Wireless sensor network dynamic clustering method and device, electronic equipment and medium

Abstract

This application provides a method, apparatus, electronic device, and medium for dynamic clustering of wireless sensor networks, belonging to the field of wireless sensor network technology. The wireless sensor network includes a central controller and multiple sensor nodes. This method, applied to the central controller, includes: receiving local information transmitted by multiple sensor nodes in the current time slot to determine the positions and remaining energy of the multiple sensor nodes and the positions of multiple target points in the current time slot; determining the coverage score and energy score of the multiple sensor nodes in the current time slot based on the position of the central controller, the positions of the multiple target points, and the positions and remaining energy of the multiple sensor nodes; and determining the optimal clustering scheme of the wireless sensor network in the current time slot based on the positions of the multiple target points, the position of the central controller, and the positions, coverage scores, and energy scores of the multiple sensor nodes. This application can improve the monitoring accuracy of wireless sensor networks for movable target points.

Description

Technical Field

[0001] This application relates to the field of wireless sensor network technology, and in particular to a method, apparatus, electronic device, and medium for dynamic clustering of wireless sensor networks. Background Technology

[0002] In wireless sensor networks, traditional clustering strategies typically focus only on the energy consumption of sensor nodes, failing to take into account other key performance indicators for comprehensive evaluation. Furthermore, they are mainly designed for static network topologies, meaning they are not suitable for monitoring mobile target points. This makes it difficult for wireless sensor networks to meet the monitoring accuracy requirements when applied in smart city scenarios. Summary of the Invention

[0003] The main purpose of this application is to propose a method, apparatus, electronic device and medium for dynamic clustering of wireless sensor networks, which can formulate a more reasonable clustering scheme by comprehensively considering the mobility of target points as well as the coverage and energy factors of wireless sensor networks, thereby improving the monitoring accuracy of wireless sensor networks for all target points.

[0004] To achieve the above objectives, one aspect of this application proposes a dynamic clustering method for a wireless sensor network, wherein the wireless sensor network includes a central controller and multiple sensor nodes, and the wireless sensor network is used to monitor multiple movable target points; the method is applied to the central controller, and the method includes:

[0005] Receive local information sent by the plurality of sensor nodes in the current time slot to determine the position and remaining energy of the plurality of sensor nodes and the position of the plurality of target points in the current time slot;

[0006] Based on the positions of the multiple sensor nodes and the multiple target points in the current time slot, the coverage score of the multiple sensor nodes in the current time slot is determined;

[0007] Based on the location and remaining energy of the plurality of sensor nodes in the current time slot and the location of the central controller, the energy score of the plurality of sensor nodes in the current time slot is determined.

[0008] Based on the locations of the multiple target points, the location of the central controller, and the locations, coverage scores, and energy scores of the multiple sensor nodes in the current time slot, the optimal clustering scheme of the wireless sensor network in the current time slot is determined.

[0009] Further, determining the coverage score of the plurality of sensor nodes in the current time slot based on the positions of the plurality of sensor nodes and the positions of the plurality of target points includes:

[0010] Based on the positions of the multiple sensor nodes and the multiple target points in the current time slot, the coverage status of the multiple sensor nodes over the multiple target points in the current time slot is determined. The coverage status includes a standard coverage status or a redundant coverage status. The standard coverage status indicates that the target point falls within the sensing range of the nearest sensor node, and the redundant coverage status indicates that the target point falls within the sensing range of a non-nearest sensor node.

[0011] For each sensor node, based on the coverage status of the sensor node over the multiple target points in the current time slot, the standard coverage quantity and redundant coverage quantity of the sensor node in the current time slot are counted to determine the coverage score of the sensor node in the current time slot.

[0012] Further, determining the energy score of the multiple sensor nodes in the current time slot based on the location and remaining energy of the multiple sensor nodes and the location of the central controller includes:

[0013] For each of the aforementioned sensor nodes, the sensor node is designated as the cluster head;

[0014] Based on the positions of the plurality of sensor nodes in the current time slot, select all sensor nodes that are closest to the cluster head and match the given number of cluster members from the plurality of sensor nodes, and take all sensor nodes as all cluster members;

[0015] The energy score of the cluster head in the current time slot is determined based on the location of the central controller, the locations of all cluster members, the location of the cluster head, and the remaining energy.

[0016] Further, determining the energy score of the cluster head in the current time slot based on the position of the central controller, the positions of all cluster members, the position of the cluster head, and the remaining energy includes:

[0017] Based on the position of the cluster head and the positions of all cluster members in the current time slot, determine the intra-cluster communication energy consumption corresponding to the cluster head in the current time slot;

[0018] Based on the location of the cluster head and the location of the central controller in the current time slot, determine the inter-cluster communication energy consumption corresponding to the cluster head in the current time slot;

[0019] The energy score of the cluster head in the current time slot is determined based on the remaining energy of the cluster head in the current time slot, as well as the intra-cluster communication energy consumption and inter-cluster communication energy consumption corresponding to the cluster head.

[0020] Further, determining the optimal clustering scheme of the wireless sensor network in the current time slot based on the locations of the multiple target points, the location of the central controller, and the locations, coverage scores, and energy scores of the multiple sensor nodes includes:

[0021] Based on the coverage score and energy score of the plurality of sensor nodes in the current time slot, the priority score of the plurality of sensor nodes in the current time slot is determined.

[0022] The system retrieves the stored locations of the multiple sensor nodes and the multiple target points in all historical time slots prior to the current time slot. Combining the locations and priority scores of the multiple sensor nodes and the locations of the multiple target points in the current time slot, it determines the maximum number of clusters in the wireless sensor network in the current time slot.

