阅读说明：本技术 一种多频分层架构无线自组织网络的蚁群分簇方法 (Ant colony clustering method of multi-frequency layered architecture wireless self-organizing network ) 是由 许豪 邵艳玲 单平平 郭俊颖 曹蕾 陈可 张政 刘玉宏 张岩 王耀宽 刘黎明 于 2021-07-23 设计创作，主要内容包括：本发明公开了一种多频分层架构无线自组织网络的蚁群分簇方法,涉及无限移动通讯技术领域,包括包括初始化网络和构建簇,其特征在于：所述初始化网络包括以下步骤,步骤1：初始化；步骤2：计算节点可靠度；步骤3：计算节点相对移动度；步骤4：计算信息素。本发明通过节点可靠度的计算,节点相对移动度的计算和信息素的计算,选择利于建簇的节点,来提高多频分层架构无线自组织网络的分簇效率,不仅为快速构建多频分层无线自组织网络提供保证,而且提高无线自组织网络的网络通信质量。(The invention discloses an ant colony clustering method of a multi-frequency layered architecture wireless self-organizing network, which relates to the technical field of wireless mobile communication, and comprises the steps of initializing the network and constructing clusters, and is characterized in that: the initialization network comprises the following steps, step 1: initializing; step 2: calculating the reliability of the node; and step 3: calculating the relative mobility of the nodes; and 4, step 4: and calculating the pheromone. According to the method, the nodes which are beneficial to cluster building are selected through the calculation of the node reliability, the calculation of the relative mobility of the nodes and the calculation of the pheromone, so that the clustering efficiency of the multi-frequency hierarchical wireless self-organizing network is improved, the guarantee is provided for quickly building the multi-frequency hierarchical wireless self-organizing network, and the network communication quality of the wireless self-organizing network is improved.)

1. An ant colony clustering method of a multi-frequency layered architecture wireless self-organizing network comprises network initialization and cluster construction, and is characterized in that: the initialization of the network comprises the following steps,

step 1: initializing, allocating sortable IDs to each node, setting the states of all nodes to be unallocated, setting interval time delta t, and enabling the sortable IDs not to be repeated;

step 2: calculating the reliability of the node, firstly selecting an arbitrary node i, then selecting a neighbor node j of the node, sending the adjacency list of the node i to the node j, selecting any node from the adjacency list of the node i by the node j, then sending a hello data packet to the node through the node i, counting the number of the forwarding data packets of the node i, and calculating the reliability s of the node i_i；

And step 3: calculating the relative mobility of the node, sending a geographic position information request instruction to a neighbor node by the node i, replying the geographic position information to the node i after the neighbor node receives the request, storing the received geographic position information by the node i, and calculating a node relative mobility value m by the node i through a formula after n delta t times_i；

And 4, step 4: calculating pheromone, calculating the reliability, relative mobility, relative node degree and residual energy of the node i, and calculating the node pheromone tau through a formula_i。

2. The ant colony clustering method for the multi-frequency hierarchical wireless ad hoc network according to claim 1, wherein: the construction of the cluster comprises the following steps,

step A: selecting any node i in the network as an initial node, and sending a forward data sequence { seq, ID to a neighbor node_iSeq is the data sequence number, ID_iIs a sequence of nodes i;

and B: when the node j receives the forward data sequence in the step A, the node j immediately replies a backward data sequence { seq, ID to the node i_i，ID_j，τ_j，hops_ij}，ID_jIs a nodeSerial number of j, τ_jPheromones, hoss, for node j_ijFor the number of hops from node j to node i, node j simultaneously sends hops_ijAdded to the forward data sequence, the modified forward data sequence is { seq, ID_i，hops_ijAfter the forward data sequence is modified, the node j sends the modified forward data sequence to the neighbor node of the node j;

and C: all nodes repeat the step B until the delta t time;

step D: after the delta t time in the step C, dividing all nodes with hop number hoss less than or equal to r in the received backward data sequence into a cluster by the initial node in the step A, selecting a cluster head node according to the size of each node pheromone, and sending member node information in the cluster to a cluster head;

step E: repeating the step A, B, C, D, and sequentially changing the states of all nodes in the initial network in the step a, thereby completing network clustering.

