CN113596855B - Distributed method and system for establishing dual random communication matrix in unidirectional strong communication network - Google Patents

Abstract

The invention discloses a distributed method and a system for establishing a double random communication matrix in a unidirectional strong communication network, wherein the method comprises the steps of calculating a communication topological structure of the communication network according to a strong communication diagram of the unidirectional strong communication network; calculating all loops in the communication network according to the communication topological structure of the communication network; and calculating the maximum loop including all nodes in all loops in the communication network, summing and unitizing to obtain the double random communication matrix of the unidirectional strong communication network. The invention only needs to give out the communication network with a strong communication with a maximum ring, and can establish the double random communication matrix for the communication network without other conditions, which has better applicability and wider application range compared with other methods for double randomizing the communication network.

Description

Distributed method and system for establishing dual random communication matrix in unidirectional strong communication network

Technical Field

The invention relates to the technical field of multi-intelligent system, in particular to a distributed method and a system for establishing a double random communication matrix in a unidirectional strong communication network.

Background

Related applications of multi-agent systems generally rely on an average consistency algorithm to coordinate the behavior of multiple nodes, with the precondition that a dual random communication matrix has been established in the system. However, in the initial stage of deployment of the multi-intelligent system, the dual random communication matrix does not exist naturally, and proper weights are set for the received data and the transmitted data respectively through a proper node negotiation mechanism, so that the dual random communication matrix is finally obtained. That is, at the beginning of deployment of the multi-agent system, a good negotiation mechanism is not established in the multi-agent system, and it is difficult to set appropriate weights for the received data and the transmitted data respectively, so that it is difficult to obtain a dual random communication matrix, and therefore, the method of dual randomizing the communication network by setting weights for the received data and the transmitted data has poor applicability in practical applications.

Disclosure of Invention

The invention aims at least solving the technical problems in the prior art, and particularly creatively provides a distributed method and a system for establishing a double-random communication matrix in a unidirectional strong communication network, which effectively solve the problem that the method for realizing double randomization of the communication network by setting weights for received data and transmitted data in the prior art has poor applicability in practical application.

To achieve the above object of the present invention, according to a first aspect of the present invention, there is provided a distributed method of establishing a dual random communication matrix in a unidirectional strong communication network, the method comprising the steps of:

s1, calculating a communication topological structure of a communication network according to a strong connectivity diagram of a unidirectional strong connectivity communication network;

s2, calculating all loops in the communication network according to the communication topological structure of the communication network;

and S3, calculating the maximum loop including all nodes in all loops in the communication network, summing and unitizing to obtain the double random communication matrix of the unidirectional strong communication network.

Preferably, each node in the communication network is assumed to have a unique identifier, denoted { p, q }; the identifiers of the nodes are provided with order relations which can be compared in size; the directed edges from node p to node q are denoted by (p, q), and the nodes p are each provided with a transmission variable S _p Receiving variable R _p Local variable L _p And temporary storage variable P _p ；

The step S1 comprises the following steps:

s11, respectively transmitting variable S of node p _p Receiving variable R _p Local variable L _p And temporary storage variable P _p Initialized to S _p [0]、R _p [0]、P _p [0]、L _p [0]The initialization formula is as follows:

wherein ,representing an empty set, and ζ represents a valuation operation;

s12, marking the data received by the node p in the kth step as R _p [k]There is

Wherein if the communication topology has directed edges (p, q), T _p,q Is the complete set, otherwise T _p,q Is an empty set; n (N) _q Representing the incoming neighbor set of the node q, wherein, U represents intersection operation, U represents union operation;

s13, the data R received by the node p in the kth step _p [k]Record to temporary variable P after processing _p Obtain P _p [k]The processing formula is as follows:

wherein (beta, alpha) represents the set R _p [k]Any element in (a);

s14, according to the received data R _p [k]Updating the local variable of node p to L _p [k]The update formula is as follows:

L _p [k]←L _p [k-1]∪P _p [k]

s15, the data sent by the node p in the kth step is recorded as S _p [k]Then

S _p [k]←P _p [k]；

S16, if k is smaller than r, jumping to the step S12, otherwise executing the step S2, wherein r is the radius of the strong communication diagram.

