CN109451429B - Ad Hoc network virtual backbone node identification method - Google Patents

Ad Hoc network virtual backbone node identification method Download PDF

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CN109451429B
CN109451429B CN201811615122.6A CN201811615122A CN109451429B CN 109451429 B CN109451429 B CN 109451429B CN 201811615122 A CN201811615122 A CN 201811615122A CN 109451429 B CN109451429 B CN 109451429B
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牛钊
马涛
马春来
黄郡
束妮娜
王怀习
王晨
单洪
常超
李航
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National University of Defense Technology
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    • H04W4/02—Services making use of location information
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Abstract

The invention relates to a method for identifying virtual backbone nodes of an Ad Hoc network, belongs to the technical field of communication, and solves the problem that backbone nodes of the Ad Hoc network cannot be effectively identified in the prior art. The method comprises the following steps: the method comprises the steps that nodes in the Ad Hoc network are distinguished and positioned through a radio positioning method, and the number of the nodes, node position information and the size of a node deployment area are obtained; obtaining an important communication distance according to the number of the nodes and the size of a node deployment area; deducing network physical topology according to the node position information and the important communication distance; and according to the result of the network physical topology inference, identifying the virtual backbone nodes by using a unified connected dominating set. The method realizes automatic identification of the virtual backbone nodes in the Ad Hoc network. The result obtained by the method is beneficial to protecting the backbone nodes in the network, and the overall performance of the Ad Hoc network is improved by improving the computing capacity and the information processing capacity of the backbone nodes.

Description

Ad Hoc network virtual backbone node identification method
Technical Field
The invention relates to the technical field of communication, in particular to a method for identifying virtual backbone nodes of an Ad Hoc network.
Background
Ad hoc networks are a more Ad hoc wireless network. Different from a general wireless network, the Ad hoc network has the characteristics of rapid deployment, no need of network facilities, capability of moving nodes in the network according to needs and the like, so that the Ad hoc network is widely applied to civil communication and military communication.
At present, the security of the Ad hoc network has received more and more attention, wherein the identification of backbone nodes in the Ad hoc network is of great significance, and specifically, the protection of backbone nodes in the network is facilitated in a targeted manner, and meanwhile, the performance of the whole network can be improved to a great extent by improving the computing capability and the information processing capability of the backbone nodes.
The prior art mainly focuses on the construction of backbone nodes, and related identification research aiming at the backbone nodes mainly stays in the identification of key nodes. In particular, a key node is usually selected from the network, and the set of nodes influencing network connectivity and network performance is not considered.
Disclosure of Invention
In view of the foregoing analysis, embodiments of the present invention provide a method for identifying a virtual backbone node of an Ad Hoc network, so as to solve the problem that the prior art cannot effectively identify the backbone node of the Ad Hoc network.
On one hand, the embodiment of the invention provides a method for identifying virtual backbone nodes of an Ad Hoc network, which comprises the following steps:
the method comprises the steps that nodes in the Ad Hoc network are distinguished and positioned through a radio positioning method, and the number of the nodes, node position information and the size of a node deployment area are obtained;
obtaining an important communication distance according to the number of the nodes and the size of a node deployment area;
deducing network physical topology according to the node position information and the important communication distance;
and according to the result of the network physical topology inference, identifying the virtual backbone nodes by using a unified connected dominating set.
The beneficial effects of the above technical scheme are as follows: the provided method for identifying the virtual backbone nodes of the Ad Hoc network can automatically identify the backbone nodes in the Ad Hoc network. Specifically, by inference of network physical topology, the method can find out all nodes influencing network connectivity and network performance, so that the obtained backbone nodes are more representative and important, and a key node is obtained from the network for analysis and substitution in the non-prior art. Moreover, the result obtained by the method is beneficial to protecting the backbone nodes in the network in a targeted manner, and the overall performance of the network can be improved to a great extent by improving the computing capability and the information processing capability of the backbone nodes.
In another embodiment based on the foregoing method, the distinguishing and positioning the nodes in the Ad Hoc network by using the radio positioning method to obtain the number of nodes, the node location information, and the size of the node deployment area includes the following steps:
receiving signals in the working frequency band of the Ad Hoc network through a broadband receiver;
performing signal preprocessing and signal detection on the received signals in the working frequency band to obtain a signal detection result;
and distinguishing and positioning the nodes contained in the signal detection result by adopting a composite angle positioning method or a time difference positioning method to obtain the number of the nodes, the position information of the nodes and the size of a node deployment area.
