JP2018037035A - Quality degradation estimation device, quality degradation estimation method, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a quality degradation estimation device capable of estimating quality degradation value on each node by using a measured end-end value in a telecommunication network while improving the accuracy in estimation of quality degradation.SOLUTION: The quality degradation estimation device for estimating quality degradation of a node constituting a telecommunication network, includes: input means that inputs a quality measured value in each observation path, the number of connections of in a communication on each observation path, and a piece of information on each observation path; calculation means that calculates an estimation value of degradation amount on each node based on a quality measured value of the observation path from which observation paths in which the number of communication connections is smaller than the predetermined threshold level is excluded from entire observation paths and the path information of the observation path; and output means that outputs the estimation value of degradation amount on each node.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a technique for estimating / determining how much deterioration has occurred in connection points of nodes in a communication using an end-to-end quality measurement value in the communication as an input.

  In mobile communications, quality degradation occurs in various locations due to diversification of user environments and diversification of usage methods. In order to improve the quality of mobile communication services, it is important to understand the degradation location.

  However, although it is possible to perform end-to-end measurement in quality measurement, it is difficult to determine the degree of deterioration at each location (server, ISP, access node, terminal, etc.) from the measurement result. As a prior art regarding this point, there is a technique disclosed in Non-Patent Document 1. Non-Patent Document 1 discloses a technique for estimating the deterioration amount of each node with a small amount of calculation by utilizing the relationship between the nodes for which deterioration is estimated as a graph structure.

Tayuki et al., "Estimation of communication quality degradation using geographical dependence of mobile network", IEICE Technical Report, vol. 116, no. 10, CQ2016-1, pp. 1-6, April 2016

  In the prior art, for example, when the degradation location is estimated using the end-to-end quality measured in the mobile terminal, the degradation location is estimated because the number of terminals to be measured is small or the measurement performance of the terminal is low. For this reason, there arises a problem that high-precision measurement data necessary for this cannot be obtained. In the prior art, the degradation location is estimated using the relationship between nodes, so such low-reliability measurement data is not only the degradation amount estimation accuracy of the node through which the measurement data passes, but also its neighboring Multiple estimation accuracy may be affected.

  The present invention has been made in view of the above points, and improves the estimation accuracy of the quality degradation amount in the technology for estimating the value of the quality degradation amount for each node using the end-to-end measurement value in the communication network. The purpose is to provide technology.

According to the disclosed technology, a quality degradation estimation apparatus that estimates quality degradation of nodes constituting a communication network,
An input means for inputting the quality measurement value of each observation route, the number of communication connections of each observation route, and the route information of each observation route;
Calculation to calculate the estimated value of the degradation amount of each node based on the measured quality value of the observed route excluding the observed route whose number of communication connections is equal to or less than the predetermined threshold from all the observed routes and the route information of the observed route Means,
An output means for outputting an estimated value of the deterioration amount of each node is provided.

  According to the disclosed technique, a technique for improving the estimation accuracy of the quality degradation amount is provided in the technology for estimating the value of the quality degradation amount for each node using the end-to-end measurement value in the communication network.

It is a block diagram of the quality degradation estimation apparatus 100 in embodiment of this invention. It is a hardware block diagram of the quality degradation estimation apparatus 100. It is a figure which shows the deterioration amount of the node in an Example. It is a figure which shows the estimation error of deterioration amount.

  Hereinafter, an embodiment (this embodiment) of the present invention will be described with reference to the drawings. The embodiment described below is merely an example, and the embodiment to which the present invention is applied is not limited to the following embodiment. In the communication network of the present embodiment (hereinafter referred to as a target communication network), a communication device such as a server, a relay device, or a base station that is a target for estimating a quality degradation amount is referred to as a “node”. The “node” includes not only a single network device but also a configuration including a set of network devices such as an ISP and a carrier network. The target communication network is not limited to a specific type of network, and may be, for example, a mobile network, a fixed network, or a network in which a mobile network and a fixed network are mixed. However, other nets may be used.

