CN114363988A - Clustering method and device and electronic equipment - Google Patents
Clustering method and device and electronic equipment Download PDFInfo
- Publication number
- CN114363988A CN114363988A CN202111504480.1A CN202111504480A CN114363988A CN 114363988 A CN114363988 A CN 114363988A CN 202111504480 A CN202111504480 A CN 202111504480A CN 114363988 A CN114363988 A CN 114363988A
- Authority
- CN
- China
- Prior art keywords
- nodes
- node
- cluster head
- communication
- relation
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Landscapes
- Mobile Radio Communication Systems (AREA)
Abstract
The application provides a clustering method, a clustering device and electronic equipment, and relates to the technical field of communication. Wherein, the clustering method comprises the following steps: firstly, the communication score of each node can be respectively determined according to the communication quality parameters between each node and each first relation node in the network, wherein the first relation node is a node with direct communication connection. Then, according to the communication score, a plurality of cluster head nodes can be determined from each node, and the cluster head nodes are not mutually first relation nodes. And finally, first indication information can be respectively sent to the cluster head nodes and is used for the cluster head nodes to confirm the cluster head identities and establish cluster members. Therefore, data interaction among all network nodes in the clustering process can be greatly reduced, the clustering efficiency is improved, and energy loss generated in the clustering process is reduced.
Description
[ technical field ] A method for producing a semiconductor device
The present application relates to the field of communications technologies, and in particular, to a clustering method, an apparatus, and an electronic device.
[ background of the invention ]
A wireless sensor network is a network consisting of a large number of nodes with data processing and communication capabilities. When a wireless sensor network is networked, in order to improve energy utilization efficiency and reduce transmission delay, a "clustering" manner is usually adopted, that is, nodes in the network are divided into a plurality of clusters, and each cluster is responsible for communication with other clusters or external terminals by a "cluster head".
At present, common clustering methods such as an adaptive low-power-consumption hierarchical clustering algorithm and the like require a large amount of data exchange of each node in a network when clustering is performed, so that a large amount of computing resources are used, and the energy consumption of the nodes is high.
[ summary of the invention ]
The embodiment of the application provides a clustering method, a clustering device and electronic equipment, which can greatly reduce data interaction among network nodes in a clustering process, improve clustering efficiency and reduce energy loss generated in the clustering process.
In a first aspect, an embodiment of the present application provides a clustering method, including: respectively determining the communication score of each node according to the communication quality parameter between each node and each first relation node in the network, wherein the first relation node is a node with direct communication connection; determining a plurality of cluster head nodes from each node according to the communication scores, wherein the cluster head nodes are not mutually first relation nodes; and respectively sending first indication information to the cluster head nodes, wherein the first indication information is used for the cluster head nodes to confirm the cluster head identities and establish cluster members.
In one possible implementation manner, the communication quality parameter includes any one or a combination of more of the following parameters: a communication success rate; a communication retransmission rate; communication throughput; communication delay.
In one possible implementation manner, determining a communication score of each node according to a communication quality parameter between each node and a respective first relationship node in a network, where the first relationship node is a node having a direct communication connection, includes: establishing an adjacency matrix according to the communication connection relation among all nodes in a network, and establishing a communication quality matrix according to the communication quality parameters among all the nodes; obtaining a communication score matrix according to the adjacency matrix and the communication quality matrix; and summing the communication score matrixes according to columns to obtain the communication scores of all the nodes.
In one possible implementation manner, the method further includes: and determining the number N of cluster head nodes to be selected according to the product of the total number of each node in the network and a set proportion, wherein N is a positive integer.
In one possible implementation manner, determining a plurality of cluster head nodes from the nodes according to the communication score, where the cluster head nodes are not first relationship nodes with each other, includes: and determining N nodes which have the highest communication score and are not first relation nodes in each node as cluster head nodes.
In one possible implementation manner, before the first indication information is sent to the plurality of cluster head nodes, the method further includes: respectively simulating and dividing first relation nodes of the cluster head nodes into cluster members of the cluster head nodes; determining the number of remaining non-clustered nodes in the network; and if the number of the remaining nodes which are not clustered is less than a set threshold value, adding the remaining nodes which are not clustered as cluster head nodes.