The beneficial effects of the above technical scheme are: the method for obtaining the number of the nodes, the position information of the nodes and the size of the node deployment area is limited, so that the number of the nodes, the position information of the nodes and the size of the node deployment area can be automatically obtained, and manpower and cost are effectively saved. In addition, in the method, through signal preprocessing and signal detection, irrelevant information can be filtered, useful nodes can be better identified, and the information workload can be effectively reduced.
Further, the important communication distance RCCalculated by the following formula:
Figure GDA0002538947710000031
in the formula, k1Denotes the coefficient of connectivity,/1Side length, n, representing node deployment area1Indicating the number of nodes.
The beneficial effects of the further scheme are as follows: the method for acquiring the important communication distance is limited, the calculation of the important communication distance can be realized under the condition of only acquiring the size of the node deployment area and the number of the nodes, parameters such as the working power of the nodes do not need to be acquired, and the method is simple and easy to realize. The automatic calculation of the important communication distance can be realized, and the obtained result is accurate and reliable.
Further, the network physical topology inference according to the node location information and the important communication distance includes the following steps:
calculating the Euclidean distance between any two nodes in all the nodes according to the node position information;
comparing the Euclidean distance between any two nodes in all the nodes with the important communication distance, judging that a link exists between the two nodes when the Euclidean distance between the two nodes is smaller than or equal to the important communication distance, and otherwise, judging that the link does not exist between the two nodes;
and repeating the steps to find out the link sets among all the nodes, and finishing the inference of the network physical topology.
The beneficial effects of the further scheme are as follows: the method for deducing the network physical topology is limited, so that the network physical topology can be automatically deduced, and a network physical topology result can be quickly obtained. A large number of tests prove that the method is effective, reliable and accurate.
Further, the identifying the virtual backbone node by using the unified connectivity domination set according to the result of the network physical topology inference includes the following steps:
screening nodes in the physical topology inference result according to the dominating set node screening conditions, and screening out nodes with higher dominating factors compared with neighbor nodes as dominating set nodes;
screening the non-dominating set nodes in the physical topology inference result according to the screening condition of the non-connected set nodes, deleting the nodes meeting the screening condition of the non-connected set nodes, and obtaining the nodes possibly meeting the screening condition of the connected set nodes;
according to the screening condition of the connected set exception nodes, deleting unnecessary nodes from the nodes possibly meeting the screening condition of the connected set nodes to obtain necessary nodes possibly meeting the screening condition of the connected set nodes;
screening connected set nodes from the necessary nodes which possibly meet the screening conditions of the connected set nodes according to the screening conditions of the connected set nodes;
and taking the screened connected set nodes and the screened dominating set nodes as virtual backbone nodes of the Ad Hoc network.
The beneficial effects of the further scheme are as follows: the method for identifying the virtual backbone nodes by using the unified connected dominating set is limited, and the method can quickly obtain the identification result of the virtual backbone nodes in the network. A large number of tests prove that the method is effective, reliable and accurate.
Further, the signal preprocessing and the signal detection are performed on the received signals in the working frequency band to obtain a signal detection result, and the method comprises the following steps:
preprocessing the received signals in the working frequency band, deleting the signals which are not in the required frequency range, and obtaining preprocessed signals;
and carrying out signal detection on the preprocessed signal to obtain a signal detection result, wherein the signal detection result is the arrival time of the TH-PPM-UWB pulse.
The beneficial effects of the further scheme are as follows: the method for signal preprocessing and signal detection is specifically limited, can effectively screen signals, quickly obtains signals which are useful for subsequent analysis, and can effectively reduce the workload of subsequent information processing.
Further, the dominating set node screening condition is expressed as
Figure GDA0002538947710000051
In the formula, i and j represent nodes, Ni、NjRespectively representing the neighbor node sets of nodes i and j, DS representing the dominating set, di、djRepresenting a dominant factor;
the candidate set node screening condition of the connected set is expressed as
Figure GDA0002538947710000052
Figure GDA0002538947710000053
In the formula, k and n represent nodes, CS represents a connected set, CS' represents a candidate node set of the connected set, EjDenotes, DSNj、DSNkRepresenting a set formed by dominant nodes in the neighbor nodes of the nodes j and k, and d represents a dominant factor;
the screening condition of the connected set exception node is expressed as
Figure GDA0002538947710000054
In the formula, l and m represent nodes, DSNiRepresenting a set of dominant nodes in the neighbor nodes of the node i;
the connected set node screening condition is expressed as
Figure GDA0002538947710000055
Figure GDA0002538947710000056
The beneficial effects of the further scheme are as follows: and limiting specific filtering conditions of the dominating set nodes, non-connected set nodes, connected set exception nodes and connected set nodes. The method can quickly complete the screening of nodes of the domination set and the connected set. A large number of tests prove that the obtained result is reliable, effective and accurate.