Preferably, step S2 includes:

s21, according to local variable L _p [r]A set of identifiers I of the communication topology is established, wherein,

I←{α|(β,α)∈L _p (r)}

setting matrix d= (0) _n×n N is n×n-dimensional zero matrix, n is the number of elements in the identifier set I;

s22, based on a sorting algorithm, sorting the identifier set I into a list C, wherein the length of the list C is n, so that a mapping relation f is established, namely C & fwdarw {1, & gt, n }, and the mapping relation is

f(C _i )＝i

wherein ,C_i Is the i-th element in list C;

s23, opposite node C _i E I, find Loop O (C _i ) The loop starting point is node C _i The method comprises the steps of carrying out a first treatment on the surface of the The operation of the table head of the record list is H, C and I, if there is

H([α,C′])＝α

Wherein C' is any list, giving O (C _i ) Give an initial value [ C ]']Then there is the following equality relationship:

s24, if there is a unique (C _j ,H(O(C _i )))∈L _i (r), i.e. node H (O (C) _i ) With only one directed edge away from the node)

[O(C _i )]←[C _j ,O(C _i )]

If present (C) _j ,H(O(C _i )))∈L _i(r) and (C_j′ ,H(O(C _i )))∈L _i (r), and C _j ≠C _j′ I.e. node H (O (C _i ) At least two directed edges away from the node, the loops are recorded separately as follows:

O(C _i ,C _j )←[C _j ,O(C _i )],O(C _i ,C _j ′′)←[C _j′ ,O(C _i )]

s25, if C _j ＝C _i And if there is C _j′ C is then _j′ ＝C _i Starting at C _i The end point is also C _i Then find node C _i All loops O (C) _i ,..); otherwise, the process goes to step S24.

Preferably, step S3 includes:

s31, establishing a adjacency matrix B of the loop, including

Wherein for any i, j e {1,., n }, if any (C _j ,C _i )∈O(C _i ,..), let B _i,j =1, otherwise let B _i,j ＝0；

S32, if the matrix B is full rank, namely rank (B) =n, then

D←D+B；

S33, if C _i ≠C _n Then

C _i ←C _i+1

Jumping to step S23, otherwise executing step S34;

s34, obtaining a double random communication matrix D through summation and unitization calculation, wherein the calculation formula is as follows:

or ,

preferably, before step S1, the method further comprises:

and constructing a strong communication diagram of the unidirectional strong communication network to be processed, and acquiring address information of each node in the strong communication diagram.

According to a second aspect of the present invention there is also provided a distributed system for establishing a dual random communication matrix in a unidirectional strong communication network, the system comprising:

the topology structure calculation module is used for calculating the communication topology structure of the communication network according to the strong connectivity diagram of the unidirectional strong connectivity communication network;

the loop calculation module is used for calculating all loops in the communication network according to the communication topological structure of the communication network;

and the double random communication matrix generation module is used for calculating the maximum loop including all nodes in all loops in the communication network, summing and unitizing to obtain the double random communication matrix of the unidirectional strong communication network.

Preferably, each node in the communication network is assumed to have a unique identifier, denoted { p, q }; the identifiers of the nodes are provided with order relations which can be compared in size; the directed edges from node p to node q are denoted by (p, q), and the nodes p are each provided with a transmission variable S _p Receiving variable R _p Local variable L _p And temporary storage variable P _p ；

The calculating the communication topology structure of the communication network according to the strong connectivity diagram of the unidirectional strong connectivity communication network comprises the following steps:

s11, respectively transmitting variable S of node p _p Receiving variable R _p Local variable L _p And temporary storage variable P _p Initialized to S _p [0]、R _p [0]、P _p [0]、L _p [0]The initialization formula is as follows:

wherein ,representing an empty set, and ζ represents a valuation operation;

s12, marking the data received by the node p in the kth step as R _p [k]There is

Wherein if the communication topology has directed edges (p, q), T _p,q Is the complete set, otherwise T _p,q Is an empty set; n (N) _q Representing the incoming neighbor set of the node q, wherein, U represents intersection operation, U represents union operation;

s13, the data R received by the node p in the kth step _p [k]Record to temporary variable P after processing _p Obtain P _p [k]The processing formula is as follows:

wherein (beta, alpha) represents the set R _p [k]Any element in (a);

s14, according to the received data R _p [k]Updating the local variable of node p to L _p [k]The update formula is as follows:

L _p [k]←L _p [k-1]∪P _p [k]

s15, the data sent by the node p in the kth step is recorded as S _p [k]Then

S _p [k]←P _p [k]；

S16, if k is smaller than r, jumping to the step S12, otherwise, calculating all loops in the communication network according to the communication topological structure of the communication network, wherein r is the radius of the strong communication graph.

