Wireless sensor network energy consumption balancing method

Abstract

The invention discloses an energy consumption balancing method for a wireless sensor network. The wireless sensor network comprises a plurality of sensor nodes. The energy consumption balancing method comprises the following steps: dividing a plurality of sensor nodes of the wireless sensor network into a plurality of initial clusters; the base station maintains the predicted residual energy of the initial cluster through a cluster state maintenance algorithm based on a prediction mechanism; the base station determines a cluster set to be adjusted according to the predicted residual energy; and the base station notifies the cluster head of each cluster in the to-be-adjusted cluster set to re-cluster, and re-divides a plurality of sensor nodes of the wireless sensor network into a plurality of target clusters so as to balance energy consumption among the plurality of target clusters and realize balance of residual energy of the plurality of target clusters. According to the method, the nodes in the network can be re-divided into a plurality of target clusters without regularly clustering the nodes of the whole network like a traditional inter-cluster energy consumption balancing method, so that the energy of each cluster in the network is balanced, and the energy consumption generated in the inter-cluster energy balancing process is effectively reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless sensor networks, and in particular to a method for balancing energy consumption in wireless sensor networks. Background Art

[0002] In a wireless sensor network based on a distributed clustering protocol, the sensor nodes (i.e., sensors) in the network are divided into multiple clusters according to the physical distance between each other. Each cluster has multiple nodes, and the distance between the nodes is relatively close. During the operation of the clustering protocol, the cluster head is responsible for collecting the monitoring data of all nodes in the cluster, and after fusion, it sends it to the base station near the network through a single-hop or multi-hop communication method, and finally reaches the cloud server for processing. During the operation of the network, since the cluster head undertakes more tasks than other nodes, its energy consumption rate is faster than other nodes. In many application scenarios, sensor nodes are powered by batteries, and battery replacement is extremely inconvenient, which can easily cause some nodes to die prematurely, thus affecting the service life of the entire network.

[0003] In order to maintain energy consumption balance among nodes, the method commonly used in the prior art is as follows: let each node in the cluster take turns to serve as the cluster head to balance the energy consumption among the nodes in the cluster. When the residual energy of the nodes in the cluster is low, let all the nodes in the network be re-clustered, that is, re-divided into clusters, to maintain energy balance among clusters, thereby extending the survival time of the entire network. However, during the whole network re-clustering process, nodes need to communicate with each other frequently, which makes the energy consumption of the nodes higher.

[0004] Based on the above analysis, it can be seen that the inter-cluster energy consumption balancing mechanism in the prior art has the problem of high node energy consumption caused by frequent communication between nodes. Summary of the invention

[0005] In order to overcome the deficiencies of the prior art, the present invention aims to provide a wireless sensor network energy consumption balancing method, which can solve the problem of high energy consumption caused by frequent communication between nodes in the inter-cluster energy consumption balancing mechanism (i.e., timed clustering of nodes in the entire network).

[0006] In order to solve the above problems, the present invention is implemented according to the following scheme:

[0007] A method for balancing energy consumption in a wireless sensor network is provided. The wireless sensor network includes a plurality of sensor nodes. The method for balancing energy consumption includes:

[0008] Dividing a plurality of sensor nodes of the wireless sensor network into a plurality of initial clusters;

[0009] The base station maintains the predicted residual energy of the initial cluster through a cluster state maintenance algorithm based on a prediction mechanism;

[0010] The base station determines a cluster set to be adjusted according to the predicted remaining energy;

[0011] The base station notifies the cluster heads of each cluster in the cluster set to be adjusted to re-cluster, and re-divides the multiple sensor nodes of the wireless sensor network into multiple target clusters to balance the energy consumption among the multiple target clusters, and the residual energy corresponding to the multiple target clusters is balanced.

[0012] Compared with the prior art, the beneficial effects of the wireless sensor network energy consumption balancing method provided by the present invention are as follows: by adjusting only part of the clusters, without the need to regularly cluster the nodes of the entire network as required by traditional inter-cluster energy consumption balancing methods, multiple sensor nodes in the wireless sensor network can be re-divided into multiple target clusters to achieve energy consumption balancing adjustment for each cluster in the network, effectively reducing the energy consumption generated in the process of maintaining energy balance between clusters.

