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

Abstract

The invention provides a wireless sensor network dynamic clustering method and device, electronic equipment and a medium, and belongs to the technical field of wireless sensor networks. The wireless sensor network comprises a central controller and a plurality of sensor nodes, and the method is applied to the central controller and comprises the following steps: receiving local information sent by the plurality of sensor nodes in a current time slot so as to determine positions and residual energy of the plurality of sensor nodes and positions of a plurality of target points in the current time slot; determining coverage scores and energy scores of the plurality of sensor nodes in the current time slot according to the position of the central controller, the positions of the plurality of target points and the positions and residual energy of the plurality of sensor nodes in the current time slot; and determining an optimal clustering scheme of the wireless sensor network in the current time slot according to the positions of the plurality of target points, the position of the central controller and the positions, the coverage scores and the energy scores of the plurality of sensor nodes in the current time slot. According to the invention, the monitoring precision of the wireless sensor network on the movable target point can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of wireless sensor networks, and in particular to a method, device, electronic device and medium for dynamic clustering of wireless sensor networks. Background Art

[0002] In wireless sensor networks, traditional clustering strategies usually only focus on the energy consumption of sensor nodes, fail to take into account other key performance indicators for comprehensive evaluation, and are mainly designed for static network topology structures, that is, they are not suitable for monitoring movable target points, making 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 dynamic clustering method, device, electronic device and medium for wireless sensor networks, which can formulate a more reasonable clustering scheme while comprehensively considering the mobility of target points and the coverage factors and energy factors of the wireless sensor network, which is conducive to improving the monitoring accuracy of the wireless sensor network for all target points.

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

[0005] Receiving local information sent by the multiple sensor nodes in the current time slot to determine the positions and residual energies of the multiple sensor nodes and the positions of the multiple target points in the current time slot;

[0006] Determining coverage scores of the multiple sensor nodes at the current time slot according to the positions of the multiple sensor nodes and the positions of the multiple target points at the current time slot;

[0007] Determining energy scores of the multiple sensor nodes at the current time slot according to the positions and residual energies of the multiple sensor nodes at the current time slot and the position of the central controller;

[0008] According to 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, an optimal clustering scheme of the wireless sensor network in the current time slot is determined.

[0009] Further, determining the coverage scores of the multiple sensor nodes in the current time slot according to the positions of the multiple sensor nodes and the positions of the multiple target points in the current time slot includes:

[0010] Determine, according to the positions of the multiple sensor nodes and the positions of the multiple target points in the current time slot, the coverage status of the multiple sensor nodes to the multiple target points in the current time slot, the coverage status including a standard coverage status or a redundant coverage status, the standard coverage status indicates that the target point falls within the perception range of the nearest sensor node, and the redundant coverage status indicates that the target point falls within the perception range of a non-nearest sensor node;

[0011] For each of the sensor nodes, according to the coverage status of the sensor node to the multiple target points in the current time slot, the standard coverage quantity and the 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 scores of the multiple sensor nodes at the current time slot according to the positions and residual energies of the multiple sensor nodes at the current time slot and the position of the central controller includes:

[0013] For each of the sensor nodes, taking the sensor node as a cluster head;

[0014] According to the positions of the multiple sensor nodes in the current time slot, all sensor nodes which are closest to the cluster head and match the given number of cluster members are selected from the multiple sensor nodes, and all the sensor nodes are used as all cluster members;

[0015] An energy score of the cluster head at the current time slot is determined according to the position of the central controller, the positions of all cluster members, and the position and residual energy of the cluster head at the current time slot.

[0016] Further, determining the energy score of the cluster head at the current time slot according to the position of the central controller, the positions of all cluster members, and the position and residual energy of the cluster head at the current time slot includes:

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

[0018] Determine the inter-cluster communication energy consumption corresponding to the cluster head in the current time slot according to the position of the cluster head and the position of the central controller in the current time slot;

[0019] An energy score of the cluster head in the current time slot is determined according to the residual energy of the cluster head in the current time slot and 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 at the current time slot according to 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 at the current time slot includes:

[0021] Determining priority scores of the multiple sensor nodes at the current time slot according to the coverage scores and energy scores of the multiple sensor nodes at the current time slot;

[0022] Recalling the stored positions of the multiple sensor nodes and the positions of the multiple target points in all historical time slots before the current time slot, combining the positions and priority scores of the multiple sensor nodes and the positions of the multiple target points in the current time slot, and determining the maximum number of clusters of the wireless sensor network in the current time slot;