[0023] Based on the priority scores of the multiple sensor nodes in the current time slot, multiple optional clustering schemes matching the maximum number of clusters are generated. Each optional clustering scheme records the number of optional clusters and all clusters that are allowed to be formed that match the number of optional clusters. In all clusters, the priority score of each sensor node as a cluster head is higher than the priority score of each sensor node as a cluster member. The number of optional clusters recorded in each optional clustering scheme is different.

[0024] The total network energy consumption of the multiple optional clustering schemes is determined based on the positions of the multiple sensor nodes, the multiple target points, and the central controller in the current time slot.

[0025] The optimal clustering scheme for the wireless sensor network in the current time slot is selected from the multiple alternative clustering schemes based on the minimum total network power consumption.

[0026] Further, the process of calling the stored locations of the multiple sensor nodes and the multiple target points in all historical time slots prior to the current time slot, and combining the locations and priority scores of the multiple sensor nodes and the locations of the multiple target points in the current time slot, to determine the maximum number of clusters in the wireless sensor network in the current time slot includes:

[0027] When the multiple sensor nodes form a cluster with the sensor node with the highest priority score as the cluster head, the initial average network coverage rate in all time slots is determined based on the positions of the multiple sensor nodes and the positions of the multiple target points in all time slots, where all time slots include the current time slot and all historical time slots;

[0028] The number of clusters is set to 2. Based on the number of clusters, the priority scores of the multiple sensor nodes in the current time slot, and the positions of the multiple sensor nodes and the multiple target points in all time slots, the average network coverage in all time slots is determined.

[0029] When the average network coverage under all time slots is greater than or equal to the baseline value, the cluster number is incremented by 1 and used as the new cluster number. Then, the process of determining the average network coverage under all time slots is returned based on the cluster number, the priority score of the multiple sensor nodes under the current time slot, and the positions of the multiple sensor nodes and the multiple target points under all time slots.

[0030] When the average network coverage across all time slots is less than the baseline value, the cluster number is reduced by 1 to obtain the maximum cluster number of the wireless sensor network in the current time slot.

[0031] The benchmark value is determined based on the relationship between the initial average network coverage in all time slots and a preset network coverage threshold.

[0032] Furthermore, the reference value is obtained in the following way:

[0033] When the initial average network coverage under all time slots is less than the network coverage threshold, the benchmark value is determined to be the initial average network coverage under all time slots.

[0034] The baseline value is determined to be the network coverage threshold when the initial average network coverage over all time slots is greater than or equal to the network coverage threshold.

[0035] To achieve the above objectives, another aspect of this application proposes a dynamic clustering device for a wireless sensor network, wherein the wireless sensor network includes a central controller and multiple sensor nodes, the wireless sensor network being used to monitor multiple movable target points; the device is deployed on the central controller, and the device includes:

[0036] The first module is used to receive local information sent by the plurality of sensor nodes in the current time slot, so as to determine the position and remaining energy of the plurality of sensor nodes and the position of the plurality of target points in the current time slot;

[0037] The second module is used to determine the coverage score of the multiple sensor nodes in the current time slot based on the positions of the multiple sensor nodes and the multiple target points in the current time slot.

[0038] The third module is used to determine the energy score of the multiple sensor nodes in the current time slot based on the position and remaining energy of the multiple sensor nodes in the current time slot and the position of the central controller.

[0039] The fourth module is used to determine the optimal clustering scheme of the wireless sensor network in the current time slot based on the locations of the multiple target points, the location of the central controller, and the locations, coverage scores, and energy scores of the multiple sensor nodes in the current time slot.

[0040] To achieve the above objectives, another aspect of this application proposes an electronic device comprising a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0041] To achieve the above objectives, another aspect of this application proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0042] This application includes at least the following beneficial effects: considering the availability of wireless sensor networks in real-world scenarios with multiple mobile target points, the coverage factor of the wireless sensor network is evaluated based on the current location distribution of sensor nodes and target points, and the energy factor of the wireless sensor network is evaluated based on the location distribution of sensor nodes and the central controller, as well as the current remaining energy of the sensor nodes themselves. Through comprehensive analysis, a more reasonable clustering scheme can be formulated, which is conducive to improving the monitoring accuracy of the wireless sensor network for all target points and can also effectively extend the service time of the wireless sensor network. Attached Figure Description

[0043] Figure 1 This is a schematic diagram of the topology of the wireless sensor network provided in the embodiments of this application;

[0044] Figure 2 This is a flowchart of a dynamic clustering method for wireless sensor networks provided in an embodiment of this application;

[0045] Figure 3 This is a schematic diagram of the structure of a dynamic clustering device for wireless sensor networks provided in an embodiment of this application;

[0046] Figure 4This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0047] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying 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 those of this application; they are merely examples of systems and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0048] It is understood that the terms “first,” “second,” etc., used in this application may be used herein to describe various concepts, but unless otherwise stated, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the words “if,” “when,” or “in response to a determination” as used herein may be interpreted as “when…” or “when…” or “in response to a determination.”

[0049] As used in this application, the terms "at least one", "multiple", "each", "any", etc., "at least one" includes one, two or more, "multiple" includes two or more, "each" refers to each of the corresponding multiples, and "any" refers to any one of the multiples.

[0050] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0051] With the rapid development of science and technology and the advancement of the information society, smart cities are becoming a key direction for future urban planning. Wireless sensor networks play a crucial role in the construction of smart cities, especially in areas such as traffic management and urban security that require real-time monitoring of moving targets.

[0052] Clustering strategies in wireless sensor networks divide multiple sensor nodes into clusters. Each cluster member node is responsible for monitoring target points and sending sensing data to its associated cluster head node. The cluster head node then collects all sensing data sent by all its managed cluster member nodes and forwards it to the central controller, thereby significantly reducing network energy consumption. However, traditional clustering strategies typically only focus on the energy consumption of sensor nodes, failing to comprehensively evaluate other key performance indicators. Furthermore, they are mainly designed for static network topologies, making them unsuitable for monitoring moving target points. This limits the monitoring accuracy requirements of wireless sensor networks in smart city scenarios, thus restricting the applicability of traditional clustering strategies.