[0013] Optionally, the base station maintains the predicted residual energy of the initial cluster by a cluster state maintenance algorithm based on a prediction mechanism, including:

[0014] When the current round number is less than or equal to ten rounds, the predicted remaining energy corresponding to the initial cluster is not calculated;

[0015] When the current round number is greater than ten rounds, the cluster head of the initial cluster performs statistics on the weighted average query energy consumption of its corresponding cluster set; the cluster set includes the current cluster and the cluster to which the current cluster needs to forward data; the cluster to which the current cluster needs to forward data is the cluster to which the current cluster needs to forward data in the historical time round;

[0016] According to the weighted average query energy consumption, the initial cluster calculates its predicted remaining energy when the current round number is greater than ten rounds.

[0017] Optionally, when the current number of rounds is greater than ten rounds, the cluster head of the initial cluster performs statistics on the weighted average query energy consumption of its corresponding cluster set, including:

[0018] When it is determined that the initial cluster is less than or equal to ten rounds, the cluster head records the round residual energy of each round and the weighted average query frequency of its corresponding cluster set, which is calculated as follows:

[0019] p k =(x1*f1+x2*f2+…+x n *f n ) / n;

[0020] Where k is the time period from the current round number to less than or equal to ten rounds, p kis the weighted average query frequency of the cluster set in the kth round, n is the number of clusters in the cluster set to which the cluster needs to forward data, and f n is the number of times the node of the nth cluster in the cluster set is queried by the user, x n is the weight corresponding to the nth cluster in the cluster set, and the weight is the ratio of the frequency of data of this cluster being forwarded by this cluster to the frequency of data being sent by this cluster in the historical time round;

[0021] According to the round residual energy and the weighted average query frequency, the cluster head of the initial cluster performs statistics on the weighted average query energy consumption of its corresponding cluster set, and the calculation formula is as follows:

[0022] C=(E i-9 -E i ) / (p i +p i-1 +...+p i-9 )

[0023] Where C is the weighted average query energy consumption, E i-9 is the residual energy of the first round in the time period, E i is the remaining energy of the tenth round in the time period, p i ~p i-9 It is the weighted average query frequency of each round within the time period.

[0024] Optionally, the initial cluster calculates its predicted remaining energy according to the weighted average query energy consumption when the current round number is greater than ten rounds, including:

[0025] determining a final round residual energy of the initial cluster in a tenth round within a time period;

[0026] According to the weighted average query energy consumption of the ten historical rounds, the prediction parameters of the linear regression model based on the least squares method are determined, and the calculation formula is as follows:

[0027]

[0028] Where k is the time period from the current round number to less than or equal to ten rounds, C k is the historical weighted average query energy consumption of each initial cluster in the kth round, a and b are prediction parameters;

[0029] A prediction formula is constructed based on the prediction parameters, and its expression is as follows:

[0030]

[0031] Where k is the time period from the current round number to less than or equal to ten rounds, C k is the weighted average query energy consumption predicted by each initial cluster in the kth round, A jis the predicted remaining energy of the cluster in round j (j>i), E i is the remaining energy of the tenth round in the time period, p k is the weighted average query frequency of the cluster set corresponding to this cluster in the kth round;

[0032] The cluster head of the initial cluster calculates the predicted residual energy of each future round through the prediction formula.

[0033] Optionally, the base station determines, according to the predicted remaining energy, a cluster set to be adjusted, including:

[0034] The base station averages the predicted residual energies of the clusters maintained by the base station to obtain an average residual energy;

[0035] The base station determines the to-be-adjusted cluster set according to the predicted remaining energy, the average remaining energy and a preset value.

[0036] Optionally, the base station determines the to-be-adjusted cluster set according to the predicted remaining energy, the average remaining energy and a preset value, including:

[0037] The base station subtracts the preset value from the average remaining energy to obtain a low energy threshold;

[0038] The base station adds the average residual energy and the preset value to obtain a high energy threshold;

[0039] The base station determines the to-be-adjusted cluster set according to the predicted remaining energy, the low energy threshold, and the high energy threshold.

