CN114585047B - Wireless self-organizing network self-adaptive clustering method based on clustering management information - Google Patents
Wireless self-organizing network self-adaptive clustering method based on clustering management information Download PDFInfo
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Abstract
The invention provides a wireless self-organizing network self-adaptive clustering method based on clustering management information, which comprises the following implementation steps: initializing an ad hoc network; each node acquires cluster management information; initial clustering; each node carries out self-adaptive adjustment on own clustering management information; and obtaining a clustering result. According to the invention, clustering management information is designed, so that the respective clustering state, clustering action, cluster head weight and other time-varying characteristics of the nodes are represented, surrounding node clustering state information is perceived through interaction among the nodes, and self-adaptive adjustment is carried out on the clustering state, so that the effect of self-adaptive clustering of the whole network is achieved, and the reliability and timeliness of a cluster structure are improved.
Description
Technical Field
The invention belongs to the technical field of communication, and further relates to a self-adaptive clustering method for improving the reliability and the effectiveness of a wireless self-organizing network in the field of wireless communication.
Background
The wireless ad hoc network (Mobile Ad Hoc Network, MANET) is different from the traditional wireless communication network technology, does not need fixed equipment to support, does not have a base station and a central node, and each node, namely a user terminal, is self-networking, and each user node can transmit or forward data when communication is needed. The wireless self-organizing network breaks through the geographical limitation of the traditional wireless cellular network, can be deployed more quickly, conveniently and efficiently, and is suitable for special communication requirements in some emergency occasions, such as disaster relief, military use and the like.
The traditional self-organizing network organization structure is of a plain equation, functions and positions of nodes in the network are equal, and data transmission in the network depends on node forwarding, but under the large-scale networking and multi-hop range networking scenes, the traditional self-organizing network organization is disordered, the control overhead is high, time slot resources are tense, and the traditional self-organizing network organization structure is difficult to adapt to a large-scale network node scene, so that the scalability is poor. In recent years, a hierarchical network structure is constructed by using a clustering algorithm, so that the application of network bandwidth is optimized, the utilization rate of channels and network performance can be improved, and a high-performance large-scale self-organizing network is possible. Under the outdoor environment, the large-scale distributed networking also faces the severe conditions of node electric quantity limitation, obstacle shielding, node failure and the like, and therefore, higher requirements are put on the reliability and timeliness of the network.
At present, a common clustering algorithm is a self-adaptive clustering algorithm, wherein the clustering algorithm is that a central control node is not responsible for the election work of a cluster head in the cluster head selection process, and the cluster head selection process is self-adaptively completed by nodes according to a uniformly set rule through information interaction among the nodes. The algorithm is characterized in that whether the node self judges whether a certain condition is met or not to determine whether the node self becomes a cluster head or not, the node self has good expansibility, strong self-adaptive capacity and high convergence rate, can adapt to various external conditions, has small control cost consumed by clustering, and is a common algorithm in a hierarchical network in a dynamic clustering low-power consumption self-adaptive clustering layered protocol (Low Energy Adaptive Clustering Hierarchy, LEACH) in the self-adaptive clustering algorithm. However, because the cluster heads selected in each round are randomly selected, the energy of the selected cluster heads is low and the distribution is not uniform enough, which results in unstable network performance and load, and meanwhile, because the cluster heads selected in each round are different, the cluster heads need to reorganize and maintain the cluster domain network, thus increasing the control overhead of the system.
In the patent application of a self-adaptive clustering method and device of a wireless sensor network (patent application number: 202010121038.X, application publication number: CN 111405634A), a self-adaptive clustering method of a wireless sensor network is disclosed in the Chinese spatial technology institute, the characteristic information of a plurality of network nodes to be clustered in the wireless sensor network is determined, the plurality of network nodes are clustered according to the characteristic information to obtain a plurality of clusters, and whether preset re-clustering conditions are met is judged according to real-time information, although the technical problem of poor network service quality performance after clustering is solved, only clustering and merging are considered, but when common member nodes need to leave the clusters, other nodes apply for adding the clusters and the like, the reliability of the network clustering cannot be ensured under a network scene with strong node mobility, and the cost is not controlled, so that the cost is increased sharply under a network scene with large scale.
