CN113395218B - Hybrid trigger control method for avoiding network congestion - Google Patents

Hybrid trigger control method for avoiding network congestion Download PDF

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CN113395218B
CN113395218B CN202110639275.XA CN202110639275A CN113395218B CN 113395218 B CN113395218 B CN 113395218B CN 202110639275 A CN202110639275 A CN 202110639275A CN 113395218 B CN113395218 B CN 113395218B
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CN113395218A (en
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张素焕
张俊锋
黄海峰
林鹏
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Hangzhou Dianzi University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L47/00—Traffic control in data switching networks
    • H04L47/10—Flow control; Congestion control
    • H04L47/20—Traffic policing
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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Abstract

The invention discloses a mixed trigger control method of a communication network system. The invention has the following steps: step 1, data acquisition is carried out on communication flow of a network, and a state space model of the communication flow in a communication network system is established; step 2, constructing an event trigger control condition of network congestion; step 3, designing a hybrid trigger controller for the communication network system based on the positive Markov jump system modeling, and controlling the communication flow on the network line in real time; step 4, aiming at the established model and the designed controller, carrying out positive verification on the system; and 5, analyzing the random stability of the communication network system under the hybrid trigger control, and ensuring the stable operation of the system. The method of the invention can effectively solve the network congestion caused by the network resource limitation during the flow peak and ensure the high-quality data transmission in the network.

Description

Hybrid trigger control method for avoiding network congestion
Technical Field
The invention relates to the technical field of automation, in particular to a hybrid trigger control method based on a positive Markov jump system, which can be applied to the traffic management of network congestion.
Background
With the progress and development of communication technology in the information age, networks have become the core in communication systems and the foundation for realizing various social developments. The communication network needs to realize efficient data transmission and ensure the integrity and correctness of information transmission, and is inevitably developed and optimized with time so as to meet the requirements of users in various communication scenes. Due to the characteristics that network resources are undevelopable and limited, the transmission of large data volume of multiple users easily causes network congestion and even network system breakdown. Therefore, the method has very important significance in avoiding network congestion, saving bandwidth and realizing rapid and stable development of the network. The invention mainly dynamically obtains the flow value of the network line, controls the network rate according to the actual load condition of the flow, and provides a reliable network flow control method to avoid network congestion and achieve the purpose of improving the transmission efficiency.
The flow control means to control the data traffic on a channel, and since the traffic on the channel is always non-negative, the traffic can be described by a positive variable. The network congestion is caused by overhigh instantaneous peak flow at a certain position on a network line, so that the network congestion has randomness, and at the moment, the problems can be accurately described by means of a Markov jump system. In most cases, in order to ensure the performance of the network system, a time trigger strategy is often adopted to control the network system, but the strategy has the defect of wasting system resources, event trigger control can well solve the defect by designing trigger conditions, but in order to enable the network to bear the pressure of the rapid increase of the number of users, a hybrid trigger control strategy formed by combining two control methods can adopt a proper control mode according to the data transmission flow of the network system, so that the problem of bandwidth limitation is effectively solved, and network congestion is avoided. Therefore, the application aims to adopt a positive Markov jump system to model a communication network control system and design a mixed trigger control method to monitor the flow data of the network in real time and ensure the high-efficiency data transmission of the network.
Disclosure of Invention
In order to solve the limitation of the existing network bandwidth and meet the network communication requirement of the user which is increased sharply, the invention adopts the following technical scheme:
a mixed trigger control method for avoiding network congestion comprises the following steps:
step 1, establishing a state space model of a communication network control system;
step 2, constructing an event trigger control condition of communication network congestion;
step 3, designing a hybrid trigger controller of the communication network control system;
step 4, aiming at the established model and the designed controller, carrying out positive verification on the system;
and 5, analyzing the random stability of the communication network system under the control of mixed triggering.
The method comprises the following specific steps:
step 1, establishing a state space model by combining a network communication system.
Step 1.1, firstly, carrying out data acquisition on communication flow of a network, and establishing a state space model of the communication flow in a communication network control system by using the data, wherein the form is as follows:
x(k+1)＝Ar(k)x(k)+Br(k)u(k), (1)
wherein the content of the first and second substances,
Figure BDA0003106499750000021
representing the amount of data transferred at the kth sampling instant, n representing the number of channels,
Figure BDA0003106499750000022
for transmission rate control signals, m denotes bandwidth, r (k) is a markov jump process, and in a limited set S ═ 1,2, …, N,
Figure BDA0003106499750000023
the medium value is selected from the group consisting of,
Figure BDA0003106499750000024
and
Figure BDA0003106499750000025
is a known system matrix which, to simplify the above notation,
Figure BDA0003106499750000026
the system matrix may be represented as AiAnd BiAnd is and
Figure BDA00031064997500000217
step 1.2, designing a Markov jump signal r (k), wherein the communication network control system has the following mode transfer rate:
P(r(k+1)＝j|r(k)＝i)＝πij, (2)
where for each i, j ∈ S there is aijIs not less than 0, and
Figure BDA0003106499750000027
step 2, constructing an event triggering control condition of communication network congestion:
‖e(k)‖1＞β‖x(k)‖1, (3)
wherein the constant beta satisfies 0 < beta < 1, e (k) is a deviation signal, and satisfies
Figure BDA0003106499750000028
Figure BDA0003106499750000029
Represents an event-triggered state quantity |1Represents the 1 norm of the vector, i.e., the sum of the absolute values of all the elements in the vector.
Step 3, designing a mixed trigger controller of the communication network control system, wherein the construction form is as follows:
step 3.1, establishing a multilocular uncertain model, wherein a system matrix is presented in a convex hull form, and the specific form is as follows:
Figure BDA00031064997500000210
wherein co {. denotes a convex hull of a set,
Figure BDA00031064997500000211
s is 1,2, …, q, and
Figure BDA00031064997500000212
Figure BDA00031064997500000213
step 3.2, designing a state feedback law of the hybrid trigger control as follows:
Figure BDA00031064997500000214
wherein alpha isi(k) Is a Bernoulli random variable, αi(k)∈[0,1]And satisfy
Figure BDA00031064997500000215
And is
Figure BDA00031064997500000216
It represents the switching law from one triggering scheme to another, when αi(k) When 1, a time-triggered control scheme, α, is activatedi(k) When 0, the event-triggered control scheme is selected.
Figure BDA0003106499750000031
Is a controller gain matrix, and
Figure BDA0003106499750000032
the concrete form is as follows:
Figure BDA0003106499750000033
wherein 1 ismAn m-dimensional vector representing all elements as 1,
Figure BDA0003106499750000034
an m-dimensional vector representing that the iota-th element is 1, the rest being 0,
Figure BDA0003106499750000035
is an n-dimensional vector and T is a transposed symbol.
Step 3.3, the communication network control system designs the condition of stable data transmission under the mixed trigger control, as follows:
design constant μ > 0, if there is an n-dimensional vector
Figure BDA0003106499750000036
Such that the following inequality holds:
Figure BDA0003106499750000037
wherein Φ is ═ I- β 1n×n,Ψ＝I+β1×n，
Figure BDA0003106499750000038
Figure BDA0003106499750000039
Then is closedHybrid trigger control law of ring system
Figure BDA00031064997500000310
The following are positive and randomly stable.
Step 4, according to step 1, step 2 and step 3.2, the following steps are carried out:
Figure BDA00031064997500000311
due to alphai(k)∈[0,1]In conjunction with step 2, under non-event triggered control:
Figure BDA00031064997500000313
according to step 3.1, it can be further concluded that:
Figure BDA00031064997500000312
from the conditions in step 3.3 it is possible to obtain:
Figure BDA0003106499750000041
thus, the closed loop system is positive under the state feedback law of the hybrid triggering control designed in step 3.2.
And 5, analyzing the random stability of the closed-loop system under the mixed trigger control on the basis of the previous step.
Step 5.1, constructing a random residual Lyapunov function for the closed-loop system, wherein the specific form is as follows:
V(x(k),r(k)＝i)＝xT(k)v(i), (12)
the mathematical expectation of its difference is:
Figure BDA0003106499750000042
step 5.2, according to step 3.1 and step 3.2, has:
Figure BDA0003106499750000043
step 5.3, the following inequality can be obtained from the conditions in step 3.3:
Figure BDA0003106499750000044
step 5.4, combining step 5.2 and step 5.3, the mathematical expectation of the Lyapunov function difference satisfies:
Figure BDA0003106499750000045
further combining with step 3.3, a
Figure BDA0003106499750000051
Summing both sides of the above inequality from 0 to ∞ simultaneously to obtain:
Figure BDA0003106499750000052
thus, under non-negative initial conditions, the above equation can be converted to:
Figure BDA0003106499750000053
therefore, under the feedback law of the mixed trigger control state designed in the step 3.2, the closed-loop system is randomly stable.
The invention has the advantages and beneficial effects that:
aiming at the conflict problems of bandwidth limitation and high-quality network communication in the current communication network system, a state space model of the network control system established by using the modern control theory technology is provided, the positivity and the stability of the state space model are analyzed, and a hybrid trigger controller is designed to ensure that the data communication rate is maximized on the basis of no network congestion, so that the network system resources are fully utilized.
Drawings
Fig. 1 is a schematic structural diagram of a communication network control system in the present invention.
Fig. 2 is a diagram of a hybrid trigger control architecture of a network control system modeled based on a positive markov jump system in accordance with the present invention.
Detailed Description
The present invention is further illustrated by the following examples, which are not intended to limit the invention to these embodiments. It will be appreciated by those skilled in the art that the present invention encompasses all alternatives, modifications and equivalents as may be included within the scope of the claims.
As shown in fig. 1 and 2, the present embodiment provides a method for controlling a hybrid trigger of a communication network system based on a positive markov jump system modeling, which includes the following specific steps:
step 1, establishing a state space model by combining a network communication system.
Step 1.1, firstly, carrying out data acquisition on communication flow of a network, and establishing a state space model of the communication flow in a communication network control system by using the data, wherein the form is as follows:
x(k+1)＝Ar(k)x(k)+Br(k)u(k), (1)
wherein the content of the first and second substances,
Figure BDA0003106499750000054
representing the amount of data transferred at the kth sampling instant, n representing the number of channels,
Figure BDA0003106499750000055
for control signals of transmission rate, m denotes the bandwidth, r (k) is a Markov jumpThe process is varied, in a limited set S ═ {1,2, …, N },
Figure BDA0003106499750000056
the medium value is selected from the group consisting of,
Figure BDA0003106499750000057
and
Figure BDA0003106499750000058
is a known system matrix which, to simplify the above notation,
Figure BDA0003106499750000059
the system matrix may be represented as AiAnd BiAnd is and
Figure BDA00031064997500000617
step 1.2, designing a Markov jump signal r (k), wherein the communication network control system has the following mode transfer rate:
P(r(k+1)＝j|r(k)＝i)＝πij, (2)
where for each i, j ∈ S there is aijIs not less than 0, and
Figure BDA0003106499750000061
step 2, constructing an event triggering control condition of communication network congestion:
‖e(k)‖1＞β‖x(k)‖1, (3)
wherein the constant beta satisfies 0 < beta < 1, e (k) is a deviation signal, and satisfies
Figure BDA0003106499750000062
Figure BDA0003106499750000063
Represents an event-triggered state quantity |1Represents the 1 norm of the vector, i.e., the sum of the absolute values of all the elements in the vector.
Step 3, designing a mixed trigger controller of the communication network control system, wherein the construction form is as follows:
step 3.1, establishing a multilocular uncertain model, wherein a system matrix is presented in a convex hull form, and the specific form is as follows:
Figure BDA0003106499750000064
wherein co {. denotes a convex hull of a set,
Figure BDA0003106499750000065
s is 1,2, …, q, and
Figure BDA0003106499750000066
Figure BDA0003106499750000067
step 3.2, designing a state feedback law of the hybrid trigger control as follows:
Figure BDA0003106499750000068
wherein alpha isi(k) Is a Bernoulli random variable, αi(k)∈[0,1]And satisfy
Figure BDA0003106499750000069
And is
Figure BDA00031064997500000610
It represents the switching law from one triggering scheme to another, when αi(k) When 1, a time-triggered control scheme, α, is activatedi(k) When 0, the event-triggered control scheme is selected.
Figure BDA00031064997500000611
Is a controller gain matrix, and
Figure BDA00031064997500000612
the concrete form is as follows:
Figure BDA00031064997500000613
wherein 1 ismAn m-dimensional vector representing all elements as 1,
Figure BDA00031064997500000614
an m-dimensional vector representing that the iota-th element is 1, the rest being 0,
Figure BDA00031064997500000615
is an n-dimensional vector and T is a transposed symbol.
Step 3.3, the communication network control system designs the condition of stable data transmission under the mixed trigger control, as follows:
design constant μ > 0, if there is an n-dimensional vector
Figure BDA00031064997500000616
Such that the following inequality holds:
Figure BDA0003106499750000071
wherein Φ is ═ I- β 1n×n,Ψ＝I+β1n，
Figure BDA0003106499750000072
Figure BDA0003106499750000073
The closed loop system is in the mixed trigger control law
Figure BDA0003106499750000074
The following are positive and randomly stable.
Step 4, according to step 1, step 2 and step 3.2, the following steps are carried out:
Figure BDA0003106499750000075
due to alphai(k)∈[0,1]In conjunction with step 2, under non-event triggered control:
Figure BDA0003106499750000079
according to step 3.1, it can be further concluded that:
Figure BDA0003106499750000076
from the conditions in step 3.3 it is possible to obtain:
Figure BDA0003106499750000077
thus, under the state feedback law of the hybrid triggering control designed in step 3.2, the closed-loop system is positive.
And 5, analyzing the random stability of the closed-loop system under the mixed trigger control on the basis of the previous step.
Step 5.1, constructing a random residual Lyapunov function for the closed-loop system, wherein the specific form is as follows:
V(x(k),r(k)＝i)＝xT(k)v(i), (12)
the mathematical expectation of its difference is:
Figure BDA0003106499750000078
step 5.2, according to step 3.1 and step 3.2, has:
Figure BDA0003106499750000081
step 5.3, the following inequality can be obtained from the conditions in step 3.3:
Figure BDA0003106499750000082
step 5.4, combining step 5.2 and step 5.3, the mathematical expectation of the Lyapunov function difference satisfies:
Figure BDA0003106499750000083
further combining with step 3.3, a
Figure BDA0003106499750000084
Summing both sides of the above inequality from 0 to ∞ simultaneously to obtain:
Figure BDA0003106499750000085
thus, under non-negative initial conditions, the above equation can be converted to:
Figure BDA0003106499750000086
therefore, under the feedback law of the mixed trigger control state designed in the step 3.2, the closed-loop system is randomly stable.

Claims (3)

1. A hybrid trigger control method for avoiding network congestion is characterized by comprising the following steps:
step 1, establishing a state space model of a communication network control system;
step 2, constructing an event trigger control condition of communication network congestion;
step 3, designing a hybrid trigger controller of the communication network control system;
step 4, aiming at the established model and the designed controller, carrying out positive verification on the system;
step 5, analyzing the random stability of the communication network system under the mixed trigger control;
the step 1 is as follows:
step 1.1, firstly, data acquisition is carried out on communication flow of a network, and a state space model of the communication flow in a communication network control system is established by using the data, wherein the form is as follows:
x(k+1)＝Ar(k)x(k)+Br(k)u(k), (1)
wherein the content of the first and second substances,
Figure FDA0003560497500000011
representing the amount of data transferred at the kth sampling instant, n representing the number of channels,
Figure FDA0003560497500000012
for transmission rate control signals, m denotes bandwidth, r (k) is a markov jump process, and in a limited set S ═ 1,2, …, N,
Figure FDA0003560497500000013
the medium value is selected from the group consisting of,
Figure FDA0003560497500000014
and
Figure FDA0003560497500000015
is a known system matrix which, to simplify the above notation,
Figure FDA0003560497500000016
the system matrix may be represented as AiAnd BiAnd is and
Figure FDA0003560497500000017
step 1.2, a Markov jump signal r (k) is designed, and a communication network control system has the following mode transfer rates:
P(r(k+1)＝j|r(k)＝i)＝πij, (2)
where for each i, j ∈ S there is aijIs not less than 0, and
Figure FDA0003560497500000018
the event trigger control condition in the step 2 is constructed in the following form:
‖e(k)‖1＞β‖x(k)‖1, (3)
wherein the constant beta satisfies 0 < beta < 1, e (k) is a deviation signal, and satisfies
Figure FDA0003560497500000019
Figure FDA00035604975000000110
Represents an event-triggered state quantity |1Represents the 1 norm of the vector, i.e., the sum of the absolute values of all elements in the vector;
the design of the mixed trigger controller of the communication network control system in the step 3 comprises the following steps:
step 3.1, establishing a multilocular uncertain model, wherein a system matrix is presented in a convex hull form, and the specific form is as follows:
Figure FDA00035604975000000111
wherein co {. denotes a convex hull of a set,
Figure FDA00035604975000000112
s is 1,2, …, q, and
Figure FDA00035604975000000113
Figure FDA00035604975000000114
step 3.2, designing a feedback law of the mixed trigger control state as follows:
Figure FDA0003560497500000021
wherein alpha isi(k) Is a Bernoulli random variable, αi(k)∈[0,1]And satisfy
Figure FDA0003560497500000022
And is
Figure FDA0003560497500000023
It represents the switching law from one triggering scheme to another, when αi(k) When 1, a time-triggered control scheme, α, is activatedi(k) When the value is 0, selecting an event triggering control scheme; the communication network can be well controlled by selecting the feedback control law of the mixed trigger state, so that network congestion is avoided;
Figure FDA0003560497500000024
is a controller gain matrix, and
Figure FDA0003560497500000025
the concrete form is as follows:
Figure FDA0003560497500000026
wherein 1 ismAn m-dimensional vector representing all elements as 1,
Figure FDA0003560497500000027
an m-dimensional vector representing that the iota-th element is 1, the rest being 0,
Figure FDA0003560497500000028
is an n-dimensional vector, T is a transposed symbol;
step 3.3, the communication network control system designs the condition of stable data transmission under the mixed trigger control, as follows:
design constant μ > 0, if there is an n-dimensional vector
Figure FDA0003560497500000029
Such that the following inequality holds:
Figure FDA00035604975000000210
wherein Φ is ═ I- β 1n×n,
Figure FDA00035604975000000211
Figure FDA00035604975000000212
The closed loop system is in the mixed trigger control law
Figure FDA00035604975000000213
The following are positive and randomly stable.
2. The hybrid trigger control method for avoiding network congestion according to claim 1, wherein: the positive validation process in step 4 is as follows:
according to step 1, step 2 and step 3.2:
Figure FDA00035604975000000214
due to alphai(k)∈[0,1]In conjunction with step 2, under non-event triggered control:
Figure FDA0003560497500000031
according to step 3.1, it can be further concluded that:
Figure FDA0003560497500000032
from the conditions in step 3.3 it is possible to obtain:
Figure FDA0003560497500000033
thus, under the feedback law of the hybrid trigger control state designed in step 3.2, the closed-loop system is positive.
3. The hybrid trigger control method for avoiding network congestion according to claim 2, wherein the step 5 of ensuring the random stability of the closed-loop system under the hybrid trigger control comprises the following steps:
step 5.1, constructing a random residual Lyapunov function for the closed-loop system, wherein the specific form is as follows:
V(x(k),r(k)＝i)＝xT(k)v(i), (12)
the mathematical expectation of its difference is:
Figure FDA0003560497500000034
step 5.2, according to step 3.1 and step 3.2, has:
Figure FDA0003560497500000035
step 5.3, the following inequality can be obtained from the conditions in step 3.3:
Figure FDA0003560497500000041
step 5.4, combining step 5.2 and step 5.3, the mathematical expectation of the Lyapunov function difference satisfies:
Figure FDA0003560497500000042
further combining with step 3.3, a
Figure FDA0003560497500000043
Summing both sides of the above inequality from 0 to ∞ simultaneously to obtain:
Figure FDA0003560497500000044
thus, under non-negative initial conditions, the above equation can be converted to:
Figure FDA0003560497500000045
therefore, under the feedback law of the mixed trigger control state designed in the step 3.2, the closed-loop system is randomly stable.
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