[0040] Optionally, the cluster set to be adjusted includes a low-energy cluster set to be adjusted and a high-energy cluster set to be adjusted;

[0041] The base station determines the to-be-adjusted cluster set according to the predicted remaining energy, the low energy threshold, and the high energy threshold, including:

[0042] The base station determines whether the predicted remaining energies of all initial clusters in the wireless sensor network are higher than or equal to the low energy threshold and lower than or equal to the high energy threshold, if yes, the set of clusters to be adjusted does not exist, otherwise, the set of clusters to be adjusted exists;

[0043] Determine the initial cluster corresponding to the predicted remaining energy lower than the low energy threshold in the wireless sensor network as the low energy cluster set to be adjusted;

[0044] Determine the initial cluster corresponding to the predicted remaining energy in the wireless sensor network that is higher than the high energy threshold as the high energy cluster set to be adjusted;

[0045] The initial clusters corresponding to the predicted remaining energies in the wireless sensor network that are higher than or equal to the low energy threshold and lower than or equal to the high energy threshold are determined as cluster sets that do not need to be adjusted, and the cluster sets that do not need to be adjusted do not need to be clustered again.

[0046] Optionally, when the cluster set to be adjusted is the low-energy cluster set to be adjusted, the base station notifies the cluster head of each cluster in the cluster set to be adjusted to re-cluster, and re-divides the multiple sensor nodes of the wireless sensor network into multiple target clusters, including:

[0047] Determine the cluster with the lowest energy in the set of low-energy clusters to be adjusted as the lowest energy cluster;

[0048] Determine a plurality of clusters that are one hop away from the lowest energy cluster as a first cluster set;

[0049] Re-dividing the plurality of sensor nodes in the first cluster set into a plurality of target clusters having the same number of clusters according to a node clustering strategy in a clustering protocol;

[0050] Repeat the above steps for clusters other than the first cluster set in the low-energy cluster set to be adjusted, until all clusters in the low-energy cluster set to be adjusted are re-divided;

[0051] The remaining unadjusted initial clusters are determined as the target clusters.

[0052] Optionally, when the cluster set to be adjusted is the high-energy cluster set to be adjusted, the base station notifies the cluster head of each cluster in the cluster set to be adjusted to re-cluster, and re-divides the multiple sensor nodes of the wireless sensor network into multiple target clusters, including:

[0053] Determine the cluster with the highest energy in the set of high-energy clusters to be adjusted as the highest energy cluster;

[0054] determining a plurality of clusters that are one hop away from the highest energy cluster as a second cluster set;

[0055] Re-dividing the plurality of sensor nodes in the second cluster set into a plurality of target clusters having the same number of clusters according to a node clustering strategy in a clustering protocol;

[0056] Repeat the above steps for clusters other than the second cluster set in the high energy cluster set to be adjusted, until all clusters in the high energy cluster set to be adjusted are re-divided;

[0057] The remaining unadjusted initial clusters are determined as the target clusters. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 It is a flow chart of the energy consumption balancing method of the present invention;

[0059] Figure 2 It is a schematic diagram of re-clustering the cluster set to be adjusted in the present invention. DETAILED DESCRIPTION

[0060] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0061] When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the attached claims. In the description of the present application, it should be understood that the terms "first", "second", "third", etc. are only used to distinguish similar objects, and do not have to be used to describe a specific order or sequence, nor can they be understood as indicating or implying relative importance. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to the specific circumstances.

[0062] See also Figure 1 As shown, the present invention provides a method for balancing energy consumption in a wireless sensor network, wherein the wireless sensor network includes a plurality of sensor nodes; the method for balancing energy consumption includes:

[0063] S1: Divide multiple sensor nodes of the wireless sensor network into multiple initial clusters, including:

[0064] Firstly, the physical distances between multiple sensor nodes are determined, and then based on a clustering protocol, multiple sensor nodes in a wireless sensor network are divided into multiple initial clusters according to the physical distances, each of which includes multiple sensor nodes with relatively short physical distances.

[0065] S2: The base station maintains the predicted remaining energy of the initial cluster through a cluster state maintenance algorithm based on a prediction mechanism, including:

[0066] Determine the current round number of the wireless sensor network, and determine whether the current round number is greater than ten rounds. When the current round number is less than or equal to ten rounds, the predicted remaining energy corresponding to the initial cluster is not calculated. When the current round number is greater than ten rounds, a cluster state maintenance algorithm based on a prediction mechanism is used to calculate the predicted remaining energy corresponding to the initial cluster. During the operation of the wireless sensor network, the energy consumption of the nodes in the first ten rounds accounts for a very small proportion of the total energy. Therefore, it is considered that the remaining energy of all initial clusters in the wireless sensor network is basically the same, that is, only the predicted remaining energy corresponding to the initial clusters of the eleventh round and subsequent rounds needs to be calculated.