In the patent application of Beijing university of post, namely an adaptive clustering method based on active threshold setting (patent application number: 201610325841.9, application publication number: CN 105898821A), an adaptive clustering method based on active threshold setting is provided, and the method comprises the steps of firstly arranging neighbor nodes from small to large according to Euclidean distance of each node, then comparing weights of the neighbor nodes with weights of all other neighbor nodes, and selecting whether to set a neighbor node quantity threshold. Although the method can achieve the effect of self-adaptive clustering and has obvious advantages in load balance, the method has the advantages that the weight of the nodes is single in consideration, parameters such as node mobility, node connectivity and the like are not considered, so that the reliability of the cluster structure is lower, the cluster structure is only self-adaptively adjusted along with the distance between the nodes, and the self-adaptive adjustment of the clusters in a fixed control period is not performed, so that the timeliness of the method is lower.
Disclosure of Invention
The invention aims to overcome the defects of the existing wireless self-organizing network clustering method, and provides a wireless self-organizing network self-adapting clustering method based on clustering management information, so that the clustering reliability and timeliness are improved, and meanwhile, the cost caused by clustering is reduced.
In order to achieve the above purpose, the technical scheme of the invention comprises the following steps:
(1) Initializing a wireless self-organizing network:
the initialization includes N nodes z= { Z 1 ,Z 2 ,...,Z n ,...,Z N Wireless ad hoc network, node Z n Cluster head weight of (2) is W n ，Z n Forms a neighbor list S by nodes within a communication radius of (a) n ，Z n The management stage of (1) is divided into start, select and self-adapting, Z n The clustering state of (1) is divided into a start state, a to-be-clustered state, a cluster member state, a cluster head state and a Z state n The clustering actions of (1) are static, clustered fission, clustered merging and cluster head replacement, wherein N is more than or equal to 3, Z n Represents an nth node;
(2) Each node acquires cluster management information:
each node obtains own cluster head weight W n Neighbor list S n And W is taken as n 、S n The management stage, the clustering state and the clustering action are used as own clustering management information, and the management stage, the clustering state and the clustering action in the clustering management information are initialized to be started, started and static;
(3) Initial clustering:
(3a) Each node Z n To oneself S n Each node in the network node (a) sends clustering management information with a management stage as a starting stage, so that interaction of the clustering management information is realized;
(3b) Each node Z n Judging own cluster head weight W n If the cluster weight is smaller than the cluster weight of all other neighbor nodes, adjusting the clustering state of the cluster to be the cluster, and executing the step (3 c), otherwise, executing the step (3 d);
(3c) Node Z with cluster head in cluster state n To oneself S n Each node in the network node (a) sends clustering management information with a management stage being a selection stage, so that interaction of the clustering management information is realized;
(3d) Node Z with cluster state not being cluster head n Judging whether cluster management information with the management stage being the selection stage is received, if so, judging the node Z n The cluster state of (2) is adjusted to be a cluster member, then step (3 e) is executed, otherwise node Z is executed n The clustering state of the cluster is adjusted to be the cluster to be clustered, and the step (4) is executed;
(3e) Node Z with cluster status of cluster members n Judging whether cluster management information with a plurality of management stages as selection stages is received or not, if yes, W is contained in the cluster management information n The smallest cluster head nodes form clusters, then the step (4) is executed, otherwise, the cluster head nodes which are the only and self interaction management stage are the cluster management information of the selection stage form clusters, and then the step (4) is executed;
(4) Each node carries out self-adaptive adjustment on own clustering management information:
(4a) Each node Z n Judging whether the clustering state of the self-body is a cluster head, if so, executing the step (4 b), otherwise, executing the step (4 k);
(4b) Node Z with cluster head in cluster state n Judging whether any node Z exists in the communication range of the self m W of (2) m Less than node Z n W of (2) n If yes, executing the step (4 c), otherwise, executing the step (4 f);
(4c) Node Z with cluster head in cluster state n Judgment of Z m If the Monte Carlo condition is met, executing the step (4 d) if the Monte Carlo condition is met, otherwise, executing the step (4 e);
the method aims at avoiding the phenomenon of frequent cluster head replacement caused by jitter of node weight due to instability of a wireless channel by introducing Monte Carlo judging conditions when the nodes replace the cluster heads and combine the cluster heads, and reducing a lot of unnecessary expenditure.
