CN106792845B - Anchor node selection method in mobile self-organizing network - Google Patents
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Abstract
The invention discloses a method for selecting an anchor node in a mobile self-organizing network, which comprises the following steps: determining the number of clusters required to be formed in the mobile self-organizing network and the number of anchor nodes required to be additionally selected according to the required number of the anchor nodes, and reasonably clustering all nodes in the network in a distributed manner to obtain the required number of clusters; and step two, based on the clustering condition obtained in the step one, in each cluster, selecting some nodes with moderate distance to the clustering center of mass according to the distance value condition between each node and the clustering center of mass in the cluster by the cluster head node, and using the selected nodes as the anchor node candidate set and the like in the cluster. And step three, selecting three anchor nodes from the anchor node candidate set of each cluster according to the optimal distribution rule of the anchor nodes. The invention can select anchor nodes with reasonable distribution in the network, thereby being beneficial to improving the performance of the network and having simple operation.
Description
Technical Field
The invention relates to an anchor node selection method in the technical field of mobile communication, in particular to an anchor node selection method in a mobile self-organizing network.
Background
The mobile ad hoc network has the advantages of fast networking, independence on infrastructure and the like, and is widely applied to a plurality of fields such as emergency service, post-disaster search and rescue, intelligent transportation, factory automation and the like. The structure of the mobile ad hoc network can be divided into a planar structure, a layered structure and the like, wherein the layered structure can effectively reduce the problems of high end-to-end communication delay, unbalanced network communication load and the like caused by the planar structure, and can improve the expandability of the network. In a mobile ad hoc network, a hierarchical structure is proposed mainly for the purpose of reducing the total energy consumption and communication load of nodes in the network, and the like, a networking node (which may be a person, a robot, a vehicle, and the like, and hereinafter referred to as a node) in the network needs to be divided into roles, for example, in a typical two-layer structure, the node is divided into an anchor node and a user node, that is, the anchor node forms an upper layer, and the user node forms a lower layer; the anchor node can realize reasonable resource scheduling of the user node, such as distribution of calculation tasks and the like, and the user node depends on the anchor node to realize functions, such as positioning of the user node through ranging communication with the anchor node and the like. The formation of a multi-layer structure in the mobile self-organizing network is an expansion form of a two-layer structure. Therefore, the problem of reasonable selection of anchor nodes in the mobile ad hoc network is receiving more and more attention.
In a mobile ad hoc network, nodes have the same characteristics, that is, each node can implement the same function, such as self-positioning by a Global Positioning System (GPS). If a hierarchical structure is to be formed in the mobile ad hoc network to improve the performance of the network, a certain number of nodes need to be selected from the nodes as anchor nodes. The distribution of the anchor nodes affects the performance of the mobile ad hoc network, such as total energy consumption of the nodes in the network, the proportion of user nodes in the network that can communicate with the anchor nodes, the communication load of the anchor nodes, and the corresponding implementation of services provided by the network; therefore, the anchor nodes with reasonable distribution are selected, so that the performance in the mobile ad hoc network is improved, and the service quality provided by the network is improved; for example, in a mobile ad hoc network with a positioning user node as a main service, reasonable anchor node distribution can improve the number of user nodes that can be positioned in the network and the positioning accuracy that can be achieved by a positioning process for the user nodes, thereby showing the importance of the anchor node selection problem in the mobile ad hoc network.
Through the search of the prior art, the current schemes for selecting the anchor nodes in the mobile ad hoc network include a uniform distribution scheme, a random distribution scheme and the like. The uniform distribution refers to planning the positions of the anchor nodes with required number when the anchor nodes are uniformly distributed in the network under the condition that the initial positions of all the nodes in the network are known, and selecting the nodes closest to the positions in the network as the anchor nodes; the random distribution means that nodes with required number are randomly selected from all nodes to be used as anchor nodes; in the two schemes, a central controller in the network is required to carry out overall control on the selection process of the anchor nodes, and in the mobile ad hoc network with the same initial roles of all the nodes, the anchor nodes which are uniformly or randomly distributed are selected and are difficult to realize, so a distributed method is required to select the anchor nodes which are reasonably distributed in the network.
