Clustering maintenance method and device, equipment and storage medium

Abstract

The invention provides a clustering maintenance method and device, equipment and a storage medium, and the method applied to a non-cluster head node comprises the steps: generating a first node score; obtaining a second node score and a cluster evaluation index; wherein the second node score is generated and sent by other non-cluster head nodes, and the cluster evaluation index is generated and sent by a cluster head node of a cluster where the non-cluster head nodes are located; and determining that the cluster evaluation index meets a preset condition, and performing cluster recombination based on the first node score and the second node score. Through the technical scheme of the invention, the problems of uneven cluster head load and poor network stability in a traditional clustering method can be solved, and the life cycle of a cluster network is prolonged.

Description

Technical Field

[0001] This application relates to the technical field of wireless ad-hoc networks, and in particular, to a clustering maintenance method, apparatus, device, and storage medium. Background Art

[0002] In the related art, the clustering algorithms generally have the following deficiencies: 1. Only select cluster heads based on the attributes of the nodes themselves; 2. Lack of a quantitative evaluation mechanism for the overall performance of the cluster; 3. Lack of consideration for the overall performance of the cluster when a node chooses to join a certain cluster; 4. Unable to flexibly adjust the performance of the clustering algorithm according to the requirements of different application scenarios. Summary of the Invention

[0003] This application aims to solve at least one of the technical problems in the related art to some extent.

[0004] In a first aspect, this application proposes a clustering maintenance method, which is applied to non-cluster-head nodes in a clustering network. The method includes: generating a first node score; obtaining a second node score and a cluster evaluation index; where the second node score is generated and sent by other non-cluster-head nodes, and the cluster evaluation index is generated and sent by the cluster head node of the cluster where the non-cluster-head node is located; determining that the cluster evaluation index meets a preset condition, and performing cluster reorganization based on the first node score and the second node score.

[0005] In one implementation, the performing cluster reorganization based on the first node score and the second node score includes: determining that the first node score is greater than the second node score, and the difference between the first node score and the maximum value of the first node score and the second node score is greater than a preset threshold, and obtaining the remaining energy of itself; determining that the remaining energy is greater than a preset energy threshold, and sending a cluster head declaration message; where the cluster head declaration message is used to declare itself as the new cluster head of its own cluster; generating and sending a first cluster reliability evaluation value; where the first cluster reliability evaluation value is used for other non-cluster-head nodes to perform cluster selection.

[0006] In one implementation, the performing cluster reorganization based on the first node score and the second node score includes: determining that there is a score in the second node score that is greater than the first node score, and obtaining at least one second cluster reliability evaluation value; where the second cluster reliability evaluation value is the evaluation value sent by the cluster head node after cluster reorganization; joining the cluster corresponding to the maximum value of the at least one second cluster reliability evaluation value.

[0007] In one implementation, generating the first node score includes: obtaining network performance metrics; where the network performance metrics include at least one of the following: energy score, link quality improvement rate, node-to-cluster ratio, cluster-to-degree ratio, centrality, capacity utilization rate; obtaining the first node score based on the network performance metrics.

[0008] In one implementation, the cluster evaluation metrics include at least one of the following: the number of nodes within the cluster, the remaining energy of the cluster head node, the cluster - to - cluster communication efficiency evaluation value, the evaluation value of the distribution of nodes within the cluster, the evaluation value of the stability of the cluster structure, the evaluation value of the balance of energy consumption, the cluster stability score, the third cluster reliability evaluation value; determining that the cluster evaluation metrics meet the preset conditions includes: in response to at least one of the cluster evaluation metrics being less than or equal to the corresponding preset threshold, determining that the cluster evaluation metrics meet the preset conditions.

[0009] In a second aspect, the present application proposes a clustering maintenance method, characterized in that the method is applied to a cluster head node in a clustered network, and the method includes: obtaining cluster evaluation metrics; sending the cluster evaluation metrics; determining that a cluster head declaration message is obtained, and ceding the cluster head authority.

[0010] In one implementation, the cluster evaluation metrics include at least one of the following: the number of nodes within the cluster, the remaining energy of the cluster head node, the cluster - to - cluster communication efficiency evaluation value, the evaluation value of the distribution of nodes within the cluster, the evaluation value of the stability of the cluster structure, the evaluation value of the balance of energy consumption, the cluster stability score, the cluster reliability evaluation value.

[0011] In a third aspect, the present application proposes a clustering maintenance device, which is applied to a non - cluster head node, and the device includes: a first processing module, configured to generate a first node score; an obtaining module, configured to obtain a second node score and cluster evaluation metrics; where the second node score is generated and sent by other non - cluster head nodes, and the cluster evaluation metrics are generated and sent by the cluster head node of the cluster where the non - cluster head node is located; a second processing module, configured to determine that the cluster evaluation metrics meet the preset conditions, and perform cluster reorganization based on the first node score and the second node score.

