KR102199432B1 - Methods and devices for selecting optimal controller in Software Defined Networking - Google Patents

Abstract

A method for selecting an optimal controller among a plurality of controllers in software defined networking comprises: setting a plurality of controllers and a plurality of functions as criteria for selecting an optimal controller; evaluating scores according to the importance for each of the plurality of functions for each of the plurality of controllers, performing qualitative analysis based on an analytic network process (ANP) based on the evaluated scores, and selecting the optimal controller based on a block matrix obtained as a result of the qualitative analysis. Therefore, the natural language understanding on a user voice can be efficiently performed.

Description

Methods and devices for selecting optimal controller in Software Defined Networking

The present disclosure relates to a method and an apparatus for selecting an optimal controller in Software Defined Networking.

Software Defined Networking is a technology that reduces the complexity of a conventional network device by logically separating a control function and a data transfer function. SDN's network devices are controlled and managed by a centralized controller.

Software-defined networking controllers provide an environment in which operators can program data delivery devices and distribute policies. Meanwhile, it is important to select the optimal software-defined networking controller for network optimization.

However, in the prior art, the optimal software-defined networking controller was selected by quantitatively comparing network performance indicators such as benchmarking tools, processing time, and delay time.

Various embodiments are provided to provide a method and apparatus for selecting an optimal controller in Software Defined Networking. The technical problem to be achieved by the present disclosure is not limited to the technical problems as described above, and other technical problems may be inferred from the following embodiments.

According to an aspect of the present disclosure, in a method of selecting an optimal controller from among a plurality of controllers in software defined networking,

Setting a plurality of controllers and a plurality of functions serving as a reference for selecting an optimal controller; Evaluating a score according to importance for each of the plurality of functions for each of the plurality of controllers; Performing a qualitative analysis based on ANP (Analytic Network Process) based on the evaluated score; And selecting an optimal controller based on a block matrix obtained as a result of the qualitative analysis.

In addition, it may further include performing a quantitative analysis using a simulation on each of the plurality of controllers.

In addition, the performing of the qualitative analysis may include: generating a first comparison matrix indicating relative importance between the plurality of controllers for each of the plurality of functions; Calculating a first consistency ratio (CR) of the first comparison matrix; Determining whether the first CR is 0.1 or less; Generating a second comparison matrix indicating relative importance between the plurality of functions for each of the controllers; Calculating a second consistency ratio (CR) of the second comparison matrix; And determining whether the second CR is 0.1 or less.

In addition, the determining whether the first CR is less than or equal to 0.1 may include determining a first comparison matrix as a first final comparison matrix when the first CR is less than 0.1,

When the first CR is greater than 0.1, reevaluating a score according to the importance of each of the plurality of functions for each of the plurality of controllers, and determining whether the second CR is less than or equal to 0.1, the step of 2 When CR is less than 0.1, the second comparison matrix is determined as the second final comparison matrix, and when the second CR is greater than 0.1, the importance of each of the plurality of functions is determined for each of the plurality of controllers. The resulting score can be reevaluated.

Also, the block matrix may be generated based on the first final comparison matrix and the second final comparison matrix.

In addition, generating an extreme block matrix by repeating the power of the block matrix; And selecting a controller having the highest value in the limit block matrix as an optimal controller.

According to another aspect of the present disclosure, in a computer-readable recording medium in which a program for implementing a method for selecting an optimal controller among a plurality of controllers in Software Defined Networking is recorded, the method comprises: , Setting a plurality of controllers and a plurality of functions serving as a criterion for selecting an optimal controller; Evaluating a score according to importance for each of the plurality of functions for each of the plurality of controllers; Performing a qualitative analysis based on ANP (Analytic Network Process) based on the evaluated score; And selecting an optimal controller based on a block matrix obtained as a result of the qualitative analysis.

According to another aspect of the present disclosure, in a computer program stored in a medium to execute a method of selecting an optimal controller among a plurality of controllers in software defined networking, combined with hardware, the method comprises: , Setting a plurality of controllers and a plurality of functions serving as a criterion for selecting an optimal controller; Evaluating a score according to importance for each of the plurality of functions for each of the plurality of controllers; Performing a qualitative analysis based on ANP (Analytic Network Process) based on the evaluated score; And selecting an optimal controller based on a block matrix obtained as a result of the qualitative analysis.

1 is a flowchart illustrating an example of selecting an optimal controller from among a plurality of controllers in software defined networking.
FIG. 2 is a diagram illustrating an example of an ANP network structure set to select an optimal controller.
3 shows an example of a flowchart for performing qualitative analysis based on ANP.