[0067] When the current round number is less than or equal to ten rounds, first determine the round residual energy of the initial cluster in each round before the tenth round. The round residual energy is the actual residual energy information collected by the cluster head of the initial cluster from the member nodes of the local cluster. The cluster head accumulates the actual residual energy of these nodes to obtain the actual residual energy of the initial cluster, which is the round residual energy; then the cluster head of each initial cluster counts the query message broadcast by the base station, because each cluster head can receive the query message and the corresponding path each time the base station sends the query message, so it can count the weighted average query frequency of each cluster in the whole network, and determine the weighted average query frequency of the cluster set corresponding to the initial cluster in each round before the tenth round. The calculation formula is as follows:

[0068] p k =(x1*f1+x2*f2+…+x n *f n ) / n;

[0069] Where k is the time period from the current round number to less than or equal to ten rounds, p k is the weighted average query frequency of the cluster set in the kth round, n is the number of clusters in the cluster set to which the cluster needs to forward data, and f n is the number of times the node of the nth cluster in the cluster set is queried by the user, x n is the weight corresponding to the nth cluster in the cluster set, and the weight is the ratio of the frequency of data of the cluster being forwarded via the cluster to the frequency of data being sent by the cluster in the historical time round.

[0070] According to the round residual energy and weighted average query frequency, the cluster head of the initial cluster counts the weighted average query energy consumption of its corresponding cluster set. The calculation formula is as follows:

[0071] C=(E i-9 -E i ) / (p i +p i-1 +...+p i-9 )

[0072] Where C is the weighted average query energy consumption, E i-9 is the residual energy of the first round in the time period, E i is the remaining energy of the tenth round in the time period, p i ~p i-9 It is the weighted average query frequency of each round in the time period. The cluster set corresponding to the initial cluster includes the current cluster and the cluster to which the current cluster needs to forward data. The cluster to which the current cluster needs to forward data is the cluster to which the current cluster needs to forward data in the historical time round.

[0073] In the field of wireless sensor networks, the popular model for calculating the energy consumption of sensor nodes is as follows:

[0074] The transmission energy consumption of transmitting an L-bit message for d meters is:

[0075]

[0076] The energy consumption of a sensor node receiving an L-bit message is:

[0077] E R (L) = E elec L

[0078] Among them, E T (L,d) is the transmission energy consumption, E R (L) is the receiving energy consumption, L is the size of the data transmitted or received, d0 is the distance threshold between the two nodes of the data transmission, E elec The energy consumption of an electronic device to send or receive one bit of data, ∈ fs With ∈ mp are the energy consumption of free space propagation and multipath propagation, respectively.

[0079] During the operation of a specific clustering protocol, the energy consumption of a cluster in the wireless sensor network mainly includes the following aspects:

[0080] (1) The energy consumption of cluster heads receiving base station broadcast messages, such as user query messages, is calculated as follows:

[0081] E b =E elec L b

[0082] Among them, E b is the energy consumption of cluster head receiving the broadcast message of base station, E elec The energy consumption of an electronic device to send or receive one bit of data, L b The size of the broadcast message.

[0083] (2) The energy consumption of the cluster head collecting monitoring data of all nodes in the cluster, including the cluster head sending notification data to cluster member nodes and cluster member nodes sending monitoring data to the cluster head, is calculated as follows:

[0084]

[0085] Among them, E intra The cluster head collects the energy consumption of all nodes in the cluster, n c is the number of nodes in the cluster, i is the i-th node, p i is the probability that the i-th node sends data in the current round, L i is the size of monitoring data sent by the i-th node, d intra is the average distance from the cluster node to the cluster head, L b2is the size of the notification data sent by the cluster head to the member nodes, E elec The energy consumption of an electrical device to send or receive one bit of data, ∈ fs is the energy consumption for free space propagation.

[0086] (3) The energy consumption of the cluster in sending its own data and forwarding other clusters’ data is calculated as follows:

[0087]

[0088] E relay is the energy consumption of sending data of this cluster and forwarding data of other clusters, Q is the cluster set from which this cluster forwards data, n q is the number of nodes in the cluster set Q, j is the jth node, p j is the probability that the jth node in the cluster set sends data in the current round, L j is the size of monitoring data sent by the i-th node in the cluster set, d inter is the distance between clusters in the cluster set, E elec The energy consumption of an electronic device to send or receive one bit of data, ∈ mp is the energy consumption of multipath propagation, n c is the number of nodes in this cluster, i is the i-th node in this cluster, p i is the probability that the i-th node in the cluster sends data in the current round, L i The size of monitoring data sent by the i-th node in this cluster.