[0012] In one implementation, the second processing module can be used to: determine that the first node score is greater than the second node score, and the difference between the first node score and the maximum value of the first node score and the second node score is greater than a preset threshold, and obtain its own remaining energy; determine that the remaining energy is greater than a preset energy threshold, and send a cluster head declaration message; where the cluster head declaration message is used to declare itself as the new cluster head of its own cluster; generate and send a first cluster reliability evaluation value; where the first cluster reliability evaluation value is used by other non - cluster head nodes for cluster selection.

[0013] In one implementation, the second processing module may be configured to: determine that there is a score in the second node scores that is greater than the first node score, and obtain at least one second cluster reliability evaluation value; wherein, the second cluster reliability evaluation value is the evaluation value sent by the cluster head node after cluster reorganization; and join the cluster corresponding to the maximum value among the at least one second cluster reliability evaluation value.

[0014] In one implementation, the first processing module may be configured to: obtain network performance metrics; wherein, the network performance metrics include at least one of the following: energy score, link quality improvement rate, node-to-cluster ratio, cluster-to-degree ratio, centrality, capacity utilization rate; and obtain the first node score based on the network performance metrics.

[0015] In one implementation, the cluster evaluation metrics include at least one of the following: the number of nodes within the cluster, the remaining energy of the cluster head node, the cluster-to-cluster communication efficiency evaluation value, the node distribution evaluation value within the cluster, the cluster structure stability evaluation value, the energy consumption balance evaluation value, the cluster stability score, the third cluster reliability evaluation value; the second processing module may be configured to: determine that in response to at least one of the cluster evaluation metrics being less than or equal to a corresponding preset threshold, it is determined that the cluster evaluation metrics meet the preset conditions.

[0016] In a fourth aspect, the present application provides a cluster maintenance device, which is applied to a cluster head node in a clustered network. The device includes: a first processing module, configured to obtain cluster evaluation metrics; a sending module, configured to send the cluster evaluation metrics; and a second processing module, configured to determine that a cluster head declaration message is obtained and transfer the cluster head authority.

[0017] In one implementation, the cluster evaluation metrics include at least one of the following: the number of nodes within the cluster, the remaining energy of the cluster head node, the cluster-to-cluster communication efficiency evaluation value, the node distribution evaluation value within the cluster, the cluster structure stability evaluation value, the energy consumption balance evaluation value, the cluster stability score, the cluster reliability evaluation value.

[0018] In a fifth aspect, the present application provides an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the cluster maintenance method as described in the first aspect.

[0019] In a sixth aspect, the present application provides an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the cluster maintenance method as described in the second aspect.

[0020] In a seventh aspect, the present application provides a computer-readable storage medium storing instructions that, when executed, implement the method as described in the first aspect.

[0021] In an eighth aspect, the present application provides a computer-readable storage medium storing instructions that, when executed, implement the method as described in the second aspect.

[0022] In a ninth aspect, the present application provides a computer program product including a computer program that, when executed by a processor, implements the steps of the cluster maintenance method as described in the first aspect.

[0023] In a tenth aspect, the present application provides a computer program product including a computer program that, when executed by a processor, implements the steps of the cluster maintenance method as described in the second aspect.

[0024] For the cluster maintenance method, device, equipment, and storage medium provided by the present application, the cluster head node can obtain and send cluster evaluation metrics, so that when the cluster evaluation metrics meet the preset conditions, the non-cluster head nodes can perform cluster reorganization based on their own node scores and the node scores of other non-cluster head nodes. This can solve the problems of uneven cluster head load and poor network stability in traditional clustering methods and improve the lifecycle of the cluster network.

[0025] Additional aspects and advantages of the present application will be given in part in the following description, become apparent in part from the following description, or be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The above and / or additional aspects and advantages of the present application will become apparent and be readily understood from the following description of the embodiments in conjunction with the drawings, where:

[0027] Figure 1 is a flowchart of a cluster maintenance method provided by an embodiment of the present application;

[0028] Figure 2 is a flowchart of another cluster maintenance method provided by an embodiment of the present application;

[0029] Figure 3 is a flowchart of yet another cluster maintenance method provided by an embodiment of the present application;

[0030] Figure 4 is a flowchart of yet another cluster maintenance method provided by an embodiment of the present application;

[0031] Figure 5 is a schematic structural diagram of a cluster maintenance device provided by an embodiment of the present application;

[0032] Figure 6 It is a schematic structural diagram of another cluster maintenance device provided by an embodiment of the present application;

[0033] Figure 7 It is a schematic structural diagram of an electronic device provided by an embodiment of the present application. Specific Embodiments

[0034] The embodiments of the present application will be described in detail below. The examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to explain the present application, and should not be construed as limiting the present application.