Further, when k is1When the communication rate of the Ad Hoc network is 0.8, the communication rate of the Ad Hoc network is kept about 100%, and no isolated node exists in the Ad Hoc network; and, the important communication distance RCIs composed of
Figure GDA0002538947710000061
The beneficial effects of the further scheme are as follows: proved by a large number of experiments, when k is1When the communication rate of the Ad Hoc network is about 100%, namely, no isolated node exists in the Ad Hoc network, so that the analysis is performed according to the important node, the relationship between the nodes can be simulated more effectively, and the practical situation is fitted more.
Further, the Euclidean distance between any two nodes in all the nodes is expressed as
Figure GDA0002538947710000062
In the formula, a and b represent any two nodes, (x)a,ya) Represents the coordinates of node a, (x)b,yb) Representing the node b coordinates.
The beneficial effects of the further scheme are as follows: the Euclidean distance is limited, the method is simple and easy to operate, and the Euclidean distance between any two nodes in all the nodes can be obtained through the formula.
Further, the signal preprocessing adopts a wavelet denoising method for removing high-frequency noise in the signal in the working frequency band;
and the signal detection adopts a piecewise correlation average method and is used for detecting the arrival time of the TH-PPM-UWB pulse.
The beneficial effects of the further scheme are as follows: the piecewise correlation averaging method is generally used for signal detection under the condition of low signal-to-noise ratio, and the wavelet is used for denoising, so that high-frequency noise in signals in a working frequency band can be effectively removed, the signal-to-noise ratio is improved, and further, the piecewise correlation averaging algorithm is used for signal detection.
In the invention, the technical schemes can be combined with each other to realize more preferable combination schemes. Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
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The drawings are only for purposes of illustrating particular embodiments and are not to be construed as limiting the invention, wherein like reference numerals are used to designate like parts throughout.
Fig. 1 is a schematic step diagram of an Ad Hoc network virtual backbone node identification method according to embodiment 1 of the present invention;
fig. 2 is a schematic diagram of a step of distinguishing and positioning nodes in an Ad Hoc network by a radio positioning method according to embodiment 2 of the present invention;
FIG. 3 is a schematic diagram of the steps of inferring the network physical topology according to the node location information and the important communication distance in embodiment 2 of the present invention;
fig. 4 is a schematic diagram of the step of identifying a virtual backbone node using a unified connected dominating set according to the result of inference of the network physical topology according to embodiment 2 of the present invention;
FIG. 5 is a schematic diagram of a simulation environment constructed by using the EXAta software in embodiment 3 of the present invention;
fig. 6 is a physical topology diagram formed by physical communication links between wireless communication nodes in an Ad Hoc network obtained in embodiment 3 of the present invention;
fig. 7 is a schematic diagram of an identification result of a virtual backbone node in an Ad Hoc network according to embodiment 3 of the present invention.
Detailed Description
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate preferred embodiments of the invention and together with the description, serve to explain the principles of the invention and not to limit the scope of the invention.
Example 1
A specific embodiment of the present invention discloses a method for identifying a virtual backbone node in an Ad Hoc network, as shown in fig. 1, comprising the following steps:
s1, distinguishing and positioning nodes in the Ad Hoc network by a radio positioning method, and obtaining the number of the nodes, the position information of the nodes and the size of a node deployment area.
And S2, obtaining an important communication distance according to the number of the nodes and the size of the node deployment area.
And S3, deducing the network physical topology according to the node position information and the important communication distance.
And S4, identifying the virtual backbone nodes by using a unified connected dominating set according to the result of the network physical topology inference.
The basic concept involved in embodiment 1 is briefly described below.
Ad Hoc network: a multi-hop, centerless, ad hoc wireless network consisting of a set of wireless communication nodes, also known as a multi-hop network, an infrastructure-less network, or an ad hoc network. Has strong destroy resistance and self-organizing property and wide application.