[0053] In view of this, embodiments of this application provide a method, apparatus, electronic device, and medium for dynamic clustering of wireless sensor networks. This scheme takes into account the availability of wireless sensor networks in actual scenarios with multiple movable target points. It evaluates the coverage factor of the wireless sensor network based on the current location distribution of sensor nodes and target points, and evaluates the energy factor of the wireless sensor network based on the location distribution of sensor nodes and central controller and the current remaining energy of the sensor nodes themselves. Through comprehensive analysis, a more reasonable clustering scheme can be formulated, which is conducive to improving the monitoring accuracy of the wireless sensor network for all target points and can also effectively extend the service time of the wireless sensor network.

[0054] This application provides a method for dynamic clustering of wireless sensor networks, relating to the field of wireless sensor network technology. It can be applied to terminals, servers, or software running on either a terminal or server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, or in-vehicle terminal, but is not limited to these. The server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server can also be a node server in a blockchain network. The software can be an application implementing the above-described method for dynamic clustering of wireless sensor networks, but is not limited to these forms.

[0055] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0056] Figure 1 This is a topology diagram of a wireless sensor network provided in an embodiment of this application. The wireless sensor network includes multiple sensor nodes and a central controller. Each sensor node has the same sensing range. The wireless sensor network is mainly used to monitor multiple mobile target points. It should be noted that when the wireless sensor network is applied in different scenarios, the central controller and each sensor node can be in a fixed position or their positions can change over time. In this application, the case where the positions of the central controller and each sensor node are fixed is preferred.

[0057] Figure 2 This is an optional flowchart of a dynamic clustering method for wireless sensor networks provided in an embodiment of this application. Figure 2 The method described above is mainly applied to the central controller, and the method may include, but is not limited to, steps S101 to S104:

[0058] Step S101: Receive local information sent by multiple sensor nodes in the current time slot to determine the location and remaining energy of multiple sensor nodes and the location of multiple target points in the current time slot;

[0059] Step S102: Determine the coverage score of multiple sensor nodes in the current time slot based on the positions of multiple sensor nodes and multiple target points in the current time slot;

[0060] Step S103: Determine the energy score of multiple sensor nodes in the current time slot based on the location and remaining energy of multiple sensor nodes and the location of the central controller.

[0061] Step S104: Based on the locations of multiple target points, the location of the central controller, and the locations, coverage scores, and energy scores of multiple sensor nodes in the current time slot, determine the optimal clustering scheme for the wireless sensor network in the current time slot.

[0062] Steps S101 to S104 shown in the embodiments of this application, by comprehensively considering the mobility of the target points as well as the coverage and energy factors of the wireless sensor network, formulate a more reasonable clustering scheme, which is beneficial to improving the monitoring accuracy of the wireless sensor network for all target points.

[0063] In step S101 of some embodiments, in the current time slot, the local information actively sent by each sensor node to the central controller includes the sensor node's own position and remaining energy, as well as the relative position information between the sensor node and each target point it covers. The relative position information includes distance and azimuth. After receiving the local information sent by multiple sensor nodes, the central controller aggregates and analyzes it. The position of the target point can be calculated using the positions of different sensor nodes and the distances between these sensor nodes and the same target point. Alternatively, for any sensor node covering the target point, the position of the target point can be calculated based on the sensor node's position and its distance and azimuth to the target point. This application does not limit this.

[0064] In some embodiments, step S102 may include, but is not limited to, steps S201 to S202:

[0065] Step S201: Determine the coverage status of multiple sensor nodes over multiple target points in the current time slot based on the positions of multiple target points and multiple sensor nodes in the current time slot.

[0066] The coverage status includes redundant coverage status or standard coverage status. Redundant coverage status reflects that the target point falls within the sensing range of a non-nearest sensor node, while standard coverage status reflects that the target point falls within the sensing range of the nearest sensor node.

[0067] Specifically, for each target point, based on its position in the current time slot and the positions of multiple sensor nodes, the distance from the target point to each sensor node in the current time slot is calculated. Then, taking the condition that the target point falls within the sensing range of a sensor node as a constraint, all sensor nodes that satisfy this constraint are selected from the multiple sensor nodes, and the coverage set corresponding to the target point in the current time slot is generated. This can be defined using the following expression:

[0068]

[0069] In the formula, Let M be the set of coverage corresponding to target point n in the current time slot t. s Let m be the set of all sensor nodes contained in the wireless sensor network, and let m be the set of M. s The sensor nodes included Let m be the position of sensor node m in the current time slot t. Let n be the position of target point n in the current time slot t. R is the distance between target point n and sensor node m in the current time slot t. s Let be the sensing radius of the sensor node, and the sensing radius of each sensor node is the same;

[0070] Finally, the sensor node closest to the target point is selected from the coverage set corresponding to the target point in the current time slot. The coverage state of the selected sensor node for the target point is determined to be the standard coverage state. All sensor nodes not selected from the coverage set corresponding to the target point in the current time slot are determined to have redundant coverage states for the target point. In addition, since other sensor nodes not falling in the coverage set corresponding to the target point in the current time slot cannot cover the target point, the coverage state of these sensor nodes for the target point can be set to invalid.

[0071] Step S202: For each sensor node, based on its coverage status over multiple target points in the current time slot, calculate the standard coverage quantity and redundant coverage quantity of the sensor node in the current time slot to determine its coverage score. This score can be calculated using the following expression:

[0072]

[0073] In the formula, CS m (t) represents the coverage score of sensor node m in the current time slot t. Let be the standard coverage number of sensor node m in the current time slot t, representing the number of pairs of sensor nodes m in the current time slot t. Standard coverage is performed on each target point, C s (t) represents the unit fraction of sensor nodes participating in standard coverage in the current time slot t. Let be the number of redundant coverage points for sensor node m in the current time slot t, representing the number of redundant coverage points for sensor node m in the current time slot t. Redundant coverage is performed on each target point, C r (t) represents the unit fraction of sensor nodes participating in redundant coverage in the current time slot t, and C s (t) and C r (t) are all positive.