[0089] According to the above three energy consumption expressions of a cluster during the operation of the clustering protocol, it can be seen that E intra With E relay The value is proportional to the weighted average query frequency of the cluster set Q, while other parameters remain basically unchanged when the number of clusters remains unchanged. In addition, considering that there are more nodes in the cluster and the node monitoring data is larger than the query message broadcast by the base station, E relay +E intra Much larger than E b Therefore, when the network condition does not change significantly, the energy consumption of a cluster is proportional to the weighted average query frequency of its corresponding cluster set Q, that is, the prediction formula needs to be determined based on the weighted average query frequency of the cluster set.

[0090] Then, based on the weighted average query energy consumption, the initial cluster calculates its predicted remaining energy when the current round number is greater than ten rounds, including:

[0091] The predicted remaining energy of the initial cluster in the tenth round is determined as the final round remaining energy; according to the round remaining energy corresponding to the tenth round and the weighted average query energy consumption, the initial cluster determines the prediction parameters of the weighted average query energy consumption in each future round based on the linear regression model of the least squares method, and the calculation formula is as follows:

[0092]

[0093] Among them, k is the time period less than or equal to ten rounds from the current round, is the historical weighted average query energy consumption of each initial cluster in the kth round, and a and b are prediction parameters.

[0094] The initial cluster determines the remaining energy of the tenth round as the remaining energy of the final round. After determining the prediction parameters, it can construct a prediction formula for predicting the remaining energy of each future round. The principle of the prediction formula is that the predicted remaining energy of each future round is the final round remaining energy minus the predicted unit query energy consumption of each future round multiplied by the actual weighted query frequency. At the same time, the cluster head of this cluster sends the parameters of the prediction formula to the base station. The expression of the prediction formula is as follows:

[0095]

[0096] Where k is the time period from the current round number to less than or equal to ten rounds, C k is the weighted average query energy consumption predicted by each initial cluster in the kth round, A j is the predicted remaining energy of the cluster in round j (j>i), E i is the remaining energy of the tenth round in the time period, p k is the weighted average query frequency of the cluster set corresponding to this cluster in the kth round.

[0097] Based on the above prediction formula, the base station can obtain the predicted remaining energy of each cluster in the network in each round greater than 10 rounds without communicating with the clusters in the network, thereby reducing the energy consumption of nodes in the network due to communication.

[0098] Further, determining whether the prediction formula for calculating the predicted residual energy of the initial cluster needs to be updated, determining the actual residual energy of the initial cluster in each round when it is greater than ten rounds, the actual residual energy is the node residual energy received by the cluster head of the initial cluster from each member node, and determining the sum of the node residual energy of each member node as the actual residual energy of each cluster, and when the difference between the actual residual energy and the predicted residual energy is greater than a preset threshold, updating the prediction formula, including:

[0099] The final round residual energy is updated to the actual residual energy, that is, the final round residual energy is replaced by the actual residual energy of the latest round; the weighted average query energy consumption is recalculated according to the conditions of the current round and within ten rounds; the cluster head of the initial cluster determines the new prediction parameters according to the recalculated weighted average query energy consumption and the actual remaining energy, and sends the new prediction parameters to the base station; then the base station updates the prediction formula according to the received new prediction parameters. The updating process is the same as the process of constructing the prediction formula mentioned above, which will not be described in detail here.

[0100] S3: The base station determines a set of clusters to be adjusted according to the predicted remaining energy, including:

[0101] First, the base station averages the predicted residual energy of each cluster it maintains to obtain the average residual energy, which is calculated as follows:

[0102]

[0103] Among them, E avg is the average residual energy, E1 is the predicted residual energy of the first initial cluster in the network, E2 is the predicted residual energy of the second initial cluster in the network, and E n is the predicted residual energy of the nth initial cluster in the network, and n is the number of initial clusters in the network.

[0104] Then, the average remaining energy is subtracted from the preset value to obtain a low energy threshold, and the average remaining energy and the preset value are added to obtain a high energy threshold.

