CN111711976A - Node clustering method, system, terminal equipment and computer readable storage medium - Google Patents
Node clustering method, system, terminal equipment and computer readable storage medium Download PDFInfo
- Publication number
- CN111711976A CN111711976A CN202010500545.4A CN202010500545A CN111711976A CN 111711976 A CN111711976 A CN 111711976A CN 202010500545 A CN202010500545 A CN 202010500545A CN 111711976 A CN111711976 A CN 111711976A
- Authority
- CN
- China
- Prior art keywords
- node
- cluster head
- cluster
- network
- nodes
- 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.)
- Pending
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W40/00—Communication routing or communication path finding
- H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
- H04W40/04—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources
- H04W40/10—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources based on available power or energy
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W40/00—Communication routing or communication path finding
- H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
- H04W40/20—Communication route or path selection, e.g. power-based or shortest path routing based on geographic position or location
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W40/00—Communication routing or communication path finding
- H04W40/24—Connectivity information management, e.g. connectivity discovery or connectivity update
- H04W40/32—Connectivity information management, e.g. connectivity discovery or connectivity update for defining a routing cluster membership
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The present disclosure provides a method, a system, a terminal device and a computer readable storage medium for clustering nodes, wherein a network includes cluster head nodes of elected cluster heads and common nodes of non-elected cluster heads, the method includes: respectively calculating a clustering threshold value between each common node and each cluster head node in the network; based on the calculation result, respectively screening out cluster head nodes with the minimum clustering threshold value between each common node and all cluster head nodes; and adding each common node into the cluster where the cluster head node with the minimum cluster entering threshold value is located. The clustering method provided by the embodiment of the disclosure can realize uniform clustering of nodes in a network, at least balance the energy of cluster heads in the network, and ensure network connectivity.
Description
Technical Field
The present disclosure relates to the field of communications technologies, and in particular, to a node clustering method, a node clustering system, a terminal device, and a computer-readable storage medium.
Background
Energy of nodes in the wireless sensor network is very important for network connectivity, how to balance network energy consumption becomes a key point for research in the wireless sensor network, and clustering is one of effective methods for saving network energy. In a cluster, the main function of the cluster head is to collect information of other nodes in the cluster and transmit the information to the base station, and as can be seen from the working mechanism of the cluster, the energy consumption rate of the cluster head node is far higher than that of other nodes in the cluster due to the fact that the cluster head node bears more preprocessing work such as data fusion and forwarding work. Therefore, how to realize reasonable clustering of nodes in a clustering algorithm to balance energy of each cluster head node in the network is key.
Disclosure of Invention
The present disclosure provides a node clustering method, system, terminal device and computer readable storage medium to at least solve the above problems.
According to an aspect of the embodiments of the present disclosure, there is provided a method for entering a cluster of nodes, where nodes in a network are divided into cluster head nodes of elected cluster heads and common nodes of non-elected cluster heads, the method including:
respectively calculating a clustering threshold value between each common node and each cluster head node in the network;
based on the calculation result, respectively screening out cluster head nodes with the minimum clustering threshold value between each common node and all cluster head nodes; and the number of the first and second groups,
and respectively adding each common node into the cluster where the cluster head node with the minimum cluster entering threshold value is located.
In one embodiment, before separately calculating the clustering threshold between each common node and each cluster head node in the network, the method further includes:
respectively acquiring the information of each cluster head node when a cluster head is selected; wherein the message includes a position, a remaining energy, and a centrality of the cluster head node.
In one embodiment, the separately calculating the clustering threshold between each common node and each cluster head node in the network includes:
respectively acquiring the residual energy and the centrality of each cluster head node at the current moment;
respectively calculating the distance between each common node and each cluster head node in the network; and the number of the first and second groups,
and respectively calculating a clustering threshold value between each common node and each cluster head node in the network based on the residual energy and the centrality of each cluster head node at the current moment and the distance between each common node and each cluster head node in the network.
In an embodiment, the calculating the clustering threshold between each common node and each cluster head node in the network respectively is obtained according to the following formula:
wherein, PcRepresenting the clustering threshold between the regular node and the cluster head node, di-CHRepresents the distance between the common node and the cluster head node, dmaxRepresents the maximum distance between any two surviving nodes in the network, E0Indicating initial energy of cluster head node, EcurRepresents the remaining energy of the cluster head node at the current moment, CmaxRepresenting the centrality maximum, C, of all nodes in the networkcurAnd representing the centrality of the cluster head node at the current moment.