[0074] The unit fraction C of sensor nodes participating in standard coverage in the current time slot t. s (t) and the unit fraction C of sensor nodes participating in redundant coverage in the current time slot t. r The relationship between (t) is explained as follows:

[0075] Under the current time slot t, the overall coverage of sensor node m over multiple target points may be one of the following four:

[0076] The first scenario: When and At that time, sensor node m provides full redundant coverage of multiple target points in the current time slot t;

[0077] The second scenario: when and At that time, in the current time slot t, sensor node m has no coverage over multiple target points;

[0078] The third scenario: when and At that time, sensor node m performs mixed coverage of multiple target points in the current time slot t;

[0079] The fourth scenario: when and At that time, sensor node m provides full standard coverage of multiple target points in the current time slot t;

[0080] To ensure the coverage performance of wireless sensor networks, sensor nodes with full redundant coverage and no coverage should be prioritized as cluster heads. Sensor nodes with mixed coverage or full standard coverage should be avoided. Assuming there is a first sensor node with full redundant coverage, a second sensor node with no coverage, a third sensor node with mixed coverage, and a fourth sensor node with full standard coverage, when selecting a cluster head from these four nodes, the first sensor node should be prioritized, followed by the second sensor node, and finally either the third or fourth sensor node. Therefore, in the current time slot t, the unit fraction C of sensor nodes participating in standard coverage is... s (t) and the unit fraction C of sensor nodes participating in redundant coverage in the current time slot t. r The following relationship should be satisfied between (t):

[0081]

[0082] In the formula, This represents the maximum number of redundant coverage values ​​among all sensor nodes included in the wireless sensor network in the current time slot t. It represents the minimum standard coverage number of all sensor nodes included in the wireless sensor network in the current time slot t.

[0083] In step S102 above, considering the movement behavior of the target point, the coverage importance of the sensor node can be evaluated from the perspective of the target point, which can effectively avoid unnecessary energy consumption.

[0084] In some embodiments, step S103 may include, but is not limited to, steps S301 to S302:

[0085] Step S301: For each sensor node, take the sensor node as the cluster head, and based on the positions of multiple sensor nodes in the current time slot, select all sensor nodes that are closest to the cluster head and match the given number of cluster members from the multiple sensor nodes, and then take all the selected sensor nodes as all cluster members managed by the cluster head.

[0086] Step S302: Based on the location of the central controller, the locations of all cluster members, and the remaining energy and location of the cluster head in the current time slot, determine the energy score of the cluster head in the current time slot. The energy score is mainly obtained by comprehensively evaluating the remaining energy of the cluster head and related communication energy consumption.

[0087] In some embodiments, step S302 may include, but is not limited to, steps S401 to S403:

[0088] Step S401: Based on the location of the cluster head and the locations of all cluster members in the current time slot, determine the intra-cluster communication energy consumption corresponding to the cluster head in the current time slot. This can be calculated using the following expression:

[0089]

[0090] In the formula, m = CH0, This represents the intra-cluster communication energy consumption corresponding to cluster head CH0 in the current time slot t. L is the set of all cluster members managed by the cluster head CH0. d Let be the size of the sensing data packets for each sensor node, and let j be the set. The j-th cluster member contained in r j S (t) represents the position of the j-th cluster member in the current time slot t. E represents the position of cluster head CH0 in the current time slot t. t(x,y) represents the transmitter transmission energy consumption function included in the first-order radio energy consumption model.

[0091] Step S402: Based on the location of the central controller and the cluster head in the current time slot, determine the inter-cluster communication energy consumption corresponding to the cluster head in the current time slot. This can be calculated using the following expression:

[0092]

[0093] In the formula, m = CH0, Let ρ be the inter-cluster communication energy consumption corresponding to cluster head CH0 in the current time slot t, ρ be the data aggregation rate, M be the total number of sensor nodes in the wireless sensor network, and G be the assumed number of clusters that can be divided in the wireless sensor network. G is a manually assigned value that can be flexibly adjusted according to the actual application scenario and requirements. r represents the number of members in a given cluster. K (t) represents the position of the central controller K in the current time slot t.

[0094] Step S403: Based on the remaining energy of the cluster head in the current time slot, as well as the inter-cluster communication energy consumption and intra-cluster communication energy consumption corresponding to the cluster head, determine the energy score of the cluster head in the current time slot. This score can be calculated using the following expression:

[0095]

[0096] In the formula, m = CH0,ES m (t) represents the energy score of cluster head CH0 in the current time slot t. This represents the remaining energy of the cluster head CH0 in the current time slot t.

[0097] In step S103 above, by combining the remaining energy of the sensor node with the intra-cluster communication distance and inter-cluster communication distance related to the sensor node for comprehensive analysis, the energy state of the sensor node can be directly and effectively evaluated. Compared with the scheme proposed by some existing technologies that weights and sums the relevant communication distance and remaining energy of the sensor node to complete the energy state evaluation, the parameter setting can be simplified and the practicality and adaptability of the algorithm can be improved.

[0098] Furthermore, the following explanation is provided regarding the first-order radio power consumption model mentioned in step S401 above:

[0099] This first-order radio energy consumption model includes a transmitter transmission energy consumption function and a receiver reception energy consumption function. The transmitter includes a transmission circuit and a transmission amplifier, and the receiver includes a reception circuit.