Disclosure of Invention
The invention aims to provide a method for selecting anchor nodes in a mobile self-organizing network, which can select reasonably distributed anchor nodes in the network, is favorable for improving the performance of the network and is simple to operate.
The invention solves the technical problems through the following technical scheme: a method for selecting an anchor node in a mobile ad hoc network comprises the following steps:
determining the number of clusters required to be formed in the mobile self-organizing network and the number of anchor nodes required to be additionally selected according to the required number of the anchor nodes, and reasonably clustering all nodes in the network in a distributed manner to obtain the required number of clusters;
secondly, based on the clustering condition obtained in the first step, in each cluster, the cluster head node selects some nodes with moderate distance to the clustering center of mass according to the distance value condition between each node and the clustering center of mass in the cluster, and the selected nodes are used as a selected anchor node candidate set in the cluster;
step three, according to the anchor node candidate sets corresponding to the clusters obtained in the step two, aiming at each cluster, selecting three nodes which are distributed most closely to a regular triangle from the corresponding anchor node candidate sets as the selected anchor nodes in the cluster by the cluster head nodes;
and step four, if anchor nodes needing to be additionally selected exist, collecting the nodes which are closest to the boundary of the deployment area in each cluster at the boundary of the node deployment area through communication among cluster head nodes of each cluster in the network, and randomly selecting the anchor nodes needing to be additionally selected from the nodes, so that the anchor nodes which are in the specified number and reasonably distributed in the whole network are obtained.
Preferably, the first step comprises the steps of:
step ten, the total number of nodes in the mobile self-organizing network is N, and the anchor node number N is selected according to the requirementaAnd calculating the number of clusters to be formed as shown in the following formula:
wherein
Is composed of
Rounded down values of (d); and simultaneously calculating the number of anchor nodes needing to be additionally selected as follows: n is a radical ofa′＝Na-3×Ncluster；
Step eleven, clustering nodes in the mobile ad hoc network by using a similarity propagation clustering algorithm, wherein the clustering algorithm is a distributed algorithm and only depends on similarity values between different nodes and similarity values of the nodes, a negative value of a Euclidean distance between a node i and a node j (i, j is 1.., N, j ≠ i) is used as the similarity value between the node i and the node j, and the distance between the node i and the node j is shown as the following formula:
the two-dimensional position of the initial time node i is shown as follows: pi＝[xi,yi]TThe similarity between node i and node j is shown as follows: s (i, j) ═ dijTo nodeiAnd respectively carrying out ranging communication with other nodes in the network to obtain the distance between the node and other nodesThe distance between the points is set to Di，dmedianIs DiThe similarity of the node i itself is set as follows: s (i, i) ═ dmedian·fscaleWherein, fscaleBy adjusting f for the multiplication factorscaleThe value of s (i, i) can be changed, and then clusters with different numbers can be obtained in the clustering process;
step twelve, in the process of clustering the nodes, clusters are formed and cluster head nodes in each cluster are obtained at the same time, the selection process of the anchor nodes in each cluster is controlled by the cluster head nodes of the cluster, and the anchor nodes needing to be additionally selected are obtained through communication among the cluster head nodes of each cluster.
