with the minimum distance to obtain a clustering result;
if the number of the current clusters is larger than a preset value, repeatedly executing the step of calculating the distance between the clusters, combining the two clusters with the minimum distance to obtain a clustering result, and determining the current clustering result as a final clustering result until the number of the current clusters is smaller than or equal to the preset value;
decomposing the network to be laid into a plurality of sub-networks according to the final clustering result;
and respectively simulating the optimal layout position in each sub-network, and replacing the switching node at the optimal layout position in each sub-network with the software-defined network switching node to form a software-defined network layout network.
2. The method of claim 1, wherein after the step of determining the number of current clusters is less than or equal to a predetermined value, and before the step of determining the current clustering result as the final clustering result, the method further comprises:
calculating the Dunn index of the current clustering result;
And if the Dunn index is larger than or equal to a preset value, judging the current clustering result as the final clustering result.
3. The method of software defined network switching node placement according to claim 2, further comprising:
if the Dunn index of the current clustering result is smaller than a preset value, changing the preset value;
and returning to the step of initializing the switching nodes in the network to be distributed into a plurality of clusters according to the topological structure of the network to be distributed until the Dunn index of the current clustering result is greater than or equal to a preset value, and judging the current clustering result as the final clustering result.
4. The method of claim 2, wherein the Dunn index of the current clustering result is calculated by the following formula:
where d (x, y) represents the dissimilarity of the clusters, dis (G)i,Gj) Represents the minimum difference between the two clusters, dia (G)l) Representing the maximum difference between the two clusters.
5. A software-defined network switching node placement arrangement, comprising:
the data initialization module is used for initializing the switching nodes in the network to be distributed into a plurality of clusters according to the topological structure of the network to be distributed;
The cluster merging module is used for calculating the distance between the clusters and merging the two clusters with the minimum distance to obtain a clustering result;
the clustering module is used for repeatedly calculating the distance between clusters if the number of the current clusters is larger than a preset value, combining the two clusters with the smallest distance to obtain a clustering result, and determining the current clustering result as a final clustering result by the clustering module until the number of the current clusters is smaller than or equal to the preset value;
the network decomposition submodule is used for decomposing the network to be laid into a plurality of sub-networks according to the final clustering result;
and the switching node replacing module is used for respectively simulating the optimal layout position in each sub-network, and replacing the switching node at the optimal layout position in each sub-network with the software-defined network switching node to form the software-defined network layout network.
6. The apparatus of claim 5, wherein the apparatus further comprises:
the Dunn index calculation module is used for calculating the Dunn index of the current clustering result;
and the clustering result evaluation module is used for judging the current clustering result as the final clustering result if the Dunn index is larger than or equal to a preset value.
7. The apparatus of claim 6, wherein the apparatus further comprises:
and the cluster threshold changing module is used for changing the preset value if the Dunn index of the current clustering result is smaller than the preset value, returning to the step of initializing the switching nodes in the network to be distributed into a plurality of clusters according to the topological structure of the network to be distributed until the Dunn index of the current clustering result is larger than or equal to the preset value, and judging the current clustering result as the final clustering result.
8. The apparatus of claim 6, wherein the Dunn index of the current clustering result is calculated by the following formula:
where d (x, y) represents the dissimilarity of the clusters, dis (G)i,Gj) Represents the minimum difference between the two clusters, dia (G)l) Representing the maximum difference between the two clusters.
9. A computer device, comprising:
at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to perform the software defined network switching node placement method of any one of claims 1-4.
10. A computer-readable storage medium storing computer instructions for causing a computer to perform the software defined network switching node placement method of any one of claims 1-4.
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| WO2021147107A1 (en) * | 2020-01-23 | 2021-07-29 | 华为技术有限公司 | Communication method and apparatus |
| CN111404731A (en) * | 2020-03-05 | 2020-07-10 | 山东工商学院 | SDN network controller deployment method and system based on double heuristic algorithm |
| CN111669396A (en) * | 2020-06-15 | 2020-09-15 | 绍兴文理学院 | Self-learning security defense method and system for software-defined Internet of things |
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