[0035] It should be noted that the cluster maintenance method and device of the embodiments of the present application can be applied to an ad hoc communication system including at least one cluster. Each network node in the system is assigned a unique node identifier, and the system includes the following preset cycle parameters: a boot period for initial cluster formation; a control period for controlling packet broadcast; a declaration period for cluster head selection; an inspection period for neighbor status inspection; and a cluster selection period for cluster member assignment. Among them, the control period is less than the topology change period, and can be set to 1.5 seconds to ensure that the network state is updated in a timely manner. The cycle length can be appropriately increased in a network with a high node density; to avoid overly frequent cluster head changes and improve network stability, the declaration period is an integer multiple of the control period (for example, 5 times); to give sufficient time to compensate for link failures and packet losses, the inspection period needs to be greater than the control packet period (for example, 3 times the control packet period); the cluster selection period can be equal to the control period to simplify the system synchronization mechanism and ensure that the cluster member selection is based on the latest network state information for cluster maintenance.

[0036] The cluster maintenance method and device of the embodiments of the present application will be described below with reference to the accompanying drawings.

[0037] Figure 1 It is a schematic flowchart of a cluster maintenance method provided by an embodiment of the present application. As Figure 1 shown, this method can be applied to any non-cluster head node in a clustered network, and this method may include but is not limited to the following steps:

[0038] Step S101: Generate a first node score.

[0039] Among them, in the embodiments of the present application, the first node score is the node performance score corresponding to the non-cluster head node.

[0040] Exemplarily, a non-cluster head node obtains relevant information that can characterize its own communication performance, and generates a first node score for evaluating the node communication performance based on the above information. For example, the above relevant information may include, but is not limited to, information related to the energy level, link quality, connectivity, etc. of the node.

[0041] In some embodiments, the non-cluster head node broadcasts a control packet containing its own node score in each control period.

[0042] Exemplarily, the non-cluster head node can broadcast its own node score through a core clustering control packet, and the core clustering control packet may contain necessary cluster head selection information, such as packet type, node ID, cluster ID, node score.

[0043] In some embodiments, the generating of the first node score includes:

[0044] Step A1: Obtain communication performance metrics.

[0045] Wherein, the communication performance metrics include at least one of the following: energy score, link quality improvement rate, node-to-cluster degree ratio (NCDR), cluster-to-degree ratio (CDR), centrality, capacity utilization rate.

[0046] Exemplarily, the non-cluster head node obtains the consumed energy of the node according to the energy consumption of the node in different states and the corresponding working duration, obtains the remaining energy of the node according to the consumed energy and the nominal energy, and further obtains the ratio of the remaining energy to the nominal energy as the energy score.

[0047] Exemplarily, the non-cluster head node calculates the value of LQC (Link Quality Change) for each neighbor node, monitors the link quality using the received signal strength indicator (e.g., RSSI (Received Signal Strength Indication)), and calculates the difference between the current SINR (Signal to Interference plus Noise Ratio) and the historical average SINR. When the difference is greater than a preset first threshold, LQC is set to +1; when the difference is less than a preset second threshold, LQC is set to -1; when the difference is within the interval composed of the first threshold and the second threshold, LQC is set to 0. The number of links with LQC greater than or equal to 0 among all neighbors of the node is counted, and the ratio of this number of links to the total number of neighbors is calculated as the link quality improvement rate.

[0048] Exemplarily, the non-cluster head node counts the number of direct neighbor nodes, uses the maximum node degree among the neighbor nodes as the normalization factor, and calculates the ratio of its own current node degree to the normalization factor as the node-to-cluster degree ratio.

[0049] Exemplarily, the non-cluster head node constructs a connection graph based on the node neighbor relationship, uses the maximum clique search algorithm to find the maximum complete subgraph where the node is located, and calculates the ratio of the maximum clique size to the node degree to obtain the cluster-to-degree ratio.

[0050] Exemplarily, the non-cluster head node counts the average degree of all neighbor nodes and calculates the ratio of the average degree to the common degree as the centrality.

[0051] Exemplarily, the non-cluster head node counts the total number of control and data packets processed by the node and calculates the ratio of the processed data volume to the channel capacity as the cluster-to-degree ratio.

[0052] Step A2: Obtain the first node score based on the communication performance metrics.

[0053] Exemplarily, the non-cluster head node uses a normalized weighted calculation method to calculate and obtain the first node score in combination with the communication performance metrics.

