Routing control method based on node neighbor energy peak value and agglomeration hierarchical clustering

Abstract

The invention discloses a routing control method based on a node neighbor energy peak value and aggregation hierarchical clustering, which can reduce network energy consumption so as to prolong a network life cycle. The method comprises the following specific steps: firstly, clustering sensor nodes through an agglomerated hierarchical clustering algorithm; then, parameters about the radius of the cluster are set in the cluster, the value of the total residual energy of all nodes within a certain distance is solved, and the node corresponding to the maximum value is taken as a cluster head; and finally, selecting the most suitable routing node to which the next hop arrives by adopting a formula screening method according to the distance, and transmitting the data to the base station by multiple jumps. According to the method, the network life cycle is prolonged to a certain extent. In the invention, the cluster head is selected according to the energy of the nearby (within a certain range) points, so that the nodes with high nearby node density and very low nearby energy are not selected, and the communication efficiency is improved.

Description

Technical Field

[0001] The present invention belongs to the field of wireless sensor routing, and is a routing control method based on the energy peak of node neighbors and agglomerative hierarchical clustering. Background Art

[0002] Nowadays, the Internet of Things is developing rapidly, and wireless sensor networks have extensive applications in smart homes, traffic control, military, medical, experimental, environmental monitoring, and waste disposal. However, due to the limited energy, storage capacity, and computing power of nodes, the development of wireless sensor networks is restricted to a certain extent. Summary of the Invention

[0003] In order to solve the problems in the above background art, the present invention proposes a routing control method based on the energy peak of node neighbors and agglomerative hierarchical clustering. In the present invention, the selection of the cluster head is based on the energy of the points near it (within a certain range), so that nodes with a large density of nearby nodes but very low nearby energy will not be selected, improving the communication efficiency.

[0004] To achieve this purpose, the solution of the present invention is as follows:

[0005] A routing control method based on the energy peak of node neighbors and agglomerative hierarchical clustering, comprising the following specific steps:

[0006] (1) By using the agglomerative hierarchical clustering method, the nodes in the network are clustered, and the specific steps are as follows:

[0007] (101) Initialize, with each node as a separate cluster.

[0008] (102) Calculate the Euclidean distance l between all clusters and store it in the distance matrix. For example, the calculation formula for the Euclidean distance l0 between the point (x1, y1, z1) and the point (x2, y2, z2) is as follows:

[0009]

[0010] (103) Among all clusters, merge the two closest clusters.

[0011] (104) Update the distance matrix, where the Euclidean distance between one cluster and another cluster is the average value of the Euclidean distances between all points of this cluster and all points of the other cluster.

[0012] (105) Repeat steps (102)-(104) until the distance between any two clusters is greater than or equal to k times the farthest point in the cluster. Where k is a proportionality coefficient, and 0 < k ≤ 1. The value of k can be adjusted according to actual needs.

[0013] (106) Return the clustering list.

[0014] (2) In each cluster, the cluster head is selected by the peak method. The specific steps are as follows:

[0015] (201) Set parameters λ and R. Where, is the radius of the smallest circle that can contain all points in the cluster. λ is a proportional coefficient and 0<λ≤1, which can be adjusted according to actual needs.

[0016] (202) All nodes in the cluster are set to an unvisited state.

[0017] (203) Randomly select an unvisited node, change the state of the point to visited, and calculate the total residual energy TRES of all nodes within λR (including λR) from the point, and record it as the total residual energy near the point. The formula is:

[0018] TRES(i)=∑RE(p), p∈A(2-2)

[0019] Where TRES(i) is the total residual energy of nodes near point i, RE(p) is the residual energy of point p. A is the set of all nodes in the cluster whose distance to node i is within λR (including λR).

[0020] (204) Repeat step (203) until all nodes in the cluster are visited.

[0021] (205) In each cluster, the node with the maximum value (peak value) of neighbor energy is selected as the cluster head of the cluster.

[0022] (3) Select the route. The steps are as follows:

[0023] (301) Determine whether there is a candidate routing node near the cluster head node. If there is no candidate routing node, directly transmit to the base station without selecting the next hop candidate routing node (no longer executing steps (302)-(303)).