[0023] Generate a plurality of optional clustering schemes matching the maximum number of clusters according to the priority scores of the plurality of sensor nodes at the current time slot, each of the optional clustering schemes recording the number of optional clusters and all clusters that are allowed to be formed and matching the number of optional clusters, in all the 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 of the optional clustering schemes is different;

[0024] Determine the total network energy consumption of the multiple optional clustering schemes according to the positions of the multiple sensor nodes, the positions of the multiple target points and the position of the central controller at the current time slot;

[0025] The optional clustering scheme with the minimum total network energy consumption is selected from the multiple optional clustering schemes to serve as the optimal clustering scheme of the wireless sensor network in the current time slot.

[0026] Further, calling the stored positions of the multiple sensor nodes and the positions of the multiple target points in all historical time slots before the current time slot, combining the positions and priority scores of the multiple sensor nodes and the positions of the multiple target points in the current time slot, and determining the maximum number of clusters of 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 a cluster head, determining the initial average network coverage in all time slots according to the positions of the multiple sensor nodes and the positions of the multiple target points in all time slots, wherein all time slots include the current time slot and all historical time slots;

[0028] The number of clusters is set to 2, and an average network coverage rate in all time slots is determined according to 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 positions of the multiple target points in all time slots;

[0029] When the average network coverage rate in all the time slots is greater than or equal to the reference value, the number of clusters is increased by 1 and used as the new number of clusters, and then returning to the step of determining the average network coverage rate in all the time slots according to 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 positions of the multiple target points in all the time slots;

[0030] When the average network coverage rate in all the time slots is less than the reference value, subtracting 1 from the number of clusters as the maximum number of clusters of the wireless sensor network in the current time slot;

[0031] The reference value is determined according to the relationship between the initial average network coverage in all the time slots and a preset network coverage threshold.

[0032] Furthermore, the reference value is obtained by:

[0033] When the initial average network coverage rate in all the time slots is less than the network coverage rate threshold, determining the reference value to be the initial average network coverage rate in all the time slots;

[0034] When the initial average network coverage in all the time slots is greater than or equal to the network coverage threshold, the reference value is determined to be the network coverage threshold.

[0035] To achieve the above object, another aspect of the present application provides a wireless sensor network dynamic clustering device, the wireless sensor network includes a central controller and multiple sensor nodes, the wireless sensor network is used to monitor multiple movable target points; the device is deployed in the central controller, and the device includes:

[0036] The first module is used to receive the local information sent by the multiple sensor nodes in the current time slot to determine the positions and residual energy of the multiple sensor nodes and the positions of the multiple target points in the current time slot;

[0037] A second module is used to determine the coverage scores of the multiple sensor nodes in the current time slot according to the positions of the multiple sensor nodes and the positions of the multiple target points in the current time slot;

[0038] A third module is used to determine the energy scores of the multiple sensor nodes in the current time slot according to the positions and residual energies 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 according to 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.

[0040] To achieve the above objective, another aspect of the present application provides an electronic device, the electronic device comprising a memory and a processor, the memory storing a computer program, and the processor implementing the above method when executing the computer program.

[0041] To achieve the above objective, another aspect of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program implements the above method when executed by a processor.

[0042] The present application includes at least the following beneficial effects: taking into account the availability of wireless sensor networks in actual scenarios with multiple movable 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 central controllers and the current remaining energy of the sensor nodes themselves. After 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. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 is a topological diagram of a wireless sensor network provided in an embodiment of the present application;

[0044] Figure 2 is a flow chart of a wireless sensor network dynamic clustering method provided by an embodiment of the present application;

[0045] Figure 3 It is a structural schematic diagram of a wireless sensor network dynamic clustering device provided in an embodiment of the present application;

[0046] Figure 4It is a schematic diagram of the hardware structure of the electronic device provided in the embodiment of the present application. DETAILED DESCRIPTION

[0047] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail below in conjunction with the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. 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 embodiments of the present application. They are only examples of systems and methods consistent with some aspects of the embodiments of the present application as detailed in the attached claims.

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

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

[0050] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are 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 the focus of future urban planning. Wireless sensor networks play a vital role in the construction of smart cities, especially in areas such as traffic management and urban safety that require real-time monitoring of mobile targets.