[0100] The transmitter's power consumption function can be expressed by the following expression:

[0101]

[0102] The receiver's power consumption function can be expressed by the following expression:

[0103] E r (z)=zE elec ;

[0104] In the formula, E t (x, y) represents the transmitter's power consumption function, where x is the size of the data packet transmitted by the transmitter, y is the wireless transmission distance, and E... elec ε represents the energy consumed by the transmitting and receiving circuits during operation. fs ε is the signal power amplification factor in the free-space model. amp Here, d is the signal power amplification factor under the multipath fading channel model, d0 is a given wireless transmission distance threshold, and E is the signal power amplification factor. r (z) is the receiver's power consumption function, where z is the size of the data packet received by the receiver.

[0105] In some embodiments, step S104 may include, but is not limited to, steps S501 to S505:

[0106] Step S501: Based on the energy scores and coverage scores of multiple sensor nodes in the current time slot, determine the priority scores of multiple sensor nodes in the current time slot. This can be calculated using the following expression:

[0107]

[0108]

[0109] In the formula, For CS m The normalization result of CS(t), min (t) represents the minimum coverage score among multiple sensor nodes in the current time slot t, CS max (t) represents the maximum coverage score among multiple sensor nodes in the current time slot t. For ES m The normalized result of (t), ES min (t) represents the minimum energy score of multiple sensor nodes in the current time slot t, ES max (t) represents the maximum energy score of multiple sensor nodes in the current time slot t, CHS m (t) represents the priority score of sensor node m in the current time slot t, where α is a weight parameter and α∈[0,1], mainly used to control the relative importance of coverage score and energy score in the cluster head selection task.

[0110] Step S502: Retrieve the original stored locations of multiple target points and multiple sensor nodes in all historical time slots. All historical time slots are before the current time slot. Combine the priority scores and locations of multiple sensor nodes in the current time slot with the locations of multiple target points to determine the maximum number of clusters in the wireless sensor network in the current time slot.

[0111] In this step, the number of clusters is gradually increased. Each time the number of clusters is increased, based on the priority scores of multiple sensor nodes in the current time slot, all sensor nodes with higher priority that match the current number of clusters are selected to form a current cluster head set. The current cluster head set does not participate in any target point monitoring. Then, for each time slot included in all time slots, the network coverage corresponding to the current cluster head set in that time slot is calculated based on the positions of multiple target points in that time slot and the positions of all sensor nodes in the wireless sensor network except for the current cluster head set. The calculated network coverage corresponding to the current cluster head set in all time slots is then averaged to obtain the average network coverage corresponding to the current cluster head set in all time slots. This average network coverage is compared with a coverage threshold. If the average network coverage is greater than or equal to the coverage threshold, the number of clusters is increased again to update the current cluster head set and calculate and detect the average network coverage. If the average network coverage is less than the coverage threshold, the current number of clusters is reduced by 1 to obtain the maximum number of clusters in the wireless sensor network in the current time slot.

[0112] All time slots include the current time slot and all historical time slots before the current time slot. For example, when the current time slot is t, all historical time slots include time slot 1 to time slot t-1.

[0113] Step S503: Based on the priority scores of multiple sensor nodes in the current time slot, generate multiple optional clustering schemes that match the maximum number of clusters; wherein, each optional clustering scheme records the number of optional clusters and all clusters that are allowed to be formed that match the number of optional clusters, and in all clusters, the priority score of each sensor node as a cluster head is higher than the priority score of each sensor node as a cluster member, and the number of optional clusters recorded in each optional clustering scheme is different.

[0114] In this step, the number of clusters is gradually increased. Each time the number of clusters is increased, a corresponding optional clustering scheme is generated based on the priority scores of multiple sensor nodes in the current time slot. This method is followed until the maximum number of clusters is reached.

[0115] Specifically, the maximum number of clusters in the wireless sensor network in the current time slot will be denoted as G. maxThe initial cluster size is set to 1. The sensor node with the highest priority score in the current time slot is selected from multiple sensor nodes to serve as a cluster head. All other sensor nodes are assigned as cluster members managed by this cluster head, resulting in the first optional clustering scheme. The cluster size is then increased to 2. The two sensor nodes with the highest priority score in the current time slot are selected as two cluster heads. All other sensor nodes are assigned as cluster members according to the nearest neighbor principle, forming two clusters managed by these two cluster heads, resulting in the second optional clustering scheme. The cluster size is then increased to 3. The three sensor nodes with the highest priority score in the current time slot are selected as three cluster heads. All other sensor nodes are assigned as cluster members according to the nearest neighbor principle, forming three clusters managed by these three cluster heads, resulting in the third optional clustering scheme. This process continues until the current cluster size is increased to G. max And obtain the corresponding G max One optional clustering scheme.

[0116] The nearest neighbor principle states that for each cluster member contained in a cluster, the distance between that cluster member and the cluster head contained in that cluster is less than the distance between that cluster member and the cluster heads contained in other clusters.

[0117] Step S504: Determine the total network energy consumption of multiple optional clustering schemes based on the location of the central controller, the locations of multiple target points, and the locations of multiple sensor nodes in the current time slot.

[0118] Specifically, for each cluster allowed to be formed as described in each optional clustering scheme, the cluster contains a sensor node as a cluster head and multiple sensor nodes as cluster members. Based on the position of the cluster head and the position of the central controller in the current time slot, the energy consumption value of the cluster head in the current time slot is calculated. Based on the position of the cluster head, the position of each cluster member, the positions of multiple target points, and the position of the central controller in the current time slot, the energy consumption value of each cluster member in the current time slot is calculated. Then, the energy consumption values ​​of all sensor nodes contained in the cluster are added together to obtain the energy consumption value of the cluster. According to this implementation method, the energy consumption values ​​of all clusters allowed to be formed as described in the optional clustering scheme are calculated. Finally, the energy consumption values ​​of all clusters are added together to obtain the total network energy consumption of the optional clustering scheme.