[0024] (302) When there are candidate routing nodes near the cluster head node, the threshold d0 set by the first-order radio model is compared with the distance from the cluster head node to the base station. If the distance from the cluster head node to the base station is less than or equal to the threshold d0, data is directly transmitted to the base station using a single hop method, and no other cluster heads are selected as the next hop routing nodes (step (303) is no longer executed).

[0025] (303) If the distance from the cluster head node to the base station is greater than the threshold d0 and there are candidate routing nodes nearby, the cluster head will establish a selection function f based on the total residual energy TRES, angle θ and distance d of the routing nodes nearby, and then calculate the selection function value of each nearby routing node, and select the node with the largest selection function value as the next hop routing node. The established selection function is:

[0026]

[0027] Where cosθ is the cosine value of the angle between the line connecting the current node and the base station and the line connecting the current node and the candidate node, d s is the distance between the candidate routing node and the base station. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a node clustering presentation diagram of the present invention.

[0029] Figure 2 It is a schematic diagram of cluster head selection of the present invention.

[0030] Figure 3 It is a schematic diagram of routing selection of the present invention. DETAILED DESCRIPTION

[0031] The technical solution of the present invention is described in detail below in conjunction with the accompanying drawings.

[0032] A routing control method based on node neighbor energy peak and agglomerative hierarchical clustering includes the following steps:

[0033] Step 1: Cluster the nodes in the network using the agglomerative hierarchical clustering method. The node clustering is shown in the figure below: Figure 1 Shown

[0034] Step 2: In each cluster, select the cluster head by the peak method. The schematic diagram of cluster head selection is as follows: Figure 2 shown.

[0035] Step 3: When selecting the route in the data transmission phase, the distance is combined and the formula screening method is used to jump to the next hop routing node and transmit it back to the base station in a multi-hop or single-hop manner. The route selection is as follows: Figure 3 shown.

[0036] The specific process of step 1 is:

[0037] (101) is initialized, treating each node as a separate cluster.

[0038] (102) Calculate the Euclidean distance l between all clusters and store it in the distance matrix. For example, the Euclidean distance l0 between point (x1, y1, z1) and point (x2, y2, z2) is calculated as follows:

[0039]

[0040] (103) Among all clusters, the two clusters with the closest distance are merged.

[0041] (104) Update the distance matrix, where the Euclidean distance between one cluster and another is the average of the Euclidean distances between all points in one cluster and all points in the other cluster.

[0042] (105) Repeat steps (102)-(104) until the distance between any two clusters is greater than or equal to k times the farthest point in the cluster. Here, k is a proportionality coefficient, and 0 < k ≤ 1. The value of k can be adjusted according to actual needs.

[0043] (106) Return the clustering list.

[0044] The specific process of step 2 is as follows:

[0045] (201) Set parameters λ and R. Among them, R is the radius of the smallest circle that can enclose all points in the cluster. λ is a proportionality coefficient and 0 < λ ≤ 1, which can be adjusted according to actual needs.

[0046] (202) Set all nodes in the cluster to the unvisited state.

[0047] (203) Arbitrarily select an unvisited node, change the status of this point to visited, and calculate the total remaining energy TRES of all nodes whose distance from this point is within λR (including λR), and record it as the total remaining energy near this point. The formula is:

[0048] TRES(i) = ∑RE(p), p ∈ A(2 - 2)

[0049] Among them, TRES(i) is the total remaining energy of the nodes near point i, RE(p) is the remaining energy of point p. A is the set of all in-cluster nodes whose distance from node i is within λR (including λR).

[0050] (204) Repeat step (203) until all nodes in the cluster are visited.

[0051] (205) In each cluster, select the maximum value (peak value) of the node's neighbor energy as the cluster head of this cluster.

[0052] The specific process of step 3 is as follows:

[0053] (301) Determine whether there are candidate routing nodes near the cluster head node. If there are no candidate routing nodes, directly transmit to the base station and no longer select the next-hop candidate routing node (no longer execute steps (302)-(303)).