[0052] The clustering strategy is used in wireless sensor networks to divide multiple sensor nodes into several clusters. Each cluster member node is responsible for monitoring the target point and sending the sensing data to the cluster head node associated with it. The cluster head node is responsible for collecting all the sensing data sent by all the cluster member nodes it manages and forwarding them to the central controller, thereby significantly reducing the energy consumption of the network. However, traditional clustering strategies usually only focus on the energy consumption of sensor nodes, fail to take into account other key performance indicators for comprehensive evaluation, and are mainly designed for static network topology structures, that is, they are not suitable for monitoring movable target points, making it difficult for wireless sensor networks to meet the monitoring accuracy requirements when applied in smart city scenarios. The scope of application of traditional clustering strategies is limited.

[0053] In view of this, the embodiments of the present application provide a dynamic clustering method, device, electronic device and medium for a wireless sensor network. The scheme takes into account the availability of the wireless sensor network in an actual scenario with multiple movable target points, and evaluates the coverage factor of the wireless sensor network based on the current position distribution of the sensor nodes and the target points, and evaluates the energy factor of the wireless sensor network based on the position distribution of the sensor nodes and the central controller and the current remaining energy of the sensor nodes themselves. After 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.

[0054] A method for dynamic clustering of wireless sensor networks provided in an embodiment of the present application relates to the technical field of wireless sensor networks, and can be applied to terminals, servers, or software running in terminals or servers. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, and a vehicle-mounted terminal, etc., but is not limited thereto; the server side can be configured as an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms, and the server can also be a node server in a blockchain network; the software can be an application that implements the above-mentioned method for dynamic clustering of wireless sensor networks, etc., but is not limited to the above forms.

[0055] The present application can be used in many general or special computer system environments or configurations. For example: 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, distributed computing environments including any of the above systems or devices, etc. The present 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. The present application can also be practiced in distributed computing environments, in which tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0056] Figure 1 It is a topological diagram of a wireless sensor network provided in an embodiment of the present application. The wireless sensor network includes multiple sensor nodes and a central controller. The sensing range of each sensor node is the same. The wireless sensor network is mainly used to monitor multiple movable 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 fixed in position or can change in position over time. In the present application, it is preferred to consider the situation that the central controller and each sensor node are fixed in position.

[0057] Figure 2 is an optional flow chart of a wireless sensor network dynamic clustering method provided in an embodiment of the present application. Figure 2 The method is mainly applied to the central controller, and the method may include but is not limited to steps S101 to S104:

[0058] Step S101, receiving local information sent by multiple sensor nodes in the current time slot to determine the positions and residual energy of the multiple sensor nodes and the positions of multiple target points in the current time slot;

[0059] Step S102, determining coverage scores of the plurality of sensor nodes in the current time slot according to the positions of the plurality of sensor nodes and the positions of the plurality of target points in the current time slot;

[0060] Step S103, determining energy scores of the multiple sensor nodes in the current time slot according to the positions and residual energies of the multiple sensor nodes in the current time slot and the position of the central controller;

[0061] Step S104: determining the optimal clustering scheme of the wireless sensor network in the current time slot according to the positions of multiple target points, the position of the central controller, and the positions, coverage scores, and energy scores of multiple sensor nodes in the current time slot.

[0062] Steps S101 to S104 shown in the embodiment of the present application formulate a more reasonable clustering scheme by comprehensively considering the mobility of the target points and the coverage factors and energy factors of the wireless sensor network, which is conducive 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 position and remaining energy of the sensor node itself and the relative position information between the sensor node itself and each target point it covers, and the relative position information includes distance and azimuth. After receiving the local information sent by multiple sensor nodes, the central controller collects and analyzes the information. The position of the target point can be inferred by using the positions of different sensor nodes themselves and the distances between these sensor nodes themselves and the same target point. The position of the target point can also be inferred for any sensor node covering the target point based on the position of the sensor node and the distance and azimuth between the sensor node and the target point. The present application does not limit this.