According to another aspect of the embodiments of the present disclosure, there is provided a node clustering system in which nodes in a network are divided into cluster head nodes of elected cluster heads and common nodes of non-elected cluster heads, the system including:
a calculation module configured to calculate a clustering threshold between each common node and each cluster head node in the network, respectively;
the screening module is set to screen out the cluster head node with the minimum clustering threshold value between each common node and all cluster head nodes respectively based on the calculation result; and the number of the first and second groups,
and the cluster entering module is set to respectively add each common node into the cluster where the cluster head node with the minimum cluster entering threshold value is located.
In one embodiment, the system further comprises:
the acquisition module is arranged for respectively acquiring the information of elected cluster heads of all the cluster head nodes before the calculation module calculates the threshold value of the elected cluster; wherein the message includes a position, a remaining energy, and a centrality of the cluster head node.
In one embodiment, the computing module includes:
an acquisition unit configured to acquire the remaining energy and the centrality of each cluster head node at the current time, respectively;
a first calculation unit configured to calculate distances between each common node and each cluster head node in the network, respectively; and the number of the first and second groups,
and the second calculation unit is arranged to calculate the clustering threshold value between each common node and each cluster head node in the network respectively based on the residual energy and the centrality of each cluster head node at the current moment and the distance between each common node and each cluster head node in the network.
In one embodiment, the calculation module is obtained according to the following formula:
wherein, PcRepresenting the clustering threshold between the regular node and the cluster head node, di-CHRepresents the distance between the common node and the cluster head node, dmaxRepresents the maximum distance between any two surviving nodes in the network, E0Indicating initial energy of cluster head node, EcurRepresents the remaining energy of the cluster head node at the current moment, CmaxRepresenting the centrality maximum, C, of all nodes in the networkcurAnd representing the centrality of the cluster head node at the current moment.
According to another aspect of the embodiments of the present disclosure, there is provided a terminal device, including a memory and a processor, where the memory stores a computer program, and when the processor runs the computer program stored in the memory, the processor executes the node clustering method.
According to still another aspect of the embodiments of the present disclosure, there is provided a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the processor executes the node clustering method.
The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects:
according to the node clustering method, the node clustering system, the terminal device and the computer readable storage medium provided by the embodiment of the disclosure, the clustering threshold between each common node and each cluster head node in the network is respectively calculated, based on the calculation result, the cluster head node with the minimum clustering threshold between each common node and all cluster head nodes is respectively screened out, and then each common node is respectively added into the cluster where the cluster head node with the minimum clustering threshold is located. The embodiment of the invention can realize the uniform clustering of the nodes in the network, at least balance the energy of the cluster heads in the network and ensure the network connectivity.
Additional features and advantages of the disclosure will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the disclosure. The objectives and other advantages of the disclosure may be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
The accompanying drawings are included to provide a further understanding of the disclosed embodiments and are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the example serve to explain the principles of the disclosure and not to limit the disclosure.
Fig. 1 is a schematic flowchart of a node clustering method according to an embodiment of the present disclosure;
fig. 2 is a schematic flowchart of a node clustering method according to another embodiment of the present disclosure;
fig. 3 is a schematic structural diagram of a node clustering system according to an embodiment of the present disclosure;
FIG. 4 is a schematic diagram of the computing module of FIG. 3;
fig. 5 is a schematic structural diagram of a terminal device according to an embodiment of the present disclosure.
Detailed Description
To make the objects, technical solutions and advantages of the embodiments of the present disclosure more apparent, specific embodiments of the present disclosure are described below in detail with reference to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating the present disclosure, are given by way of illustration and explanation only, not limitation.
It should be noted that the terms "first," "second," and the like in the description and claims of the present disclosure and in the above-described drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order; also, the embodiments and features of the embodiments in the present disclosure may be arbitrarily combined with each other without conflict.
In which the terminology used in the embodiments of the disclosure is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. As used in the disclosed embodiments 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.
In the following description, suffixes such as "module", "component", or "unit" used to denote elements are used only for the convenience of explanation of the present disclosure, and have no specific meaning in themselves. Thus, "module", "component" or "unit" may be used mixedly.
In order to solve the above problem, the embodiments of the present disclosure provide a method for enabling nodes to enter a cluster, which is capable of ensuring network connectivity, and simultaneously enabling the nodes to enter the cluster by using the factors such as node residual energy, distance, node centrality, and the like, with the goal of balancing energy consumption in the network, so as to ensure that network nodes are clustered uniformly to the maximum extent, and energy consumption among clusters is consumed in a balanced manner.