Preferably, the second step comprises the steps of:
twenty, based on the clustering condition obtained in the first step, aiming at the cluster Cm(m＝1,...,Ncluster) Wherein the kth node is represented as Cmk(k＝1,...,Nm)，NmIs CmThe number of middle nodes; the centroid of the cluster is om(ii) a The cluster head node collects the initial positions of all nodes in the cluster, and the initial positions are shown according to the following formula:
calculate the formula
Twenty-one, CmCluster head node of (1) calculating each node C in a clustermkAnd omThe value of the distance between dkoAnd form a set Do，dmedAnd dmaxAre respectively DoMedian and maximum values of;
twenty-two, extracting DoIs represented by the following formula: (d)med,(dmax+dmed) /2) interval distance values, the node set corresponding to these distance values is CmAnchor node candidate set S in (1)m。
Preferably, step three comprises the steps of:
thirty step, according to the cluster C obtained in the second stepm(m＝1,...,Ncluster) Anchor node candidate set SmCalculating SmEvery two nodes in
The distance between
Step thirty one, from SmIn selecting three different nodes
And
the area of the triangle formed by the position distribution is calculated by the Helen formula as follows:
wherein p is represented by the formula:
is a node
And node
The distance between them;
step thirty-two, the distances from the centroid of a triangle to its three vertices are assigned as
And
the triangle reaches its maximum area when it becomes a regular triangle, which is calculated as follows:
step thirty-three, in order to evaluate the node
And
the degree of the formed triangle approaching to the regular triangle defines the similarity of the regular triangle as follows:
step thirty-four, repeating the step eleven, the step twelve and the step thirteen until S is detectedmAnd traversing all the nodes by taking three nodes as combinations to obtain a node combination with the maximum regular triangle similarity, wherein the three nodes are the cluster CmThe selected anchor node;
and step thirty-five, setting m to be m +1, and repeating the step eleven, the step twelve, the step thirteen and the step fourteen until all clusters complete the selection of the anchor nodes.
Preferably, the fourth step comprises the steps of:
fortieth, N obtained in step tenaIf not, continuing to perform the step forty one and the step forty two, otherwise, completing the selection process of the anchor node in the mobile self-organizing network;
fourthly, collecting the node which is closest to the boundary of the node deployment area in each cluster at the boundary of the node deployment area to the cluster head node corresponding to the cluster close to the central position of the deployment area through communication among the cluster head nodes corresponding to the clusters;
step forty-two, the cluster head node randomly selects N from the collected nodesa' anchor node, to this end, the selection of anchor node in mobile ad hoc network is completedThe process.
The positive progress effects of the invention are as follows: the invention can plan the cluster number required to be formed in the network and the anchor node number required to be additionally selected according to the anchor node number required to be obtained; based on the known initial position of each node in the network, the nodes in the whole network can be reasonably clustered by using a distributed clustering method to obtain clusters with required number, and three nodes which are relatively uniformly distributed are selected from each cluster to serve as anchor nodes; and selecting anchor nodes needing to be additionally selected near the boundary of the node deployment area, thereby obtaining an anchor node set with reasonable distribution in the whole network. A large number of computer simulations and actual experiments prove that due to reasonable cluster distribution, uniform distribution of selected nodes in each cluster in corresponding clusters and the like, the anchor node selection method provided by the invention can distributively select the anchor nodes with reasonable distribution in a mobile self-organizing network with known initial positions of the nodes, and is favorable for improving the network performance.
Drawings
Fig. 1 is a general architecture diagram of an anchor node selection method in a mobile ad hoc network;
fig. 2 is a diagram showing an example of distribution of anchor nodes obtained in the anchor node selection method in the mobile ad hoc network;
fig. 3 is a comparison of positioning accuracy results obtained when cooperative positioning is performed on user nodes in a network by using an unparameterized belief propagation algorithm based on anchor node distribution, anchor node uniform distribution and anchor node random distribution obtained by an anchor node selection method in a mobile self-organizing network.
Detailed Description
The following provides a detailed description of the preferred embodiments of the present invention with reference to the accompanying drawings.
As shown in fig. 1, the method for selecting an anchor node in a mobile ad hoc network of the present invention includes the following steps:
step one, determining the number of clusters (three anchor nodes need to be selected in each cluster) which need to be formed in the mobile self-organizing network and the number of anchor nodes which need to be additionally selected according to the number of required anchor nodes, and reasonably clustering all nodes in the network in a distributed manner to obtain the required number of clusters;
secondly, based on the clustering condition obtained in the first step, in each cluster, the cluster head node selects some nodes with moderate distance to the clustering center of mass according to the distance value condition between each node and the clustering center of mass in the cluster, and the selected nodes are used as a selected anchor node candidate set in the cluster;
step three, according to the anchor node candidate sets corresponding to the clusters obtained in the step two, aiming at each cluster, selecting three nodes which are distributed most closely to a regular triangle from the corresponding anchor node candidate sets as the selected anchor nodes in the cluster by the cluster head nodes;
and step four, if the anchor nodes needing to be additionally selected exist, the nodes which are positioned at the boundary of the node deployment region and are closest to the boundary of the deployment region in each cluster (excluding the anchor nodes selected in the step three) need to be collected through communication among the cluster head nodes of each cluster in the network, and the anchor nodes needing to be additionally selected are randomly selected from the nodes, so that the specified number of the anchor nodes with reasonable distribution in the whole network are obtained.