Hereinafter, exemplary embodiments will be described in detail with reference to the accompanying drawings. It goes without saying that the following description is only for specifying the embodiments and does not limit or limit the scope of the invention. What can be easily inferred by experts in the art from the detailed description and examples is interpreted as belonging to the scope of the rights.

The terms “consisting of” or “including” used herein should not be construed as necessarily including all of the various elements or various steps described in the specification, and some of the elements or some steps It should be interpreted that they may not be included, or may further include additional components or steps.

In addition, terms including ordinal numbers such as'first' or'second' used in the present specification may be used to describe various elements, but the elements should not be limited by the terms. These terms are only used for the purpose of distinguishing one component from another component.

Terms used in the present specification have selected general terms that are currently widely used as possible while considering functions in the present invention, but this may vary depending on the intention or precedent of a technician working in the field, the emergence of new technologies, and the like. In addition, in certain cases, there are terms arbitrarily selected by the applicant, and in this case, the meaning of the terms will be described in detail in the description of the corresponding invention. Therefore, the terms used in the present invention should be defined based on the meaning of the term and the overall contents of the present invention, not a simple name of the term.

The present embodiments relate to a method and apparatus for optimizing a mission plan of an unmanned aerial vehicle, and detailed descriptions of matters widely known to those of ordinary skill in the art to which the following embodiments belong will be omitted.

1 is a flowchart illustrating an example of selecting an optimal controller from among a plurality of controllers in software defined networking.

Referring to FIG. 1, in step 110, an apparatus for selecting an optimal controller in Software Defined Networking may set a plurality of controllers and a plurality of functions that serve as a criterion for selecting the optimal controller. .

A plurality of controllers can be represented by Equation 1 below.

As shown in Equation 1, a plurality of controllers may correspond to a total of N controllers. For example, optimal controllers may be selected from a total of six controllers, but are not limited thereto, and a newly disclosed controller may be added or an existing controller may be removed.

For example, six controllers may be shown in Table 1 below. In Table 1 below, the names and expressions of each of the six controllers are described.

turn Controller name expression One FLOODLIGHT

2 ODL

3 ONOS

4 POX

5 RYU

6 TREMA

In addition, a plurality of functions can be represented by Equation 2 below.

As shown in Equation 2, the plurality of functions may correspond to a total of M functions. For example, a plurality of functions may correspond to 10 functions, but are not limited thereto, and new functions may be added or existing functions may be removed as necessary.

For example, 10 functions may be shown in Table 2 below. In Table 2 below, the names, expressions, descriptions and subdivisions of each of the ten functions are described.

turn Function name expression Description and subdivision One OpenFlow support

OpenFlow 1.0 ~ 1.5 2 Graphical user interface support

Python based, Web based. 3 Northbound API support

REST API. 4 Clustering support

To avoid single point of failure (reliability) 5 OpenStack networking support

Enabling different network technologies via Quantum API. 6 Synchronization

State synchronization of the network. 7 productivity

For developing software. 8 Partnership

Cisco, IBM, Intel, Linux Foundation and Juniper. 9 Supported operating system

Windows, Linux, Mac. 10 Modularization support

The extent of dividing the code in submodules.

In step 120, the device for selecting the optimal controller in the software-defined networking may evaluate a score according to the importance of each of the plurality of functions for each of the plurality of controllers. For example, Very High, High, according to the importance. It can be expressed as either Medium or Low. Alternatively, it can be expressed as either Yes or No depending on the importance. For each of the controllers in Table 1, the results of evaluating scores according to the importance of each function in Table 2 may be as shown in Table 3.

controller function

Medium Very High Yes Yes No Medium Medium Low Low Medium

High High Yes Yes Yes Medium Medium Very High High High

High High Yes Yes Yes Low Medium High High High

Low Medium No No No Low High Low High Low

Very High Low No Yes No High High Medium Low Medium

Low Low No Yes No Low High Low Low Medium

In step 130, the device for selecting an optimal controller in software-defined networking may perform a qualitative analysis based on an Analytic Network Process (ANP) based on the evaluated score.

ANP (Analytic Network Process) is a decision-making system using a network structure that includes interrelationships and dependencies among the three elements of goals, criteria, and alternatives.

The ANP process can be classified into 4 steps. In one step, we can perform network structuring of elements to solve the problem. Priority can be set for each element in 2 steps Consistency can be verified in 3 steps, and in the last 4 steps, an extreme super matrix can be created that derives complex priorities.