In one possible implementation manner, if the number of remaining non-clustered nodes is greater than the set threshold, the method further includes: newly adding M nodes which have the highest communication score and are not first relation nodes in the rest nodes which are not clustered as cluster head nodes; simulating cluster dividing members for each newly added cluster head node and confirming that the number of the newly remained nodes which are not clustered is less than the set threshold value; and determining the value of M according to the number of the remained nodes which are not clustered.
In a second aspect, an embodiment of the present application provides a clustering apparatus, including: a determining module, configured to determine, according to communication quality parameters between each node and a respective first relationship node in a network, a communication score of each node, where the first relationship node is a node in which a direct communication connection exists; the selecting module is used for determining a plurality of cluster head nodes from each node according to the communication scores, and the cluster head nodes are not mutually first relation nodes; and the indicating module is used for respectively sending first indicating information to the cluster head nodes, and the first indicating information is used for the cluster head nodes to confirm the cluster head identities and establish cluster members.
In a third aspect, an embodiment of the present application provides an electronic device, including: at least one processor; and at least one memory communicatively coupled to the processor, wherein: the memory stores program instructions executable by the processor, the processor being capable of performing the method of the first aspect when invoked by the processor.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium storing computer instructions for causing a computer to perform the method according to the first aspect.
By the technical scheme, data interaction among network nodes in the clustering process can be greatly reduced, the clustering efficiency is improved, and energy loss generated in the clustering process is reduced.
[ description of the drawings ]
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a flowchart of a clustering method provided in an embodiment of the present application;
fig. 2 is a flowchart of another clustering method provided in the embodiment of the present application;
fig. 3 is a schematic structural diagram of a clustering device according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
[ detailed description ] embodiments
For better understanding of the technical solutions of the present application, the following detailed descriptions of the embodiments of the present application are provided with reference to the accompanying drawings.
It should be understood that the embodiments described are only a few embodiments of the present application, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terminology used in the embodiments of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in the examples of this application and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
An embodiment of the present application may provide a clustering device, configured to execute the clustering method provided in the embodiment of the present application. The clustering device may be, for example, any one of wireless sensor nodes in a wireless sensor network, and may also be a control device independent of the wireless sensor network. The embodiment of the present application does not limit this.
Fig. 1 is a flowchart of a clustering method provided in an embodiment of the present application, and as shown in fig. 1, the clustering method may include:
In this embodiment of the present application, the first relationship node refers to a node having direct communication connection, that is, data transmission between the first relationship node and the second relationship node does not need to be forwarded by an intermediate node.
For any node in the network, the embodiment of the application can determine each first relation node of the node, and determine the communication score of the node according to the communication quality parameter between the node and each first relation node. The communication quality parameter may include any one or a combination of a plurality of communication success rates, communication retransmission rates, communication throughputs, and communication delays within a set time length. The communication score can be used for representing the association degree between each node and the rest of the nodes, and the higher the communication score is, the higher the association degree between the communication score and the rest of the nodes is, and the closer the connection is.
In the embodiment of the present application, the adjacency matrix H may be established according to a communication connection relationship between nodes in a network, and the communication quality matrix P may be established according to communication quality parameters between nodes. Then, a communication score matrix C can be calculated based on the adjacency matrix H and the communication quality matrix P. And finally, summing the communication score matrix C according to columns, wherein the sum value of each column is the communication score of the node corresponding to the column. The communication score matrix C can be calculated according to the following formula:
C＝PH(I-PH)-1
wherein I is an identity matrix.
And step 102, determining a plurality of cluster head nodes from each node according to the communication scores, wherein the cluster head nodes are not first relation nodes.
In the embodiment of the application, firstly, the number of cluster head nodes to be selected can be determined according to the total number of nodes in the network. In a possible implementation manner, the total number of the nodes may be multiplied by a set ratio, and the obtained product N is used as the number of cluster head nodes to be selected. Wherein, the value of the set proportion can be determined according to the empirical value.