[0054] Step S102: Obtain the second node score and the cluster evaluation metrics.

[0055] Among them, the second node score is generated and sent by other non-cluster head nodes, and the cluster evaluation metrics are generated and sent by the cluster head node of the cluster where the non-cluster head node is located.

[0056] It should be noted that in the embodiments of the present application, the method for each node to obtain its corresponding node score can be the same.

[0057] Exemplarily, the non-cluster head node obtains the second node score sent by other non-cluster head nodes and the cluster evaluation metrics sent by the cluster head of the cluster where it is located.

[0058] Among them, in the embodiments of the present application, the cluster evaluation metrics are sent by the cluster head node of each cluster and are evaluation metrics used to characterize relevant information such as the internal connection density and communication efficiency of the cluster.

[0059] Step S103: Determine that the cluster evaluation metrics meet the preset conditions, and perform cluster reorganization based on the first node score and the second node score.

[0060] In one implementation, the cluster evaluation metrics include at least one of the following: the number of nodes within the cluster, the remaining energy of the cluster head node, the evaluation value of the inter-cluster communication efficiency, the evaluation value of the distribution of nodes within the cluster, the evaluation value of the stability of the cluster structure, the evaluation value of the balance of energy consumption, the cluster stability score; determining that the cluster evaluation metrics meet the preset conditions includes: in the case where at least one of the cluster evaluation metrics is less than or equal to the corresponding preset threshold, determining that the cluster evaluation metrics meet the preset conditions.

[0061] Exemplarily, taking the cluster evaluation metrics including at least the number of nodes within the cluster as an example, if the number of nodes within the cluster is less than the preset numerical value, it is determined that the cluster evaluation metrics meet the preset conditions.

[0062] Exemplarily, taking the cluster evaluation metrics including at least the remaining energy of the cluster head node as an example, if the remaining energy of the cluster head node is less than or equal to the preset energy threshold (for example, 30% of the nominal energy of the node), it is determined that the cluster evaluation metrics meet the preset conditions.

[0063] Exemplarily, taking the cluster evaluation metrics including at least the evaluation value of the inter-cluster communication efficiency as an example, if the evaluation value of the inter-cluster communication efficiency is less than or equal to the corresponding preset threshold, it is determined that the cluster evaluation metrics meet the preset conditions.

[0064] Exemplarily, taking the cluster evaluation metrics including at least the evaluation value of the stability of the cluster structure as an example, if the evaluation value of the stability of the cluster structure is less than or equal to the corresponding preset threshold, it is determined that the cluster evaluation metrics meet the preset conditions.

[0065] Exemplarily, taking the cluster evaluation metrics including at least the evaluation value of the balance of energy consumption as an example, if the evaluation value of the balance of energy consumption is less than or equal to the corresponding preset threshold, it is determined that the cluster evaluation metrics meet the preset conditions.

[0066] Exemplarily, taking the cluster evaluation metrics including at least the cluster stability score as an example, if the cluster stability score is less than or equal to the preset score threshold, it is determined that the cluster evaluation metrics meet the preset conditions.

[0067] It should be noted that in the embodiments of the present application, nodes can obtain different cluster evaluation metrics within different preset periods.

[0068] Exemplarily, non-cluster head nodes can obtain the cluster reliability score sent by the cluster head node during the cluster selection period.

[0069] By implementing the embodiments of the present application, non-cluster head nodes can perform cluster reorganization based on node scores when the cluster evaluation metrics meet the preset conditions. It can solve the problems of uneven cluster head load and poor network stability in traditional clustering methods, and improve the lifespan of the cluster network.

[0070] In some embodiments, a non-cluster head node that meets the preset conditions can become the new cluster head node after cluster reorganization. As an example, please refer to Figure 2 , Figure 2 which is a schematic flowchart of another cluster maintenance method provided by an embodiment of the present application. This method can be applied to any non-cluster head node in a clustered network, such as Figure 2 shown, and this method may include but is not limited to the following steps:

[0071] Step S201: Generate a first node score.

[0072] In the embodiments of the present application, step S201 can be implemented in any one of the embodiments of the present application. The embodiments of the present application do not make any limitations in this regard and will not be elaborated further.

[0073] Step S202: Obtain a second node score and a cluster evaluation index.

[0074] In the embodiments of the present application, step S202 can be implemented in any one of the embodiments of the present application. The embodiments of the present application do not make any limitations in this regard and will not be elaborated further.

[0075] Step S203: Determine that the cluster evaluation index meets the preset conditions, and the first node score is greater than the second node score, and the difference between the first node score and the maximum value of the second node scores is greater than a preset threshold, and obtain its remaining energy.