FIG. 2 is a diagram illustrating an example of an ANP network structure set to select an optimal controller.

Referring to FIG. 2, a network structure of an ANP set to select an optimal controller is shown. As shown in FIG. 2, the network structure of ANP may have a tree structure represented by a sequential flow of targets, criteria, and alternatives.

3 shows an example of a flowchart for performing qualitative analysis based on ANP.

In step 310, the apparatus for selecting an optimal controller in software defined networking may generate a first comparison matrix indicating relative importance between the plurality of controllers for each of the plurality of functions. The first comparison matrix may be generated to set priority according to each of the plurality of functions. When a plurality of controllers correspond to a total of N controllers and a plurality of functions correspond to a total of M functions, the first comparison matrix may be an M matrix of NxN. For example, when generating a first comparison matrix indicating the relative importance between the controllers of Table 1 for each of the functions of Table 2, a total of 10 matrices of 6X6 may be generated.

In the first comparison matrix, the (i,j) element of the matrix denotes a relative estimated weight representing the relative importance of Ci with respect to the controller Cj. In the first comparison matrix, since the (i,i) element of the matrix is a relative estimated weight between the same controllers, values of the diagonal elements of the matrix may correspond to 1.

Meanwhile, the relative estimated weight may be determined by the scale table of Table 4 below.

Scale Description One Equally important 2 Equally to moderately more important 3 Moderately more important 4 Moderately to significantly more important 5 Significantly more important 6 Significantly to remarkably more important 7 Remarkably more important 8 Remarkably to excessively more important 9 Excessively more important

In Table 4, relative estimated weights indicating relative importance may be expressed as 1 to 9. The scale value can be expressed as an reciprocal in the opposite case. Accordingly, a value corresponding to the (i,j) element of the matrix may correspond to the reciprocal of the value corresponding to the (j,i) element of the matrix. For example, the first comparison matrix of F1 indicating the relative importance between the controllers of Table 1 with respect to the F1 function (whether open flow is supported) of Table 2 may be as follows.

In the first comparison matrix of F1, the importance of the controller C1 for the F1 function is medium, and the importance of the controller C2 for the F1 function is high, so the value corresponding to the (1,2) element of the matrix is 1, which is the inverse of 3 Can be determined by /3.

In step 320, the apparatus for selecting an optimal controller in software-defined networking may calculate a first consistency ratio (CR) of the first comparison matrix.

In order to calculate the coherence ratio first CR, a first standard matrix obtained by dividing the value of each element of the first comparison matrix by the sum of columns may be obtained. For example, a first standard matrix obtained by dividing the value of each element of the first comparison matrix of F1 by the total number of columns may be as follows.

Next, the Eigenvector X used as the importance vector can be calculated. The i-th element xi of the high value can be calculated by Equation 5 below.

는 제 1 비교 행렬의 (i,j) 요소에 해당하는 값이다. Referring to Equation 3, the first standard matrix can be obtained by dividing the sum of the columns of the first comparison matrix by the number of columns.

Is a value corresponding to the (i,j) element of the first comparison matrix.

Next, it is possible to add a high value to the first standard matrix. For example, the case of adding a high value to the first standard matrix of F1 may be as follows.

Next, in order to calculate the first CR, a Consistency Measure (CM), a Consistency Index (CI), and a Rank Index (RI) may be calculated.

CM Yj can be calculated by Equation 7 below.

는 고윳값 X의 j번째 요소에 해당할 수 있다. In Equation 7, F corresponds to the first comparison matrix and X corresponds to the high value.

May correspond to the j-th element of the high value X.

를 구할 수 있으며, 이를 이용하여 CI를 계산할 수 있다. CI는 하기 수학식 5 에 의해 계산될 수 있다. At this time, the average of Yj

Can be obtained, and CI can be calculated using this. CI can be calculated by Equation 5 below.

Meanwhile, the RI may be a fixed value determined according to Table 5 below as a ratio of the index.

Count One 2 3 4 5 6 7 8 9 10 RI 0.00 0.00 0.58 0.90 1.12 1.24 1.32 1.41 1.45 1.49

For example, in the case of the first standard matrix of F ₁ , since n = 6, RI may be 1.24.

Finally, CR can be calculated by Equation 6 below.

According to Equation 6, the first CR of the consistency ratio of the first comparison matrix of Table 2 may be calculated as 0.09.

In step 330, the device for selecting an optimal controller in software defined networking may determine whether the first CR is 0.1 or less.