(4d) Node Z with cluster head in cluster state n Judgment of Z m If the cluster state is the cluster head, executing the step (4 j), otherwise, executing the step (4 e);
(4e) Node Z with cluster head in cluster state n In the Z direction m The transmission management stage is an adaptive stage, and the clustering action is cluster head replacementClustering management information and grouping node Z n The cluster state information of the cluster is adjusted to be a cluster member, and then the step (5) is executed;
(4f) Node Z with cluster head in cluster state n Judging whether the user receives a new cluster-entering application or not, and adding the number of the members in the current cluster to the number of the members in the new cluster to reachIf yes, selecting a node with the lowest cluster head weight in the cluster as a new cluster head, then executing the step (4 g), otherwise, executing the step (4 h);
(4g) Node Z with cluster head in cluster state n Broadcasting cluster management information of which the management stage is an adaptive stage and the clustering action is cluster fission to member nodes in a cluster, and then executing the step (5);
(4h) Node Z with cluster head in cluster state n Judging whether the sum of the number of cluster members of the own cluster and a certain adjacent cluster is smaller thanIf yes, executing the step (4 i), otherwise, executing the step (5);
(4i) Node Z with cluster head in cluster state n Judging whether the cluster head weight of the self cluster head is larger than the cluster head weight of the adjacent cluster head, if so, executing the step (4 j), otherwise, executing the step (5);
(4j) Node Z with cluster head in cluster state n Broadcasting the cluster management information with the management stage being the self-adaptive stage and the clustering action being the cluster combination to the members in the own cluster, adjusting the self-clustering state to be the cluster members, and then executing the step (5);
(4k) Node Z n Judging whether the clustering state of the self-clustering method is a cluster member, if so, executing the step (4 m), otherwise, executing the step (4 s);
(4 m) node Z whose cluster state is a cluster member n Judging whether the self-receiving management stage is a self-adapting stage and the clustering action is the clustering management information replaced by the cluster head, if so, executing the step (4 n), otherwise, executing the step (4 o);
(4 n) node Z whose cluster state is a cluster member n Saving the intra-cluster member information in the cluster head replacement information, and storing Z n The clustering state of the cluster head is adjusted to be the cluster head, and then the step (5) is executed;
(4 o) node Z whose cluster state is a cluster member n Judging whether the self-receiving management stage is a self-adapting stage and the clustering action is clustering management information of clustering fission, if so, executing the step (4 p), otherwise, executing the step (4 r);
(4 p) node Z whose cluster state is a cluster member n Judging whether the cluster head is a new cluster head generated by clustered fission, if so, judging Z n The clustering state of the cluster is adjusted to be the cluster head, then the step (5) is executed, otherwise, the step (4 q) is executed;
(4 q) node Z whose cluster state is a cluster member n Judging whether the node is a neighbor node of a new cluster head or not, if so, Z n Selecting a new cluster to join and adjusting the clustering state of the new cluster to be a cluster to be clustered, and then executing the step (5), otherwise, directly executing the step (5);
(4 r) node Z whose cluster state is a cluster member n Judging whether the clustering management information of which the clustering action is clustering combination is received or not, if yes, judging Z n The clustering state of the cluster is adjusted to be the cluster to be clustered, then the step (5) is executed, otherwise, the step (5) is directly executed;
(4 s) node Z n Judging whether the clustering state of the self-clustering method is to be clustered, if so, executing the step (4 t), otherwise, executing the step (5);
(4 t) the clustering state is the node Z to be clustered n Judging whether nodes with clustering states of cluster heads exist in the neighbor list of the self, if so, executing the step (4 u), otherwise, executing the step (4 v);
(4 u) the clustering state is the node Z to be clustered n Judging whether only one cluster head node exists in the neighbor list, if so, adding the cluster, adjusting the node clustering state of the cluster to be a cluster member, and then executing the step (5), otherwise, selecting the cluster head node with the lowest cluster head weight from a plurality of cluster head nodes, adding the cluster head node, and adding the node Z n Is adjusted to cluster members and then executedA row step (5);
(4 v) the clustering state is the node Z to be clustered n Selecting the cluster head with the lowest weight value from the cluster where the neighbor node is located, then adjusting the node clustering state of the cluster head to be a cluster member, and then executing the step (5);
(5) Obtaining a clustering result:
each node sends updated clustering management information to a neighbor node thereof, and the neighbor node adaptively adjusts the clustering state of the neighbor node according to the received updated clustering management information to obtain the member number smaller than that of the member numberIs included in the plurality of clusters of the plurality of clusters.