[0076] Exemplarily, the non-cluster head node determines that the cluster evaluation index of the cluster it belongs to meets the preset conditions, and its own node score is greater than all the obtained second node scores, and the difference between its own node score and the maximum value of the second node scores is greater than the preset difference threshold, and obtains its remaining energy.

[0077] Step S204: Determine that the remaining energy is greater than a preset energy threshold, and send a cluster head declaration message.

[0078] Wherein, the cluster head declaration message is used to declare that it becomes the new cluster head of the cluster it belongs to.

[0079] Exemplarily, the non-cluster head node determines that its remaining energy is greater than the preset energy threshold, and broadcasts and sends a cluster head declaration message during the cluster declaration period. This cluster head declaration message is used to inform other nodes that the non-cluster head node becomes the new cluster head of the cluster it belongs to.

[0080] Step S205: Generate and send a first cluster reliability evaluation value.

[0081] Wherein, the first cluster reliability evaluation value is used for other nodes except the non-cluster head node to perform cluster selection.

[0082] Exemplarily, a first cluster reliability evaluation value is generated and sent. The first cluster reliability evaluation value is an evaluation value used to characterize the reliability of the cluster where it is located, and the first cluster reliability evaluation value is used by other nodes except itself for cluster selection.

[0083] Exemplarily, a non-cluster head node sends the first cluster reliability evaluation value during the cluster selection period.

[0084] By implementing the embodiments of the present application, non-cluster head nodes that meet the conditions can send cluster head declaration information to inform other nodes that they have become new cluster heads, and send a second cluster reliability evaluation value, so that other non-cluster head nodes can select a suitable cluster to join according to the at least one cluster reliability evaluation value obtained, thereby completing cluster reorganization. It can solve the problems of uneven cluster head load and poor network stability in traditional clustering methods, and improve the lifecycle of the cluster network.

[0085] In some embodiments, non-cluster head nodes that do not meet the preset conditions can select a new cluster to join according to the obtained cluster evaluation value. As an example, please refer to Figure 3 , Figure 3 is a schematic flowchart of another clustering maintenance method provided by the embodiments of the present application. As shown in Figure 3 shown, this method is applied to non-cluster head nodes in a clustered network, and this method may include but is not limited to the following steps:

[0086] Step S301: Generate a first node score.

[0087] In the embodiments of the present application, step S301 can be implemented in any one of the embodiments of the present application. The embodiments of the present application do not limit this and will not elaborate further.

[0088] Step S302: Obtain a second node score and a cluster evaluation index.

[0089] In the embodiments of the present application, step S301 can be implemented in any one of the embodiments of the present application. The embodiments of the present application do not limit this and will not elaborate further.

[0090] Step S303: Determine that the cluster evaluation index meets the preset conditions, and there is a score in the second node scores that is greater than the first node score, and obtain at least one second cluster reliability evaluation value.

[0091] Exemplarily, a non-cluster head node determines that there is at least one score in the obtained second node scores that is greater than its own score, and obtains a third cluster score. The third cluster score is the score sent by the cluster head after cluster reorganization.

[0092] It can be understood that the cluster heads after cluster reorganization include the new cluster heads generated during the cluster reorganization process and the original cluster heads that have not changed during the cluster reorganization process.

[0093] Step S303: Add the cluster corresponding to the maximum value among the at least one second cluster reliability evaluation value.

[0094] Exemplarily, a non-cluster head node selects the one with the highest second cluster reliability evaluation value as the target cluster reliability evaluation value, and adds the cluster corresponding to the target cluster reliability evaluation value.

[0095] By implementing the embodiments of the present application, non-cluster head nodes that do not meet the preset conditions can select appropriate clusters to join based on the cluster evaluation values sent by the cluster heads after cluster reorganization. It can solve the problems of uneven cluster head load and poor network stability in traditional clustering methods, and improve the lifespan of the cluster network.

[0096] The above embodiments of the present application illustrate the clustering maintenance method of the present application from the perspective of non-cluster head nodes. Next, the clustering maintenance method of the present application will be further described from the perspective of cluster head nodes.

[0097] Please refer to Figure 4 , Figure 4 which is a schematic flowchart of another clustering maintenance method provided by the embodiments of the present application. As Figure 4 shown, this method is applied to a cluster head in a clustered network, and this method may include but is not limited to the following steps:

[0098] Step S401: Obtain cluster evaluation metrics.

[0099] Among them, in the embodiments of the present application, the above cluster evaluation metrics include at least one of the following: the number of nodes in the cluster, the remaining energy of the cluster head node, the cluster intercommunication efficiency evaluation value, the cluster internal node distribution evaluation value, the cluster structure stability evaluation value, and the energy consumption balance evaluation value.