Then, according to the communication scores of the nodes, traversing the nodes from high to low according to the communication scores until determining N nodes which are not the first relation nodes. Then, the N nodes may be determined as cluster head nodes.
103, respectively sending first indication information to the plurality of cluster head nodes, wherein the first indication information is used for the plurality of cluster head nodes to confirm the cluster head identities and establish cluster members.
In the embodiment of the present application, a specific implementation manner of the cluster head node for establishing the cluster member may refer to the prior art, for example, the cluster head node may send a cluster request to each first relationship node, and receive a cluster response.
By the technical scheme, a large number of calculation processes for determining the cluster head nodes can be concentrated in the clustering equipment, so that data interaction among all network nodes in the clustering process can be greatly reduced, the clustering efficiency is improved, and energy loss generated in the clustering process is reduced.
Fig. 2 is a flowchart of another clustering method provided in the embodiment of the present application. As shown in fig. 2, the clustering method provided in the embodiment of the present application may include:
In the embodiment of the present application, before sending the first indication information to each cluster head node, it may be determined whether the allocation number of the cluster head nodes is reasonable. Specifically, the cluster members can be divided for each cluster head node in a simulation manner according to the condition of the cluster head node for building the cluster members. The condition that the cluster head node constructs a cluster member may be that the cluster head node is a first relationship node. It should be noted that the simulation of dividing cluster members means that simulation calculation is performed on the cluster members of the respective cluster head nodes, and it is not actual cluster member construction.
After the cluster member simulation division is completed, based on the limitation of the communication connection relationship, the remaining non-cluster-entering nodes may still exist in the network. It can be understood that the remaining non-clustered nodes are not the first relationship nodes of any cluster head node and cannot become cluster members of any cluster head node. At this point, statistics may be made on the number of remaining ungrouped nodes in the network.
If the number of the remaining non-cluster-entering nodes in the network is smaller than the set threshold, the distribution number of the current cluster head nodes can be considered to be reasonable. If the number of the remaining non-clustered nodes is not 0, step 205 may be executed to add the remaining non-clustered nodes as cluster head nodes. The set threshold may be determined according to the total number of nodes in the network, and may be, for example, 5% of the total number of nodes.
Conversely, if the number of remaining non-clustered nodes in the network is greater than the set threshold, then the allocated number of current cluster head nodes may be considered unreasonable. At this time, step 202 may be re-executed to increase the number of cluster head nodes.
In re-executing step 202, in order to improve the efficiency of cluster head determination, each cluster head node that has been previously determined may be retained. And selecting the cluster head node to be newly added from the rest nodes which are not clustered.
Specifically, the number of cluster head nodes to be newly added may be determined according to the number of remaining non-clustered nodes. For example, the product M of the number of remaining non-clustered nodes and the aforementioned set ratio may be determined as the number of cluster head nodes to be newly added. When selecting, M nodes which have the highest communication score and are not the first relation nodes among the rest nodes which are not clustered can be newly added as cluster head nodes.
And step 205, adding the remaining nodes which are not clustered into a cluster head node.
And step 206, respectively sending first indication information to each cluster head node, wherein the first indication information is used for each cluster head node to confirm the cluster head identity and establish cluster members.
Through the technical scheme, before the first indication information is sent to each cluster head node, the rationality verification of cluster head node distribution can be completed locally by the clustering equipment. Thus, unnecessary energy consumption can be avoided, and clustering efficiency can be improved.
Fig. 3 is a schematic structural diagram of a clustering device according to an embodiment of the present application. As shown in fig. 3, the clustering apparatus may include: a determination module 31, a selection module 32 and an indication module 33.
The determining module 31 is configured to determine, according to the communication quality parameter between each node in the network and each first relationship node, a communication score of each node, where the first relationship node is a node in which a direct communication connection exists.
And the selecting module 32 is configured to determine a plurality of cluster head nodes from each node according to the communication score, where the plurality of cluster head nodes are not mutually first relationship nodes.