[0105] The base station needs to determine whether there are clusters to be adjusted that are lower than the low energy threshold or higher than the high energy threshold in the wireless sensor network. If so, re-clustering is required. If not, re-clustering is not required. That is, it is determined whether it is necessary to perform inter-cluster energy adjustment on the clusters in the network. When the predicted remaining energy gap between the clusters in the network is not large, it is not necessary to perform inter-cluster energy adjustment on the clusters in the network. When the predicted remaining energy gap between the clusters in the network exceeds the set threshold, it is necessary to perform inter-cluster energy adjustment on the clusters in the network to balance the energy consumption between clusters. At this time, only the initial clusters with predicted remaining energy lower than the low energy threshold and the initial clusters with predicted remaining energy higher than the high energy threshold are re-clustered, that is, local inter-cluster energy adjustment.

[0106] When inter-cluster energy adjustment is required, the initial clusters corresponding to the predicted residual energy below the low energy threshold in the wireless sensor network are determined as the low energy cluster set to be adjusted; the initial clusters corresponding to the predicted residual energy above the high energy threshold in the wireless sensor network are determined as the high energy cluster set to be adjusted; the initial clusters in the wireless sensor network except the low energy cluster to be adjusted and the high energy cluster to be adjusted are determined as the cluster set that does not need to be adjusted, and the cluster set that does not need to be adjusted does not need to be re-clustered.

[0107] S4: The base station notifies the cluster heads of each cluster in the cluster set to be adjusted to re-cluster, and re-divides the multiple sensor nodes of the wireless sensor network into multiple target clusters to balance the residual energy corresponding to the multiple target clusters.

[0108] When the cluster set to be adjusted is a low-energy cluster set to be adjusted, the base station notifies the cluster heads of each cluster in the cluster set to be adjusted to re-cluster, and re-divides the multiple sensor nodes of the wireless sensor network into multiple target clusters, including:

[0109] First, the base station determines the cluster with the lowest energy in the low-energy cluster set to be adjusted as the lowest energy cluster, and determines multiple clusters that are one hop away from the lowest energy cluster as the first cluster set, that is, the cluster adjacent to the lowest energy cluster; then, multiple sensor nodes in the first cluster set are re-divided into multiple target clusters with the same number of clusters, and the residual energy between the multiple target clusters obtained after the division is the same, so as to achieve energy balance between clusters; finally, the above steps are repeated for clusters other than the first cluster set in the low-energy cluster set to be adjusted, until all clusters in the low-energy cluster set to be adjusted are re-divided; the remaining unadjusted initial clusters are determined as target clusters.

[0110] When the cluster set to be adjusted is a high-energy cluster set to be adjusted, the base station notifies the cluster heads of each cluster in the cluster set to be adjusted to re-cluster, and re-divides the multiple sensor nodes of the wireless sensor network into multiple target clusters, including:

[0111] First, the base station determines the cluster with the highest energy in the high-energy cluster set to be adjusted as the highest energy cluster, and determines multiple clusters that are one hop away from the highest energy cluster as the second cluster set, that is, the clusters adjacent to the highest energy cluster; then, multiple sensor nodes in the second cluster set are re-divided into multiple target clusters with the same number of clusters, and the residual energy between the multiple target clusters obtained after the division is the same, so as to achieve energy balance between clusters; repeat the above steps for clusters other than the second cluster set in the high-energy cluster set to be adjusted, until all clusters in the high-energy cluster set to be adjusted are re-divided; and the remaining unadjusted initial clusters are determined as target clusters.

[0112] Next, the energy balancing method is further explained in combination with the specific implementation process, as follows:

[0113] See also Figure 2As shown in the figure, each square represents a cluster, and the cluster name in the grid is followed by the predicted remaining energy of each cluster; cluster 4 in the figure is determined as the lowest energy cluster, that is, clusters 3, 4, 5, 8, 9, and 10 are determined as the first cluster set (light-colored area); the first cluster set includes multiple sensor nodes, and according to the physical distance (location information) between the sensor nodes and their corresponding predicted remaining energies, the multiple sensor nodes in the first cluster set are re-divided into multiple target clusters, and the number of clusters before and after the division of the first cluster set remains unchanged, that is, the number of clusters in the first cluster set before the division is 6, and the number of clusters after the division is also 6.

[0114] Cluster 17 in the figure is determined as the highest energy cluster, that is, clusters 11, 12, 13, 16, 17, and 18 are determined as the second cluster set (dark area); the second cluster set includes multiple sensor nodes, and the multiple sensor nodes in the second cluster set are re-divided into multiple target clusters according to the physical distance (location information) between the sensor nodes and their corresponding predicted residual energies. The number of clusters in the second cluster set remains unchanged before and after the division, that is, the number of clusters in the second cluster set before the division is 6, and the number of clusters after the division is also 6.