[0054] (302) When there are candidate routing nodes near the cluster head node, the threshold d0 set by the first-order radio model is compared with the distance from the cluster head node to the base station. If the distance from the cluster head node to the base station is less than or equal to the threshold d0, data is directly transmitted to the base station using a single hop method, and no other cluster heads are selected as the next hop routing nodes (step (303) is no longer executed).

[0055] (303) If the distance from the cluster head node to the base station is greater than the threshold d0 and there are candidate routing nodes nearby, the cluster head will establish a selection function f based on the total residual energy TRES, angle θ and distance d of the routing nodes nearby, and then calculate the selection function value of each nearby routing node, and select the node with the largest selection function value as the next hop routing node. The established selection function is:

[0056]

[0057] Where cosθ is the cosine value of the angle between the line connecting the current node and the base station and the line connecting the current node and the candidate node, d s is the distance between the candidate routing node and the base station.

Claims

1. A routing control method based on node neighbor energy peak and agglomerative hierarchical clustering, characterized by The routing control of the wireless routing sensor is divided into three steps, including clustering, selecting a cluster head, and selecting the next-hop routing node. The steps are as follows: (1) Cluster the nodes in the network through the agglomerative hierarchical clustering method. The specific steps are as follows: (101) Initialize by taking each node as a separate cluster. (102) Calculate the Euclidean distance l between all clusters and store it in the distance matrix. For example, the calculation formula for the Euclidean distance l0 between the point (x1, y1, z1) and the point (x2, y2, z2) is as follows: (103) In all clusters, merge the two closest clusters. (104) Update the distance matrix, where the Euclidean distance between one cluster and another is the average value of the Euclidean distances between all points in this cluster and all points in the other cluster. (105) Repeat steps (102)-(104) until the distance between any two clusters is greater than or equal to k times the farthest point in the cluster. Here, k is the proportionality coefficient, and 0 < k ≤ 1. The value of k can be adjusted according to actual needs. (106) Return the clustering list. (2) Select the cluster head within each cluster through the peak method. The specific steps are as follows: (201) Set the parameters λ and R. Among them, R is the radius of the smallest circle that can enclose all points in the cluster. λ is the proportionality coefficient and 0 < λ ≤ 1, which can be adjusted according to actual needs. (202) Set all nodes in the cluster to the unvisited state. (203) Arbitrarily select an unvisited node, change the state of this point to visited, and calculate the total remaining energy TRES of all nodes whose distance from this point is within λR (including λR). Denote it as the total remaining energy near this point. The formula is: TRES(i) = ΣRE(p), p ∈ A(2 - 2) where TRES(i) is the total remaining energy of the nodes near the i-th point, RE(p) is the remaining energy of the p-th point. A is the set of all in-cluster nodes whose distance from node i is within λR (including λR). (204) Repeat step (203) until all nodes in the cluster are visited. (205) In each cluster, select the maximum value (peak) of the node's neighbor energy as the cluster head of this cluster. (3) Select the route. The steps are as follows: (301) Determine whether there are candidate routing nodes near the cluster head node. If there are no candidate routing nodes, directly transmit to the base station and no longer select the next-hop candidate routing node (no longer execute steps (302)-(303)). (302) When there are candidate routing nodes near the cluster head node, compare the threshold d0 set by the first-order radio model with the distance from the cluster head node to the base station. If the distance from the cluster head node to the base station is less than or equal to this threshold d0, directly transmit data to the base station using the single-hop method and no longer select other cluster heads as the next-hop routing node (no longer execute step (303)). (303) If the distance from the cluster head node to the base station is greater than the threshold d0 and there are candidate routing nodes nearby, the cluster head will establish a selection function f based on the total residual energy TRES, angle θ and distance d of the routing nodes nearby, and then calculate the selection function value of each nearby routing node, and select the node with the largest selection function value as the next hop routing node. The established selection function is: Where cosθ is the cosine value of the angle between the line connecting the current node and the base station and the line connecting the current node and the candidate node, d s is the distance between the candidate routing node and the base station.

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