And the indicating module 33 is configured to send first indicating information to the plurality of cluster head nodes, where the first indicating information is used for the plurality of cluster head nodes to perform cluster head identity confirmation and establish cluster members.
In a specific implementation manner, the communication quality parameter includes any one or more of the following parameters: a communication success rate; a communication retransmission rate; communication throughput; communication delay.
In a specific implementation manner, the determining module 31 is specifically configured to establish an adjacency matrix according to a communication connection relationship between nodes in a network, and establish a communication quality matrix according to a communication quality parameter between nodes; obtaining a communication score matrix according to the adjacency matrix and the communication quality matrix; and summing the communication score matrixes according to columns to obtain the communication scores of all the nodes.
In a specific implementation manner, the selecting module 32 is further configured to determine the number N of cluster head nodes to be selected according to a product of the total number of each node in the network and a set proportion, where N is a positive integer.
In a specific implementation manner, the selecting module 32 is specifically configured to determine, as the cluster head node, N nodes that have the highest communication score and are not the first relationship nodes with each other among the nodes.
In a specific implementation manner, the apparatus further includes a dividing module 34, configured to, before the indicating module 33 sends the first indication information to the plurality of cluster head nodes, respectively, divide the first relationship nodes of the plurality of cluster head nodes into cluster members of the plurality of cluster head nodes in an analog manner; determining the number of the nodes which are not clustered in the network; and if the number of the remaining nodes which are not clustered is less than the set threshold, adding the remaining nodes which are not clustered as cluster head nodes.
In a specific implementation manner, if the number of the remaining non-clustered nodes is greater than the set threshold, the dividing module 34 is further configured to add, as cluster head nodes, M nodes that have the highest communication score and are not mutually the first relationship nodes among the remaining non-clustered nodes; simulating cluster dividing members for each newly added cluster head node and confirming that the number of the newly remained nodes which are not clustered is less than a set threshold value; and the value of M is determined according to the number of the remained nodes which are not clustered.
In the above technical solution, first, the determining module 31 may determine the communication score of each node according to the communication quality parameter between each node and each first relationship node in the network. Then, the selection module can determine a plurality of cluster head nodes from each node according to the communication scores. Finally, the indication module can respectively send first indication information to the cluster head nodes so that the cluster head nodes can confirm the cluster head identities and establish cluster members. Therefore, data interaction among all network nodes in the clustering process can be greatly reduced, the clustering efficiency is improved, and energy loss generated in the clustering process is reduced.
Fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present application. As shown in fig. 4, the electronic device may include at least one processor; and at least one memory communicatively coupled to the processor, wherein: the memory stores program instructions executable by the processor, and the processor calls the program instructions to execute the clustering method provided by the embodiment of the application.
The electronic device may be a cluster device, and the embodiment does not limit the specific form of the electronic device.
FIG. 4 illustrates a block diagram of an exemplary electronic device suitable for use in implementing embodiments of the present application. The electronic device shown in fig. 4 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.
As shown in fig. 4, the electronic device is in the form of a general purpose computing device. Components of the electronic device may include, but are not limited to: one or more processors 410, a memory 430, and a communication bus 440 that connects the various system components (including the memory 430 and the processors 410).
Electronic devices typically include a variety of computer system readable media. Such media may be any available media that is accessible by the electronic device and includes both volatile and nonvolatile media, removable and non-removable media.
A program/utility having a set (at least one) of program modules, including but not limited to an operating system, one or more application programs, other program modules, and program data, may be stored in memory 430, each of which examples or some combination may include an implementation of a network environment. The program modules generally perform the functions and/or methodologies of the embodiments described herein.
The electronic device may also communicate with one or more external devices (e.g., keyboard, pointing device, display, etc.), one or more devices that enable a user to interact with the electronic device, and/or any devices (e.g., network card, modem, etc.) that enable the electronic device to communicate with one or more other computing devices. Such communication may occur via communication interface 420. Furthermore, the electronic device may also communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public Network such as the Internet) via a Network adapter (not shown in FIG. 4) that may communicate with other modules of the electronic device via the communication bus 440. It should be appreciated that although not shown in FIG. 4, other hardware and/or software modules may be used in conjunction with the electronic device, including but not limited to: microcode, device drivers, Redundant processing units, external disk drive Arrays, disk array (RAID) systems, tape Drives, and data backup storage systems, among others.