Compared with the prior art, the invention has the following advantages:
firstly, the invention realizes the interaction of the cluster management information among the nodes in the initial clustering process, and then perceives and analyzes the change of the cluster states of surrounding nodes in real time through the internal module, thereby adjusting the self-clustering state, ensuring that the cluster structure in the network can be updated in real time, and in the wireless self-organizing network with stronger node mobility, the self-adaptive adjustment of the cluster fracture phenomenon caused by the disconnection of the communication link can be performed in time, and the reliability and the timeliness of the cluster structure are improved.
Secondly, in the process of self-adaptive adjustment of the clustering management information of each node, whether any node in the communication range of the node meets the Monte Carlo condition is judged by the node with the clustering state as the cluster head, and the cluster head replacement or the cluster head combination can be performed only after the condition is met, so that the phenomenon of frequent cluster head replacement caused by jitter of the node weight due to instability of a wireless channel is avoided, and a lot of unnecessary expenses are reduced.
Drawings
FIG. 1 is a flow chart of an implementation of the present invention;
FIG. 2 is a schematic diagram of the structure of a network node of the present invention;
fig. 3 is a flow chart of an implementation of each node for adaptively adjusting its own cluster management information.
Detailed Description
The invention is described in further detail below with reference to the drawings and the specific examples.
Referring to fig. 1, the present invention includes the following steps.
Step 1) initializing a wireless self-organizing network:
the initialization includes 36 nodes z= { Z 1 ,Z 2 ,...,Z n ,...,Z 36 Wireless ad hoc network of each node Z n The structure of (1) is shown in figure 2, and comprises an autonomous analysis module, an autonomous adjustment module and a wireless transmission module; the autonomous analysis module is used for acquiring the clustering management information, judging the clustering state of the autonomous analysis module and comparing the cluster head weight with other nodes; the autonomous adjustment module is used for adjusting the cluster management information; the wireless transmission module is used for interacting cluster management information with other nodes, and node Z n Cluster head weight of (2) is W n ，W n Representing its corresponding node Z n To a degree suitable for functioning as a cluster head node, the W n The lower the more suitable to be used as a cluster head node in a wireless self-organizing network, the calculation formula is as follows:
W n ＝a×D+b×M+c×S
wherein a, b, c are weight factors of different values, and a+b+c=1, d, m, s are clustered weight parameters, Z n Forms a neighbor list S by nodes within a communication radius of (a) n Indicated at node Z n All except Z in communication range n Set of nodes other than Z n The management stage of (1) is divided into start, select and self-adapting, Z n The clustering state of (1) is divided into a start state, a to-be-clustered state, a cluster member state, a cluster head state and a Z state n The clustering actions of (1) are classified into rest, clustering fission, clustering merging and cluster head replacement, wherein Z n Represents an nth node;
step 2) each node acquires cluster management information:
each node obtains own cluster head weight W n Neighbor list S n And W is taken as n 、S n And management stage, clusteringThe state and the clustering action are used as own clustering management information, and a management stage, a clustering state and the clustering action in the clustering management information are initialized to be started, started and static;
step 3) initial clustering:
(3a) Each node Z n To oneself S n Each node in the network node (a) sends clustering management information with a management stage as a starting stage, so that interaction of the clustering management information is realized;
(3b) Each node Z n Judging own cluster head weight W n If the cluster weight is smaller than the cluster weight of all other neighbor nodes, adjusting the clustering state of the cluster to be the cluster, and executing the step (3 c), otherwise, executing the step (3 d);