In software-defined networking, an apparatus for selecting an optimal controller may allow only a CR value of 0.1 or less to determine the consistency of the comparison matrix. If the CR value exceeds 0.1, proceed to step 310, and if the CR value is less than 0.1, proceed to step 340. When the CR value is 0.1 or less, the corresponding first comparison matrix may be determined as the first final comparison matrix. If the CR value exceeds 0.1, it is considered that the qualitative evaluation is inconsistent, and the scores according to the importance of each of the plurality of functions are re-evaluated for each of the plurality of controllers. Accordingly, a first comparison matrix is newly generated.

In step 340, the apparatus for selecting an optimal controller in software defined networking may generate a second comparison matrix indicating relative importance between the plurality of functions for each of the controllers.

When a plurality of controllers correspond to a total of N controllers and a plurality of functions correspond to a total of M functions, the second comparison matrix may be a matrix of N MxMs. For example, when generating a second comparison matrix representing the relative importance between the functions of Table 2 for each of the controllers of Table 1, a total of 6 matrices of 10×10 may be generated. The process of generating the second comparison matrix may be the same as the process of generating the first comparison matrix, and thus is omitted.

In step 350, the apparatus for selecting an optimal controller in software-defined networking may calculate a second consistency ratio (CR) of the second comparison matrix. The process of calculating the second CR of the consistency ratio of the second comparison matrix may be the same as the process of calculating the first CR of the first comparison matrix, and thus is omitted.

In step 360, the device for selecting an optimal controller in software-defined networking may determine whether the second CR is 0.1 or less.

If the second CR value exceeds 0.1, the process proceeds to step 340, and if the second CR value is less than 0.1, the process ends. When the second CR value is 0.1 or less, the second comparison matrix may be determined as the second final comparison matrix. If the second CR value exceeds 0.1, it is considered that the qualitative evaluation is inconsistent, and the scores according to the importance of each of the plurality of functions are reevaluated for each of the plurality of controllers. Accordingly, a second comparison matrix is newly generated.

Returning to FIG. 1 again, in step 140, the apparatus for selecting an optimal controller in software-defined networking may select an optimal controller based on a block matrix obtained as a result of qualitative analysis.

The block matrix may be generated based on the first final comparison matrix and the second final comparison matrix. If a plurality of controllers correspond to a total of N controllers and a plurality of functions correspond to a total of M functions, a block matrix having a high value as an element of the matrix is a (N+M) X (N+M) matrix. May be applicable.

The block matrix for the controllers of Table 1 and the functions of Table 2 may be as follows.

Meanwhile, an extreme block matrix may be generated by repeating the power of the generated block matrix. It is possible to repeat the power of the block matrix until the values of the elements constituting the matrix do not change.

An example of an extreme block matrix for the controllers of Table 1 and the functions of Table 2 may be as follows.

Referring back to FIG. 1, in step 140, an apparatus for selecting an optimum controller in software defined networking may select an optimum controller based on a block matrix obtained as a result of qualitative analysis.

For example, a controller having the highest value in an extreme block matrix generated by repeating the power of the block matrix may be selected as the optimal controller.

Controller C2 may be selected as an optimal controller from the limiting block matrix for the controllers in Table 1 and the functions in Table 2 above.

Meanwhile, an apparatus for selecting an optimal controller in software defined networking may additionally perform a quantitative analysis using a simulation on each of a plurality of controllers. In the process of quantitative analysis, for example, topologies such as the European reference network, the USA backbone IP network, and OS3E can be considered. Alternatively, the network manager can perform simulation by simulating the structure of the currently operated network.

The simulation tool may correspond to an open source tool such as Mininet, a commercial tool, or a discrete test tool, but is not limited thereto. The comparative performance index in quantitative analysis may be, but is not limited to, the topology detection time of the controller, the delay time, the packet throughput of the controller, and the CPU capacity of the controller.

According to the quantitative analysis result, the effectiveness of the controller derived from the above-described ANP qualitative analysis result can be confirmed. For example, if the controller with the highest priority has a significantly lower rating from another controller in the qualitative performance analysis, the qualitative evaluation can be performed again.

Meanwhile, the above-described embodiments of the present invention can be written as a program that can be executed on a computer, and can be implemented in a general-purpose digital computer that operates the program using a computer-readable recording medium. In addition, the structure of the data used in the above-described embodiment of the present invention can be recorded on a computer-readable recording medium through various means. The computer-readable recording medium includes a storage medium such as a magnetic storage medium (for example, a ROM, a floppy disk, a hard disk, etc.) and an optical reading medium (for example, a CD-ROM, a DVD, etc.).