The processor 410 executes programs stored in the memory 430 to perform various functional applications and data processing, for example, implement the clustering method provided by the embodiment of the present application.
The embodiment of the present application further provides a computer-readable storage medium, where the computer-readable storage medium stores computer instructions, and the computer instructions enable the computer to execute the clustering method provided in the embodiment of the present application.
The computer-readable storage medium described above may take any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a Read Only Memory (ROM), an Erasable Programmable Read Only Memory (EPROM), a flash Memory, an optical fiber, a portable compact disc Read Only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present application, "plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing steps of a custom logic function or process, and alternate implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present application.
The word "if" as used herein may be interpreted as "at … …" or "when … …" or "in response to a determination" or "in response to a detection", depending on the context. Similarly, the phrases "if determined" or "if detected (a stated condition or event)" may be interpreted as "when determined" or "in response to a determination" or "when detected (a stated condition or event)" or "in response to a detection (a stated condition or event)", depending on the context.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions in actual implementation, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
The above description is only exemplary of the present application and should not be taken as limiting the present application, as any modification, equivalent replacement, or improvement made within the spirit and principle of the present application should be included in the scope of protection of the present application.
Claims (10)
1. A clustering method, comprising:
respectively determining the communication score of each node according to the communication quality parameter between each node and each first relation node in the network, wherein the first relation node is a node with direct communication connection;
determining a plurality of cluster head nodes from each node according to the communication scores, wherein the cluster head nodes are not mutually first relation nodes;
and respectively sending first indication information to the cluster head nodes, wherein the first indication information is used for the cluster head nodes to confirm the cluster head identities and establish cluster members.
2. The method of claim 1, wherein the communication quality parameter comprises any one or more of the following parameters:
a communication success rate;
a communication retransmission rate;
communication throughput;
communication delay.
3. The method according to claim 1 or 2, wherein the determining the communication score of each node according to the communication quality parameter between each node and the respective first relation node in the network, the first relation node being a node having a direct communication connection, comprises:
establishing an adjacency matrix according to the communication connection relation among all nodes in a network, and establishing a communication quality matrix according to the communication quality parameters among all the nodes;
obtaining a communication score matrix according to the adjacency matrix and the communication quality matrix;
and summing the communication score matrixes according to columns to obtain the communication scores of all the nodes.
4. The method of claim 1, further comprising:
and determining the number N of cluster head nodes to be selected according to the product of the total number of each node in the network and a set proportion, wherein N is a positive integer.
5. The method according to claim 4, wherein determining a plurality of cluster head nodes from the nodes according to the communication score, the plurality of cluster head nodes not being first relationship nodes with each other, comprises:
and determining N nodes which have the highest communication score and are not first relation nodes in each node as cluster head nodes.
6. The method according to claim 1, wherein before the first indication information is sent to the plurality of cluster head nodes, respectively, the method further comprises:
respectively simulating and dividing first relation nodes of the cluster head nodes into cluster members of the cluster head nodes;
determining the number of remaining non-clustered nodes in the network;
and if the number of the remaining nodes which are not clustered is less than a set threshold value, adding the remaining nodes which are not clustered as cluster head nodes.
7. The method according to claim 6, wherein if the number of the remaining non-clustered nodes is greater than the set threshold, the method further comprises:
newly adding M nodes which have the highest communication score and are not first relation nodes in the rest nodes which are not clustered as cluster head nodes;
simulating cluster dividing members for each newly added cluster head node and confirming that the number of the newly remained nodes which are not clustered is less than the set threshold value;
and determining the value of M according to the number of the remained nodes which are not clustered.