(3c) Node Z with cluster head in cluster state n To oneself S n Each node in the network node (a) sends clustering management information with a management stage being a selection stage, so that interaction of the clustering management information is realized;
(3d) Node Z with cluster state not being cluster head n Judging whether cluster management information with the management stage being the selection stage is received, if so, judging the node Z n The cluster state of (2) is adjusted to be a cluster member, then step (3 e) is executed, otherwise node Z is executed n The clustering state of the cluster is adjusted to be the cluster to be clustered, and the step (4) is executed;
(3e) Node Z with cluster status of cluster members n Judging whether cluster management information with a plurality of management stages as selection stages is received or not, if yes, W is contained in the cluster management information n The smallest cluster head nodes form clusters, then the step (4) is executed, otherwise, the cluster head nodes which are the only and self interaction management stage are the cluster management information of the selection stage form clusters, and then the step (4) is executed;
the nodes acquire the respective clustering management information respectively and interact the clustering management information of the beginning stage with surrounding nodes to perform initial clustering, so that all the nodes in the wireless self-organizing network are equally divided into three clustering states: the cluster head, the cluster to be clustered and the cluster members are used for carrying out self-adaptive adjustment on cluster management information;
step 4), each node carries out self-adaptive adjustment on own clustering management information, and the implementation steps are shown in fig. 3:
(4a) Each node Z n Judging whether the clustering state of the self-body is a cluster head, if so, executing the step (4 b), otherwise, executing the step (4 k);
(4b) Node Z with cluster head in cluster state n Judging whether any node Z exists in the communication range of the self m W of (2) m Less than node Z n W of (2) n If yes, executing the step (4 c), otherwise, executing the step (4 f);
(4c) Node Z with cluster head in cluster state n Judgment of Z m If the Monte Carlo condition is met, executing the step (4 d) if the Monte Carlo condition is met, otherwise, executing the step (4 e);
(4d) Node Z with cluster head in cluster state n Judgment of Z m If the cluster state is the cluster head, executing the step (4 j), otherwise, executing the step (4 e);
(4e) Node Z with cluster head in cluster state n In the Z direction m Transmitting the clustering management information with the self-adaptive management stage and the clustering action replaced by the cluster head, and transmitting the node Z n The cluster state information of the cluster is adjusted to be a cluster member, and then the step (5) is executed;
(4f) Node Z with cluster head in cluster state n Judging whether a new cluster-entering application is received or not, and 6 members are added to the number of the members in the current cluster, if so, selecting the node with the lowest cluster head weight in the cluster as a new cluster head, and then executing the step (4 g), otherwise, executing the step (4 h);
(4g) Node Z with cluster head in cluster state n Broadcasting cluster management information of which the management stage is an adaptive stage and the clustering action is cluster fission to member nodes in a cluster, and then executing the step (5);
(4h) Node Z with cluster head in cluster state n Judging whether the sum of the cluster member numbers of the self cluster and a certain adjacent cluster is smaller than 6, if so, executing the step (4 i), otherwise, executing the step (5);
(4i) Node Z with cluster head in cluster state n Judging whether the cluster head weight of the cluster head is large or notExecuting the step (4 j) on the cluster head weight of the adjacent cluster head if yes, otherwise executing the step (5);
(4j) Node Z with cluster head in cluster state n Broadcasting the cluster management information with the management stage being the self-adaptive stage and the clustering action being the cluster combination to the members in the own cluster, adjusting the self-clustering state to be the cluster members, and then executing the step (5);