  In the present embodiment, each node constituting the target communication network has a value, and the larger the value, the larger the deterioration amount. And the quality degradation estimation apparatus 100 estimates the value of each node which comprises a communication network from the quality measurement value (end-end quality measurement) between two arbitrary nodes. Hereinafter, the apparatus configuration and processing contents will be described.

(Device configuration)
FIG. 1 shows a configuration diagram of a quality degradation estimation apparatus 100 in the present embodiment. As shown in FIG. 1, the quality degradation estimation apparatus 100 includes an input unit 101 that inputs data used for quality degradation estimation, a computation unit 102 that performs quality degradation estimation, and an output unit 103 that outputs the result of the computation. And a data storage unit 104 that stores input data, mid-calculation data, calculation results, programs, and the like.

  The quality degradation estimation apparatus 100 in the present embodiment can be realized by causing a computer to execute a program describing the processing contents described in the present embodiment. That is, the function of the quality degradation estimation apparatus 100 can be realized by executing a program corresponding to processing executed in the apparatus using hardware resources such as a CPU and a memory built in the computer. Is possible. The above-mentioned program can be recorded on a computer-readable recording medium (portable memory or the like), stored, or distributed. It is also possible to provide the program through a network such as the Internet or electronic mail.

  FIG. 2 is a diagram illustrating a hardware configuration example of the quality degradation estimation apparatus 100 according to the present embodiment. 2 includes a drive device 150, an auxiliary storage device 152, a memory device 153, a CPU 154, an interface device 155, a display device 156, an input device 157, and the like that are mutually connected by a bus B. .

  A program that realizes processing in the quality degradation estimation apparatus 100 is provided by a recording medium 151 such as a CD-ROM or a memory card, for example. When the recording medium 151 storing the program is set in the drive device 150, the program is installed from the recording medium 151 into the auxiliary storage device 152 via the drive device 150. However, the program does not necessarily have to be installed from the recording medium 151, and may be downloaded from another computer via a network. The auxiliary storage device 152 stores the installed program and also stores necessary files and data.

  The memory device 153 reads the program from the auxiliary storage device 152 and stores it when there is an instruction to start the program. The CPU 154 realizes functions related to the quality degradation estimation apparatus 100 in accordance with a program stored in the memory device 153. The interface device 155 is used as an interface for connecting to a network. The display device 156 displays a GUI (Graphical User Interface) or the like by a program. The input device 157 includes a keyboard and mouse, buttons, a touch panel, and the like, and is used to input various operation instructions.

(Operation of the quality degradation estimation apparatus 100)
Next, as an operation of the quality degradation estimation apparatus 100, the quality degradation estimation method in the present embodiment will be described in detail.

<Definition>
As described above, a communication device such as a server, a relay device, or a base station that is a target for estimating the amount of quality degradation in the target communication network is called a node. A set of a plurality of nodes of the same type, such as a plurality of servers and a plurality of terminals, is called a group. In this embodiment, there are group 1 and group 2, and nodes belonging to group 1 are represented as a ₁ , a ₂ ,..., A _N1, and nodes belonging to group 2 are represented as b ₁ , b _{2 ,.} Represent. Further, the degradation amount of the node belonging to the group 1 is represented as x = (x ₁ x ₂ ... X _N1 ) ^、, and the degradation amount of the node belonging to the group 2 is represented as y = (y ₁ y ₂ ... Y _N2 ) ^Τ .

  For the nodes belonging to group 1, the similarity of deterioration amounts between nodes is represented by a graph structure, and the undirected graph is represented by G. Note that the similarity of the deterioration amounts is whether the deterioration amounts are similar.

A path between the node a _i belonging to the group 1 and the node b _j belonging to the group 2 is represented as an observation path (i, j). Let N _{i, j be the} number of communication connections on route (i, j). The number of communication connections is the number of communications performed through the route.

<Input>
At least the following data is input to the input unit 101 of the quality degradation estimation apparatus 100. The input data is stored in the data storage unit 104, and is read out and calculated by the calculation unit 102 in the subsequent processing. In addition to the following input data, values such as a threshold value N _th necessary for processing are also input as appropriate.