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

[0065] Step S201, determining the coverage status of the multiple sensor nodes to the multiple target points in the current time slot according to the positions of the multiple target points and the positions of the multiple sensor nodes in the current time slot;

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

[0067] Specifically, for each target point, according to the position of the target point and the positions of multiple sensor nodes in the current time slot, the distance between the target point and each sensor node in the current time slot is calculated, and then the target point falls within the sensing range of the sensor node as a constraint, all sensor nodes that meet the constraint are selected from multiple sensor nodes and the corresponding coverage set of the target point in the current time slot is generated, which can be defined by the following expression:

[0068]

[0069] In the formula, is the corresponding covering set of the target point n in the current time slot t, M s is the set formed by all sensor nodes included in the wireless sensor network, and m is the set M s The sensor nodes included in is the position of sensor node m at the current time slot t, is the position of the target point n at the current time slot t, is the distance between the target point n and the sensor node m at the current time slot t, R s is 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 screened out from the coverage set corresponding to the target point in the current time slot, and the coverage state of the target point by the screened out sensor node is determined to be the standard coverage state, and the coverage state of the target point by all sensor nodes that are not screened out in the coverage set corresponding to the target point in the current time slot is determined to be the redundant coverage state; in addition, since other sensor nodes that are not 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 to the target point can be set to invalid.

[0071] Step S202: for each sensor node, according to the coverage status of the sensor node to 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, which can be calculated using the following expression:

[0072]

[0073] In the formula, CS m (t) is the coverage score of sensor node m at the current time slot t, is the standard coverage number of sensor node m in the current time slot t, indicating the coverage of sensor node m to target points for standard coverage, C s (t) is the unit fraction of sensor nodes participating in the standard coverage at the current time slot t, is the number of redundant coverage of sensor node m in the current time slot t, indicating the redundant coverage of sensor node m in the current time slot t. target points for redundant coverage, C r (t) is the unit fraction of sensor nodes participating in redundant coverage at the current time slot t, and C s (t) and C r (t) are all positive values.

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

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

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

[0077] The second situation: When and When , the sensor node m has no coverage for multiple target points in the current time slot t;

[0078] The third situation: When and When , the sensor node m performs mixed coverage on multiple target points in the current time slot t;

[0079] The fourth situation: When and When , the sensor node m performs full standard coverage of multiple target points in the current time slot t;

[0080] In order to ensure the coverage performance of wireless sensor networks, sensor nodes with full redundant coverage and no coverage should be given priority as cluster heads, and sensor nodes with mixed coverage or full standard coverage should be avoided as cluster heads. Assuming that 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 considering selecting a sensor node as a cluster head from these four sensor nodes, the first sensor node should be given priority, followed by the second sensor node, and finally the third sensor node or the fourth sensor node. For this purpose, the unit fraction C of the sensor node participating in the standard coverage at the current time slot t is s (t) and the unit fraction C of sensor nodes participating in redundant coverage at the current time slot t r (t) should satisfy the following relationship:

[0081]

[0082] In the formula, is the maximum value of the redundant coverage quantity of all sensor nodes contained in the wireless sensor network at the current time slot t, It is the minimum value of the standard coverage number of all sensor nodes contained in the wireless sensor network at the current time slot t.

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

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

[0085] Step S301: for each sensor node, the sensor node is used as a cluster head, and according to the positions of multiple sensor nodes in the current time slot, all sensor nodes that are closest to the cluster head and match the given number of cluster members are screened out from multiple sensor nodes, and then all the screened out sensor nodes are used as all cluster members managed by the cluster head;

[0086] Step S302: Determine 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, and the remaining energy and position 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, the above step S302 may include but is not limited to steps S401 to S403:

[0088] Step S401: According to 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, which can be calculated using the following expression:

[0089]

[0090] Wherein, m = CH 0 , is the cluster head CH in the current time slot t 0 The corresponding intra-cluster communication energy consumption is The cluster head CH 0 The set of all managed cluster members, L d is the size of the sensor node’s perception data packet, and the size of each sensor node’s perception data packet is the same, j is the set The jth cluster member contained in j S (t) is the position of the jth cluster member at the current time slot t, is the cluster head CH in the current time slot t 0 The location of E t (x,y) represents the transmitter transmission energy consumption function included in the first-order radio energy consumption model.

[0091] Step S402: According to the position of the central controller and the position of 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, which can be calculated using the following expression:

[0092]

[0093] Wherein, m = CH 0 , is the cluster head CH in the current time slot t 0 The corresponding inter-cluster communication energy consumption, ρ is the data aggregation rate, M is the number of all sensor nodes contained in the wireless sensor network, and G is the number of clusters that can be divided in the wireless sensor network. That is, G is an artificially given value and can be flexibly adjusted according to actual application scenarios and requirements. represents the number of members in a given cluster, r K (t) is the position of the central controller K at the current time slot t.