Preferably, said calculating all loops in the communication network according to the communication topology of the communication network comprises:

s21, according to local variable L _p [r]A set of identifiers I of the communication topology is established, wherein,

I←{α|(β,α)∈L _p (r)}

setting matrix d= (0) _n×n N is n×n-dimensional zero matrix, n is the number of elements in the identifier set I;

s22, based on a sorting algorithm, sorting the identifier set I into a list C, wherein the length of the list C is n, so that a mapping relation f is established, namely C & fwdarw {1, & gt, n }, and the mapping relation is

f(C _i )＝i

wherein ,C_i Is the i-th element in list C;

s23, opposite node C _i E I, find Loop O (C _i ) The loop starting point is node C _i The method comprises the steps of carrying out a first treatment on the surface of the The operation of the table head of the record list is H, C and I, if there is

H([α,C′])＝α

Wherein C' is any list, giving O (C _i ) Give an initial value [ C ]']The following are equalRelationship:

s24, if there is a unique (C _j ,H(O(C _i )))∈L _i (r), i.e. node H (O (C) _i ) With only one directed edge away from the node)

[O(C _i )]←[C _j ,O(C _i )]

If present (C) _j ,H(O(C _i )))∈L _i(r) and (C_j′ ,H(O(C _i )))∈L _i (r), and C _j ≠C _j′ I.e. node H (O (C _i ) At least two directed edges away from the node, the loops are recorded separately as follows:

O(C _i ,C _j )←[C _j ,O(C _i )],O(C _i ,C _j′ ）←[C _j′ ,O(C _i )]

s25, if C _j ＝C _i And if there is C _j′ C is then _j ′＝C _i Starting at C _i The end point is also C _i Then find node C _i All loops O (C) _i ,..); otherwise, the process goes to step S24.

Preferably, said calculating the maximum loop including all nodes in all loops in said communication network and summing and unitizing, obtaining a dual random communication matrix of said unidirectional strong communication network comprises:

s31, establishing a adjacency matrix B of the loop, including

Wherein for any i, j e {1,., n }, if any (C _j ,C _i )∈O(C _i ,..), let B _i,j =1, otherwise let B _i,j ＝0；

S32, if the matrix B is full rank, namely rank (B) =n, then

D←D+B；

S33, if C _i ≠C _n Then

C _i ←C _i+1

Jumping to step S23, otherwise executing step S34;

s34, obtaining a double random communication matrix D through summation and unitization calculation, wherein the calculation formula is as follows:

or ,

preferably, the distributed system for establishing a dual random communication matrix in a unidirectional strong connectivity communication network further comprises:

the strong communication diagram construction module is used for constructing a strong communication diagram of the unidirectional strong communication network to be processed before calculating the communication topological structure of the communication network according to the strong communication diagram of the unidirectional strong communication network, and acquiring the address information of each node in the strong communication diagram

As can be seen from the above scheme, the present invention provides a distributed method and system for establishing a dual random communication matrix in a unidirectional strong communication network, where the method includes calculating a communication topology structure of the communication network according to a strong communication graph of the unidirectional strong communication network; calculating all loops in the communication network according to the communication topological structure of the communication network; and calculating the maximum loop including all nodes in all loops in the communication network, summing and unitizing to obtain the double random communication matrix of the unidirectional strong communication network. The invention only needs to give out the communication network with a strong communication with a maximum ring, and can establish the double random communication matrix for the communication network without other conditions, which has better applicability and wider application range compared with other methods for double randomizing the communication network. The method effectively solves the problem that the method for realizing double randomization of the communication network by setting weights on the received data and the transmitted data in the prior art has poor applicability in practical application. Because the unidirectional strong communication balanced communication network and the bidirectional communication network (also called undirected communication/undirected graph) are special unidirectional strong communication networks, the method and the system of the invention are also applicable to establishing the double random communication matrix in the unidirectional strong communication balanced communication network and the bidirectional communication network. The invention can be applied to the primary stage of multi-agent system deployment.

Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.

Drawings

The foregoing and/or additional aspects and advantages of the invention will become apparent and may be better understood from the following description of embodiments taken in conjunction with the accompanying drawings in which:

FIG. 1 is a flow chart of a distributed method of establishing a dual random communication matrix in a unidirectional strong communication network in accordance with a preferred embodiment of the present invention;

FIG. 2 is a flow chart of a distributed method of establishing a dual random communication matrix in a unidirectional strong communication network in accordance with an embodiment of the present invention;

fig. 3 is a schematic diagram of a distributed system for establishing a dual random communication matrix in a unidirectional strong communication network in accordance with a preferred embodiment of the present invention.

Detailed Description

Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

It will be understood by those skilled in the art that all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs unless defined otherwise. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

Term interpretation:

multi-agent system: the group system with certain overall functions is formed by mutual information communication and interaction among a plurality of autonomous individuals.

Unidirectional strong connectivity communication network: the topology graph in the network representing the communication relationship between the nodes is a unidirectional and strongly connected communication network.

Unidirectional strong connectivity balanced communication network: the topology graph representing the communication relationship between nodes in the network is a unidirectional, strongly connected and balanced communication network. Wherein balancing means that the outbound and inbound degrees of each node are equal.

Two-way connectivity communication network: the topology graph in the network representing the communication relationship between the nodes is a two-way and connected communication network (also called an undirected connected communication network).

Dual random communication matrix: the adjacency matrix corresponding to the communication topological graph is a double random matrix, namely, each element in the matrix is a real number not smaller than zero, and the summation of each row and each column is 1.

Strong connectivity diagram: in the directed graph, if there is one path from v1 to v2 and from v2 to v1 for each pair of vertices v1 and v2, then the graph is referred to as a strong communication graph.

Communication topology: the communication topology refers to a topology diagram representing communication relations between nodes in a communication network.

And (3) a loop: and the paths are connected end to end in the topological graph.

Maximum loop: the loops of the topological graph comprise loops with the most nodes.

As shown in fig. 1, which is a flowchart of a distributed method for establishing a dual random communication matrix in a unidirectional strong communication network according to a preferred embodiment of the present invention, the method may include the steps of:

s101, calculating a communication topological structure of a communication network according to a strong connectivity diagram of a unidirectional strong connectivity communication network;

in the initial stages of multi-intelligent system deployment, the dual random communication matrix is not naturally occurring, and thus it is necessary to establish the dual random communication matrix in a unidirectional strong communication network. Firstly, a communication topological structure of a communication network needs to be found according to a pre-constructed strong connectivity diagram of a to-be-processed unidirectional strong connectivity communication network, which is the basis for finding a loop in the communication network. In particular, each node uses a distributed method to search the communication topology structure of the communication network in an iterative mode.

S102, calculating all loops in a communication network according to a communication topological structure of the communication network;

after the communication topology structure of the communication network is found, all loops in the communication network need to be found according to the obtained communication topology structure. In particular, all loops in the communication network can be found in an iterative manner.

And S103, calculating the maximum loop including all nodes in all loops in the communication network, summing and unitizing to obtain the double random communication matrix of the unidirectional strong communication network.

Finally, according to all loops in the communication network, the largest loop including all nodes is found out in all loops, and the double random communication matrix of the unidirectional strong communication network is obtained by calculating the largest loop through a summation and unitization method.

As can be seen from the foregoing, the present embodiment provides a distributed method for establishing a dual random communication matrix in a unidirectional strong communication network, and first, a communication topology structure of the communication network is calculated according to a strong communication graph of the unidirectional strong communication network; then, all loops in the communication network are calculated according to the communication topological structure of the communication network; and finally, calculating the maximum loop including all nodes in all loops in the communication network, summing and unitizing to obtain the double random communication matrix of the unidirectional strong communication network. The invention only needs to give out the communication network with a strong communication with a maximum ring, and can establish the double random communication matrix for the communication network without other conditions, which has better applicability and wider application range compared with other methods for double randomizing the communication network.

In other embodiments of the present invention, the method may further include the following steps, based on the above embodiments:

before step S101, a strong connectivity graph of a unidirectional strong connectivity communication network to be processed is constructed, and address information of each node in the strong connectivity graph is obtained.