8. A clustering apparatus, comprising:
a determining module, configured to determine, according to communication quality parameters between each node and a respective first relationship node in a network, a communication score of each node, where the first relationship node is a node in which a direct communication connection exists;
the selecting module is used for determining a plurality of cluster head nodes from each node according to the communication scores, and the cluster head nodes are not mutually first relation nodes;
and the indicating module is used for respectively sending first indicating information to the cluster head nodes, and the first indicating information is used for the cluster head nodes to confirm the cluster head identities and establish cluster members.
9. An electronic device, comprising:
at least one processor; and
at least one memory communicatively coupled to the processor, wherein:
the memory stores program instructions executable by the processor, the processor invoking the program instructions to perform the method of any of claims 1 to 7.
10. A computer-readable storage medium storing computer instructions for causing a computer to perform the method of any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111504480.1A CN114363988B (en) | 2021-12-10 | 2021-12-10 | Clustering method and device and electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111504480.1A CN114363988B (en) | 2021-12-10 | 2021-12-10 | Clustering method and device and electronic equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114363988A true CN114363988A (en) | 2022-04-15 |
| CN114363988B CN114363988B (en) | 2023-07-07 |
Family
ID=81100232
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111504480.1A Active CN114363988B (en) | 2021-12-10 | 2021-12-10 | Clustering method and device and electronic equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114363988B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115086325A (en) * | 2022-06-30 | 2022-09-20 | 蚂蚁区块链科技(上海)有限公司 | Block link point grouping method and block link points |
Citations (22)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101227413A (en) * | 2008-02-22 | 2008-07-23 | 北京交通大学 | Cluster energy saving route algorithm applied in wireless sensor network |
| CN101360051A (en) * | 2008-07-11 | 2009-02-04 | 西安电子科技大学 | Energy efficient wireless sensor network routing method |
| CN101594271A (en) * | 2008-05-27 | 2009-12-02 | 华为技术有限公司 | Wireless self-organization network establishment and method of work and network of relation and equipment |
| KR20100105130A (en) * | 2009-03-20 | 2010-09-29 | 전북대학교산학협력단 | Clustreing method and system in wireless sensor networks |
| CN104320823A (en) * | 2014-10-24 | 2015-01-28 | 西安电子科技大学 | Wireless sensor network clustering method based on Sink trust value evaluation |
| EP2908597A1 (en) * | 2014-02-14 | 2015-08-19 | Alcatel Lucent | Wireless communication network node and method |
| WO2015135561A1 (en) * | 2014-03-10 | 2015-09-17 | Nokia Solutions And Networks Oy | Distribution of popular content between user nodes of a social network community via direct proximity-based communication |
| CN106412820A (en) * | 2016-05-23 | 2017-02-15 | 北京邮电大学 | Mobile ad hoc network cluster head determination method and apparatus |
| CN107295597A (en) * | 2017-07-28 | 2017-10-24 | 北京邮电大学 | A kind of adaptive cluster routing method, device and electronic equipment |
| CN107657797A (en) * | 2017-08-21 | 2018-02-02 | 胡书恺 | A kind of multilist centralized meter-reading system |
| CN107659974A (en) * | 2017-11-03 | 2018-02-02 | 广东工业大学 | Wireless sense network route method, apparatus, equipment and computer-readable recording medium |
| CA3041916A1 (en) * | 2016-10-31 | 2018-05-03 | Atomic Energy Of Canada Limited/Energie Atomique Du Canada Limitee | System and method for indirectly monitoring one or more environmental conditions |
| WO2018098753A1 (en) * | 2016-11-30 | 2018-06-07 | 深圳天珑无线科技有限公司 | Management method for distributed network, node and system |