Important communication distance: and ensuring the minimum communication distance value of the Ad Hoc network connection.
Ad Hoc network physical topology: in general, a physical topology diagram consisting of physical communication links between wireless communication nodes in an Ad Hoc network is shown.
Ad Hoc network virtual backbone node: in order to effectively cope with broadcast storms, save energy, reduce interference and prolong the service life of an Ad Hoc network, part of nodes are usually selected in the Ad Hoc network to construct a virtual backbone, and the backbone nodes are nodes in a backbone framework in the Ad Hoc network.
Compared with the prior art, the method for identifying the virtual backbone nodes of the Ad Hoc network provided by the embodiment can automatically identify the backbone nodes in the Ad Hoc network. Specifically, by inference of network physical topology, the method can find out all nodes influencing network connectivity and network performance, so that the obtained backbone nodes are more representative and important, and a key node is obtained from the network for analysis and substitution in the non-prior art. Moreover, the result obtained by the method is beneficial to protecting the backbone nodes in the network in a targeted manner, and the overall performance of the network can be improved to a great extent by improving the computing capability and the information processing capability of the backbone nodes.
Example 2
The optimization is performed on the basis of embodiment 1, and as shown in fig. 2, the above step S1 can be further refined into the following steps:
s11, receiving signals in the working frequency band of the Ad Hoc network through a broadband receiver;
s12, signal preprocessing and signal detection are carried out on the received signals in the working frequency band, useless signals are eliminated, and a signal detection result is obtained;
and S13, distinguishing and positioning the nodes contained in the signal detection result by adopting a composite angle positioning method or a time difference positioning method, and obtaining the number of the nodes, the position information of the nodes and the size of a node deployment area.
Specifically, the composite angle positioning method is based on radio direction finding work, direction finding is carried out on the same signal through a plurality of radio monitoring stations, and positioning is carried out by utilizing intersection of direction finding rays (angles). The time difference positioning method is based on the time when the signal reaches the monitoring station, and intersection positioning is carried out through time distance conversion. Those skilled in the art will appreciate that no further details are provided herein.
Preferably, step S12 can be further refined into the following steps:
s121, preprocessing the received signals in the working frequency band, deleting the signals which are not in the required frequency range, and obtaining preprocessed signals;
and S122, carrying out signal detection on the preprocessed signal to obtain a signal detection result, wherein the signal detection result is the arrival time of the TH-PPM-UWB pulse.
Preferably, in step S121, the signal preprocessing includes wavelet denoising to remove high frequency noise in the received signal and improve the signal-to-noise ratio. The signal preprocessing adopts a wavelet denoising method for removing high-frequency noise in the signal in the working frequency band. The signal detection adopts a segment correlation average method for detecting the arrival time of the TH-PPM-UWB pulse. Specifically, the reference to the segmentation correlation average method is "a new method for detecting ultra-wideband signal under negative signal-to-noise ratio" published by the authors in the seas, china army and young calves, and the details are not repeated herein. It is noted that the TH-PPM-UWB pulse has a direction.
Preferably, step S2 can be further refined into the following steps:
and S21, analyzing the Ad Hoc network from the network connectivity perspective. Specifically, the distribution rule of the nodes is analyzed to obtain the connectivity coefficient.
And S22, obtaining an important communication distance according to the number of the nodes and the size of the node deployment area.
When calculating the important communication distance in step S22, the following theorem exists:
theorem 1: for n1Each node is assumed to have a communication distance of r, and all the nodes are randomly distributed in
Figure GDA0002538947710000101
In the region of (b), wherein d 12 denotes a two-dimensional plane, assuming
Figure GDA0002538947710000102
α＞0，r＝r(l1)＜＜l1，n1＝n1(l1) > 1, if
Figure GDA0002538947710000103
Or
Figure GDA0002538947710000104
And r ═ r (l)1) > 1, the entire communication graph is fully connected, where
Figure GDA0002538947710000105
Theorem 2: suppose n is1Each node is arranged at
Figure GDA0002538947710000106
In the region of (b), wherein d1＝2，r＝r(l1)＜＜l1，n1＝n1(l1) > 1. If it is not
Figure GDA0002538947710000107
The communication graph is not connected.