The following describes in detail, by way of specific examples, the distributed method of establishing a dual random communication matrix in a unidirectional strong communication network according to the present invention:

as shown in fig. 2, a flow chart of a distributed method for establishing a dual random communication matrix in a unidirectional strong communication network in accordance with an embodiment of the present invention is shown. Assuming that each node in the communication network has a unique identifier, the unique identifier is { p, q }, and the identifier of the node can be a parameter capable of representing the identity uniqueness of the node, such as a MAC address or an IP address; the identifiers of the nodes have strict sequence relation, namely the identifiers of the nodes can be compared in size; the directed edges from node p to node q are denoted by (p, q), and the nodes p are each provided with a transmission variable S _p (Send), receive variable R _p (Receive), local variable L _p (Local) and scratch variables P _p (Provisional). The specific steps for establishing the double random communication matrix are as follows:

step 1, respectively transmitting variable S of node p _p Receiving variable R _p Local variable L _p And temporary storage variable P _p Initialized to S _p [0]、R _p [0]、P _p [0]、L _p [0]The initialization formula is as follows:

wherein ,representing an empty set, and ζ represents a valuation operation;

step 2, the data received by the node p in the kth step is recorded as R _p [k]There is

R _p [k]←∪ _q∈Nq (T _p,q ∩S _q [k])

Wherein if the communication topology has directed edges (p, q), T _p,q Is the complete set, otherwise T _p,q Is an empty set; n (N) _q Representing the incoming neighbor set of the node q, wherein, U represents intersection operation, U represents union operation;

step 3, the data R received by the node p in the kth step is obtained _p [k]Record to temporary variable P after processing _p Obtain P _p [k]The processing formula is as follows:

wherein (beta, alpha) represents the set R _p [k]Any element in (a);

step 4, according to the received data R _p [k]Updating the local variable of node p to L _p [k]The update formula is as follows:

L _p [k]←L _p [k-1]∪P _p [k]

step 5, the data sent by the node p in the kth step is recorded as S _p [k]Then

S _p [k]←P _p [k]；

Step 6, if k is less than r, jumping to step S12, otherwise executing step 7, wherein r is the radius of the strong communication diagram;

step 7, according to the local variable L _p [r]A set of identifiers I of the communication topology is established, wherein,

I←{α|(β,α)∈L _p (r)}

setting matrix d= (0) _n×n N is n×n-dimensional zero matrix, n is the number of elements in the identifier set I;

step 8, based on the sorting algorithm, sorting the identifier set I into a list C, wherein the length of the list C is n, so that a mapping relation f is established, namely C-1, n is established, and the mapping relation is

f(C _i )＝i

wherein ,C_i Is the i-th element in list C;

step 9, for node C _i E I, find Loop O (C _i ) The loop starting point is node C _i The method comprises the steps of carrying out a first treatment on the surface of the The operation of the table head of the record list is H, C and I, if there is

H([α,C′])＝α

Wherein C' is any list, giving O (C _i ) Give an initial value [ C ]']Then there is the following equality relationship:

step 10, if there is a unique (C _j ,H(O(C _i )))∈L _i (r), i.e. node H (O (C) _i ) With only one directed edge away from the node)

[O(C _i )]←[C _j ,O(C _i )]

If present (C) _j ,H(O(C _i )))∈L _i(r) and (C_j′ ,H(O(C _i )))∈L _i (r), and C _j ≠C _j′ I.e. node H (O (C _i ) At least two directed edges away from the node, the loops are recorded separately as follows:

O(C _i ,C _j )←[C _j ,O(C _i )],O(C _i ,C _j ′)←[C _j′ ,O(C _i )]

step 11, if C _j ＝C _i And if there is C _j′ C is then _j ′＝C _i Starting at C _i The end point is also C _i Then find node C _i All loops O (C) _i ,..); otherwise, jumping to step 10;

step 12, establishing a adjacency matrix B of the loop, including

Wherein for any i, j e {1,., n }, if any (C _j ,C _i )∈O(C _i ,..), let B _i,j =1, otherwise let B _i,j ＝0；