The first step comprises the following steps:
step ten, the total number of nodes in the mobile self-organizing network is N, and the anchor node number N is selected according to the requirementaCalculating the number N of clusters to be formedclusterAs shown in the following formula (1), wherein
Is composed of
Rounded down values of (d); simultaneously calculating the number N 'of anchor nodes needing additional selection'aAs shown in the following formula (2);
Na′＝Na-3×Ncluster......(2)
step eleven, clustering nodes in the mobile ad hoc network by using a similarity propagation clustering algorithm, wherein the clustering algorithm is a distributed algorithm and only depends on similarity values between different nodes and similarity values of the nodes, a negative value of a Euclidean distance (hereinafter referred to as a distance) between a node i and a node j (i, j is 1.., N, j is not equal to i) is used as the similarity value between the node i and the node j, and the distance between the node i and the node j is shown as the following formula (3):
wherein, the two-dimensional position P of the initial time node iiAs shown in the following formula (4),
Pi＝[xi,yi]T......(4)
the similarity between the node i and the node j is shown in the following equation (5),
s(i,j)＝-dij.......(5)
for the node i, the distance set D between the node i and other nodes is obtained by respectively carrying out distance measurement communication with other nodes in the networki，dmedianIs DiThe similarity of the node i itself is set as shown in the following formula (6),
s(i,i)＝-dmedian·fscale,......(6)
wherein f isscaleBy adjusting f for the multiplication factorscaleChanging the value of s (i, i), and further obtaining clusters with different numbers in the clustering process;
step twelve, in the process of clustering the nodes, clusters are formed and cluster head nodes in each cluster are obtained at the same time, the selection process of the anchor nodes in each cluster is controlled by the cluster head nodes of the cluster, and the anchor nodes needing to be additionally selected are obtained through communication among the cluster head nodes of each cluster.
The second step comprises the following steps:
twenty, based on the clustering condition obtained in the first step, aiming at the cluster Cm(m＝1,...,Ncluster) Wherein the kth node is represented as Cmk(k＝1,...,Nm)，NmIs CmThe number of middle nodes; the centroid of the cluster is om(ii) a The cluster head node collects the initial positions of all nodes in the cluster, and the initial positions are calculated according to the following formula (7) and are shown in the following formula (8);
twenty-one, CmCluster head node of (1) calculating each node C in a clustermkAnd omThe value of the distance between dkoAnd form a set Do，dmedAnd dmaxAre respectively DoMedian and maximum values of;
twenty-two, extracting DoThe distance values in the interval shown in the following formula (9), and the node set corresponding to the distance values is CmAnchor node candidate set S in (1)m。
(dmed,(dmax+dmed)/2)......(9)
The third step comprises the following steps:
thirty step, according to the cluster C obtained in the second stepm(m＝1,...,Ncluster) Anchor node candidate set SmCalculating SmEvery two nodes in
The distance between
Step thirty one, from SmIn selecting three different nodes
And
the area of the triangle formed by the position distribution is calculated by the Helen formula as shown in the following formula (10),
wherein p is represented by the following formula (11),
is a node
And node
The distance between them;
step thirty-two, assuming a triangle, the distances from its centroid to its three vertices are assigned as
And
(
is a node
And CmCenter of mass omThe distance therebetween), the triangle reaches its maximum area when it becomes a regular triangle, and the maximum area is calculated as shown in the following equation (12);
step thirty-three, in order to evaluate the node
And
the degree of the formed triangle close to the regular triangle, and the similarity of the regular triangle is defined as the following formula (13);
step thirty-four, repeating the step eleven, the step twelve and the step thirteen until S is detectedmAnd traversing all the nodes by taking three nodes as combinations to obtain a node combination with the maximum regular triangle similarity, wherein the three nodes are the cluster CmThe selected anchor node;
and step thirty-five, setting m to be m +1, and repeating the step eleven, the step twelve, the step thirteen and the step fourteen until all clusters complete the selection of the anchor nodes.