Referring to fig. 1, fig. 1 is a flowchart illustrating a node clustering method according to an embodiment of the present disclosure, where nodes in a network are divided into cluster head nodes of elected cluster heads and common nodes of non-elected cluster heads, and the method includes steps S101 to S103.
In step S101, a clustering threshold between each common node and each cluster head node in the network is calculated.
In the related technology, when nodes are clustered, selected cluster head messages broadcast by each cluster head node are mainly received through the nodes, and clustering is carried out according to signal strength.
According to the method and the device, a cluster entering threshold is introduced, the cluster entering threshold between the nodes of the nodes and the cluster head is calculated, the factors such as the distance between the nodes and the cluster head, the residual energy of the cluster head, the cluster head centrality and the like are comprehensively considered, and then the cluster head with the minimum cluster entering threshold is selected and added into the cluster of the cluster head. Compared with the related art, the embodiment adds the nodes into the cluster head node with the minimum clustering threshold, so that the problem of a large cluster or a small cluster caused by selecting the cluster head according to the signal intensity is avoided.
In step S102, based on the calculation result, the cluster head node with the minimum clustering threshold between each common node and all cluster head nodes is respectively filtered out.
It can be understood that the clustering threshold is used for evaluating the rationality of the nodes for adding into the related cluster head nodes, the smaller the clustering threshold is, the more suitable the nodes for adding into the corresponding cluster head nodes are shown, and energy balance in the network is ensured by adding each node into the cluster with the minimum clustering threshold.
In step S103, each common node is added to the cluster where the cluster head node with the smallest cluster entering threshold is located.
Specifically, before calculating the clustering threshold between each common node and each cluster head node in the network respectively (i.e., step S101), the method further includes the following steps:
respectively acquiring the information of each cluster head node when a cluster head is selected; wherein the message includes a position, a remaining energy, and a centrality of the cluster head node.
Specifically, firstly, network initialization is performed, different types of sensor nodes are deployed randomly, each cluster head node broadcasts a cluster head selection message to all common nodes after selection of cluster heads in the network is completed, and the message includes information such as the position, the residual energy and the centrality of the cluster head node. And calculating the clustering threshold value by the common nodes, and selecting the cluster head corresponding to the minimum clustering threshold value by each common node to successfully cluster.
It should be noted that the cluster head selection may be selected based on a manner of comparing a random number generated by the node [0, 1] with a cluster head selection threshold, and the manner of selecting the cluster head is not limited to this embodiment and is not described herein again.
Referring to fig. 2, fig. 2 is a flowchart illustrating a method for clustering nodes according to another embodiment of the present disclosure, and this embodiment illustrates a specific calculation manner for calculating a cluster entry threshold between a normal node and a cluster head node based on the previous embodiment, and specifically, step S101 is further divided into steps S201 to S203.
In step S201, the remaining energy and the centrality of each cluster head node at the current time are respectively obtained.
It can be understood that the greater the remaining energy and the centrality of the cluster head node at the current time, the greater the reliability for transmitting data. The centrality is used for evaluating the importance of the node, and is mainly evaluated by three dimensions, namely the centrality of the node, the centrality of the medium and the centrality of the feature vector, which are not described herein again.
In step S202, the distance between each common node and each cluster head node in the network is calculated.
Specifically, the shorter the distance between the node and the cluster head node is, the smaller the energy required to be consumed for transmitting data is, whereas the longer the distance is, the larger the energy required to be consumed is, and when the clustering threshold is calculated, the distance factor is considered to balance the energy of the nodes in the network.
In step S203, a clustering threshold between each common node and each cluster head node in the network is respectively calculated based on the remaining energy and the centrality of each cluster head node at the current time and the distance between each common node and each cluster head node in the network.
Specifically, in step S203, a clustering threshold between each common node and each cluster head node in the network is calculated respectively, and is obtained according to the following formula:
wherein, PcRepresenting the clustering threshold between the regular node and the cluster head node, di-CHRepresents the distance between the common node and the cluster head node, dmaxRepresents the maximum distance between any two surviving nodes in the network, E0Indicating initial energy of cluster head node, EcurRepresents the remaining energy of the cluster head node at the current moment, CmaxRepresenting the centrality maximum, C, of all nodes in the networkcurAnd representing the centrality of the cluster head node at the current moment.