According to the above theorem 1, the following relationship exists between the important communication distance and the number of nodes and the size of the deployment area in the Ad Hoc network
Figure GDA0002538947710000108
Whether the network is in a connected state can be ensured, and the setting is closely related to the value of alpha
Figure GDA0002538947710000109
The important communication distance R can be obtained by transforming the formulaCThe calculation formula of (a) is as follows:
Figure GDA00025389477100001010
in the formula, k1Denotes the coefficient of connectivity,/1Representing a node deployment region (area l)1 2) Side length of (n)1Indicating the number of nodes.
The following conclusions can be drawn by function fitting: when k is1The network connectivity is basically kept at about 100% when the network connectivity is more than or equal to 0.8No isolated node exists in the Ad Hoc network. In step S22, the embodiment selects and finds k1Important communication distance of 0.8 hours
Figure GDA0002538947710000111
Preferably, as shown in fig. 3, the step S3 can be further refined into the following steps:
and S31, calculating the Euclidean distance between any two nodes in all the nodes according to the node position information. With node a (x)a,ya) And node b (x)b,yb) For example, the Euclidean distance between two nodes can be expressed as
Figure GDA0002538947710000112
S32, comparing the Euclidean distance between any two nodes in all the nodes with the important communication distance, judging that a link exists between the two nodes when the Euclidean distance between the two nodes is smaller than or equal to the important communication distance, and otherwise, judging that the link does not exist between the two nodes;
and S33, repeating the steps, finding out a link set among all the nodes, and finishing the inference of the physical topology of the network.
Preferably, in step S33, the finding out the link set among all nodes to complete the network physical topology inference can be further detailed as the following steps:
and S331, constructing an adjacency matrix, and storing the communication relation between the nodes as a link set among all the nodes. Specifically, the adjacency matrix is initially set to 0, and if a link exists between two nodes, the corresponding value in the adjacency matrix is modified to 1, and the elements in the adjacency matrix are traversed.
The adjacency matrix may be expressed in the form
Figure GDA0002538947710000121
In the formula, aijRepresenting the communication relation between the ith node and the jth node, wherein i and j are any numerical values from 1 to n, n represents the total number of the nodes, and if a link exists between the ith node and the jth node, aij1, otherwise, aij＝0。
And S332, deducing the physical topology of the Ad Hoc network according to the position information of the node and the adjacency matrix, and constructing a physical topology map of the Ad Hoc network.
Preferably, as shown in fig. 4, the step S4 can be further refined into the following steps:
and S41, screening the nodes in the physical topology inference result according to the dominating set node screening condition (DS rule), and screening out the nodes with higher dominating factors compared with the neighbor nodes as dominating set nodes.
And S42, screening the non-dominating set nodes in the physical topology inference result according to the screening condition (non-CS rule) of the non-connected set nodes, deleting the nodes meeting the screening condition of the non-connected set nodes, and obtaining the nodes possibly meeting the screening condition of the connected set nodes.
S43, according to the screening condition (CS exception rule) of the connected set exception nodes, deleting unnecessary nodes from the nodes possibly meeting the screening condition of the connected set nodes, and obtaining necessary nodes possibly meeting the screening condition of the connected set nodes. Specifically, if a node satisfies the connected set exception rule, the node is deleted as an unnecessary node, and subsequent connected set screening condition judgment is not performed any more.
S44, screening connected set nodes from the necessary nodes which possibly accord with the connected set node screening conditions according to the connected set node screening conditions (CS rules);
and S45, taking the screened connected set nodes and the screened dominating set nodes as virtual backbone nodes of the Ad Hoc network.
Preferably, the dominating set node screening condition can be expressed as
Figure GDA0002538947710000131
In the formula, i and j represent nodes,Ni、Njrespectively representing the neighbor node sets of nodes i and j, DS representing the dominating set, di、djIndicating the dominant factor.
Specifically, a node i to become a member of the DS needs to satisfy the following condition:
1) among the neighbors of node i (denoted as j), it has the highest dominance diIn which case node i designates itself as a member of the DS;
2) a node j finds that, in its neighborhood (denoted k), node i has the highest dominance factor, in which case node j designates node i as a member of the DS;
3) if the dominant control factor of a node is the same as one of its neighbors (called a DS twin), then the selection is made by the node id. In this manner, a node will designate itself or a member of the DS by an adjacent node.
By using the screening condition of the dominating set node, the distance between any node and the DS cannot exceed 1 hop.
Preferably, the screening condition of the node of the connected set candidate set can be expressed as
Figure GDA0002538947710000132
Figure GDA0002538947710000133
In the formula, k and n represent nodes, CS represents a connected set, CS' represents a candidate node set of the connected set, EjDenotes, DSNj、DSNkAnd d represents a dominant factor, and represents a set of dominant nodes among the neighbor nodes of the nodes j and k.