[0119] The energy consumption value of this cluster head in the current time slot can be calculated using the following expression:

[0120]

[0121]

[0122]

[0123]

[0124] In the formula, E CH (t) represents the energy consumption value of the cluster head CH in the current time slot t. The energy consumption for data aggregation in the cluster head CH at the current time slot t. E represents the communication energy consumption of the cluster head CH in the current time slot t. DA M is the energy consumption coefficient for data aggregation. CH L is the set of all cluster members managed by the cluster head CH. m (t) is a set M CH The size of the perception data packet of the cluster member m contained in E t (x,y) is the transmitter transmission energy consumption function, L CH (t) represents the size of the aggregated data packets in the cluster head CH in the current time slot t. L represents the position of the cluster head CH in the current time slot t. c To control data packet size, E r (z) is the receiver's power consumption function.

[0125] The energy consumption value of each cluster member in the current time slot can be calculated using the following expression:

[0126]

[0127]

[0128]

[0129] In the formula, E m (t) represents set M in the current time slot t. CH The energy consumption value of cluster member m included in , For set M in the current time slot t CH The data-aware energy consumption of cluster member m included in the dataset. For set M in the current time slot t CH The communication energy consumption of cluster member m included, E s To sense the energy consumption coefficient, N m For falling within set M cH The set formed by all target points within the perception range of cluster member m. For set M in the current time slot tCH The position of cluster member m contained therein. Let n be the position of the target point n contained in set N in the current time slot t.

[0130] Step S505: Select the clustering scheme with the minimum total network energy consumption from multiple optional clustering schemes, and take it as the optimal clustering scheme for the wireless sensor network in the current time slot.

[0131] It should be noted that if there are k optional clustering schemes with the minimum total network energy consumption among multiple optional clustering schemes, where k is a positive integer and k>1, the total network energy consumption of these k optional clustering schemes is equal. Considering that the cluster head does not participate in the target point perception task, the increase of the cluster head will lead to the increase of the number of clusters, thereby leading to a decrease in network coverage. Therefore, this application prefers to select the optional clustering scheme with the minimum number of optional clusters from these k optional clustering schemes as the optimal clustering scheme for the wireless sensor network in the current time slot.

[0132] In step S104 above, by introducing an adaptive cluster number selection strategy, the clustering of the wireless sensor network can be dynamically adjusted according to the network status (such as coverage and energy level) in the current time slot. This helps to reduce network energy consumption, avoid resource waste, and effectively extend network service time.

[0133] In some embodiments, step S502 may include, but is not limited to, steps S601 to S603:

[0134] Step S601: When all sensor nodes in the wireless sensor network form a cluster, the cluster uses the sensor node with the highest priority score among the multiple sensor nodes as the cluster head. Based on the positions of multiple target points and multiple sensor nodes in all time slots, the initial average network coverage in all time slots is determined, and then the number of clusters is set to k=2.

[0135] The initial average network coverage across all time slots can be calculated using the following expression:

[0136]

[0137] In the formula, P represents the initial average network coverage across all time slots. τ (CH1) represents the initial network coverage in time slot τ, and N is the number of target points included in the wireless sensor network. CH1 is the set of all cluster members managed by cluster head CH1, which is the sensor node with the highest priority score among multiple sensor nodes. For the set in time slot τ The location of cluster member m1 contained therein. Let n be the location of the target point n in the wireless sensor network, and u(a) be the indicator function. When a>0, u(a)=1, and when a≤0, u(a)=0.

[0138] Step S602: Determine the average network coverage in all time slots based on the number of clusters k, the priority scores of multiple sensor nodes in the current time slot, and the positions of multiple target points and multiple sensor nodes in all time slots.

[0139] Specifically, the k sensor nodes with the highest priority scores are selected from multiple sensor nodes, and these k selected sensor nodes are used as k cluster heads to form a cluster head set, denoted as CH. total_k ={CH1,CH2,...,CH k}, excluding the cluster head set CH from multiple sensor nodes total_k All sensor nodes other than M form a cluster member set. total_k Then, based on the positions of multiple target points in all time slots and the cluster member set M totalk The locations of all sensor nodes included are used to calculate the average network coverage across all time slots using the following expression:

[0140]

[0141] In the formula, P represents the average network coverage across all time slots. τ (CH total_k () represents the average network coverage under time slot τ. Let M be the cluster membership set in time slot τ. total_k The location of cluster member m2 contained therein.

[0142] Step S603: Compare the average network coverage under all time slots with the benchmark value to determine whether the average network coverage under all time slots is less than the benchmark value. If so, subtract 1 from the current cluster number k to obtain the maximum cluster number of the wireless sensor network under the current time slot. If not, add 1 to the current cluster number k and use it as the new cluster number, that is, assign k+1 to k, and then return to execute the above step S602.

[0143] The benchmark value is determined based on the relationship between a preset network coverage threshold and the initial average network coverage in all time slots. The corresponding implementation method is as follows: compare the initial average network coverage in all time slots with the network coverage threshold, and determine whether the initial average network coverage in all time slots is less than the network coverage threshold; if so, the initial average network coverage in all time slots is used as the benchmark value; if not, the network coverage threshold is used as the benchmark value.

[0144] Since the optimal clustering scheme of the wireless sensor network in the current time slot is obtained after performing the above step S104, according to all the clusters that can be formed as recorded in the optimal clustering scheme, for each cluster containing one sensor node as the cluster head and multiple sensor nodes as cluster members, the central controller assigns intra-cluster tasks to the sensor node as the cluster head so that it can subsequently collect cluster member data and report it to the central controller, and assigns intra-cluster tasks to each sensor node as a cluster member so that it can subsequently perform target point perception and report the relevant perception data to the associated cluster head, thereby completing the entire network clustering task.