It will be appreciated that the network comprises i nodes, and CH cluster head nodes, PcThe values of (a) are respectively the clustering threshold values, d, between each common node i and each cluster head node CHi-CHIs the distance between the common node i and the cluster head node CH. Wherein d ismaxThe maximum value of the distance between any two surviving nodes is obtained, and no common node or cluster head node is distinguished in any two surviving nodes.
From the above formula, it can be seen that the distance d between the node and the cluster headi-CHThe smaller the cluster head is, the residual energy E at the current momentcurThe larger the cluster head is, the centrality node C at the current momentcurCluster head threshold P between node and cluster headcThe smaller the current time represents the current time when the node is clustered, it can be understood that, along with the period of data transmission, the energy of the node in the network is continuously consumed, and the position, the number and the quality of the node are also continuously changed, that is, the node centrality is also changed.
Based on the same technical concept, the embodiment of the present disclosure correspondingly provides a node clustering system, where nodes in a network are divided into cluster head nodes of elected cluster heads and common nodes of non-elected cluster heads, as shown in fig. 3, the system includes a computing module 31, a screening module 32, and a clustering module 33, where,
a calculation module 31 configured to calculate a clustering threshold between each common node and each cluster head node in the network, respectively;
a screening module 32 configured to screen out a cluster head node having a minimum clustering threshold between each common node and all cluster head nodes, respectively, based on the calculation result; and the number of the first and second groups,
and a clustering module 33 configured to add each common node to the cluster where the cluster head node with the smallest clustering threshold value is located.
In one embodiment, the system further comprises:
the acquisition module is arranged for respectively acquiring the information of elected cluster heads of all the cluster head nodes before the calculation module calculates the threshold value of the elected cluster; wherein the message includes a position, a remaining energy, and a centrality of the cluster head node.
In one embodiment, as shown in fig. 4, the calculation module 31 includes:
an obtaining unit 311 configured to obtain the remaining energy and the centrality of each cluster head node at the current time, respectively;
a first calculation unit 312 arranged to calculate the distance between each common node and each cluster head node in the network, respectively; and the number of the first and second groups,
a second calculating unit 313 configured to calculate a cluster entry threshold between each common node and each cluster head node in the network based on the remaining energy and the centrality of each cluster head node at the current time and the distance between each common node and each cluster head node in the network, respectively.
In one embodiment, the calculation module is obtained according to the following formula:
wherein, PcRepresenting the clustering threshold between the regular node and the cluster head node, di-CHRepresents the distance between the common node and the cluster head node, dmaxRepresents the maximum distance between any two surviving nodes in the network, E0Indicating initial energy of cluster head node, EcurRepresents the remaining energy of the cluster head node at the current moment, CmaxRepresenting the centrality maximum, C, of all nodes in the networkcurAnd representing the centrality of the cluster head node at the current moment.
Based on the same technical concept, the embodiment of the present disclosure correspondingly provides a terminal device, as shown in fig. 5, the terminal device includes a memory 51 and a processor 52, the memory 51 stores a computer program 52, and when the processor 52 runs the computer program stored in the memory 51, the processor 52 executes the node clustering method.
Based on the same technical concept, embodiments of the present disclosure correspondingly provide a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the processor executes the node clustering method.
To sum up, according to the node clustering method, the node clustering system, the terminal device, and the computer-readable storage medium provided by the embodiments of the present disclosure, the clustering threshold between each common node and each cluster head node in the network is respectively calculated, based on the calculation result, the cluster head node with the minimum clustering threshold between each common node and all cluster head nodes is respectively screened out, and then each common node is added to the cluster where the cluster head node with the minimum clustering threshold is located. The embodiment of the disclosure can realize uniform clustering of nodes in a network, at least balance the energy of cluster heads in the network and ensure network connectivity; furthermore, the cluster entering threshold value is calculated by the method and the device, the factors such as node residual energy, distance and node centrality are considered, and after the nodes are clustered based on the method, the network nodes can be guaranteed to be clustered uniformly on the premise of guaranteeing network connectivity, and energy consumption among clusters is balanced.
It will be understood by those of ordinary skill in the art that all or some of the steps of the methods, systems, functional modules/units in the devices disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. In a hardware implementation, the division between functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be performed by several physical components in cooperation. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as is well known to those of ordinary skill in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can accessed by a computer. In addition, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media as known to those skilled in the art.
Finally, it should be noted that: the above embodiments are only used for illustrating the technical solutions of the present disclosure, and not for limiting the same; while the present disclosure has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present disclosure.