3. The ant colony clustering method for the multi-frequency hierarchical wireless ad hoc network according to claim 1, wherein: said forward data sequence { seq, ID_iSeq ID No. seq_iGenerated by each node according to the sequence of natural numbers, and numbered by the node i_iIs a non-repeating natural number and is assigned when the network is initialized.

4. The ant colony clustering method for the multi-frequency hierarchical wireless ad hoc network according to claim 1, wherein: the backward data sequence comprises a sequence number seq_iNode i number id_iNeighbor node j number id_jNeighbor node pheromone τ_jHop count hoss of node i to the neighbor node_ij。

5. The ant colony clustering method for the multi-frequency hierarchical wireless ad hoc network according to claim 4, wherein: the initial value of the hop count is 1 and is automatically increased by one through a node.

6. The ant colony clustering method for the multi-frequency hierarchical wireless ad hoc network according to claim 2, wherein: the node reliability s_iThe calculation formula is as follows:

recv_num_irepresents the number of data packets, send _ num, received by node i in time interval t and to be forwarded_iRepresenting the number of data packets actually transmitted at time interval t.

7. The ant colony clustering method for the multi-frequency hierarchical wireless ad hoc network according to claim 2, wherein: the relative nodal degree delta_iThe calculation formula is as follows:

wherein d is_iIs a degree of node, ω₁Is inter-cluster bandwidth, omega₂Is the bandwidth in the cluster and N is the number of nodes.

8. The ant colony clustering method for the multi-frequency hierarchical wireless ad hoc network according to claim 2, wherein: relative mobility m of the node_iThe calculation formula is as follows:

wherein the content of the first and second substances,the distance from a node i to a node j at time t is defined, where j ═ {1,2, 3.. multidata, n } is a neighbor node of the node i, and n is the number of neighbor nodes of the node i.

9. The ant colony clustering method for the multi-frequency hierarchical wireless ad hoc network according to claim 2, wherein: the pheromone tau_jCalculating the cluster head according to the following formula:

wherein s is_iAs node reliability, e_{i_rem}To node residual energy, e_{i_init}Is the initial energy of the node, delta_iIs a relative node degree, m_iIs the relative mobility of the nodes. c. C₁，c₂，c₃，c₄Is the correlation coefficient of each item of data.

Technical Field

The invention relates to the technical field of wireless mobile communication, in particular to an ant colony clustering method of a multi-frequency layered architecture wireless self-organizing network.

Background

The wireless self-organizing network is internally provided with no central node, no fixed network special equipment such as a router, a gateway and the like, and the network node not only can receive and transmit data, but also has a routing function. By forwarding data between nodes, multi-node communication can be realized. However, energy of each node is limited, and if each node receives and transmits data out of order, network congestion is easily caused, and communication efficiency of the whole wireless ad hoc network is reduced.

In order to improve the communication efficiency of the wireless ad hoc network, the nodes in the network are clustered. Each cluster is composed of a plurality of network nodes, wherein each network node comprises a cluster head node and a plurality of member nodes in the cluster. The cluster head node is directly communicated with the member nodes in the cluster; communication between member nodes in the cluster needs to be realized through cluster head forwarding. The cluster heads of each cluster can adopt the same frequency band for communication to form a virtual backbone network, thereby forming a first layer network. The cluster head nodes and the member nodes in the cluster can communicate by adopting another frequency band to form a communication subnet in the cluster to form a second layer network. Through clustering, a multi-frequency layered architecture of the wireless self-organizing network can be realized. This may limit the transmission of portions of data over the wireless ad hoc network to within a single cluster. Network congestion caused when a large amount of data is transmitted on the network is avoided.