[0100] Exemplarily, the cluster head node analyzes the number of nodes in different clusters within the cluster, obtains the ratio of the average number of nodes in the cluster to the number of nodes in the cluster, and uses it as the cluster internal node distribution evaluation value.

[0101] Exemplarily, the cluster head node calculates the average capacity utilization rate of the nodes in the cluster, evaluates the ratio of the intra-cluster traffic to the inter-cluster traffic, analyzes the efficiency value of the data packet forwarding path, and calculates the cluster intercommunication efficiency evaluation value based on the above average capacity utilization rate, ratio, and efficiency value.

[0102] Exemplarily, the cluster head node calculates the average value of the link quality changes of all nodes in the cluster, evaluates the link state change trend, analyzes the influence value of node mobility on the cluster structure stability, and obtains the cluster structure stability evaluation value based on the above average value, change trend, and influence value.

[0103] Exemplarily, the cluster head node analyzes the variance of the energy consumption of the nodes within the cluster, evaluates the energy consumption ratio value between the cluster head and the ordinary nodes, and obtains an energy consumption balance evaluation value based on the above variance and ratio value.

[0104] Step S402: Send the cluster evaluation metrics.

[0105] Among them, in the embodiments of the present application, the cluster evaluation metrics include at least one of the following: the number of nodes within the cluster, the remaining energy of the cluster head node, the cluster - to - cluster communication efficiency evaluation value, the evaluation value of the distribution of nodes within the cluster, the evaluation value of the stability of the cluster structure, the energy consumption balance evaluation value, the cluster stability score, and the cluster reliability evaluation value.

[0106] In some embodiments, the cluster head node can calculate the cluster reliability evaluation value by using a normalized weighted algorithm in combination with the cluster evaluation metrics based on the cluster - to - cluster communication efficiency evaluation value, the evaluation value of the distribution of nodes within the cluster, the evaluation value of the stability of the cluster structure, the energy consumption balance evaluation value, and the cluster stability score.

[0107] Exemplarily, the cluster head node calculates the cluster reliability evaluation value based on the cluster - to - cluster communication efficiency evaluation value, the evaluation value of the distribution of nodes within the cluster, the evaluation value of the stability of the cluster structure, the energy consumption balance evaluation value, and the cluster stability score, and broadcasts the cluster reliability score during the cluster selection period.

[0108] Exemplarily, the cluster head node can broadcast the cluster reliability evaluation value through a cluster announcement packet, and the cluster announcement packet can also include the packet type, the cluster ID, the cluster reliability evaluation value, and the cluster size.

[0109] Step S403: Determine that a cluster head declaration message is obtained and transfer the cluster head authority.

[0110] Exemplarily, in response to obtaining a cluster head declaration message sent by a non - cluster - head node within the cluster, the cluster head node transfers the cluster head authority to the node that sent the cluster declaration message.

[0111] Exemplarily, the cluster head declaration message can include the node ID of the non - cluster - head node that sent this information.

[0112] In some embodiments, the above method further includes: obtaining the cluster evaluation metrics sent by the neighbor cluster head node; calculating the cluster reliability score after merging with the neighbor cluster based on the cluster evaluation metrics sent by the neighbor cluster head node; determining that the cluster reliability score after merging with the neighbor cluster is greater than a preset reliability score threshold, and merging with the neighbor cluster.

[0113] By implementing the embodiments of the present application, the cluster head node can generate and send a cluster score based on the obtained cluster evaluation metrics, so that non - cluster nodes can perform cluster reorganization when the cluster evaluation metrics do not meet the preset conditions. It can solve the problems of uneven cluster head load and poor network stability in traditional clustering methods, and improve the lifespan of the cluster network.

[0114] In some embodiments, the cluster head node can be initialized and the complete network state updated by broadcasting a complete clustering control packet, which can include packet type, node ID, cluster ID, node score, and optional fields such as common degree, LQIR (Link Quality Improvement Rate), clique ID, clique size, CU (Capacity Utilization), and neighbor ID list.

[0115] Please refer to Figure 5 , Figure 5 which is a schematic structural diagram of a clustering maintenance device provided by an embodiment of the present application. As Figure 5 shown, the device 500 is applied to a non-cluster head node in a clustered network. The device 500 includes: a first processing module 501 for generating a first node score; an acquisition module 502 for acquiring a second node score and a cluster evaluation index, where the second node score is the node performance score corresponding to the neighbor node; and a second processing module 503 for determining that the cluster evaluation index meets a preset condition and performing cluster reorganization based on the first node score and the second node score.