(4k) Node Z n Judging whether the clustering state of the self-clustering method is a cluster member, if so, executing the step (4 m), otherwise, executing the step (4 s);
(4 m) node Z whose cluster state is a cluster member n Judging whether the self-receiving management stage is a self-adapting stage and the clustering action is the clustering management information replaced by the cluster head, if so, executing the step (4 n), otherwise, executing the step (4 o);
(4 n) node Z whose cluster state is a cluster member n Saving the intra-cluster member information in the cluster head replacement information, and storing Z n The clustering state of the cluster head is adjusted to be the cluster head, and then the step (5) is executed;
(4 o) node Z whose cluster state is a cluster member n Judging whether the self-receiving management stage is a self-adapting stage and the clustering action is clustering management information of clustering fission, if so, executing the step (4 p), otherwise, executing the step (4 r);
(4 p) node Z whose cluster state is a cluster member n Judging whether the cluster head is a new cluster head generated by clustered fission, if so, judging Z n The clustering state of the cluster is adjusted to be the cluster head, then the step (5) is executed, otherwise, the step (4 q) is executed;
(4 q) node Z whose cluster state is a cluster member n Judging whether the node is a neighbor node of a new cluster head or not, if so, Z n Selecting a new cluster to join and adjusting the clustering state of the new cluster to be a cluster to be clustered, and then executing the step (5), otherwise, directly executing the step (5);
(4 r) node Z whose cluster state is a cluster member n Judging whether the clustering management information of which the clustering action is clustering combination is received or not, if yes, judging Z n The cluster state of the cluster is adjusted to be the cluster to be clustered, then the step (5) is executed, otherwise, the cluster is straightExecuting the step (5);
(4 s) node Z n Judging whether the clustering state of the self-clustering method is to be clustered, if so, executing the step (4 t), otherwise, executing the step (5);
(4 t) the clustering state is the node Z to be clustered n Judging whether nodes with clustering states of cluster heads exist in the neighbor list of the self, if so, executing the step (4 u), otherwise, executing the step (4 v);
(4 u) the clustering state is the node Z to be clustered n Judging whether only one cluster head node exists in the neighbor list, if so, adding the cluster, adjusting the node clustering state of the cluster to be a cluster member, and then executing the step (5), otherwise, selecting the cluster head node with the lowest cluster head weight from a plurality of cluster head nodes, adding the cluster head node, and adding the node Z n The cluster states of the cluster are adjusted to be cluster members, and then the step (5) is executed;
(4 v) the clustering state is the node Z to be clustered n Selecting the cluster head with the lowest weight value from the cluster where the neighbor node is located, then adjusting the node clustering state of the cluster head to be a cluster member, and then executing the step (5);
the nodes in the three clustering states interact with the clustering management information of other nodes in the self-adaption stage respectively, so that the clustering management information of all the nodes can be self-adaption adjusted according to the change of the surrounding environment. In the processes of cluster merging and cluster breaking, the number of the members in the cluster is always kept to be less than 6 due to the constraint on the number of the members in the cluster, so that the load of each cluster head is more balanced, and the cluster structure is more stable.
Step 5) obtaining clustering results:
each node sends updated clustering management information to the neighbor nodes, so that the nodes of the whole network can adaptively adjust the self-clustering state through the received clustering management information of the neighbor nodes, the effect of self-adaptive clustering of the network is achieved, and the number of members in each cluster is smaller than 6.