Therefore, multiple multi-frequency layering is adopted at present, and as can be known from the prior art, the existing multi-frequency layered architecture wireless self-organizing network cannot select nodes which are beneficial to cluster building in terms of node selection to build clusters, so that on one hand, the clustering efficiency of the multi-frequency layered architecture wireless self-organizing network is low, and on the other hand, the constructed clusters still have the phenomena of poor network communication quality and network blockage; therefore, the invention provides an ant colony clustering method of a multi-frequency layered architecture wireless self-organizing network.

Disclosure of Invention

The present invention provides an ant colony clustering method for a multi-frequency hierarchical wireless ad hoc network, so as to solve the above-mentioned problems in the background art.

In order to achieve the purpose, the invention provides the following technical scheme:

an ant colony clustering method of a multi-frequency layered architecture wireless self-organizing network comprises the steps of initializing the network and constructing clusters, wherein the constructing clusters comprise the following steps,

step A: selecting any node i in the network as an initial node, and sending a forward data sequence { seq, ID to a neighbor node_iSeq is the data sequence number, ID_iIs a sequence of nodes i;

and B: when the node j receives the forward data sequence in the step A, the node j immediately replies a backward data sequence { seq, ID to the node i_i，ID_j，τ_j，hops_ij}，ID_jIs the serial number of node j, τ_jPheromones, hoss, for node j_ijFor the number of hops from node j to node i, node j simultaneously sends hops_ijAdded to the forward data sequence, the modified forward data sequence is { seq, ID_i，hops_ijAfter the forward data sequence is modified, the node j sends the modified forward data sequence to the neighbor node of the node j;

and C: all nodes repeat the step B until the delta t time;

step D: after the delta t time in the step C, dividing all nodes with hop number hoss less than or equal to r in the received backward data sequence into a cluster by the initial node in the step A, selecting a cluster head node according to the size of each node pheromone, and sending member node information in the cluster to a cluster head;

step E: repeating the step A, B, C, D, and sequentially changing the states of all nodes in the initial network in the step a, thereby completing network clustering.

Preferably, the initializing the network comprises the steps of,

step 1: initializing, allocating sortable IDs to each node, setting the states of all nodes to be unallocated, setting interval time delta t, and enabling the sortable IDs not to be repeated;

step 2: calculating the reliability of the node, firstly selecting an arbitrary node i, then selecting a neighbor node j of the node, sending the adjacency list of the node i to the node j, selecting any node from the adjacency list of the node i by the node j, then sending a hello data packet to the node through the node i, counting the number of the forwarding data packets of the node i, and calculating the reliability s of the node i_i；

And step 3: calculating the relative mobility of the node, sending a geographic position information request instruction to a neighbor node by the node i, replying the geographic position information to the node i after the neighbor node receives the request, storing the received geographic position information by the node i, and calculating a node relative mobility value m by the node i through a formula after n delta t times_i；

And 4, step 4: calculating pheromone, calculating the reliability, relative mobility, relative node degree and residual energy of the node i, and calculating the node pheromone tau through a formula_i。

Preferably, said forward data sequence { seq, ID_iSeq ID No. seq_iGenerated by each node according to the sequence of natural numbers, and numbered by the node i_iIs a non-repeating natural number and is assigned when the network is initialized.

Preferably, the backward data sequence includes sequence number seq_iNode i number id_iNeighbor node j number id_jNeighbor node pheromone τ_jHop count hoss of node i to the neighbor node_ij。

Preferably, the initial value of the hop count is 1, and one is automatically added through one node.

Preferably, the node reliability s_iThe calculation formula is as follows:

recv_num_irepresents the number of data packets, send _ num, received by node i in time interval t and to be forwarded_iRepresenting the number of data packets actually transmitted at time interval t.

Preferably, the relative nodal degree δ_iThe calculation formula is as follows:

wherein d is_iIs a degree of node, ω₁Is inter-cluster bandwidth, omega₂Is the bandwidth in the cluster and N is the number of nodes.