[0116] In one implementation, the second processing module 503 can be used to: determine that there is a score in the second node scores that is greater than the score, and the difference between the score and the maximum value in the second node scores is greater than a preset threshold, and acquire the remaining energy; determine that the remaining energy is greater than a preset energy threshold and send a cluster head declaration message, where the cluster head declaration message is used to declare that the becomes the new cluster head of the cluster where it is located; generate and send a first cluster reliability evaluation value, where the first cluster reliability evaluation value is used for other nodes except to perform cluster selection.

[0117] In one implementation, the second processing module 503 can be used to: determine that there is a score in the second node scores that is greater than the score, and acquire at least one second cluster reliability evaluation value, where the second cluster reliability evaluation value is the evaluation value sent by the cluster head node after cluster reorganization; and join the cluster corresponding to the maximum value in the at least one second cluster reliability evaluation value.

[0118] In one implementation, the first processing module 501 can be used to: acquire network performance metrics, where the network performance metrics include at least one of the following: energy score, link quality improvement rate, node-to-cluster degree ratio, cluster-to-degree ratio, centrality, capacity utilization; and acquire the score based on the network performance metrics.

[0119] In one implementation, the cluster evaluation metrics include at least one of the following: the number of nodes within the cluster, the remaining energy of the cluster head node, the evaluation value of the inter-cluster communication efficiency, the evaluation value of the distribution of nodes within the cluster, the evaluation value of the stability of the cluster structure, the evaluation value of the balance of energy consumption, the cluster stability score, and the third cluster reliability evaluation value; the second processing module 503 may be configured to: in response to at least one of the cluster evaluation metrics being less than or equal to a corresponding preset threshold, determine that the cluster evaluation metrics meet the preset conditions.

[0120] Please refer to Figure 6 , Figure 6 which is a schematic structural diagram of another cluster maintenance device provided by an embodiment of the present application. As Figure 6 shown, the device 600 is applied to the cluster head node in the clustering network. The device 600 includes: a first processing module 601, configured to obtain cluster evaluation metrics; a sending module 602, configured to send the cluster evaluation metrics; and a second processing module 603, configured to determine that a cluster head declaration message is obtained and transfer the cluster head authority.

[0121] In one implementation, the cluster evaluation metrics include at least one of the following: the number of nodes within the cluster, the remaining energy of the cluster head node, the evaluation value of the inter-cluster communication efficiency, the evaluation value of the distribution of nodes within the cluster, the evaluation value of the stability of the cluster structure, the evaluation value of the balance of energy consumption, the cluster stability score, and the cluster reliability evaluation value.

[0122] Through the device of the embodiment of the present application, the cluster head node can obtain and send the cluster evaluation metrics, so that the non-cluster head nodes can perform cluster reorganization based on the node scores when the cluster evaluation metrics meet the preset conditions. It can solve the problems of uneven cluster head load and poor network stability in the traditional clustering method and improve the life cycle of the cluster network.

[0123] It should be noted that the foregoing explanation of the embodiment of the clustering maintenance method also applies to the clustering maintenance device of this embodiment, and will not be repeated here.

[0124] To implement the above embodiment, the present application also proposes an electronic device. Please refer to Figure 7 , Figure 7 which is a schematic structural diagram of the electronic device provided by an embodiment of the present application. As Figure 7 shown, the electronic device 700 includes: a processor 701 and a memory 702 communicatively connected to the processor 701; the memory 702 stores computer execution instructions; the processor 701 executes the computer execution instructions stored in the memory to implement the method provided in the foregoing embodiment.

[0125] To implement the above embodiments, the present application also provides a computer-readable storage medium storing computer-executable instructions, which when executed by a processor are used to implement the method provided by the foregoing embodiments.

[0126] To implement the above embodiments, the present application also provides a computer program product including a computer program, which when executed by a processor implements the method provided by the foregoing embodiments.

[0127] In the description of the present application, unless otherwise specified, " / " means "or". For example, A / B may represent A or B. The "and / or" herein is merely a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist simultaneously, and B exists alone.

[0128] In the description of the foregoing embodiments, the descriptions with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, without conflict, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0129] In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present application, "a plurality" means at least two, such as two, three, etc., unless otherwise specifically defined.

[0130] Any process or method description shown in the flowchart or described in other ways herein may be understood to represent a module, segment, or part of code including one or more executable instructions for implementing a customized logic function or process. The scope of the preferred embodiments of the present application includes additional implementations, where the functions may be executed in a substantially simultaneous manner or in a reverse order according to the involved functions, rather than in the order shown or discussed, which should be understood by those skilled in the art to which the embodiments of the present application belong.