Input 1: Number of communication connections for each observation route with M observation routes and measurement data z _{m for} each observation route
Input 2: Graph Laplacian for graph structure G that represents the similarity of degradation between nodes in group 1: L
Input 3: Matrix representing route information (nodes composing communication) of observation route when input 1 is measured: A ₁ , A ₂
<Details of input 2>
A method for obtaining the graph Laplacian L constituting the graph G of the number of nodes N ₁ of the group 1 with respect to the input 2 will be described.

A distance d _{j, k} between nodes a _j and a _k included in the graph G is defined. This distance d is an index representing the similarity of deterioration between nodes. The distance d can be, for example, a geographical distance, but is not limited thereto, and may be any value as long as the similarity is a decreasing function of the distance d. Here, the attenuation function is defined as f (x).

  The graph Laplacian L is calculated by L = D-C. C and D are as follows.

C is an N × N adjacency matrix, and the element c _{j, k} (j, k = 1,2, ..., N ₁ ) of C is 0 when j = k, c _{j, k} = c _{k, Satisfies j} . c _{j, k} when j = k is not different between the unweighted graph and the weighted graph as follows.

In the case of a weightless graph in which no weight is given to the branch of the graph G, c _{j, k} = 1 if d _{j, k} is equal to or less than a certain threshold value e *, and c _{j, k} = 0 otherwise. In the case of a weighted graph, c _{j, k} = f (d _{j, k} ).

D is an N × N degree matrix, and the elements g _{j, k} (j, k = 1,2,..., N) of D are diagonal matrices of 0 when j ≠ k, and g _{j, j} Is given by:

<Details of input 3>
A ₁ of input 3 is a matrix of (observed path number M) × (number of nodes of group 1 N ₁ ) consisting of 0 or 1 and A ₂ of input 3 is composed of 0 or 1 (number of observed paths M ) × (number of nodes in group 2 N ₂ ).

The (m, n ₁ ) component of A ₁ (m = 1,2,… M, n ₁ = 1,2,… N ₁ ) has an observation path (i _m , j _m ) passing through the node an _n1 1 if so, 0 otherwise. In addition, the (m, n ₂ ) component of A2 (m = 1,2,… M, n ₂ = 1,2, ... N ₂ ) passes through the node b _n2 through the observation path (i _m , j _m ). 1 if yes, 0 otherwise.

  In the present embodiment, the input 2 (graph Laplacian L) may be calculated in advance outside the quality degradation estimation device 100 and input to the quality degradation estimation device 100, or may be input to the quality degradation estimation device 100. By giving the information of the graph G and the distance d to the unit 101, the calculation unit 102 may calculate the graph Laplacian L and store it in the data storage unit 104. Also, U, which will be described later, may be calculated in advance outside the quality degradation estimation apparatus 100 and input to the quality degradation estimation apparatus 100, or may be calculated by the quality degradation estimation apparatus 100.

(Processing procedure for estimating quality degradation)
Next, processing for estimating quality degradation performed by the calculation unit 102 based on the inputs 1 to 3 and the like will be described. Basically, the results of the processing executed by the calculation unit 102 are sequentially stored in the data storage unit 104, and read and used by the calculation unit 102 in the next processing.

<Create U>
First, the calculation unit 102 obtains eigenvalues λ _i (i = 1, 2,... N ₁ ) of the graph Laplacian L of the graph G. Also, an eigenvector u _i corresponding to the eigenvalue λ _i is obtained, and a matrix U = (u ₁ u ₂ ... U _N1 ) (N1 × N1 matrix) in which eigenvectors are arranged is created. Here, U is an orthonormal matrix.

<Rejection processing of measurement data with low reliability>
The m-th (m = 1, 2,... M) observation path in the number M of observation paths is represented as (i _m , j _m ). As already described, (i _m , j _m ) is a path between the node a _{im in} group 1 and the node b _{jm in} group 2. The end-to-end quality obtained by the k-th connection of the observation path (i _m , j _m ⁾ is expressed as z _m ^(k) . At this time, the measurement data z _m obtained on the observation path (i _m , j _m ) is given by the following equation. That is, for a certain observation path, the average quality for each connection is the quality of the observation path.