[0145] The proposed method for dynamic clustering of wireless sensor networks in this application takes into account the availability of wireless sensor networks in real-world scenarios with multiple movable target points. It evaluates the coverage factor of the wireless sensor network based on the current location distribution of sensor nodes and target points, and evaluates the energy factor of the wireless sensor network based on the location distribution of sensor nodes and the central controller, as well as the current remaining energy of the sensor nodes themselves. Through comprehensive analysis, a more reasonable clustering scheme can be formulated, which is beneficial to improving the monitoring accuracy of the wireless sensor network for all target points and can also effectively extend the service time of the wireless sensor network.

[0146] Please see Figure 3 This application also provides a wireless sensor network dynamic clustering device, which can implement the above-described wireless sensor network dynamic clustering method. The wireless sensor network includes multiple sensor nodes and a central controller. The wireless sensor network is mainly used to monitor multiple movable target points. The device is mainly deployed in the central controller and includes:

[0147] The first module 701 is used to receive local information sent by multiple sensor nodes in the current time slot, so as to determine the position of multiple target points and the remaining energy and position of multiple sensor nodes in the current time slot.

[0148] The second module 702 is used to determine the coverage score of multiple sensor nodes in the current time slot based on the positions of multiple target points and multiple sensor nodes in the current time slot.

[0149] The third module 703 is used to determine the energy score of multiple sensor nodes in the current time slot based on the position of the central controller and the remaining energy and position of multiple sensor nodes in the current time slot.

[0150] The fourth module 704 is used to determine the optimal clustering scheme of the wireless sensor network in the current time slot based on the location of the central controller, the locations of multiple target points, the locations of multiple sensor nodes, energy scores, and coverage scores in the current time slot.

[0151] It is understood that the content of the above method embodiments is applicable to this system embodiment. The specific functions implemented in this system embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0152] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method for dynamic clustering of wireless sensor networks. This electronic device can include any smart terminal such as a tablet computer or an in-vehicle computer.

[0153] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0154] Please see Figure 4 , Figure 4 This illustrates the hardware structure of an electronic device according to another embodiment, the electronic device comprising:

[0155] The processor 801 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application.

[0156] The memory 802 can be implemented as a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 802 can store the operating system and other application programs. When the technical solutions provided in the embodiments of this application are implemented through software or firmware, the relevant program code is stored in the memory 802 and is called and executed by the processor 801.

[0157] The 803 input / output interface is used to implement information input and output.

[0158] The communication interface 804 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0159] Bus 805 transmits information between various components of the device (e.g., processor 801, memory 802, input / output interface 803, and communication interface 804);

[0160] The processor 801, memory 802, input / output interface 803, and communication interface 804 are connected to each other within the device via bus 805.

[0161] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for dynamic clustering of wireless sensor networks.

[0162] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0163] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0164] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0165] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0166] The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0167] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0168] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0169] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0170] In the embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between systems or units may be electrical, mechanical, or other forms.

[0171] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0172] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0173] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0174] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A method for dynamic clustering of wireless sensor networks, characterized in that, The wireless sensor network includes a central controller and multiple sensor nodes, and is used to monitor multiple mobile target points. The method is applied to the central controller, and the method includes: Receive local information sent by the plurality of sensor nodes in the current time slot to determine the position and remaining energy of the plurality of sensor nodes and the position of the plurality of target points in the current time slot; Based on the positions of the multiple sensor nodes and the multiple target points in the current time slot, the coverage score of the multiple sensor nodes in the current time slot is determined; Based on the location and remaining energy of the plurality of sensor nodes in the current time slot and the location of the central controller, the energy score of the plurality of sensor nodes in the current time slot is determined; Based on the locations of the multiple target points, the location of the central controller, and the locations, coverage scores, and energy scores of the multiple sensor nodes in the current time slot, the optimal clustering scheme of the wireless sensor network in the current time slot is determined. The step of determining the optimal clustering scheme of the wireless sensor network in the current time slot based on the locations of the multiple target points, the location of the central controller, and the locations, coverage scores, and energy scores of the multiple sensor nodes includes: Based on the coverage score and energy score of the plurality of sensor nodes in the current time slot, the priority score of the plurality of sensor nodes in the current time slot is determined. The system retrieves the stored locations of the multiple sensor nodes and the multiple target points in all historical time slots prior to the current time slot. Combining the locations and priority scores of the multiple sensor nodes and the locations of the multiple target points in the current time slot, it determines the maximum number of clusters in the wireless sensor network in the current time slot. Based on the priority scores of the multiple sensor nodes in the current time slot, multiple optional clustering schemes matching the maximum number of clusters are generated. Each optional clustering scheme records the number of optional clusters and all clusters that are allowed to be formed that match the number of optional clusters. In all clusters, the priority score of each sensor node as a cluster head is higher than the priority score of each sensor node as a cluster member. The number of optional clusters recorded in each optional clustering scheme is different. The total network energy consumption of the multiple optional clustering schemes is determined based on the positions of the multiple sensor nodes, the multiple target points, and the central controller in the current time slot. The optimal clustering scheme for the wireless sensor network in the current time slot is selected from the multiple alternative clustering schemes based on the minimum total network power consumption.

2. The method for dynamic clustering of wireless sensor networks according to claim 1, characterized in that, The step of determining the coverage score of the plurality of sensor nodes in the current time slot based on the positions of the plurality of sensor nodes and the positions of the plurality of target points in the current time slot includes: Based on the positions of the multiple sensor nodes and the multiple target points in the current time slot, the coverage status of the multiple sensor nodes over the multiple target points in the current time slot is determined. The coverage status includes a standard coverage status or a redundant coverage status. The standard coverage status indicates that the target point falls within the sensing range of the nearest sensor node, and the redundant coverage status indicates that the target point falls within the sensing range of a non-nearest sensor node. For each sensor node, based on the coverage status of the sensor node over the multiple target points in the current time slot, the standard coverage quantity and redundant coverage quantity of the sensor node in the current time slot are counted to determine the coverage score of the sensor node in the current time slot.