[0131] The logic and / or steps represented in the flowchart or otherwise described herein can, for example, be considered as a definitional sequence list of executable instructions for implementing logical functions, and can be embodied specifically in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device), or in conjunction with these instruction execution systems, apparatuses, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. More specific examples (non-exhaustive list) of computer-readable media include the following: an electrical connection part with one or more wirings (electronic device), a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpretation, or otherwise processing as appropriate, and then storing it in a computer memory.

[0132] It should be understood that various parts of the present application can be implemented by hardware, software, firmware, or combinations thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0133] Those of ordinary skill in the art of this technology can understand that all or part of the steps carried by the methods of the above embodiments can be completed by instructing relevant hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiments.

[0134] In addition, each functional unit in various embodiments of the present application may be integrated into one processing module, may exist separately as individual physical units, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. When the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0135] The above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disc, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A clustering maintenance method, characterized in that, The method is applied to non-cluster head nodes, and the method includes: Generating a first node score; Obtaining a second node score and a cluster evaluation metric; wherein, the second node score is generated and sent by other non-cluster head nodes, and the cluster evaluation metric is generated and sent by the cluster head node of the cluster where the non-cluster head node is located; Determining that the cluster evaluation metric meets a preset condition, and performing cluster reorganization based on the first node score and the second node score.

2. The method according to claim 1, wherein The performing cluster reorganization based on the first node score and the second node score includes: Determining that the first node score is greater than the second node score, and the difference between the first node score and the maximum value of the second node score is greater than a preset threshold, and obtaining its remaining energy; Determining that the remaining energy is greater than a preset energy threshold, and sending a cluster head declaration message; wherein, the cluster head declaration message is used to declare itself as the new cluster head of its own cluster; Generating and sending a first cluster reliability evaluation value; wherein, the first cluster reliability evaluation value is used for other non-cluster head nodes to perform cluster selection.

3. The method according to claim 1, characterized in that, The performing cluster reorganization based on the first node score and the second node score includes: Determining that there is a score in the second node scores that is greater than the first node score, and obtaining at least one second cluster reliability evaluation value; wherein, the second cluster reliability evaluation value is the evaluation value sent by the cluster head node after cluster reorganization; Joining the cluster corresponding to the maximum value among the at least one second cluster reliability evaluation value.

4. The method according to claim 1, characterized in that, The generating a first node score includes: Obtaining network performance metrics; wherein, the network performance metrics include at least one of the following: energy score, link quality improvement rate, node-to-cluster degree ratio, cluster-to-degree ratio, centrality, capacity utilization rate; Obtaining the first node score based on the network performance metrics.

5. The method according to claim 1, characterized in that, The cluster evaluation metric includes at least one of the following: the number of nodes in the cluster, the remaining energy of the cluster head node, the cluster intercommunication efficiency evaluation value, the cluster internal node distribution evaluation value, the cluster structure stability evaluation value, the energy consumption balance evaluation value, the cluster stability score, the third cluster reliability evaluation value; The determining that the cluster evaluation metric meets a preset condition includes: Responding to at least one of the cluster evaluation metrics being less than or equal to the corresponding preset threshold, and determining that the cluster evaluation metric meets the preset condition.

6. A clustering maintenance method, characterized in that The method is applied to a cluster head node in a clustered network, and the method includes: Obtaining a cluster evaluation metric; Sending the cluster evaluation metric; Determining that a cluster head declaration message is obtained, and ceding the cluster head authority.

7. A cluster maintenance device, characterized in that, The device is applied to non-cluster head nodes, and the device includes: A first processing module, configured to generate a first node score; An obtaining module, configured to obtain a second node score and a cluster evaluation metric; wherein, the second node score is generated and sent by other non-cluster head nodes, and the cluster evaluation metric is generated and sent by the cluster head node of the cluster where the non-cluster head node is located; A second processing module, configured to determine that the cluster evaluation metric meets a preset condition, and perform cluster reorganization based on the first node score and the second node score.

8. A cluster maintenance device, characterized in that, The device is applied to a cluster head node in a clustered network, and the device includes: A first processing module, configured to obtain a cluster evaluation metric; A sending module, configured to send the cluster evaluation metric; The second processing module is used to determine that the cluster head declaration message is obtained and transfer the cluster head authority.

9. An electronic device, characterized in that, It includes: a processor, and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 5, or to implement the method according to claim 6.

10. A computer-readable storage medium, characterized in that, Computer-executable instructions are stored in the computer-readable storage medium, and when the computer-executable instructions are executed by a processor, they are used to implement the method according to any one of claims 1 to 5, or to implement the method according to claim 6.

11. A computer program product, characterized in that, It includes a computer program, and when the computer program is executed by a processor, it implements the method according to any one of claims 1 to 5, or implements the method according to claim 6.

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