In this embodiment, a threshold value N _th is set for N _{im, jm} , and the calculation unit 102 evaluates the reliability of z _m using the threshold value N _th . That is, the arithmetic unit 102 determines that z _m is low-reliable measurement data if N _{im, jm} ≦ N _th and rejects it. The number of measurement data remaining without being rejected is represented by M, and a set representing the measurement data is represented by an observation vector z = (z ₁ z ₂ ... Z _M ) ^Τ . Further, the respective also A ₁ and A _2, except for the row corresponding to the observation path has been rejected from the first A ₁ and A ₂ Gyorei.

<Node quality estimation process>
The relationship between z obtained as described above, the degradation amount x of the nodes belonging to group 1, and the degradation amount y of the nodes belonging to group 2 is given by the following equation.

z = A ₁ x + A ₂ y
The above formula indicates that the sum of the values of the nodes on the observation path is the quality measurement value.

Further, x is expressed as x = Us using the matrix U. However, s = (s ₁ s ₂ ... S _N1 ) ^Τ . Thus, the above relational expression can be expressed as follows.

z = A ₁ Us + A ₂ y
As described above, since a relationship in which the relationship between the observation (measurement value) vector and the unknown vector is expressed linearly is obtained, the calculation unit 102 solves the linear inverse problem based on the relationship as an optimization problem. Thus, the vectors s and y are estimated and further converted to estimate the vector x that is the value of each node in group 1. Specifically, it is as follows. Hereinafter, Lasso (Least absolute shrinkage and selection operator) is used as an estimation method, but estimation may be performed by a method other than Lasso. Lasso is a normalized estimation method using the sum of absolute values (L1 norm) of regression coefficients as a normalization term. For example, “Seung-Jean Kim; Stanford Univ., Stanford; Koh, K.; Lustig, M.; Boyd, S. et al.“ An Interior-Point Method for Large-Scale l1- Regularized Least Squares "".

  Specifically, the calculation unit 102 estimates a vector s by solving a Lasso estimation expression represented by the following expression using sparse approximation.

However, λ ₁ and λ ₂ are parameters. Further, with respect to the vector _{w = (w 1 w 2 ...} w N) Τ, || w || l (l = 1,2) is given by the following equation.

The calculation unit 102 obtains x by x = Us using s obtained as a solution to the optimization problem.

<Output>
Subsequently, the output unit 103 outputs the obtained result. In this embodiment, x and y are output. Note that outputting the values of x and y is an example, and another value obtained from x and y may be output.

(Example)
An embodiment as a specific example in which the quality degradation estimation apparatus 100 performs quality degradation estimation by the above-described method will be described.

In this embodiment, the number of nodes in group 1 is N ₁ = 25, the number of nodes in group 2 is N ₂ = 10, and the graph structure between nodes in group 1 and the amount of degradation are given as shown in FIG. The deterioration amount of the nodes belonging to group 2 is given as shown in FIG. In addition, the diagonal line shown in the graph structure of Fig.3 (a) shows the contour line of deterioration amount.

Under the above assumption, as an experiment, quality measurement for each observation path is performed and input to the quality degradation estimation apparatus 100. The quality degradation estimation apparatus 100 estimates the value of each node by the method already described. It was. Here, estimation was performed for each of N _th = 0 and N _th = 14.

FIG. 4A shows an estimation error of the group 1 node when N _th = 0, that is, when the experiment for estimating the deterioration amount is performed 100 times without rejecting the measurement data. The estimation error is the difference between the actual deterioration amount of each node given as a premise and the estimated deterioration amount estimated by the quality deterioration estimation device 100. FIG. 4B shows an estimation error when the measurement data is rejected with N _th = 14.

  As shown in FIGS. 4A and 4B, it can be seen that the estimation accuracy is improved by rejecting the low-reliability measurement data.

(Effect of embodiment)
For example, when the existing technology of Non-Patent Document 1 is used to estimate the amount of degradation of communication devices constituting a mobile network, stable and reliable measurement data is always obtained due to a phenomenon unique to mobile communication such as movement of a terminal. It cannot be acquired. When low-reliable measurement data is used, it affects not only the amount of degradation of the communication device on the observation path from which the measurement data was acquired but also the estimation accuracy of other communication devices.

  The technology according to the present embodiment is a technology that compensates for such problems of the existing technology, and improves the estimation accuracy of the amount of quality degradation by selecting measurement data according to its reliability. . The technique according to the present embodiment is not merely for rejecting data with low reliability, but interpolates a decrease in estimation accuracy that should be caused by rejected measurement data by a graph structure representing the degree of similarity of the deterioration amount. Yes.

(Summary of embodiment)
As described above, according to the present embodiment, a quality deterioration estimation device that estimates the quality deterioration of nodes constituting a communication network, the quality measurement value of each observation path, the number of communication connections of each observation path, and Based on the input means for inputting the route information of each observation route, the quality measurement value of the observation route excluding the observation route whose number of communication connections is a predetermined threshold or less from all the observation routes, and the route information of the observation route There is provided a quality deterioration estimation device comprising: an arithmetic means for calculating an estimated value of the deterioration amount of each node; and an output means for outputting the estimated value of the deterioration amount of each node.

  The calculation means is a matrix in which a vector composed of the quality measurement values, a matrix composed of the path information, and an eigenvector of a graph Laplacian matrix corresponding to a graph structure representing the similarity of deterioration between nodes are arranged. It is good also as calculating the estimated value of the degradation amount of each node by solving the estimation formula using these.

  The input unit 101, the calculation unit 102, and the output unit 103 described in the embodiment are examples of an input unit, a calculation unit, and an output unit, respectively.

  Although the present embodiment has been described above, the present invention is not limited to the specific embodiment, and various modifications and changes can be made within the scope of the gist of the present invention described in the claims. Is possible.

DESCRIPTION OF SYMBOLS 100 Quality degradation estimation apparatus 101 Input part 102 Operation part 103 Output part 104 Data storage part 150 Drive apparatus 151 Recording medium 152 Auxiliary storage apparatus 153 Memory apparatus 154 CPU
155 Interface device 156 Display device 157 Input device

Claims (5)

A quality degradation estimation device for estimating quality degradation of nodes constituting a communication network,
An input means for inputting the quality measurement value of each observation route, the number of communication connections of each observation route, and the route information of each observation route;
Calculation to calculate the estimated value of the degradation amount of each node based on the measured quality value of the observed route excluding the observed route whose number of communication connections is equal to or less than the predetermined threshold from all the observed routes and the route information of the observed route Means,
An output means for outputting an estimated value of the deterioration amount of each node. The calculation means is a matrix in which a vector composed of the quality measurement values, a matrix composed of the path information, and an eigenvector of a graph Laplacian matrix corresponding to a graph structure representing the similarity of deterioration between nodes are arranged. The quality degradation estimation apparatus according to claim 1, wherein an estimated value of the degradation amount of each node is calculated by solving an estimation formula using A quality degradation estimation method executed by a quality degradation estimation device that estimates quality degradation of nodes constituting a communication network,
An input step for inputting the quality measurement value of each observation route, the number of communication connections of each observation route, and route information of each observation route;
Calculation to calculate the estimated value of the degradation amount of each node based on the measured quality value of the observed route excluding the observed route whose number of communication connections is equal to or less than the predetermined threshold from all the observed routes and the route information of the observed route Steps,
An output step of outputting an estimated value of the deterioration amount of each node. In the calculation step, the quality degradation estimation device is configured to provide a graph Laplacian corresponding to a vector composed of the quality measurement values, a matrix composed of the path information, and a graph structure representing similarity of degradation between nodes. The quality degradation estimation method according to claim 3, wherein an estimated value of a degradation amount of each node is calculated by solving an estimation formula using a matrix in which eigenvectors of the matrix are arranged.   The program for functioning a computer as each means in the quality degradation estimation apparatus of Claim 1 or 2.