[0115] The above-mentioned re-dividing of the sensor nodes of the first cluster set and the second cluster set into multiple target clusters is all re-divided according to the node clustering strategy in the clustering protocol, which is the existing technology and will not be described in detail here.

[0116] By adjusting some clusters in a wireless sensor network, energy balance among multiple clusters in the wireless sensor network can be achieved. By adjusting only some clusters, all sensor nodes in the wireless sensor network can be re-divided into multiple clusters without the need to periodically cluster the nodes of the entire network as in traditional inter-cluster energy balance methods. This can reduce the energy consumption generated in the process of maintaining inter-cluster energy balance. Therefore, by determining the set of clusters to be adjusted that need to be re-clustered, it is possible to achieve energy balance in the network without re-clustering the entire network. This effectively reduces the energy consumption generated in the process of maintaining inter-cluster energy balance, and solves the problem of high energy consumption caused by frequent communication between nodes in the inter-cluster energy balance mechanism.

[0117] The above are only preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A method for balancing energy consumption in a wireless sensor network, characterized in that: The wireless sensor network includes a plurality of sensor nodes; the energy consumption balancing method includes: Dividing a plurality of sensor nodes of the wireless sensor network into a plurality of initial clusters; The base station maintains the predicted residual energy of the initial cluster through a cluster state maintenance algorithm based on a prediction mechanism; The base station determines a cluster set to be adjusted according to the predicted remaining energy; The base station notifies the cluster heads of each cluster in the cluster set to be adjusted to re-cluster, and re-divides the multiple sensor nodes of the wireless sensor network into multiple target clusters to balance the energy consumption among the multiple target clusters, and the residual energy corresponding to the multiple target clusters is balanced.

2. A wireless sensor network energy consumption balancing method according to claim 1, characterized in that: The base station maintains the predicted residual energy of the initial cluster by a cluster state maintenance algorithm based on a prediction mechanism, including: When the current round number is less than or equal to ten rounds, the predicted remaining energy corresponding to the initial cluster is not calculated; When the current round number is greater than ten rounds, the cluster head of the initial cluster performs statistics on the weighted average query energy consumption of its corresponding cluster set; the cluster set includes the current cluster and the cluster to which the current cluster needs to forward data; the cluster to which the current cluster needs to forward data is the cluster to which the current cluster needs to forward data in the historical time round; According to the weighted average query energy consumption, the initial cluster calculates its predicted remaining energy when the current round number is greater than ten rounds.

3. A wireless sensor network energy consumption balancing method according to claim 2, characterized in that: When the current round number is greater than ten rounds, the cluster head of the initial cluster performs statistics on the weighted average query energy consumption of its corresponding cluster set, including: When it is determined that the initial cluster is less than or equal to ten rounds, the cluster head records the round residual energy of each round and the weighted average query frequency of its corresponding cluster set, which is calculated as follows: p k =(x1*f1+x2*f2+…+x n *f n ) / n; Where k is the time period from the current round number to less than or equal to ten rounds, p k is the weighted average query frequency of the cluster set in the kth round, n is the number of clusters in the cluster set to which the cluster needs to forward data, and f n is the number of times the node of the nth cluster in the cluster set is queried by the user, x n is the weight corresponding to the nth cluster in the cluster set, and the weight is the ratio of the frequency of data of this cluster being forwarded by this cluster to the frequency of data being sent by this cluster in the historical time round; According to the round residual energy and the weighted average query frequency, the cluster head of the initial cluster performs statistics on the weighted average query energy consumption of its corresponding cluster set, and the calculation formula is as follows: C=(E i-9 -E i ) / (p i +p i-1 +...+p i-9 ) Where C is the weighted average query energy consumption, E i-9 is the residual energy of the first round in the time period, E i is the remaining energy of the tenth round in the time period, p i ~p i-9 It is the weighted average query frequency of each round within the time period.