| CN109560885A (en) * | 2018-12-24 | 2019-04-02 | 广东理致技术有限公司 | A kind of wireless sensor network quality data communication means and device |
| CN110121200A (en) * | 2019-05-09 | 2019-08-13 | 江南大学 | The network-building method of energy efficient in a kind of heterogeneous Sensor Network |
| CN110248393A (en) * | 2019-06-17 | 2019-09-17 | 西北工业大学 | A kind of cluster-dividing method based on portfolio weight |
| CN110381560A (en) * | 2019-07-30 | 2019-10-25 | 广东电网有限责任公司 | Wireless sensor network communication method suitable for electric field |
| CN110650512A (en) * | 2018-06-26 | 2020-01-03 | 云南电网有限责任公司 | Fuzzy theory-based low-power-consumption wide-area heterogeneous sensor network clustering algorithm |
| CN111093201A (en) * | 2019-12-23 | 2020-05-01 | 内蒙古大学 | Wireless sensor network and clustering method thereof |
| CN111405634A (en) * | 2020-02-26 | 2020-07-10 | 中国空间技术研究院 | Method and device for self-adaptive clustering of wireless sensor network |
| GB202108487D0 (en) * | 2020-06-15 | 2021-07-28 | Univ Xidian | Topology control system and control method for dynamic network |
| CN113194031A (en) * | 2021-04-23 | 2021-07-30 | 西安交通大学 | User clustering method and system combining interference suppression in fog wireless access network |
-
2021
- 2021-12-10 CN CN202111504480.1A patent/CN114363988B/en active Active
Patent Citations (22)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101227413A (en) * | 2008-02-22 | 2008-07-23 | 北京交通大学 | Cluster energy saving route algorithm applied in wireless sensor network |
| CN101594271A (en) * | 2008-05-27 | 2009-12-02 | 华为技术有限公司 | Wireless self-organization network establishment and method of work and network of relation and equipment |
| CN101360051A (en) * | 2008-07-11 | 2009-02-04 | 西安电子科技大学 | Energy efficient wireless sensor network routing method |
| KR20100105130A (en) * | 2009-03-20 | 2010-09-29 | 전북대학교산학협력단 | Clustreing method and system in wireless sensor networks |
| EP2908597A1 (en) * | 2014-02-14 | 2015-08-19 | Alcatel Lucent | Wireless communication network node and method |
| WO2015135561A1 (en) * | 2014-03-10 | 2015-09-17 | Nokia Solutions And Networks Oy | Distribution of popular content between user nodes of a social network community via direct proximity-based communication |
| CN104320823A (en) * | 2014-10-24 | 2015-01-28 | 西安电子科技大学 | Wireless sensor network clustering method based on Sink trust value evaluation |
| CN106412820A (en) * | 2016-05-23 | 2017-02-15 | 北京邮电大学 | Mobile ad hoc network cluster head determination method and apparatus |
| CA3041916A1 (en) * | 2016-10-31 | 2018-05-03 | Atomic Energy Of Canada Limited/Energie Atomique Du Canada Limitee | System and method for indirectly monitoring one or more environmental conditions |
| WO2018098753A1 (en) * | 2016-11-30 | 2018-06-07 | 深圳天珑无线科技有限公司 | Management method for distributed network, node and system |
| CN107295597A (en) * | 2017-07-28 | 2017-10-24 | 北京邮电大学 | A kind of adaptive cluster routing method, device and electronic equipment |
| CN107657797A (en) * | 2017-08-21 | 2018-02-02 | 胡书恺 | A kind of multilist centralized meter-reading system |
| CN107659974A (en) * | 2017-11-03 | 2018-02-02 | 广东工业大学 | Wireless sense network route method, apparatus, equipment and computer-readable recording medium |
| CN110650512A (en) * | 2018-06-26 | 2020-01-03 | 云南电网有限责任公司 | Fuzzy theory-based low-power-consumption wide-area heterogeneous sensor network clustering algorithm |
| CN109560885A (en) * | 2018-12-24 | 2019-04-02 | 广东理致技术有限公司 | A kind of wireless sensor network quality data communication means and device |
| CN110121200A (en) * | 2019-05-09 | 2019-08-13 | 江南大学 | The network-building method of energy efficient in a kind of heterogeneous Sensor Network |
| CN110248393A (en) * | 2019-06-17 | 2019-09-17 | 西北工业大学 | A kind of cluster-dividing method based on portfolio weight |
| CN110381560A (en) * | 2019-07-30 | 2019-10-25 | 广东电网有限责任公司 | Wireless sensor network communication method suitable for electric field |
| CN111093201A (en) * | 2019-12-23 | 2020-05-01 | 内蒙古大学 | Wireless sensor network and clustering method thereof |