Specifically, the screening condition of the non-connected set node is that if all the neighbor nodes j and k of a node i are directly connected with each other, i is not a member of the CS.
Preferably, the screening condition of the connected set exception node can be expressed as
Figure GDA0002538947710000141
In the formula, l and m represent nodes, DSNiA set of dominant nodes among the neighbor nodes representing node i.
Specifically, the screening condition of the connected set exception node includes:
1) a common neighbor of node j or k has become a CS node, or if,
2) either j or k is not a DS node and node i has a common DS neighbor with that node.
Unless the CS rule applies to another pair of neighboring nodes l and m, the CS exception rule needs to be applied to node i.
Preferably, the screening condition of the connected set nodes is expressed as
Figure GDA0002538947710000142
Figure GDA0002538947710000143
In particular, connected set node screening conditions, i.e., one with NiThe condition for a neighbor node i to become a candidate node (CS') is: it is not yet a member of the DS and has neighbors j and k (at least one of which is a member of the DS), the DS neighbor set (DSN) of j and kjAnd DSNkIt contains j or k) as members of DS as disjoint. In the common neighborhood of twin nodes j and k belonging to CS', the node with the highest dominance factor (d) (or the highest node id-breaking rule if d is the same) becomes a CS node.
Compared with embodiment 1, the Ad Hoc network virtual backbone node identification method provided by this embodiment can automatically acquire the number of nodes, the node location information, and the size of the node deployment area through programming, and can accurately infer the network physical topology by combining with the calculated important communication distance, thereby identifying the virtual backbone node by using the unified connectivity domination set. The identification result is accurate, and the identified backbone nodes can be specially optimized in a targeted manner, so that the performance of the whole network is better.
Example 3
An example of applying the method described in embodiment 2 is provided below, and the technical effect of the Ad Hoc network virtual backbone node identification method is verified by using the method of setting up the simulation environment shown in fig. 5 by using the EXata software for testing. And randomly deploying 40 nodes in a simulation scene by using a random deployment model, wherein relevant parameters are shown in table 1.
TABLE 1
Parameter(s) Numerical value
Number of nodes 40
Deployment area size (1×1)km2
Routing protocol AODV
Fading value 4dB
Communication frequency 2.4GHz
Type of service CBR
Aiming at the size of a deployment area and the number of nodes, when the k value is set to be 0.8, the network connectivity rate approaches to 100%, and R can be obtained by calculating through an important communication distance formulaC≈332m。
And (3) performing physical topology inference by combining the node position information and the important communication distance to obtain a physical topology graph as shown in fig. 6.
The Ad Hoc network virtual backbone nodes are identified following the unified connectivity dominating set correlation rule, the dominating set and the connectivity set in the network are extracted, and the obtained identification result is shown in fig. 7.
Those skilled in the art will appreciate that all or part of the flow of the method implementing the above embodiments may be implemented by a computer program, which is stored in a computer readable storage medium, to instruct related hardware. The computer readable storage medium is a magnetic disk, an optical disk, a read-only memory or a random access memory.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention.
Those skilled in the art will appreciate that all or part of the flow of the method implementing the above embodiments may be implemented by a computer program, which is stored in a computer readable storage medium, to instruct related hardware. The computer readable storage medium is a magnetic disk, an optical disk, a read-only memory or a random access memory.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention.