4. A wireless sensor network energy consumption balancing method according to claim 2, characterized in that: The initial cluster calculates its predicted remaining energy according to the weighted average query energy consumption when the current round number is greater than ten rounds, including: determining a final round residual energy of the initial cluster in a tenth round within a time period; According to the weighted average query energy consumption of the ten historical rounds, the prediction parameters of the linear regression model based on the least squares method are determined, and the calculation formula is as follows: Where k is the time period from the current round number to less than or equal to ten rounds, C k is the historical weighted average query energy consumption of each initial cluster in the kth round, a and b are prediction parameters; A prediction formula is constructed based on the prediction parameters, and its expression is as follows: Where k is the time period from the current round number to less than or equal to ten rounds, C k is the weighted average query energy consumption predicted by each initial cluster in the kth round, A j is the predicted remaining energy of the cluster in round j (j>i), E i is the remaining energy of the tenth round in the time period, p k is the weighted average query frequency of the cluster set corresponding to this cluster in the kth round; The cluster head of the initial cluster calculates the predicted residual energy of each future round through the prediction formula.

5. A wireless sensor network energy consumption balancing method according to claim 1, characterized in that: The base station determines, according to the predicted remaining energy, a cluster set to be adjusted, including: The base station averages the predicted residual energies of the clusters maintained by the base station to obtain an average residual energy; The base station determines the to-be-adjusted cluster set according to the predicted remaining energy, the average remaining energy and a preset value.

6. A wireless sensor network energy consumption balancing method according to claim 5, characterized in that: The base station determines the cluster set to be adjusted according to the predicted remaining energy, the average remaining energy and a preset value, including: The base station subtracts the preset value from the average remaining energy to obtain a low energy threshold; The base station adds the average residual energy and the preset value to obtain a high energy threshold; The base station determines the to-be-adjusted cluster set according to the predicted remaining energy, the low energy threshold, and the high energy threshold.

7. A wireless sensor network energy consumption balancing method according to claim 6, characterized in that: The cluster set to be adjusted includes a low-energy cluster set to be adjusted and a high-energy cluster set to be adjusted; The base station determines the to-be-adjusted cluster set according to the predicted remaining energy, the low energy threshold, and the high energy threshold, including: The base station determines whether there is a cluster to be adjusted in the wireless sensor network that is lower than the low energy threshold or higher than the high energy threshold, and if so, re-clustering is required; if not, re-clustering is not required; Determine the initial cluster corresponding to the predicted remaining energy lower than the low energy threshold in the wireless sensor network as the low energy cluster set to be adjusted; Determine the initial cluster corresponding to the predicted remaining energy in the wireless sensor network that is higher than the high energy threshold as the high energy cluster set to be adjusted; Initial clusters in the wireless sensor network except the low-energy cluster set to be adjusted and the high-energy cluster set to be adjusted are determined as cluster sets that do not need to be adjusted, and the cluster sets that do not need to be adjusted do not need to be clustered again.

8. A wireless sensor network energy consumption balancing method according to claim 7, characterized in that: When the cluster set to be adjusted is the low-energy cluster set to be adjusted, the base station notifies the cluster head of each cluster in the cluster set to be adjusted to re-cluster, and re-divides the multiple sensor nodes of the wireless sensor network into multiple target clusters, including: Determine the cluster with the lowest energy in the set of low-energy clusters to be adjusted as the lowest energy cluster; Determine a plurality of clusters that are one hop away from the lowest energy cluster as a first cluster set; Re-dividing the plurality of sensor nodes in the first cluster set into a plurality of target clusters having the same number of clusters according to a node clustering strategy in a clustering protocol; Repeat the above steps for clusters other than the first cluster set in the low-energy cluster set to be adjusted, until all clusters in the low-energy cluster set to be adjusted are re-divided; The remaining unadjusted initial clusters are determined as the target clusters.

9. A wireless sensor network energy consumption balancing method according to claim 7, characterized in that: When the cluster set to be adjusted is the high-energy cluster set to be adjusted, the base station notifies the cluster head of each cluster in the cluster set to be adjusted to re-cluster, and re-divides the multiple sensor nodes of the wireless sensor network into multiple target clusters, including: Determine the cluster with the highest energy in the set of high-energy clusters to be adjusted as the highest energy cluster; determining a plurality of clusters that are one hop away from the highest energy cluster as a second cluster set; Re-dividing the plurality of sensor nodes in the second cluster set into a plurality of target clusters having the same number of clusters according to a node clustering strategy in a clustering protocol; Repeat the above steps for clusters other than the second cluster set in the high energy cluster set to be adjusted, until all clusters in the high energy cluster set to be adjusted are re-divided; The remaining unadjusted initial clusters are determined as the target clusters.

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