[0094] Step S403: Determine the energy score of the cluster head in the current time slot according to the remaining energy of the cluster head in the current time slot and the inter-cluster communication energy consumption and intra-cluster communication energy consumption corresponding to the cluster head, which can be calculated using the following expression:

[0095]

[0096] Wherein, m = CH 0 ,ES m (t) is the cluster head CH in the current time slot t 0 The energy score, is the cluster head CH in the current time slot t 0 of remaining energy.

[0097] In the above step S103, by performing a comprehensive analysis based on the residual energy of the sensor node and the intra-cluster communication distance and inter-cluster communication distance related to the sensor node, the energy state of the sensor node can be directly and effectively evaluated; compared with the solution proposed in some existing technologies of weighted summing the relevant communication distance and residual 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] In addition, the following description is made for the first-order radio energy consumption model mentioned in step S401 above:

[0099] The 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 transmission energy consumption function can be expressed as follows:

[0101]

[0102] The receiver receiving energy consumption function can be expressed as follows:

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

[0104] In the formula, E t (x,y) is the energy consumption function of the transmitter transmission, x is the size of the data packet transmitted by the transmitter, y is the wireless transmission distance, E elec is the energy consumed by the transmitting circuit and the receiving circuit during operation, ε fs is the signal power amplification factor under the free space model, ε amp is the signal power amplification factor under the multipath fading channel model, d 0 is a given wireless transmission distance threshold, E r (z) is the receiver receiving energy consumption function, and z is the size of the data packet received by the receiver.

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

[0106] Step S501: Determine the priority scores of the multiple sensor nodes in the current time slot according to the energy scores and coverage scores of the multiple sensor nodes in the current time slot, which can be calculated using the following expression:

[0107]

[0108]

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

[0110] Step S502: call the positions of multiple target points and multiple sensor nodes originally stored in all historical time slots, all historical time slots are before the current time slot, and then combine the priority scores and positions of multiple sensor nodes and the positions of 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.

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

[0112] Among them, 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: Generate multiple optional clustering schemes that match the maximum number of clusters based on the priority scores of multiple sensor nodes in the current time slot; wherein each optional clustering scheme records the number of optional clusters and all clusters that are allowed to be formed and match the number of optional clusters, and the priority score of each sensor node that serves as a cluster head in all clusters is higher than the priority score of each sensor node that serves 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 according to the priority scores of multiple sensor nodes in the current time slot. This implementation 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 is recorded as G max , setting the initial number of clusters to 1, selecting a sensor node with the highest priority score in the current time slot from multiple sensor nodes as a cluster head, and using all sensor nodes except the cluster head in the multiple sensor nodes as all cluster members managed by the cluster head, thereby obtaining the first optional clustering scheme; increasing the current number of clusters to 2, selecting two sensor nodes with the highest priority score in the current time slot from multiple sensor nodes as two cluster heads, and all sensor nodes except the two cluster heads in the multiple sensor nodes are assigned cluster members according to the nearest neighbor principle to form two clusters respectively managed by the two cluster heads, thereby obtaining the second optional clustering scheme; increasing the current number of clusters to 3, selecting three sensor nodes with the highest priority score in the current time slot from multiple sensor nodes as three cluster heads, and all sensor nodes except the three cluster heads in the multiple sensor nodes are assigned cluster members according to the nearest neighbor principle to form three clusters respectively managed by the three cluster heads, thereby obtaining the third optional clustering scheme; according to this implementation method, until the current number of clusters is increased to G max And get the corresponding G max Optional clustering schemes.

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

[0117] Step S504: determining the total network energy consumption of multiple optional clustering schemes according to the position of the central controller, the positions of multiple target points and the positions of multiple sensor nodes in the current time slot.

[0118] Specifically, for each cluster allowed to be formed recorded in each optional clustering scheme, the cluster contains a sensor node as a cluster head and multiple sensor nodes as cluster members. The energy consumption value of the cluster head in the current time slot is calculated based on the position of the cluster head and the position of the central controller in the current time slot, and the energy consumption value of each cluster member 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 values ​​of all sensor nodes included in the cluster are added 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 recorded in the optional clustering scheme are calculated, and finally the energy consumption values ​​of all clusters are added to obtain the total network energy consumption of the optional clustering scheme.