Step 13, if the matrix B is full rank, namely rank (B) =n, then

D←D+B；

Step 14, if C _i ≠C _n Then

C _i ←C _i+1

Step 9, if not, executing step 15;

step 15, obtaining a double random communication matrix D through summation and unitized calculation, wherein the calculation formula is as follows:

or ,

as shown in fig. 3, which is a schematic structural diagram of a distributed system for establishing a dual random communication matrix in a unidirectional strong communication network according to a preferred embodiment of the present invention, the system may include:

the topology structure calculation module 201 is configured to calculate a communication topology structure of the communication network according to a strong connectivity graph of the unidirectional strong connectivity communication network;

in the initial stages of multi-intelligent system deployment, the dual random communication matrix is not naturally occurring, and thus it is necessary to establish the dual random communication matrix in a unidirectional strong communication network. Firstly, a communication topological structure of a communication network needs to be found according to a pre-constructed strong connectivity diagram of a to-be-processed unidirectional strong connectivity communication network, which is the basis for finding a loop in the communication network. In particular, each node uses a distributed method to search the communication topology structure of the communication network in an iterative mode.

A loop calculation module 202, configured to calculate all loops in the communication network according to a communication topology structure of the communication network;

after the communication topology structure of the communication network is found, all loops in the communication network need to be found according to the obtained communication topology structure. In particular, all loops in the communication network can be found in an iterative manner.

The dual random communication matrix generation module 203 is configured to calculate a maximum loop including all nodes in all loops in the communication network, and sum and unitize the maximum loop to obtain a dual random communication matrix of the unidirectional strong communication network.

Finally, according to all loops in the communication network, the largest loop including all nodes is found out in all loops, and the double random communication matrix of the unidirectional strong communication network is obtained by calculating the largest loop through a summation and unitization method.

As can be seen from the foregoing, the present embodiment provides a distributed system for establishing a dual random communication matrix in a unidirectional strong communication network, and calculates a communication topology of the communication network according to a strong communication graph of the unidirectional strong communication network through a topology calculation module; calculating all loops in the communication network according to the communication topological structure of the communication network through a loop calculation module; and calculating the maximum loops containing all nodes in all loops in the communication network through a double random communication matrix generation module, summing and unitizing to obtain the double random communication matrix of the unidirectional strong communication network. The invention only needs to give out the communication network with a strong communication with a maximum ring, and can establish the double random communication matrix for the communication network without other conditions, which has better applicability and wider application range compared with other methods for double randomizing the communication network.

In other embodiments of the present invention, the system may further include, on the basis of the above embodiments:

the strong communication diagram construction module is used for constructing a strong communication diagram of the unidirectional strong communication network to be processed before the communication topological structure of the communication network is calculated according to the strong communication diagram of the unidirectional strong communication network, and acquiring the address information of each node in the strong communication diagram.

The working principle of the distributed system for establishing the dual random communication matrix in the unidirectional strong communication network disclosed in this embodiment is the same as that of the above-mentioned distributed method for establishing the dual random communication matrix in the unidirectional strong communication network, and will not be described herein.

In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.

Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative elements and steps are described above generally in terms of functionality in order to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.

The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. The software modules may be disposed in Random Access Memory (RAM), memory, read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (4)

1. A distributed method of establishing a dual random communication matrix in a unidirectional strong connectivity communication network, comprising:

s1, calculating a communication topological structure of a communication network according to a strong connectivity diagram of a unidirectional strong connectivity communication network;

s2, calculating all loops in the communication network according to the communication topological structure of the communication network;

s3, calculating the maximum loop including all nodes in all loops in the communication network, summing and unitizing to obtain a double random communication matrix of the unidirectional strong communication network;

wherein ,

assume that each node in the communication network has a unique identifier, denoted { p, q }; the identifiers of the nodes are provided with order relations which can be compared in size; the directed edges from node p to node q are denoted by (p, q), and the nodes p are each provided with a transmission variable S _p Receiving variable R _p Local variable L _p And temporary storage variable P _p ；