Preferably, the relative mobility m of the nodes_iThe calculation formula is as follows:

wherein the content of the first and second substances,the distance from a node i to a node j at time t is defined, where j ═ {1,2, 3.. multidata, n } is a neighbor node of the node i, and n is the number of neighbor nodes of the node i.

Preferably, the pheromone τ is_jCalculating the cluster head according to the following formula:

wherein s is_iAs node reliability, e_{i_rem}To node residual energy, e_{i_init}Is the initial energy of the node, delta_iIs a relative node degree, m_iIs the relative mobility of the nodes. c. C₁，c₂，c₃，c₄Is the correlation coefficient of each item of data.

Compared with the prior art, the invention has the beneficial effects that:

1. by the method, the clustering efficiency of the multi-frequency hierarchical architecture wireless self-organizing network is improved by selecting the nodes which are beneficial to cluster building through the calculation of the reliability of the nodes, the calculation of the relative mobility of the nodes and the calculation of the pheromone, thereby not only providing guarantee for quickly building the multi-frequency hierarchical wireless self-organizing network, but also improving the network communication quality of the wireless self-organizing network.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The embodiment provided by the invention comprises the following steps: an ant colony clustering method of a multi-frequency layered architecture wireless self-organizing network comprises an initialization network and a construction cluster, wherein the initialization network comprises the following steps,

step 1: initializing, allocating sortable IDs to each node, setting the states of all nodes to be unallocated, setting interval time delta t, and enabling the sortable IDs not to be repeated;

step 2: calculating the reliability of the node, firstly selecting an arbitrary node i, then selecting a neighbor node j of the node, sending the adjacency list of the node i to the node j, selecting any node from the adjacency list of the node i by the node j, then sending a hello data packet to the node through the node i, counting the number of the forwarding data packets of the node i, and calculating the reliability s of the node i_iDegree of node reliability s_iThe calculation formula is as follows:

recv_num_irepresents the number of data packets, send _ num, received by node i in time interval t and to be forwarded_iRepresents the number of data packets actually transmitted at time interval t;

the node reliability refers to the success rate of forwarding packet data by the node within a certain time interval. The node reliability reflects the communication quality of the node within a certain period of time. The greater the node reliability is, the better the node communication quality is in the period of time. In addition, the node reliability is also related to the idle degree of the nodes, the more the packets are forwarded within the time interval delta t, the higher the packet loss probability is, the lower the reliability is, the cluster head node reliability is calculated through the formula, in contrast, the cluster head node should select the node with higher reliability, and the node with high reliability is selected, so that the success rate of forwarding the data packet by the multi-frequency hierarchical wireless self-organizing network node is ensured, and the network communication quality of the wireless self-organizing network is improved.

And step 3: calculating the relative mobility of the node, sending a geographic position information request instruction to a neighbor node by the node i, replying the geographic position information to the node i after the neighbor node receives the request, storing the received geographic position information by the node i, and calculating the relative mobility value m of the node by the node i through a formula after n delta t times_i(ii) a Relative mobility m of the node_iThe calculation formula is as follows:

wherein the content of the first and second substances,the distance from a node i to a node j at the time t is defined, wherein j is {1,2, 3.. multidot.n } which is the neighbor node of the node i, and n is the number of the neighbor nodes of the node i;

because the wireless self-organizing network is a dynamic network, the nodes have the characteristic of random movement, if the moving direction of each node is consistent and the moving speed is equal, then the wireless self-organizing network is used for receiving the wireless network informationThe network is in a relatively static state, the influence on the network quality is small, and if the moving speed of a certain node relative to other nodes is high, the topological structure of the whole network is influenced; therefore, a node relative mobility concept is provided, the node relative mobility mainly refers to the speed change condition of the current node relative to the neighbor node within the delta t time interval, and the geographic position information of each node can be acquired through a GPS (global positioning system), a Beidou and other satellite systems, so that the relative mobility m of the node is obtained_iIf the relative mobility m of the current node_iValue greater than relative mobility m of neighboring nodes_iA value indicating that the node moves more intensely with respect to the neighbor node, the node is not suitable as a cluster head node if the relative mobility m of the current node_iValue less than relative mobility m of neighboring nodes_iThe value shows that the node is relatively stable relative to the neighbor node and is suitable for serving as a cluster head node, and the relative mobility m is determined through the formula_iCalculating and selecting the relative mobility m of the nodes_iValue less than relative mobility m of neighboring nodes_iThe nodes of the values are used as cluster head nodes, so that the success rate of constructing the cluster is improved, and the efficiency of constructing the cluster is further improved.