[0119] The energy consumption value of the 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) is the energy consumption value of cluster head CH in the current time slot t, is the data aggregation energy consumption of cluster head CH in the current time slot t, is the communication energy consumption of cluster head CH in the current time slot t, E DA is the data aggregation energy consumption coefficient, M CH is the set of all cluster members managed by the cluster head CH, L m (t) is the set M CH The perceived packet size of cluster member m contained in E t (x,y) is the transmitter transmission energy consumption function, L CH (t) is the aggregated data packet size of cluster head CH in the current time slot t, is the position of cluster head CH in the current time slot t, L c To control the packet size, E r (z) is the receiver receiving energy 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) is the set M in the current time slot t CH The energy consumption value of cluster member m contained in is the set M in the current time slot t CH The data-aware energy consumption of cluster member m contained in is the set M in the current time slot t CH The communication energy consumption of cluster member m is included in E s is the perceived energy consumption coefficient, N m For the set M cH The set formed by all target points within the perception range of cluster member m, is the set M in the current time slot t CH The location of the cluster member m contained in is the position of the target point n contained in the set N at the current time slot t.

[0130] Step S505: Filter out the optional clustering scheme with the minimum total network energy consumption from multiple optional clustering schemes, and use 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 smallest total network energy consumption among multiple optional clustering schemes, 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 in cluster heads will lead to an increase in the number of clusters, thereby causing a decrease in network coverage. This application preferably selects the optional clustering scheme with the smallest number of recorded 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 the above step S104, 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, which is beneficial to reducing network energy consumption, avoiding resource waste, and effectively extending the network service time.

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

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

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

[0136]

[0137] In the formula, is the initial average network coverage in all time slots, P τ (CH 1 ) is the initial network coverage rate in time slot τ, N is the number of multiple target points included in the wireless sensor network, The cluster head CH 1 The cluster head CH is the set of all cluster members managed by it. 1 is the sensor node with the highest priority score among multiple sensor nodes. is the set in time slot τ The cluster members m contained in 1 location, is the position of the target point n contained in the wireless sensor network, u(a) is the indicator function, when a>0, u(a)=1, when a≤0, u(a)=0.

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

[0139] Specifically, k sensor nodes with the highest priority scores are selected from multiple sensor nodes, and the selected k sensor nodes are used as k cluster heads to form a cluster head set, denoted as CH total_k ={CH 1 ,CH 2 ,...,CH k}, except for the cluster head set CH total_k All sensor nodes except total_k , and then according to the positions of multiple target points in all time slots and the cluster member set M totalk The positions of all sensor nodes contained in the equation are calculated using the following expression to obtain the average network coverage in all time slots:

[0140]

[0141] In the formula, is the average network coverage in all time slots, P τ (CH total_k ) is the average network coverage rate in time slot τ, is the cluster member set M in time slot τ total_k The cluster members m contained in 2 location.

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

[0143] Among them, 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: compare the initial average network coverage in all time slots with the network coverage threshold to 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 executing the above step S104, according to all the clusters allowed to be formed recorded in the optimal clustering scheme, for each cluster containing a sensor node as a cluster head and multiple sensor nodes as cluster members, the central controller allocates 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 the central controller allocates cluster tasks to each sensor node as a cluster member so that it can subsequently perceive the target point and report the relevant perception data to the associated cluster head, thereby completing the entire network clustering task.

[0145] A dynamic clustering method for a wireless sensor network proposed in an embodiment of the present application takes into account the availability of the wireless sensor network in an actual scenario with multiple movable target points, evaluates the coverage factor of the wireless sensor network based on the current position distribution of the sensor nodes and the target points, and evaluates the energy factor of the wireless sensor network based on the position distribution of the sensor nodes and the central controller and the current remaining energy of the sensor nodes themselves. After 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] See also Figure 3 The embodiment of the present application also provides a wireless sensor network dynamic clustering device, which can implement the above-mentioned 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. The device includes:

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

[0148] The second module 702 is used to determine the coverage scores of the multiple sensor nodes in the current time slot according to the positions of the multiple target points and the positions of the multiple sensor nodes in the current time slot;

[0149] The third module 703 is used to determine the energy scores of the multiple sensor nodes in the current time slot according to the position of the central controller in the current time slot and the remaining energy and position of the multiple sensor nodes;

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

[0151] It can be understood that the contents of the above method embodiments are all applicable to the present system embodiments, the functions specifically implemented by the present system embodiments 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.