Claims (4)
1. The wireless self-organizing network self-adaptive clustering method based on the clustering management information is characterized by comprising the following steps:
(1) Initializing a wireless self-organizing network:
initialization includes N nodes Z 1 ,Z 2 ,...,Z n ,...,Z N Node Z of the wireless ad hoc network of (a) n Cluster head weight of (2) is W n ，Z n Forms a neighbor list S by nodes within a communication radius of (a) n ，Z n The management stage of (1) is divided into start, select and self-adapting, Z n The clustering state of (1) is divided into a start state, a to-be-clustered state, a cluster member state, a cluster head state and a Z state n The clustering actions of (1) are static, clustered fission, clustered merging and cluster head replacement, wherein N is more than or equal to 3, Z n Represents an nth node;
(2) Each node acquires cluster management information:
each node obtains own cluster head weight W n Neighbor list S n And W is taken as n 、S n The management stage, the clustering state and the clustering action are used as own clustering management information, and the management stage, the clustering state and the clustering action in the clustering management information are initialized to be started, started and static;
(3) Initial clustering:
(3a) Each node Z n To oneself S n Each node in the network node (a) sends clustering management information with a management stage as a starting stage, so that interaction of the clustering management information is realized;
(3b) Each node Z n Judging own cluster head weight W n If the cluster weight is smaller than the cluster weight of all other neighbor nodes, adjusting the clustering state of the cluster to be the cluster, and executing the step (3 c), otherwise, executing the step (3 d);
(3c) Node Z with cluster head in cluster state n To oneself S n Each node in the network node (a) sends clustering management information with a management stage being a selection stage, so that interaction of the clustering management information is realized;
(3d) Node Z with cluster state not being cluster head n Judging whether cluster management information with the management stage being the selection stage is received, if so, judging the node Z n The cluster status of (2) is adjusted to be a cluster member, then step (3 e) is executed, otherwiseNode Z n The clustering state of the cluster is adjusted to be the cluster to be clustered, and the step (4) is executed;
(3e) Node Z with cluster status of cluster members n Judging whether cluster management information with a plurality of management stages as selection stages is received or not, if yes, W is contained in the cluster management information n The smallest cluster head nodes form clusters, then the step (4) is executed, otherwise, the cluster head nodes which are the only and self interaction management stage are the cluster management information of the selection stage form clusters, and then the step (4) is executed;
(4) Each node carries out self-adaptive adjustment on own clustering management information:
(4a) Each node Z n Judging whether the clustering state of the self-body is a cluster head, if so, executing the step (4 b), otherwise, executing the step (4 k);
(4b) Node Z with cluster head in cluster state n Judging whether any node Z exists in the communication range of the self m W of (2) m Less than node Z n W of (2) n If yes, executing the step (4 c), otherwise, executing the step (4 f);
(4c) Node Z with cluster head in cluster state n Judgment of Z m If the Monte Carlo condition is met, executing the step (4 d) if the Monte Carlo condition is met, otherwise, executing the step (4 e);
(4d) Node Z with cluster head in cluster state n Judgment of Z m If the cluster state is the cluster head, executing the step (4 j), otherwise, executing the step (4 e);
(4e) Node Z with cluster head in cluster state n In the Z direction m Transmitting the clustering management information with the self-adaptive management stage and the clustering action replaced by the cluster head, and transmitting the node Z n The cluster state information of the cluster is adjusted to be a cluster member, and then the step (5) is executed;
(4f) Node Z with cluster head in cluster state n Judging whether the user receives a new cluster-entering application or not, and adding the number of the members in the current cluster to the number of the members in the new cluster to reachIf yes, selecting the node with the lowest cluster head weight in the clusterThe point is a new cluster head, then the step (4 g) is executed, otherwise, the step (4 h) is executed;
(4g) Node Z with cluster head in cluster state n Broadcasting cluster management information of which the management stage is an adaptive stage and the clustering action is cluster fission to member nodes in a cluster, and then executing the step (5);
(4h) Node Z with cluster head in cluster state n Judging whether the sum of the number of cluster members of the own cluster and a certain adjacent cluster is smaller thanIf yes, executing the step (4 i), otherwise, executing the step (5);
(4i) Node Z with cluster head in cluster state n Judging whether the cluster head weight of the self cluster head is larger than the cluster head weight of the adjacent cluster head, if so, executing the step (4 j), otherwise, executing the step (5);
(4j) Node Z with cluster head in cluster state n Broadcasting the cluster management information with the management stage being the self-adaptive stage and the clustering action being the cluster combination to the members in the own cluster, adjusting the self-clustering state to be the cluster members, and then executing the step (5);