3. The method for dynamic clustering of wireless sensor networks according to claim 1, characterized in that, The process of determining the energy score of the multiple sensor nodes in the current time slot based on the location and remaining energy of the multiple sensor nodes and the location of the central controller includes: For each of the aforementioned sensor nodes, the sensor node is designated as the cluster head; Based on the positions of the plurality of sensor nodes in the current time slot, select all sensor nodes that are closest to the cluster head and match the given number of cluster members from the plurality of sensor nodes, and take all sensor nodes as all cluster members; The energy score of the cluster head in the current time slot is determined based on the location of the central controller, the locations of all cluster members, the location of the cluster head, and the remaining energy.

4. The method for dynamic clustering of wireless sensor networks according to claim 3, characterized in that, The process of determining the energy score of the cluster head in the current time slot based on the location of the central controller, the locations of all cluster members, the location of the cluster head, and the remaining energy includes: Based on the position of the cluster head and the positions of all cluster members in the current time slot, determine the intra-cluster communication energy consumption corresponding to the cluster head in the current time slot; Based on the location of the cluster head and the location of the central controller in the current time slot, determine the inter-cluster communication energy consumption corresponding to the cluster head in the current time slot; The energy score of the cluster head in the current time slot is determined based on the remaining energy of the cluster head in the current time slot, as well as the intra-cluster communication energy consumption and inter-cluster communication energy consumption corresponding to the cluster head.

5. The method for dynamic clustering of wireless sensor networks according to claim 1, characterized in that, The process of retrieving the stored locations of the multiple sensor nodes and the multiple target points in all historical time slots prior to the current time slot, and combining this with the locations and priority scores of the multiple sensor nodes and the locations of the multiple target points in the current time slot, determines the maximum number of clusters in the wireless sensor network in the current time slot, including: When the multiple sensor nodes form a cluster with the sensor node with the highest priority score as the cluster head, the initial average network coverage rate in all time slots is determined based on the positions of the multiple sensor nodes and the positions of the multiple target points in all time slots, where all time slots include the current time slot and all historical time slots; The number of clusters is set to 2. Based on the number of clusters, the priority scores of the multiple sensor nodes in the current time slot, and the positions of the multiple sensor nodes and the multiple target points in all time slots, the average network coverage in all time slots is determined. When the average network coverage under all time slots is greater than or equal to the baseline value, the cluster number is incremented by 1 and used as the new cluster number. Then, the process of determining the average network coverage under all time slots is returned based on the cluster number, the priority score of the multiple sensor nodes under the current time slot, and the positions of the multiple sensor nodes and the multiple target points under all time slots. When the average network coverage across all time slots is less than the baseline value, the cluster number is reduced by 1 to obtain the maximum cluster number of the wireless sensor network in the current time slot. The benchmark value is determined based on the relationship between the initial average network coverage in all time slots and a preset network coverage threshold.

6. The method for dynamic clustering of wireless sensor networks according to claim 5, characterized in that, The benchmark value is obtained in the following way: When the initial average network coverage under all time slots is less than the network coverage threshold, the benchmark value is determined to be the initial average network coverage under all time slots. The baseline value is determined to be the network coverage threshold when the initial average network coverage over all time slots is greater than or equal to the network coverage threshold.

7. A dynamic clustering device for wireless sensor networks, characterized in that, The wireless sensor network includes a central controller and multiple sensor nodes, and is used to monitor multiple mobile target points. The device is deployed in the central controller, and the device includes: The first module is used to receive local information sent by the plurality of sensor nodes in the current time slot, so as to determine the position and remaining energy of the plurality of sensor nodes and the position of the plurality of target points in the current time slot; The second module is used to determine the coverage score of the multiple sensor nodes in the current time slot based on the positions of the multiple sensor nodes and the multiple target points in the current time slot. The third module is used to determine the energy score of the multiple sensor nodes in the current time slot based on the position and remaining energy of the multiple sensor nodes in the current time slot and the position of the central controller. The fourth module is used to determine the optimal clustering scheme of the wireless sensor network in the current time slot based on the positions of the multiple target points, the position of the central controller, and the positions, coverage scores, and energy scores of the multiple sensor nodes in the current time slot. The step of determining the optimal clustering scheme of the wireless sensor network in the current time slot based on the locations of the multiple target points, the location of the central controller, and the locations, coverage scores, and energy scores of the multiple sensor nodes includes: Based on the coverage score and energy score of the plurality of sensor nodes in the current time slot, the priority score of the plurality of sensor nodes in the current time slot is determined. The system retrieves the stored locations of the multiple sensor nodes and the multiple target points in all historical time slots prior to the current time slot. Combining the locations and priority scores of the multiple sensor nodes and the locations of the multiple target points in the current time slot, it determines the maximum number of clusters in the wireless sensor network in the current time slot. Based on the priority scores of the multiple sensor nodes in the current time slot, multiple optional clustering schemes matching the maximum number of clusters are generated. Each optional clustering scheme records the number of optional clusters and all clusters that are allowed to be formed that match the number of optional clusters. In all clusters, the priority score of each sensor node as a cluster head is higher than the priority score of each sensor node as a cluster member. The number of optional clusters recorded in each optional clustering scheme is different. The total network energy consumption of the multiple optional clustering schemes is determined based on the positions of the multiple sensor nodes, the multiple target points, and the central controller in the current time slot. The optimal clustering scheme for the wireless sensor network in the current time slot is selected from the multiple alternative clustering schemes based on the minimum total network power consumption.

8. An electronic device, characterized in that, The electronic device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method according to any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 6.

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