The step S1 comprises the following steps:

s11, respectively transmitting variable S of node p _p Receiving variable R _p Local variable L _p And temporary storage variable P _p Initialized to S _p [0]、R _p [0]、P _p [0]、L _p [0]The initialization formula is as follows:

wherein ,representing an empty set, and ζ represents a valuation operation;

s12, marking the data received by the node p in the kth step as R _p [k]There is

Wherein if the communication topology has directed edges (p, q), T _p,q Is the complete set, otherwise T _p,q Is an empty set; n (N) _q Representing the incoming neighbor set of the node q, wherein, U represents intersection operation, U represents union operation;

s13, the data R received by the node p in the kth step _p [k]Proceeding placeRecord to temporary variable P after processing _p Obtain P _p [k]The processing formula is as follows:

wherein (beta, alpha) represents the set R _p [k]Any element in (a);

s14, according to the received data R _p [k]Updating the local variable of node p to L _p [k]The update formula is as follows:

L _p [k]←L _p [k-1]∪P _p [k]

s15, the data sent by the node p in the kth step is recorded as S _p [k]Then

S _p [k]←P _p [k]；

S16, if k is less than r, jumping to the step S12, otherwise executing the step S2, wherein r is the radius of the strong communication diagram;

the step S2 comprises the following steps:

s21, according to local variable L _p [r]A set of identifiers I of the communication topology is established, wherein,

I←{α|(β,α)∈L _p (r)}

setting matrix d= (0) _n×n N is n×n-dimensional zero matrix, n is the number of elements in the identifier set I;

s22, based on a sorting algorithm, sorting the identifier set I into a list C, wherein the length of the list C is n, so that a mapping relation f is established, namely C & fwdarw {1, & gt, n }, and the mapping relation is

f(C _i )＝i

wherein ,C_i Is the i-th element in list C;

s23, opposite node C _i E I, find Loop O (C _i ) The loop starting point is node C _i The method comprises the steps of carrying out a first treatment on the surface of the The operation of the table head of the record list is H, C and I, if there is

H([α,C′])＝α

Wherein C' is any list, giving O (C _i ) Give an initial value [ C ]']Then there is the following equality relationship:

s24, if there is a unique (C _j ,H(O(C _i )))∈L _i (r), i.e. node H (O (C) _i ) With only one directed edge away from the node)

[O(C _i )]←[C _j ,O(C _i )]

If present (C) _j ,H(O(C _i )))∈L _i(r) and (C_j′ ,H(O(C _i )))∈L _i (r), and C _j ≠C _j′ I.e. node H (O (C _i ) At least two directed edges away from the node, the loops are recorded separately as follows:

O(C _i ,C _j )←[C _j ,O(C _i )],O(C _i ,C _j′ )←[C _j′ ,O(C _i )]

s25, if C _j ＝C _i And if there is C _j′ C is then _j′ ＝C _i Starting at C _i The end point is also C _i Then find node C _i All loops O (C) _i ,..); otherwise, jumping to step S24;

the step S3 comprises the following steps:

s31, establishing a adjacency matrix B of the loop, including

Wherein for any i, j e {1,., n }, if any (C _j ,C _i )∈O(C _i ,..), let B _i,j =1, otherwise let B _i,j ＝0；

S32, if the matrix B is full rank, namely rank (B) =n, then

D←D+B；

S33, if C _i ≠C _n Then

C _i ←C _i+1

Jumping to step S23, otherwise executing step S34;

s34, obtaining a double random communication matrix D through summation and unitization calculation, wherein the calculation formula is as follows:

or ,

2. the distributed method of establishing a dual random communication matrix in a unidirectional strong communication network of claim 1, wherein prior to step S1, the method further comprises:

and constructing a strong communication diagram of the unidirectional strong communication network to be processed, and acquiring address information of each node in the strong communication diagram.

3. A distributed system for establishing a dual random communication matrix in a unidirectional strong connectivity communication network, comprising:

the topology structure calculation module is used for calculating the communication topology structure of the communication network according to the strong connectivity diagram of the unidirectional strong connectivity communication network;

the loop calculation module is used for calculating all loops in the communication network according to the communication topological structure of the communication network;

the dual random communication matrix generation module is used for calculating the maximum loop including all nodes in all loops in the communication network, summing and unitizing to obtain the dual random communication matrix of the unidirectional strong communication network;

wherein ,

assume that each node in the communication network has a unique identifier, denoted { p, q }; the identifiers of the nodes are provided with order relations which can be compared in size; representing the existence of node p to node q by (p, q)To the edge, the node p is respectively provided with a transmission variable S _p Receiving variable R _p Local variable L _p And temporary storage variable P _p ；