(4k) Node Z n Judging whether the clustering state of the self-clustering method is a cluster member, if so, executing the step (4 m), otherwise, executing the step (4 s);
(4 m) node Z whose cluster state is a cluster member n Judging whether the self-receiving management stage is a self-adapting stage and the clustering action is the clustering management information replaced by the cluster head, if so, executing the step (4 n), otherwise, executing the step (4 o);
(4 n) node Z whose cluster state is a cluster member n Saving the intra-cluster member information in the cluster head replacement information, and storing Z n The clustering state of the cluster head is adjusted to be the cluster head, and then the step (5) is executed;
(4 o) node Z whose cluster state is a cluster member n Judging whether the self-receiving management stage is a self-adapting stage and the clustering action is clustering management information of clustering fission, if so, executing the step (4 p), otherwise, executing the step (4 r);
(4 p) clustering state as clusteringNode Z of the member n Judging whether the cluster head is a new cluster head generated by clustered fission, if so, judging Z n The clustering state of the cluster is adjusted to be the cluster head, then the step (5) is executed, otherwise, the step (4 q) is executed;
(4 q) node Z whose cluster state is a cluster member n Judging whether the node is a neighbor node of a new cluster head or not, if so, Z n Selecting a new cluster to join and adjusting the clustering state of the new cluster to be a cluster to be clustered, and then executing the step (5), otherwise, directly executing the step (5);
(4 r) node Z whose cluster state is a cluster member n Judging whether the clustering management information of which the clustering action is clustering combination is received or not, if yes, judging Z n The clustering state of the cluster is adjusted to be the cluster to be clustered, then the step (5) is executed, otherwise, the step (5) is directly executed;
(4 s) node Z n Judging whether the clustering state of the self-clustering method is to be clustered, if so, executing the step (4 t), otherwise, executing the step (5);
(4 t) the clustering state is the node Z to be clustered n Judging whether nodes with clustering states of cluster heads exist in the neighbor list of the self, if so, executing the step (4 u), otherwise, executing the step (4 v);
(4 u) the clustering state is the node Z to be clustered n Judging whether only one cluster head node exists in the neighbor list, if so, adding the cluster, adjusting the node clustering state of the cluster to be a cluster member, and then executing the step (5), otherwise, selecting the cluster head node with the lowest cluster head weight from a plurality of cluster head nodes, adding the cluster head node, and adding the node Z n The cluster states of the cluster are adjusted to be cluster members, and then the step (5) is executed;
(4 v) the clustering state is the node Z to be clustered n Selecting the cluster head with the lowest weight value from the cluster where the neighbor node is located, then adjusting the node clustering state of the cluster head to be a cluster member, and then executing the step (5);
(5) Obtaining a clustering result:
each node sends updated clustering management information to the neighbor node, and the neighbor node carries out self-adaptive adjustment on the clustering state of the neighbor node through the received updated clustering management information to obtain the cluster management informationThe number of the personnel is smaller thanIs included in the plurality of clusters of the plurality of clusters.
2. The wireless self-organizing network self-adaptive clustering method based on clustering management information according to claim 1, wherein: each node Z in step (1) n The system comprises an autonomous analysis module, an autonomous adjustment module and a wireless transmission module; the autonomous analysis module is used for acquiring the clustering management information, judging the clustering state of the autonomous analysis module and comparing the cluster head weight with other nodes; the autonomous adjustment module is used for adjusting the cluster management information; and the wireless transmission module is used for interacting the clustering management information with other nodes.
3. The wireless self-organizing network self-adaptive clustering method based on clustering management information according to claim 1, wherein: node Z described in step (1) n Cluster head weight W of (2) n Representing its corresponding node Z n To a degree suitable for functioning as a cluster head node, the W n The lower the more suitable to be used as a cluster head node in a wireless self-organizing network, the calculation formula is as follows:
W n ＝a×D+b×M+c×S
wherein a, b, c are weight factors of different values, and a+b+c=1, d, m, s are clustered weight parameters.
4. The wireless self-organizing network self-adaptive clustering method based on clustering management information according to claim 1, wherein: the clustering state in the step (4 c) is the node Z of the cluster head n Judgment of Z m Whether the Monte Carlo condition is satisfied, i.e. judge Z m Whether the cluster head can be formed or not, the judging method is as follows:
r＝random(0,1)
p＝min{1，exp(W m -W n )}
where, when result=1 indicates satisfaction, result=0 indicates non-satisfaction, r indicates a random number between [0, 1), exp (·) indicates an exponential function based on a natural number e, and random (0, 1) indicates a function of randomly generating a random number between [0, 1).
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