The fourth step comprises the following steps:
step forty, if N is obtained in step tenaIf not, continuing to perform the step forty one and the step forty two, otherwise, completing the selection process of the anchor node in the mobile self-organizing network;
fourthly, collecting the node which is closest to the boundary of the node deployment area in each cluster at the boundary of the node deployment area to the cluster head node corresponding to the cluster close to the central position of the deployment area through communication among the cluster head nodes corresponding to the clusters;
step forty-two, the cluster head node randomly selects N from the collected nodesa' anchor nodes, to this point, the anchor node selection process in the mobile ad hoc network is completed.
In the mobile self-organizing network considered by the invention, the initial positions of all nodes are known, and firstly, the cluster number required to be formed in the network and the number of anchor nodes required to be additionally selected are planned according to the number of the required anchor nodes; the nodes in the network carry out distance measurement communication with each other to obtain the distance between the nodes, and the negative value of the distance between the nodes is taken as the similarity between the nodes; clustering nodes in the network by using a similarity propagation clustering algorithm, wherein the required clustering number can be obtained in the clustering process through reasonable assignment of the self similarity of the nodes, and meanwhile, cluster head nodes in each cluster can be obtained in the clustering process, and each cluster head node needs to be responsible for the selection process of an anchor node in the cluster in which the cluster head node is positioned, and the like; aiming at each cluster formed in the network, the cluster head nodes collect the initial positions of the nodes in the cluster, and the nodes with moderate distance and mass center can be selected from the nodes by calculating the distance between the nodes and the cluster mass center to form an anchor node candidate set in the cluster; further, three nodes distributed closest to a regular triangle are selected from the anchor node candidate set in each cluster as the anchor nodes selected from the cluster; if the anchor nodes needing to be additionally selected exist, the cluster head nodes corresponding to each cluster are communicated, the nodes (excluding the selected anchor nodes in each cluster) which are closest to the boundary of the deployment region in each cluster at the boundary of the node deployment region are collected, and the anchor nodes needing to be additionally selected are randomly selected from the nodes; and finishing the selection process of the anchor node in the mobile self-organizing network.
More specifically, in a preferred embodiment of the present invention, a mobile ad hoc network with a positioning user node as a main service is considered, and an anchor node is selected as a reference node of the user node during a cooperative positioning process, and the present invention is implemented by the following technical solution, and includes the following steps:
fifthly, calculating the number of clusters required to be formed in the network and the number of anchor nodes required to be additionally selected according to the number of the anchor nodes required to be selected; the mobile ad hoc network considered in this embodiment includes 150 nodes, the nodes are deployed in a square area of 100m × 100m, and the number of anchor nodes to be selected is 19, so that an on-network is requiredForming 6 clusters (3 anchor nodes are selected in each cluster) and 1 anchor node needing additional selection in the network, carrying out ranging communication among nodes in the network, using a similarity propagation clustering algorithm, taking a negative value of a distance between the nodes as the similarity among corresponding nodes, and simultaneously giving each node reasonable self-similarity (f)scale4) to obtain the required 6 clusters;
fifthly, acquiring an anchor node candidate set in each cluster. For each cluster Cm(m ═ 1.., 6), C was calculatedmCenter of mass omThen calculate CmEach node in the node and omOf the distance between the two, obtaining a set of distances DoAnd obtaining DoMiddle value of dmedAnd a maximum value dmaxSelecting those with omIs at a distance of (d)med,(dmax+dmed) /2) nodes in the interval as CmThe anchor node candidate set in (1);
and fifthly, selecting the anchor nodes in each cluster. For each cluster Cm(m 1.., 6), and corresponding anchor node candidate set SmEvery three nodes in the group form a combination, and a node combination with the distribution closest to a regular triangle is selected, so that the three nodes in the combination are CmSelecting an anchor node;
in the embodiment, the nodes closest to the boundary of the node deployment region in each cluster at the boundary of the node deployment region (excluding the anchor nodes selected in the step three) are collected, and one node is randomly selected from the collected nodes as the additionally selected anchor node, so that the node closest to the left boundary of the deployment region is selected as the anchor node in the embodiment, the anchor node selection process in the mobile ad hoc network is completed, and fig. 2 illustrates the distribution of the anchor nodes obtained in the preferred embodiment and each cluster formed in the network, wherein, "○" represents a user node, and "▲" represents the selected anchor node, and each cluster is surrounded by a dotted line and a deployment region boundary, and as can be seen from the figure, the distribution of the anchor nodes selected in the preferred embodiment is relatively uniform in the whole deployment region.