Claims (8)

1. A method for identifying virtual backbone nodes of an Ad Hoc network is characterized by comprising the following steps:
the method comprises the steps that nodes in the Ad Hoc network are distinguished and positioned through a radio positioning method, and the number of the nodes, node position information and the size of a node deployment area are obtained;
obtaining an important communication distance according to the number of the nodes and the size of a node deployment area;
deducing network physical topology according to the node position information and the important communication distance;
according to the result of the network physical topology inference, identifying the virtual backbone nodes by using a unified connectivity domination set;
the network physical topology inference is performed according to the node location information and the important communication distance, and the method further includes the following steps:
calculating the Euclidean distance between any two nodes in all the nodes according to the node position information;
comparing the Euclidean distance between any two nodes in all the nodes with the important communication distance, judging that a link exists between the two nodes when the Euclidean distance between the two nodes is smaller than or equal to the important communication distance, and otherwise, judging that the link does not exist between the two nodes;
repeating the steps, finding out a link set among all nodes, and finishing the inference of the network physical topology;
the identifying the virtual backbone node by using the unified connectivity domination set according to the result of the network physical topology inference further includes the following steps:
screening nodes in the physical topology inference result according to the dominating set node screening conditions, and screening out nodes with higher dominating factors compared with neighbor nodes as dominating set nodes;
screening non-dominating set nodes in the physical topology inference result according to the screening condition of the non-connected set nodes, deleting all the nodes of which the neighbor nodes are directly connected with each other, and obtaining the nodes which possibly accord with the screening condition of the connected set nodes;
according to the screening condition of the connected set exception nodes, deleting unnecessary nodes from the nodes possibly meeting the screening condition of the connected set nodes to obtain necessary nodes possibly meeting the screening condition of the connected set nodes;
screening connected set nodes from the necessary nodes which possibly meet the screening conditions of the connected set nodes according to the screening conditions of the connected set nodes;
and taking the screened connected set nodes and the screened dominating set nodes as virtual backbone nodes of the Ad Hoc network.
2. The method for identifying the virtual backbone nodes of the Ad Hoc network according to claim 1, wherein the nodes in the Ad Hoc network are distinguished and located by a radio location method to obtain the number of nodes, the location information of the nodes and the size of a node deployment area, comprising the steps of:
receiving signals in the working frequency band of the Ad Hoc network through a broadband receiver;
performing signal preprocessing and signal detection on the received signals in the working frequency band to obtain a signal detection result;
and distinguishing and positioning the nodes contained in the signal detection result by adopting a composite angle positioning method or a time difference positioning method to obtain the number of the nodes, the position information of the nodes and the size of a node deployment area.
3. The Ad Hoc network virtual backbone node identification method according to claim 1 or 2, wherein the important communication distance RCCalculated by the following formula:
Figure FDA0002647214430000021
in the formula, k1Denotes the coefficient of connectivity,/1Side length, n, representing node deployment area1Indicating the number of nodes.
4. The method for identifying the Ad Hoc network virtual backbone node according to claim 2, wherein the signal preprocessing and the signal detection are performed on the received signal within the working frequency band to obtain the signal detection result, comprising the following steps:
carrying out signal preprocessing on the received signals in the working frequency band, deleting the signals which are not in the preset frequency range, and obtaining preprocessed signals;
and carrying out signal detection on the preprocessed signal to obtain a signal detection result, wherein the signal detection result is the arrival time of the TH-PPM-UWB pulse.
5. The method of claim 1, wherein the screening condition of the dominating set node is expressed as
Figure FDA0002647214430000031
In the formula, i and j represent nodes, Ni、NjRespectively representing the neighbor node sets of nodes i and j, DS representing the dominating set, di、djRepresenting a dominant factor;
the candidate set node screening condition of the connected set is expressed as
Figure FDA0002647214430000032
Figure FDA0002647214430000033
In the formula, k and n represent nodes, CS represents a connected set, CS' represents a candidate node set of the connected set, and DSNj、DSNkRepresenting a set formed by dominant nodes in the neighbor nodes of the nodes j and k, and d represents a dominant factor;
the screening condition of the connected set exception node is expressed as
Figure FDA0002647214430000034
In the formula, l and m represent nodes, DSNiRepresenting a set of dominant nodes in the neighbor nodes of the node i;
the connected set node screening condition is expressed as
Figure FDA0002647214430000035
Figure FDA0002647214430000036
。
6. The Ad Hoc network virtual backbone node identification method of claim 3, wherein when k is1When the communication rate of the Ad Hoc network is 0.8, the communication rate of the Ad Hoc network is kept about 100%, and no isolated node exists in the Ad Hoc network; and, the important communication distance RCIs composed of
Figure FDA0002647214430000041
7. The method of claim 1 wherein the Euclidean distance between any two nodes in all nodes is expressed as
Figure FDA0002647214430000042
In the formula, a and b represent any two nodes, (x)a,ya) Represents the coordinates of node a, (x)b,yb) Representing the node b coordinates.
8. The method for identifying the Ad Hoc network virtual backbone node according to claim 4, wherein the signal preprocessing adopts a wavelet denoising method for removing high frequency noise in the signal in the working frequency band;
and the signal detection adopts a piecewise correlation average method and is used for detecting the arrival time of the TH-PPM-UWB pulse.
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