| CN111405634A (en) * | 2020-02-26 | 2020-07-10 | 中国空间技术研究院 | Method and device for self-adaptive clustering of wireless sensor network |
| GB202108487D0 (en) * | 2020-06-15 | 2021-07-28 | Univ Xidian | Topology control system and control method for dynamic network |
| CN113194031A (en) * | 2021-04-23 | 2021-07-30 | 西安交通大学 | User clustering method and system combining interference suppression in fog wireless access network |
Non-Patent Citations (4)
| Title |
|---|
| D. SONDES AND H. RIM: "CHSM-MBC cluster head selection method with multi hop balanced clustering routing protocol for heterogeneous wireless sensors networks", 《2018 ADVANCES IN SCIENCE AND ENGINEERING TECHNOLOGY INTERNATIONAL CONFERENCES (ASET)》 * |
| Q. LIU, L. CHENG, T. OZCELEBI, J. MURPHY AND J. LUKKIEN: "Deep Reinforcement Learning for IoT Network Dynamic Clustering in Edge Computing", 《2019 19TH IEEE/ACM INTERNATIONAL SYMPOSIUM ON CLUSTER, CLOUD AND GRID COMPUTING (CCGRID)》 * |
| V. K. SINGH, R. KUMAR AND S. SAHANA: "To enhance the reliability and energy efficiency of WSN using new clustering approach", 《017 INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATION AND AUTOMATION (ICCCA)》 * |
| 宋永献: "无线传感器网络数据可靠传输关键技术研究", 《中国博士学位论文全文数据库》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115086325A (en) * | 2022-06-30 | 2022-09-20 | 蚂蚁区块链科技(上海)有限公司 | Block link point grouping method and block link points |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114363988B (en) | 2023-07-07 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US9805140B2 (en) | Striping of directed graphs and nodes with improved functionality | |
| CN108960797B (en) | Block generation and verification method, device, equipment and storage medium | |
| CN109542352B (en) | Method and apparatus for storing data | |
| CN114528044B (en) | Interface calling method, device, equipment and medium | |
| CN112558875A (en) | Data verification method and device, electronic equipment and storage medium | |
| CN113381888A (en) | Control method, device, equipment and storage medium | |
| CN115580882A (en) | Dynamic network slice resource allocation method and device, storage medium and electronic equipment | |
| CN114363988B (en) | Clustering method and device and electronic equipment | |
| CN114172819B (en) | Method, system, electronic equipment and storage medium for predicting demand resources of NFV network element | |
| CN114020469A (en) | Edge node-based multi-task learning method, device, medium and equipment | |
| CN117311999B (en) | Resource scheduling method, storage medium and electronic equipment of service cluster | |
| CN113347238A (en) | Message partitioning method, system, device and storage medium based on block chain | |
| CN112835691A (en) | Edge data processing method and system for communication of Internet of things | |
| CN114201306B (en) | Multi-dimensional geographic space entity distribution method and system based on load balancing technology | |
| CN116109102A (en) | Resource allocation method and system based on genetic algorithm | |
| CN115220656A (en) | Data storage method and device, computer readable storage medium and electronic equipment | |
| CN111611068B (en) | Data writing method in distributed system, server and client | |
| CN109189746B (en) | Method, device, equipment and storage medium for realizing universal stream type Shuffle engine | |
| CN113641688A (en) | Node updating method, related device and computer program product | |
| CN102253940B (en) | Method and device for processing data by tree view | |
| CN113079179B (en) | Efficient block chain consensus method, system, computer equipment and storage medium | |
| CN114745438B (en) | Cache data processing method, device and system of multi-data center and electronic equipment | |
| CN115987998B (en) | Micro-service system leader election method, system, storage medium and electronic equipment | |
| CN117939572B (en) | Electric power Internet of things terminal access method | |
| CN115378991B (en) | Message processing method, device, equipment and computer storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |