KR101818870B1 - Reliability based distributed synchronization method in distributed network with malfunctioning terminal and apparatus therefor - Google Patents

Abstract

The present invention provides a method and a device for reliability-based distribution synchronization, which can obtain synchronization between terminals even when a malfunctioning terminal exists by utilizing a reliability-based adaptive consensus algorithm in a distributed network with the malfunctioning terminal. According to an embodiment of the present invention, the method for reliability-based distribution synchronization in a distributed network comprises the following steps of: evaluating reliability with respect to at least one neighboring terminal; determining a weight of a predetermined response function based on the evaluated reliability; and obtaining the synchronization based on the response function having the determined weight.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention [0001] The present invention relates to a reliability-based distributed synchronization method and apparatus in a distributed network in which a malfunctioning terminal exists,

The present invention relates to a reliability-based distributed synchronization technique, and more particularly, to a reliability-based distributed synchronization technique that acquires inter-terminal synchronization even in the presence of a malfunctioning terminal by using a reliability-based adaptive consensus algorithm in a distributed network in which a malfunctioning terminal exists And more particularly, to a reliability-based distributed synchronization method and apparatus.

A distributed wireless communication network is a system capable of performing communication only by cooperation among terminals without a central control type infrastructure such as a base station of an existing cellular network. Accordingly, the distributed wireless communication network can easily install and dismount the communication network as needed without construction of the base station, which consumes much time and cost, and high mobility is ensured.

Also, unlike a central control type network in which a central control type base station has to process all traffic generated in a cell, a distributed type wireless communication network performs wireless communication through autonomous cooperation among terminals, And it is attracting attention as a next generation communication technology for surging traffic.

However, due to the absence of a base station in a distributed network, various technical obstacles exist such as synchronization among terminals, resource allocation and routing. In particular, in the case of failing to acquire the inter-terminal synchronization, wireless communication can not be started. Therefore, the inter-terminal synchronization has to be acquired indispensably.

The distributed synchronization algorithm aims to ensure that all terminals belonging to the network have the same status value. Representative state values include center frequency, symbol timing, and the like. Generally, each terminal has an initial state value of a certain value between a certain minimum value and a maximum value. Hereinafter, a specific minimum value is considered to be normalized to 0 and a maximum value to 1.

In a consensus-based distributed synchronization algorithm, which is a typical distributed synchronization algorithm, terminals belonging to the network periodically transmit their state values to neighboring terminals. Then, the state values received from the neighboring terminals and their state values are inputted into a predetermined response function for one cycle, and the output values are updated to their own state values. In this case, the most general response function is the local average. That is, an average of the state values of neighboring terminals received during one period with the same weight value is obtained, and the state value is updated with this value.

In this conventional method, as shown in FIG. 1, five terminals belonging to the network have started to synchronize with different initial state values between 0 and 1, but they have converged to the same state values within 9 periods have. In this way, when all terminals belonging to the network operate according to a predetermined rule, it can be confirmed that the status values of all terminals converge to the same value.

However, if a malfunctioning terminal or a malfunctioning terminal belongs to the network for the purpose of preventing synchronization between the terminals, the existing consensus-based distributed synchronization algorithm can not guarantee synchronization between the terminals. In particular, this problem is further exacerbated when one or more malfunctioning terminals exist or terminals belonging to the network fail to receive status values from all terminals due to fading effects. These problems can easily occur in a realistic distributed network, but the solution is still lacking.

If the inter-terminal synchronization can not be obtained in the distributed network, the terminals belonging to the network can not start wireless communication. For example, if frequency synchronization between terminals, symbol timing synchronization, and the like are not obtained, communication becomes impossible due to noise and interference due to synchronization errors.

Accordingly, there is a need for a method capable of improving the synchronization performance of the terminals belonging to the network by minimizing the influence from the malfunctioning terminal when the malfunctioning terminal exists in the network.

Embodiments of the present invention provide a reliability-based distributed synchronization method capable of acquiring inter-terminal synchronization even in the presence of a malfunctioning terminal utilizing a reliability-based adaptive consensus algorithm in a distributed network in which a malfunctioning terminal exists, Device.

That is, embodiments of the present invention provide a reliability-based distributed synchronization method and apparatus capable of minimizing the influence of a malfunction generated in a synchronization process of a distributed network using an adaptive consensus algorithm based on a reliability, to provide.

The reliability-based distributed synchronization method according to an embodiment of the present invention is a reliability-based distributed synchronization method in a distributed network, the method comprising: evaluating reliability of at least one neighboring terminal; Determining a weight of a predetermined response function based on the estimated reliability; And acquiring synchronization based on the response function having the determined weight.

The evaluating step may evaluate the reliability of the neighboring terminal based on the local average calculated using the state value of the neighboring terminal and the state value of the neighboring terminal and the state value of the neighboring terminal.

The determining may determine a weight of the response function based on the evaluated reliability and a predetermined strength setting value for the response function based on the evaluated reliability.

The determining may determine a weight of the response function such that the sum of the weights is equal to one.

The acquiring may update the state value based on the response function having the determined weight, and acquire the synchronization based on the updated state value.

The response function may include a response function of the consensus algorithm.

The reliability-based distributed synchronizing apparatus according to an embodiment of the present invention includes an evaluation unit for evaluating reliability of at least one neighboring terminal in a reliability-based distributed synchronous apparatus in a distributed network; A determining unit that determines a weight of a predetermined response function based on the estimated reliability; And an acquiring unit for acquiring synchronization based on the response function having the determined weight.

The evaluator may evaluate the reliability of the neighboring terminal based on the regional average calculated using the state value of the terminal and the state value of the neighboring terminal.

The determination unit may determine a weight of the response function based on the estimated reliability and the predetermined reliability setting value for the response function based on the estimated reliability.

The determining unit may determine the weight of the response function such that the sum of the weights is equal to one.

The obtaining unit may update the state value based on the response function having the determined weight and obtain the synchronization based on the updated state value.

According to the embodiments of the present invention, it is possible to minimize the influence of malfunction generated in the synchronization process of the distributed network using the reliability-based adaptive consensus algorithm and improve the synchronization performance between the terminals.

According to the embodiments of the present invention, a relatively simple operation is required compared with the existing distributed synchronous method, so that implementation and utilization can be very easy.

FIG. 1 shows a state value change of each terminal when an average consensus algorithm is used in a distributed network in which no malfunction exists.
2 is a conceptual diagram of a representative distributed network.
3 shows a change in the state value when a static malfunctioning terminal exists in a distributed network and an average consensus algorithm is used.
FIG. 4 shows a change in state value when a dynamic malfunctioning terminal exists in a distributed network and an average consensus algorithm is used.
5 is a flowchart illustrating an operation of the reliability-based split-time synchronization method according to an embodiment of the present invention.
6 shows the synchronization performance by the conventional average consensus algorithm and the method according to the present invention in a distributed network with static malfunctions.
Figure 7 shows the synchronization performance by the existing average consensus algorithm and the method according to the present invention in a distributed network with dynamic malfunction.
FIG. 8 illustrates a configuration of a reliability-based distributed synchronization apparatus according to an embodiment of the present invention.

Hereinafter, embodiments according to the present invention will be described in detail with reference to the accompanying drawings. However, the present invention is not limited to or limited by the embodiments. In addition, the same reference numerals shown in the drawings denote the same members.

2 is a conceptual diagram of a representative distributed network.

As shown in FIG. 2A, when all the terminals belonging to the network can receive status values from all other terminals, that is, when they are fully connected, as shown in FIG. 2B, Is not able to receive status values from all other terminals, but indicates a strongly connected state when it is affected by another terminal. In other words, in the case of a strongly connected network as shown in FIG. 2B, it means that there is no terminal that can not receive a status value from an isolated terminal, that is, all other terminals belonging to the network.

FIG. 2C shows a disconnected state when an isolated terminal exists. In FIG. 2C, the terminal # 3 is an isolated terminal. In case of the terminal # 3, cooperation with peripheral terminals is impossible. Can not be obtained.

In the present invention, a network in a completely connected state and a strongly connected state, in which distributed synchronous acquisition is possible, is targeted.

이라 하고

번째 주기에서

번 단말의 상태 값을

라 하면, 네트워크에 속한 전체 노드의 상태 값들을

벡터

로 표현할 수 있다.The number of nodes belonging to the entire network

And

In the second cycle

The state value of the terminal

, The state values of all the nodes belonging to the network

vector

.

At this time, each terminal can update its state value according to a response function as shown in Equation (1) below.

[Equation 1]

는 i번 단말과 이웃한 단말의 집합(예를 들어, 도 2a의 경우

,

)을 의미하고,

는

을 만족하는 i번 단말과

번 단말 사이의 가중치를 의미할 수 있다. here,

( I. E., ≪ / RTI >< RTI ID = 0.0 &

,

),

The

I < th >

May be a weight value between terminals.

In Equation (1), various types of consensus algorithms may exist according to the weight setting method.

번 단말은 이웃 단말과 자기 자신의 가중치를 모두

로 설정한다. 즉, 자신의 상태 값과 자신과 이웃한 단말들의 상태 값들의 지역 평균(local mean)으로 자신의 상태 값을 갱신한다. 네트워크에 이러한 규칙을 지키지 않는 단말, 즉 오작동하는 단말이 존재하지 않는 경우 도 1과 같이 모든 단말의 상태 값은 네트워크에 속한 모든 단말의 초기 값의 평균값으로 수렴함으로써 네트워크는 동기를 획득하게 된다.In general, the most commonly used method is the average consensus algorithm

The terminal may calculate the weight of the neighboring terminal and its own

. That is, it updates its own state value to its own state value and the local mean of the state values of its neighboring terminals. If there is no terminal that does not obey such a rule in the network, that is, a malfunctioning terminal does not exist, as shown in FIG. 1, the status values of all terminals converge to the average values of initial values of all terminals belonging to the network.

Here, it is assumed that a malfunctioning terminal exists in the network as shown in Equation (2) or (3) below.

&Quot; (2) "

&Quot; (3) "

은 정규화된 상태 값의 최소값과 최대값인 0과 1사이에서 연속균등분포(uniform distribution)를 따르는 랜덤값을 의미할 수 있다.here,

May refer to a random value following a uniform distribution between the minimum and maximum values of the normalized state value, 0 and 1.

That is, Equation (2) implies static malfunctioning when the neighboring terminal fails to receive a status value due to a failure of the receiving apparatus or does not maliciously update its status value, 3 means dynamic malfunctioning in which an error occurs in the response function for updating the state value, thereby transmitting an erroneous value, or maliciously transmitting an erroneous state value to interfere with the acquisition of the synchronization.

FIG. 3 shows a change in state value when a static malfunctioning terminal exists in a distributed network and a mean consensus algorithm is used. FIG. 4 shows a change in state value when a dynamic malfunctioning terminal exists in a distributed network and an average consensus algorithm is used. .

As shown in FIG. 3 and FIG. 4, when there is a static malfunctioning terminal or a dynamic malfunctioning terminal exists, the terminals can not acquire the synchronization.

Embodiments of the present invention minimize the effects of malfunctions when there is a malfunction that interferes with the synchronization process between terminals in a distributed network environment without a central control type infrastructure, that is, when there is a static malfunction terminal or a dynamic malfunction terminal, And to provide a method and an apparatus capable of acquiring distributed synchronization between terminals belonging to the same.

FIG. 5 is a flowchart illustrating an operation of the reliability-based distributed synchronization method according to an exemplary embodiment of the present invention.

Referring to FIG. 5, the reliability-based distributed synchronization method according to the present invention evaluates reliability of at least one neighboring terminal using information obtainable at the time of state value update (S510).

Here, in step S510, reliability can be evaluated using Equation (4) below.

&Quot; (4) "

는

번 단말이

번 단말을 평가할 때 사용하는 신뢰도를 의미하고,

는

번 단말이

번째 단위 시간에서 수신한 이웃 단말들과 자신의 상태 값을 이용하여 측정한 지역 평균을 의미하며,

는

번 단말의

번째 단위 시간에서 상태 값의 의미할 수 있다.here,

The

Terminal

Means the reliability used when evaluating the terminal,

The

Terminal

And the average of the neighboring terminals received from the neighboring terminal and the state value of the neighboring terminal,

The

Terminal

It can mean the state value in the unit time of the ith.

번 단말이

번째 단위 시간에서 수신한 이웃 단말들과 자신의 상태 값을 이용하여 측정한 지역 평균

는 아래 <수학식 5>와 같이 계산될 수 있다.At this time,

Terminal

The average of the neighboring terminals received from the neighboring terminal and the state value

Can be calculated as Equation (5) below.

&Quot; (5) &quot;

번 단말은

번 단말의 상태 값이

번 단말의 지역 평균에 가까운 값을 가질수록 높은 신뢰도를 가진다고 평가한다.As can be seen from Equations (4) and (5) above,

Terminal

The state value of the terminal

It is evaluated that the higher the reliability of the terminal, the closer the value is to the local average of the terminal.

This is because, if the consensus-based distributed synchronization algorithm is used, the difference of the state values of all the terminals gradually decreases, while in the case of the terminal in which the static malfunction occurs, the state value does not change or in the case of the terminal in which the dynamic malfunction occurs, to be.

If the reliability of the neighboring terminal is evaluated in step S510, the weight of the predetermined response function used in updating the state value is determined based on the estimated reliability (S520).

Here, in step S520, the weight of the response function may be determined using Equation (6) below.

&Quot; (6) &quot;

는

번째 단말이

번째 단말에게 미치는 영향력의 정도를 표현하는 가중치를 의미하고,

는 0보다 큰 상수로 신뢰도 기반 가중치의 강도를 설정하는 매개변수를 의미할 수 있다. 즉,

가 큰 값을 가질수록 신뢰도가 낮은 단말의 영향을 더 많이 무시하며 신뢰도가 높은 단말에 큰 가중치를 부여한다. 반면,

가 0에 가까운 값을 가지는 경우 각 단말에 대한 가중치는 기존 평균 컨센서스 알고리즘과 동일한 가중치에 가까운 값을 가지게 된다.here,

The

Lt; th &

The second terminal is a weight representing the degree of influence of the second terminal,

May refer to a parameter that sets the strength of the confidence-based weight with a constant greater than zero. In other words,

Has a larger value, the influence of the low reliability terminal is neglected more and a high weight is given to the high reliability terminal. On the other hand,

Has a value close to 0, the weight for each terminal has a value close to the same weight as the existing average consensus algorithm.

Also, by normalizing the reliability of each terminal to the sum of the reliability of all terminals, the sum of the weights is set to be 1, thereby preventing divergence of the state value or convergence to zero.

That is, the step S520 determines the weight of the predetermined response function based on the reliability of the neighboring terminal determined by the step S510 and the intensity setting value of the predetermined weight.

As described above, according to the method of the present invention, by applying the reliability-based adaptive consensus algorithm, the weight for each neighboring terminal is adaptively changed do. Therefore, the method according to the present invention improves the synchronization performance by giving a high weight to a terminal with high reliability and a small weight to a terminal with low reliability.

If the weight of the response function is determined based on the reliability in step S520, the state value of each terminal is updated based on the response function using the determined reliability based weight (S530).

The above steps S510 to S530 are repeatedly performed. If the predetermined condition is satisfied, the process proceeds to the next step.

That is, if the state value updated in step S530 satisfies the specific condition, the distributed state is obtained using the updated state value (S540).

That is, steps S530 and S540 update the status value of the mobile station based on the response function using the weight determined based on the reliability, and acquire the synchronization using the updated status value.

As described above, the method according to the present invention minimizes the influence of the malfunction generated in the synchronization process of the distributed network and improves the synchronization performance between the terminals using the reliability-based adaptive consensus algorithm.

In addition, since the method according to the present invention requires a relatively simple operation compared to the existing distributed synchronous method, it can be implemented and utilized very easily.

6 shows the synchronization performance by the conventional average consensus algorithm and the method according to the present invention in a distributed network in which a static malfunction exists. The dotted line and the solid line shown in FIG. 6 indicate that the network is in a fully connected state, Synchronization performance results.

In FIG. 6, the synchronization performance is based on the mean square error of state values of the legitimate terminals as shown in Equation (7).

&Quot; (7) &quot;

는

번째 단위 시간에서 각 단말들의 상태 값의 평균을 의미하고,

은 각 구성 원소가 1인

벡터를 의미할 수 있다.here,

The

The average of the state values of the UEs in the first unit time,

Is composed of one constituent element

Can mean a vector.

As shown in FIG. 6, the reliability-based distributed synchronizing method according to the present invention is a method in which a plurality of statically malfunctioning terminals exist in a network, By using the reliability-based adaptive consensus algorithm, it can be seen that in the presence of static malfunctions, the synchronization performance is improved rather than using the existing average consensus algorithm.

7 shows the synchronization performance according to the conventional average consensus algorithm and the method according to the present invention in a distributed network in which a dynamic malfunction exists. The dotted line and the solid line shown in FIG. 7 indicate that the network is in a fully connected state, Synchronization performance results.

FIG. 7 also illustrates a case where ten dynamic malfunctioning terminals exist in a network. The number of valid terminals increases and a mean square error is shown. As shown in FIG. 7, the reliability- By using the reliability-based adaptive consensus algorithm, it can be seen that even when dynamic malfunction exists, higher synchronization performance is obtained than using the existing average consensus algorithm.

As described above, the method according to the present invention evaluates the reliability of each neighboring terminal using information obtainable at the time of updating the status value in the distributed network, determines the weight of the response function based on the evaluated reliability, By minimizing the influence of one state value, even when there are malfunctioning terminals in the distributed network, high synchronization performance can be obtained compared to the conventional average consensus algorithm.

FIG. 8 shows a configuration of a reliability-based distributed synchronous apparatus according to an embodiment of the present invention, and shows a configuration of an apparatus for performing the methods of FIGS. 5 to 7 described above.

Referring to FIG. 8, a distributed synchronization apparatus 800 according to an embodiment of the present invention includes an evaluation unit 810, a determination unit 820, and an acquisition unit 830.

The evaluation unit 810 evaluates the reliability of the at least one neighboring terminal using information obtainable at the time of updating the state value in the distributed network.

At this time, the evaluator 810 can evaluate the reliability of the neighboring terminal based on the regional average and the neighboring terminal's measured values using the neighboring terminals and their own state values, The higher the reliability, the better the reliability.

Specifically, the evaluation unit 810 calculates the reliability of each of the neighboring terminals, and calculates the reliability of the neighboring terminals based on the local average and the state values of the neighboring terminals, which are measured using the neighboring terminals and their own state values .

The determination unit 820 determines a weight of a predetermined response function based on the reliability of each of the neighboring terminals evaluated by the evaluation unit 810. [

At this time, the determination unit 820 can determine a weight for the response function of the predetermined consensus algorithm based on the reliability of each of the neighboring terminals evaluated by the evaluation unit 810. [

Further, the decision unit 820 normalizes the reliability of the terminal to the sum of the reliability for all the terminals, and determines the weight of the response function so that the sum of the weights is equal to 1, thereby preventing the divergence of the state value or convergence to zero can do.

If the weight of the response function is determined by the determination unit 820 based on the reliability, the acquisition unit 830 acquires the distributed motions of the respective terminals based on the response function using the determined reliability-based weight.

At this time, the obtaining unit 830 updates the state value based on the response function of the determined weight, determines the weight of the response function based on the reliability, and updates the state value when the updated state value satisfies the predetermined specific condition It is possible to obtain the distributed synchronization of each terminal.

Here, it is described that the process of updating the status value can be repeatedly performed until the specific condition is satisfied together with the reliability evaluation and the weight determination, and the process of updating the status value is performed by the obtaining unit 830. However, And may be performed in the determination unit 820. [

Although not described in FIG. 8, the apparatus according to the present invention may include all the operations and descriptions described in FIGS. 5 to 7, and conversely, the method in FIG. 5 may also include functions and descriptions for the apparatus described in FIG. .

The system or apparatus described above may be implemented as a hardware component, a software component, and / or a combination of hardware components and software components. For example, the systems, devices, and components described in the embodiments may be implemented in various forms such as, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable array ), A programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions. The processing device may execute an operating system (OS) and one or more software applications running on the operating system. The processing device may also access, store, manipulate, process, and generate data in response to execution of the software. For ease of understanding, the processing apparatus may be described as being used singly, but those skilled in the art will recognize that the processing apparatus may have a plurality of processing elements and / As shown in FIG. For example, the processing unit may comprise a plurality of processors or one processor and one controller. Other processing configurations are also possible, such as a parallel processor.

The software may include a computer program, code, instructions, or a combination of one or more of the foregoing, and may be configured to configure the processing device to operate as desired or to process it collectively or collectively Device can be commanded. The software and / or data may be in the form of any type of machine, component, physical device, virtual equipment, computer storage media, or device , Or may be permanently or temporarily embodied in a transmitted signal wave. The software may be distributed over a networked computer system and stored or executed in a distributed manner. The software and data may be stored on one or more computer readable recording media.

The method according to embodiments may be implemented in the form of a program instruction that may be executed through various computer means and recorded in a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, and the like, alone or in combination. The program instructions to be recorded on the medium may be those specially designed and configured for the embodiments or may be available to those skilled in the art of computer software. Examples of computer-readable media include magnetic media such as hard disks, floppy disks and magnetic tape; optical media such as CD-ROMs and DVDs; magnetic media such as floppy disks; Magneto-optical media, and hardware devices specifically configured to store and execute program instructions such as ROM, RAM, flash memory, and the like. Examples of program instructions include machine language code such as those produced by a compiler, as well as high-level language code that can be executed by a computer using an interpreter or the like. The hardware devices described above may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments. For example, it is to be understood that the techniques described may be performed in a different order than the described methods, and / or that components of the described systems, structures, devices, circuits, Lt; / RTI &gt; or equivalents, even if it is replaced or replaced.

Therefore, other implementations, other embodiments, and equivalents to the claims are also within the scope of the following claims.

Claims (12)

A reliability-based distributed synchronization method in a distributed network,
Evaluating reliability for at least one neighboring terminal;
Determining a weight of a predetermined response function based on the estimated reliability; And
Acquiring synchronization based on a response function having the determined weight;
Lt; / RTI &gt;
The evaluating step
And evaluating the reliability of the neighboring terminal based on the local average calculated using the state value of the neighboring terminal and the state value of the neighboring terminal, and the state value of the neighboring terminal.
delete The method according to claim 1,
The step of determining
Wherein the weight of the response function is determined on the basis of the estimated reliability based on the estimated reliability and the predetermined strength setting value for the response function.
The method according to claim 1,
The step of determining
Wherein the weights of the response functions are determined such that the sum of the weights is equal to one.
The method according to claim 1,
The obtaining step
Updates the state value based on the response function having the determined weight, and acquires synchronization based on the updated state value.
The method according to claim 1,
The response function
And a response function of a consensus algorithm.
1. A reliability-based distributed synchronization apparatus in a distributed network,
An evaluation unit for evaluating reliability of at least one neighboring terminal;
A determining unit that determines a weight of a predetermined response function based on the estimated reliability; And
And acquiring a synchronization based on a response function having the determined weight,
Lt; / RTI &gt;
The evaluating unit
The reliability-based distributed scheduler evaluates the reliability of the neighboring terminal based on the local average calculated using the state value of the terminal and the state value of the neighboring terminal.
delete 8. The method of claim 7,
The determination unit
And determines a weight of the response function based on the estimated reliability based on the estimated reliability and a predetermined strength setting value for the response function.
8. The method of claim 7,
The determination unit
And determines the weight of the response function such that the sum of the weights is equal to one.
8. The method of claim 7,
The obtaining unit
Updates the state value based on a response function having the determined weight, and acquires synchronization based on the updated state value.
8. The method of claim 7,
The response function
And a response function of a consensus algorithm.

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