In order to evaluate the performance of the anchor node selected by the anchor node selection method in the mobile ad hoc network in the present embodiment, an extensively studied cooperative positioning algorithm, that is, an unparameterized belief propagation algorithm, is selected as a positioning algorithm for the user node, and the positioning error condition of all the user nodes in the entire network is used as a performance index, where the positioning error is represented by Root Mean Square Error (RMSE), and the RMSE is defined as the following formula (14),
wherein N isaThe number of user nodes in the network; saIs a collection of user nodes in the network; x is the number ofaFor a user node naThe actual position of (a);
for a user node naEstimated positions obtained in a cooperative positioning process.
Fig. 3 lists the situation of Cumulative Distribution (CDF) of positioning errors that can be achieved when a non-parametric belief propagation algorithm is used to position user nodes in a network under the condition of 200 samples, where anchor node distribution, anchor node random distribution, and anchor node uniform distribution are obtained by the method provided in the present invention. It can be seen from the figure that, compared with the situation that anchor nodes are randomly distributed, the performance of the non-parametric belief propagation algorithm in terms of positioning accuracy when the anchor nodes are distributed based on the method provided by the present invention is close to the positioning accuracy performance when the anchor nodes are uniformly distributed, and the uniform distribution of the anchor nodes can be considered as the optimal distribution condition of the anchor nodes, so that the method provided by the present invention can select reasonable anchor node distribution for a mobile ad hoc network using positioning user nodes as main services, and improve the performance of the positioning algorithm in terms of positioning accuracy.
The above embodiments are described in further detail to solve the technical problems, technical solutions and advantages of the present invention, and it should be understood that the above embodiments are only examples of the present invention and are not intended to limit the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (4)
1. A method for selecting an anchor node in a mobile ad hoc network is characterized by comprising the following steps:
determining the number of clusters required to be formed in the mobile self-organizing network and the number of anchor nodes required to be additionally selected according to the required number of the anchor nodes, and reasonably clustering all nodes in the network in a distributed manner to obtain the required number of clusters;
secondly, based on the clustering condition obtained in the first step, in each cluster, the cluster head node selects some nodes with moderate distance to the clustering center of mass according to the distance value condition between each node and the clustering center of mass in the cluster, and the selected nodes are used as a selected anchor node candidate set in the cluster;
and selecting some nodes with moderate distance to the clustering centroid aiming at each cluster formed in the network, wherein the cluster head nodes collect the initial positions of the nodes in the cluster, and selecting the nodes with moderate distance to the centroid from the nodes by calculating the distance between the nodes and the clustering centroid to form an anchor node candidate set in the cluster.
Step three, according to the anchor node candidate sets corresponding to the clusters obtained in the step two, aiming at each cluster, selecting three nodes which are distributed most closely to a regular triangle from the corresponding anchor node candidate sets as the selected anchor nodes in the cluster by the cluster head nodes;
and step four, if anchor nodes needing to be additionally selected exist, collecting the nodes which are closest to the boundary of the deployment area in each cluster at the boundary of the node deployment area through communication among cluster head nodes of each cluster in the network, and randomly selecting the anchor nodes needing to be additionally selected from the nodes, so that the anchor nodes which are in the specified number and reasonably distributed in the whole network are obtained.