The calculating the communication topology structure of the communication network according to the strong connectivity diagram of the unidirectional strong connectivity communication network comprises the following steps:

s11, respectively transmitting variable S of node p _p Receiving variable R _p Local variable L _p And temporary storage variable P _p Initialized to S _p [0]、R _p [0]、P _p [0]、L _p [0]The initialization formula is as follows:

wherein ,representing an empty set, and ζ represents a valuation operation;

s12, marking the data received by the node p in the kth step as R _p [k]There is

Wherein if the communication topology has directed edges (p, q), T _p,q Is the complete set, otherwise T _p,q Is an empty set; n (N) _q Representing the incoming neighbor set of the node q, wherein, U represents intersection operation, U represents union operation;

s13, the data R received by the node p in the kth step _p [k]Record to temporary variable P after processing _p Obtain P _p [k]The processing formula is as follows:

wherein (beta, alpha) represents the set R _p [k]Any element in (a);

s14, according to the received data R _p [k]Updating the local variable of node p to L _p [k]The update formula is as follows:

L _p [k]←L _p [k-1]∪P _p [k]

s15, the data sent by the node p in the kth step is recorded as S _p [k]Then

S _p [k]←P _p [k]；

S16, if k is less than r, jumping to a step S12, otherwise, calculating all loops in the communication network according to the communication topological structure of the communication network, wherein r is the radius of a strong communication graph;

the calculating all loops in the communication network according to the communication topology structure of the communication network comprises the following steps:

s21, according to local variable L _p [r]A set of identifiers I of the communication topology is established, wherein,

I←{α|(β,α)∈L _p (r)}

setting matrix d= (0) _n×n N is n×n-dimensional zero matrix, n is the number of elements in the identifier set I;

s22, based on a sorting algorithm, sorting the identifier set I into a list C, wherein the length of the list C is n, so that a mapping relation f is established, namely C & fwdarw {1, & gt, n }, and the mapping relation is

f(C _i )＝i

wherein ,C_i Is the i-th element in list C;

s23, opposite node C _i E I, find Loop O (C _i ) The loop starting point is node C _i The method comprises the steps of carrying out a first treatment on the surface of the The operation of the table head of the record list is H, C and I, if there is

H([α,C′])＝α

Wherein C' is any list, giving O (C _i ) Give an initial value [ C ]']Then there is the following equality relationship:

s24, if there is a unique (C _j ,H(O(C _i )))∈L _i (r), i.e. node H (O (C) _i ) With only one directed edge away from the node)

[O(C _i )]←[C _j ,O(C _i )]

If present (C) _j ,H(O(C _i )))∈L _i(r) and (C_j′ ,H(O(C _i )))∈L _i (r), and C _j ≠C _j′ I.e. node H (O (C _i ) At least two directed edges away from the node, the loops are recorded separately as follows:

O(C _i ,C _j )←[C _j ,O(C _i )],O(C _i ,C _j′ )←[C _j′ ,O(C _i )]

s25, if C _j ＝C _i And if there is C _j′ C is then _j′ ＝C _i Starting at C _i The end point is also C _i Then find node C _i All loops O (C) _i ,..); otherwise, jumping to step S24;

calculating the maximum loop including all nodes in all loops in the communication network, summing and unitizing to obtain the double random communication matrix of the unidirectional strong communication network, wherein the double random communication matrix comprises the following steps:

s31, establishing a adjacency matrix B of the loop, including

Wherein for any i, j e {1,., n }, if any (C _j ,C _i )∈O(C _i ,..), let B _i,j =1, otherwise let B _i,j ＝0；

S32, if the matrix B is full rank, namely rank (B) =n, then

D←D+B；

S33, if C _i ≠C _n Then

C _i ←C _i+1

Jumping to step S23, otherwise executing step S34;

s34, obtaining a double random communication matrix D through summation and unitization calculation, wherein the calculation formula is as follows:

or ,

4. a distributed system for establishing a dual random communication matrix in a unidirectional strong communication network as recited in claim 3, further comprising:

the strong communication diagram construction module is used for constructing a strong communication diagram of the unidirectional strong communication network to be processed before the communication topological structure of the communication network is calculated according to the strong communication diagram of the unidirectional strong communication network, and acquiring the address information of each node in the strong communication diagram.