[0152] The embodiment of the present application also provides an electronic device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the above-mentioned wireless sensor network dynamic clustering method when executing the computer program. The electronic device may include any intelligent terminal such as a tablet computer and a car computer.

[0153] It can be understood that the contents of the above method embodiments are all applicable to the present device embodiments, the functions specifically implemented by the present device embodiments 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] See also Figure 4 , Figure 4 The hardware structure of an electronic device according to another embodiment is shown. The electronic device includes:

[0155] The processor 801 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an 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 the present application;

[0156] The memory 802 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 802 can store an operating system and other application programs. When the technical solution provided in the embodiment of the present application is implemented by software or firmware, the relevant program code is stored in the memory 802, and the processor 801 calls and executes the technical solution provided in the embodiment of the present application;

[0157] Input / output interface 803, used to implement information input and output;

[0158] The communication interface 804 is used to realize the communication interaction between the device and other devices. The communication can be realized through a wired manner (such as USB, network cable, etc.) or a wireless manner (such as mobile network, WI FI, Bluetooth, etc.);

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

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

[0161] The embodiment of the present application further provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned wireless sensor network dynamic clustering method is implemented.

[0162] It can be understood that the contents of the above method embodiments are all applicable to the present storage medium embodiments, the functions specifically implemented by the present storage medium embodiments 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.

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

[0164] The embodiments described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

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

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

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

[0168] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0169] It should be understood that in the present application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0170] In the several embodiments provided in the present 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 only schematic. For example, the division of the above units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of systems or units, which can be electrical, mechanical or other forms.

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

[0172] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0173] If the integrated unit is implemented in the form of 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 the present application, 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, and the computer software product is stored in a storage medium, including multiple instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, referred to as ROM), random access memory (Random Access Memory, referred to as RAM), disk or optical disk and other media that can store programs.

[0174] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but the scope of the rights of the present invention is not limited thereto. Any modification, equivalent substitution and improvement made by a person skilled in the art without departing from the scope and essence of the present invention should be within the scope of the rights of the present invention.

Claims

1. A dynamic clustering method for wireless sensor networks, characterized in that: The wireless sensor network includes a central controller and a plurality of sensor nodes, and the wireless sensor network is used to monitor a plurality of movable target points; The method is applied to the central controller, and the method comprises: Receiving local information sent by the multiple sensor nodes in the current time slot to determine the positions and residual energies of the multiple sensor nodes and the positions of the multiple target points in the current time slot; Determining coverage scores of the multiple sensor nodes at the current time slot according to the positions of the multiple sensor nodes and the positions of the multiple target points at the current time slot; Determining energy scores of the multiple sensor nodes at the current time slot according to the positions and residual energies of the multiple sensor nodes at the current time slot and the position of the central controller; According to 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, an optimal clustering scheme of the wireless sensor network in the current time slot is determined.

2. The wireless sensor network dynamic clustering method according to claim 1, characterized in that: Determining the coverage scores of the multiple sensor nodes at the current time slot according to the positions of the multiple sensor nodes and the positions of the multiple target points at the current time slot comprises: Determine, according to the positions of the multiple sensor nodes and the positions of the multiple target points in the current time slot, the coverage status of the multiple sensor nodes to the multiple target points in the current time slot, the coverage status including a standard coverage status or a redundant coverage status, the standard coverage status indicates that the target point falls within the perception range of the nearest sensor node, and the redundant coverage status indicates that the target point falls within the perception range of a non-nearest sensor node; For each of the sensor nodes, according to the coverage status of the sensor node to the multiple target points in the current time slot, the standard coverage quantity and the 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 wireless sensor network dynamic clustering method according to claim 1, characterized in that: Determining the energy scores of the multiple sensor nodes at the current time slot according to the positions and residual energies of the multiple sensor nodes at the current time slot and the position of the central controller comprises: For each of the sensor nodes, taking the sensor node as a cluster head; According to the positions of the multiple sensor nodes in the current time slot, all sensor nodes which are closest to the cluster head and match the given number of cluster members are selected from the multiple sensor nodes, and all the sensor nodes are used as all cluster members; An energy score of the cluster head at the current time slot is determined according to the position of the central controller, the positions of all cluster members, and the position and residual energy of the cluster head at the current time slot.