The first step comprises the following steps:
step ten, the total number of nodes in the mobile self-organizing network is N, and the anchor node number N is selected according to the requirementaAnd calculating the number of clusters to be formed as shown in the following formula:
wherein
Is composed of
Rounded down values of (d); and simultaneously calculating the number of anchor nodes needing to be additionally selected as follows: n is a radical ofa′＝Na-3×Ncluster；
Step eleven, clustering nodes in the mobile ad hoc network by using a similarity propagation clustering algorithm, wherein the clustering algorithm is a distributed algorithm and only depends on similarity values between different nodes and similarity values of the nodes, a negative value of a Euclidean distance between a node i and a node j (i, j is 1.., N, j ≠ i) is used as the similarity value between the node i and the node j, and the distance between the node i and the node j is shown as the following formula:
wherein, the two-dimensional position of the initial time node i is shown as the following formula: pi＝[xi,yi]TThe similarity between node i and node j is shown as follows: s (i, j) ═ dijFor the node i, the distance set D between the node i and other nodes is obtained by respectively carrying out distance measurement communication with other nodes in the networki，dmedianIs DiThe similarity of the node i itself is set as follows: s (i, i)＝-dmedian·fscaleWherein, fscaleBy adjusting f for the multiplication factorscaleChanging the value of s (i, i), and further obtaining clusters with different numbers in the clustering process;
step twelve, in the process of clustering the nodes, clusters are formed and cluster head nodes in each cluster are obtained at the same time, the selection process of the anchor nodes in each cluster is controlled by the cluster head nodes of the cluster, and the anchor nodes needing to be additionally selected are obtained through communication among the cluster head nodes of each cluster.
2. The method of claim 1, wherein the second step comprises the steps of:
twenty, based on the clustering condition obtained in the first step, aiming at the cluster Cm(m＝1,...,Ncluster) Wherein the kth node is represented as Cmk(k＝1,...,Nm)，NmIs CmThe number of middle nodes; the centroid of the cluster is om(ii) a The cluster head node collects the initial positions of all nodes in the cluster, and the initial positions are shown according to the following formula:
(ii) a Calculate the formula
；
Twenty-one, CmCluster head node of (1) calculating each node C in a clustermkAnd omThe value of the distance between dkoAnd form a set Do，dmedAnd dmaxAre respectively DoMedian and maximum values of;
twenty-two, extracting DoIs represented by the following formula: (d)med,(dmax+dmed) /2) interval distance values, the node set corresponding to these distance values is CmAnchor node candidate set S in (1)m。
3. The method of claim 1, wherein the third step comprises the steps of:
thirty step, according to the cluster C obtained in the second stepm(m＝1,...,Ncluster) Anchor node candidate set SmCalculating SmEvery two nodes in
The distance between
；
Step thirty one, from SmIn selecting three different nodes
And
the area of the triangle formed by the position distribution is calculated by the Helen formula as follows:
wherein p is represented by the following formula:
，
is a node
And node
The distance between them;
step thirty-two, the distances from the center of mass to the three vertexes of a triangle are respectively assignedHas a value of
And
then the triangle reaches its maximum area when it becomes a regular triangle, which is calculated as follows:
；
step thirty-three, in order to evaluate the node
And
the degree of the formed triangle approaching to the regular triangle defines the similarity of the regular triangle as follows:
；
step thirty-four, repeating the step eleven, the step twelve and the step thirteen until S is detectedmAnd traversing all the nodes by taking three nodes as combinations to obtain a node combination with the maximum regular triangle similarity, wherein the three nodes are the cluster CmThe selected anchor node;
and step thirty-five, setting m to be m +1, and repeating the step eleven, the step twelve, the step thirteen and the step fourteen until all clusters complete the selection of the anchor nodes.
4. The method of selecting an anchor node in a mobile ad hoc network according to claim 1, wherein said fourth step comprises the steps of:
fortieth, N obtained in step tenaIf' is not 0, proceed to step forty-one and step forty-two, otherwise, finish moving the self-organizing network up to this pointAn anchor node in network selection process;
fourthly, collecting the node which is closest to the boundary of the node deployment area in each cluster at the boundary of the node deployment area to the cluster head node corresponding to the cluster close to the central position of the deployment area through communication among the cluster head nodes corresponding to the clusters;
step forty-two, the cluster head node randomly selects N from the collected nodesa' anchor nodes, to this point, the anchor node selection process in the mobile ad hoc network is completed.
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