So far, the present invention has been looked at around its preferred embodiments. Those of ordinary skill in the art to which the present invention pertains will be able to understand that the present invention can be implemented in a modified form without departing from the essential characteristics of the present invention. Therefore, the disclosed embodiments should be considered from an illustrative point of view rather than a limiting point of view. The scope of the present invention is shown in the claims rather than the foregoing description, and all differences within the scope equivalent thereto should be construed as being included in the present invention.

Claims (8)

In a method of selecting an optimal controller from among a plurality of controllers in software defined networking,
Setting a plurality of controllers and a plurality of functions serving as a reference for selecting an optimal controller;
Evaluating a score according to importance for each of the plurality of functions for each of the plurality of controllers;
Performing a qualitative analysis based on ANP (Analytic Network Process) based on the evaluated score; And
Including the step of selecting an optimal controller based on the block matrix (block matrix) obtained as a result of the qualitative analysis,
The step of performing the qualitative analysis,
Generating a first comparison matrix indicating relative importance between the plurality of controllers for each of the plurality of functions;
Calculating a first consistency ratio (CR) of the first comparison matrix;
Determining whether the first CR is 0.1 or less;
Generating a second comparison matrix indicating relative importance between the plurality of functions for each of the controllers;
Calculating a second consistency ratio (CR) of the second comparison matrix; And
Including the step of determining whether the second CR is 0.1 or less,
The first CR,
The method, characterized in that calculated based on a constant corresponding to each of the total number of the controllers. The method of claim 1,
The method further comprising performing a quantitative analysis using a simulation on each of the plurality of controllers. delete The method of claim 1,
The step of determining whether the first CR is 0.1 or less,
When the first CR is less than 0.1, the first comparison matrix is determined as the first final comparison matrix,
When the first CR is greater than 0.1, a score according to the importance of each of the plurality of functions is reevaluated for each of the plurality of controllers
The step of determining whether the second CR is 0.1 or less,
When the second CR is less than 0.1, a second comparison matrix is determined as a second final comparison matrix,
When the second CR is greater than 0.1, a method of re-evaluating a score according to an importance level for each of the plurality of controllers. The method of claim 4,
The block matrix is generated based on the first final comparison matrix and the second final comparison matrix. The method of claim 1,
Generating an extreme block matrix by repeating the power of the block matrix; And
And selecting a controller having the highest value in the extreme block matrix as an optimal controller. In a computer-readable recording medium in which a program for implementing a method for selecting an optimal controller among a plurality of controllers in Software Defined Networking is recorded,
The above method,
Setting a plurality of controllers and a plurality of functions serving as a reference for selecting an optimal controller;
Evaluating a score according to importance for each of the plurality of functions for each of the plurality of controllers;
Performing a qualitative analysis based on ANP (Analytic Network Process) based on the evaluated score; And
Including the step of selecting an optimal controller based on a block matrix obtained as a result of the qualitative analysis,
The step of performing the qualitative analysis,
Generating a first comparison matrix indicating relative importance between the plurality of controllers for each of the plurality of functions;
Calculating a first consistency ratio (CR) of the first comparison matrix;
Determining whether the first CR is 0.1 or less;
Generating a second comparison matrix indicating relative importance between the plurality of functions for each of the controllers;
Calculating a second consistency ratio (CR) of the second comparison matrix; And
Including the step of determining whether the second CR is 0.1 or less,
The first CR,
The recording medium, characterized in that calculated based on a constant corresponding to each of the total number of the controllers. In a computer program stored in a medium to execute a method of selecting an optimal controller from among a plurality of controllers in software defined networking, combined with hardware,
The above method,
Setting a plurality of controllers and a plurality of functions serving as a reference for selecting an optimal controller;
Evaluating a score according to importance for each of the plurality of functions for each of the plurality of controllers;
Performing a qualitative analysis based on ANP (Analytic Network Process) based on the evaluated score; And
Including the step of selecting an optimal controller based on a block matrix obtained as a result of the qualitative analysis,
The step of performing the qualitative analysis,
Generating a first comparison matrix indicating relative importance between the plurality of controllers for each of the plurality of functions;
Calculating a first consistency ratio (CR) of the first comparison matrix;
Determining whether the first CR is 0.1 or less;
Generating a second comparison matrix indicating relative importance between the plurality of functions for each of the controllers;
Calculating a second consistency ratio (CR) of the second comparison matrix; And
Including the step of determining whether the second CR is 0.1 or less,
The first CR,
Computer program, characterized in that calculated based on a constant corresponding to each of the total number of the controllers.

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