4. The wireless sensor network dynamic clustering method according to claim 3, characterized in that: Determining the energy score of the cluster head at the current time slot according to the position of the central controller, the positions of all cluster members, and the position and residual energy of the cluster head at the current time slot includes: Determine the intra-cluster communication energy consumption corresponding to the cluster head in the current time slot according to the position of the cluster head and the positions of all cluster members in the current time slot; Determine the inter-cluster communication energy consumption corresponding to the cluster head in the current time slot according to the position of the cluster head and the position of the central controller in the current time slot; An energy score of the cluster head in the current time slot is determined according to the residual energy of the cluster head in the current time slot and the intra-cluster communication energy consumption and inter-cluster communication energy consumption corresponding to the cluster head.

5. The wireless sensor network dynamic clustering method according to claim 1, characterized in that: Determining the optimal clustering scheme of the wireless sensor network at the current time slot according to 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 at the current time slot includes: Determining priority scores of the multiple sensor nodes at the current time slot according to the coverage scores and energy scores of the multiple sensor nodes at the current time slot; Recalling the stored positions of the multiple sensor nodes and the positions of the multiple target points in all historical time slots before the current time slot, combining the positions and priority scores of the multiple sensor nodes and the positions of the multiple target points in the current time slot, and determining the maximum number of clusters of the wireless sensor network in the current time slot; Generate a plurality of optional clustering schemes matching the maximum number of clusters according to the priority scores of the plurality of sensor nodes at the current time slot, each of the optional clustering schemes recording the number of optional clusters and all clusters that are allowed to be formed and matching the number of optional clusters, in all the 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 of the optional clustering schemes is different; Determine the total network energy consumption of the multiple optional clustering schemes according to the positions of the multiple sensor nodes, the positions of the multiple target points and the position of the central controller at the current time slot; The optional clustering scheme with the minimum total network energy consumption is selected from the multiple optional clustering schemes to serve as the optimal clustering scheme of the wireless sensor network in the current time slot.

6. The wireless sensor network dynamic clustering method according to claim 5, characterized in that: The calling of the stored positions of the plurality of sensor nodes and the positions of the plurality of target points in all historical time slots before the current time slot, combining the positions and priority scores of the plurality of sensor nodes and the positions of the plurality of target points in the current time slot, and determining the maximum number of clusters of the wireless sensor network in the current time slot comprises: When the multiple sensor nodes form a cluster with the sensor node with the highest priority score as a cluster head, determining the initial average network coverage in all time slots according to the positions of the multiple sensor nodes and the positions of the multiple target points in all time slots, wherein all time slots include the current time slot and all historical time slots; The number of clusters is set to 2, and an average network coverage rate in all time slots is determined according to 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 positions of the multiple target points in all time slots; When the average network coverage rate in all the time slots is greater than or equal to the reference value, the number of clusters is increased by 1 and used as the new number of clusters, and then returning to the step of determining the average network coverage rate in all the time slots according to 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 positions of the multiple target points in all the time slots; When the average network coverage rate in all the time slots is less than the reference value, subtracting 1 from the number of clusters as the maximum number of clusters of the wireless sensor network in the current time slot; The reference value is determined according to the relationship between the initial average network coverage in all the time slots and a preset network coverage threshold.

7. The method for dynamic clustering of wireless sensor networks according to claim 6, characterized in that: The reference value is obtained by: When the initial average network coverage rate in all the time slots is less than the network coverage rate threshold, determining the reference value to be the initial average network coverage rate in all the time slots; When the initial average network coverage in all the time slots is greater than or equal to the network coverage threshold, the reference value is determined to be the network coverage threshold.

8. A wireless sensor network dynamic clustering device, characterized in that: The wireless sensor network includes a central controller and a plurality of sensor nodes, and the wireless sensor network is used to monitor a plurality of movable target points; The device is deployed in the central controller, and the device includes: The first module is used to receive the local information sent by the multiple sensor nodes in the current time slot to determine the positions and residual energy of the multiple sensor nodes and the positions of the multiple target points in the current time slot; A second module is used to determine the coverage scores of the multiple sensor nodes in the current time slot according to the positions of the multiple sensor nodes and the positions of the multiple target points in the current time slot; A third module is used to determine the energy scores of the multiple sensor nodes in the current time slot according to the positions and residual energies 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 according to 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.

9. An electronic device, characterized in that: The electronic device comprises a memory and a processor, the memory stores a computer program, and the processor implements the method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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