And 4, step 4: calculating pheromone, calculating the reliability, relative mobility, relative node degree and residual energy of the node i, and calculating the node pheromone tau through a formula_i。

In this embodiment: the construction of the cluster comprises the following steps,

step A: selecting any node i in the network as an initial node, and sending a forward data sequence { seq, ID to a neighbor node_iSeq is the data sequence number, ID_iIs a sequence of nodes i;

and B: when the node j receives the forward data sequence in the step A, the node j immediately replies a backward data sequence { seq, ID to the node i_i，ID_j，τ_j，hops_ij}，ID_jIs the serial number of node j, τ_jPheromones, hoss, for node j_ijFor the number of hops from node j to node i, node j simultaneously sends hops_ijAdded to the forward data sequence, modified forwardInto a data sequence of { seq, ID_i，hops_ijAfter the forward data sequence is modified, the node j sends the modified forward data sequence to the neighbor node of the node j;

and C: b, repeating the step B by all the nodes until delta t time, and selecting one of the forward data sequences to generate a backward data sequence when the nodes receive a plurality of forward data sequences with the same seq, and sending the backward data sequence to the initial node;

step D: after the delta t time in the step C, the initial node in the step A divides all nodes with hop number hops less than or equal to r in the received backward data sequence into a cluster, selects a cluster head node according to the size of each node pheromone, sends information of member nodes in the cluster to the cluster head, the cluster head sends a hello beacon to the member in the cluster, the self state is set as head, the member state of the cluster is set as member, and then the cluster head and the member nodes in the cluster do not participate in the clustering process;

step E: repeating the step A, B, C, D, and sequentially changing the states of all nodes in the initial network in the step a, thereby completing network clustering.

In this embodiment: said forward data sequence { seq, ID_iSeq ID No. seq_iGenerated by each node according to the sequence of natural numbers, and numbered by the node i_iIs a non-repeating natural number and is assigned when the network is initialized.

In this embodiment: the backward data sequence comprises a sequence number seq_iNode i number id_iNeighbor node j number id_jNeighbor node pheromone τ_jHop count hoss of node i to the neighbor node_ij。

In this embodiment: the initial value of the hop count is 1 and is automatically increased by one through a node.

In this embodiment: the relative nodal degree delta_iThe calculation formula is as follows:

wherein d is_iIs a degree of node, ω₁Is inter-cluster bandwidth, omega₂Is the bandwidth in the cluster and N is the number of nodes.

In this embodiment: the pheromone tau_jCalculated according to the following formula:

wherein s is_iAs node reliability, e_{i_rem}To node residual energy, e_{i_init}Is the initial energy of the node, delta_iIs a relative node degree, m_iAs degree of relative movement of nodes, c₁，c₂，c₃，c₄A correlation coefficient for each item of data;

the pheromone tau_jPheromone tau, the primary factor for cluster head selection_jReflecting the comprehensive performance of each node, if the current node receives the pheromone tau in the backward data sequence sent by all nodes one hop away from the current node_jThe values are all larger than the pheromone tau of the current node_jIf the value is small, the current node can be used as a cluster head node; if the current node receives the pheromone tau in the backward data sequence sent by all nodes one hop away from the current node_jHaving a value greater than the current node pheromone tau_jThe node of the value, then the current node can be used as the node in the cluster by aiming at the pheromone tau_jAnd (4) calculating to select a cluster head node and a cluster internal node, thereby further improving the cluster building efficiency.

It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.