Claims (10)
1. A node clustering method is characterized in that nodes in a network are divided into cluster head nodes of elected cluster heads and common nodes of non-elected cluster heads, and the method comprises the following steps:
respectively calculating a clustering threshold value between each common node and each cluster head node in the network;
based on the calculation result, respectively screening out cluster head nodes with the minimum clustering threshold value between each common node and all cluster head nodes; and the number of the first and second groups,
and respectively adding each common node into the cluster where the cluster head node with the minimum cluster entering threshold value is located.
2. The method of claim 1, prior to separately calculating the clustering threshold between each common node and each cluster head node in the network, further comprising:
respectively acquiring the information of each cluster head node when a cluster head is selected; wherein the message includes a position, a remaining energy, and a centrality of the cluster head node.
3. The method of claim 2, wherein separately calculating the clustering threshold between each common node and each cluster head node in the network comprises:
respectively acquiring the residual energy and the centrality of each cluster head node at the current moment;
respectively calculating the distance between each common node and each cluster head node in the network; and the number of the first and second groups,
and respectively calculating a clustering threshold value between each common node and each cluster head node in the network based on the residual energy and the centrality of each cluster head node at the current moment and the distance between each common node and each cluster head node in the network.
4. The method of claim 3, wherein the calculating the clustering threshold between each common node and each cluster head node in the network is performed according to the following formula:
wherein, PcRepresenting the clustering threshold between the regular node and the cluster head node, di-CHRepresents the distance between the common node and the cluster head node, dmaxRepresents the maximum distance between any two surviving nodes in the network, E0Indicating initial energy of cluster head node, EcurRepresents the remaining energy of the cluster head node at the current moment, CmaxRepresenting the centrality maximum, C, of all nodes in the networkcurAnd representing the centrality of the cluster head node at the current moment.
5. A node clustering system, wherein nodes in a network are divided into cluster head nodes of elected cluster heads and common nodes of non-elected cluster heads, the system comprising:
a calculation module configured to calculate a clustering threshold between each common node and each cluster head node in the network, respectively;
the screening module is set to screen out the cluster head node with the minimum clustering threshold value between each common node and all cluster head nodes respectively based on the calculation result; and the number of the first and second groups,
and the cluster entering module is set to respectively add each common node into the cluster where the cluster head node with the minimum cluster entering threshold value is located.
6. The system of claim 5, further comprising:
the acquisition module is arranged for respectively acquiring the information of elected cluster heads of all the cluster head nodes before the calculation module calculates the threshold value of the elected cluster; wherein the message includes a position, a remaining energy, and a centrality of the cluster head node.
7. The system of claim 6, wherein the computing module comprises:
an acquisition unit configured to acquire the remaining energy and the centrality of each cluster head node at the current time, respectively;
a first calculation unit configured to calculate distances between each common node and each cluster head node in the network, respectively; and the number of the first and second groups,
and the second calculation unit is arranged to calculate the clustering threshold value between each common node and each cluster head node in the network respectively based on the residual energy and the centrality of each cluster head node at the current moment and the distance between each common node and each cluster head node in the network.
8. The system of claim 7, wherein the calculation module is configured to obtain the following equation:
wherein, PcRepresenting the clustering threshold between the regular node and the cluster head node, di-CHRepresents the distance between the common node and the cluster head node, dmaxRepresents the maximum distance between any two surviving nodes in the network, E0Indicating initial energy of cluster head node, EcurRepresents the remaining energy of the cluster head node at the current moment, CmaxRepresenting the centrality maximum, C, of all nodes in the networkcurAnd representing the centrality of the cluster head node at the current moment.
9. A terminal device comprising a memory and a processor, the memory having a computer program stored therein, the processor performing the node clustering method according to any one of claims 1 to 4 when the processor runs the computer program stored in the memory.
10. A computer-readable storage medium, on which a computer program is stored, which, when executed by a processor, performs the node clustering method according to any one of claims 1 to 4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010500545.4A CN111711976A (en) | 2020-06-04 | 2020-06-04 | Node clustering method, system, terminal equipment and computer readable storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010500545.4A CN111711976A (en) | 2020-06-04 | 2020-06-04 | Node clustering method, system, terminal equipment and computer readable storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111711976A true CN111711976A (en) | 2020-09-25 |
Family
ID=72539201
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010500545.4A Pending CN111711976A (en) | 2020-06-04 | 2020-06-04 | Node clustering method, system, terminal equipment and computer readable storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111711976A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113395357A (en) * | 2021-08-16 | 2021-09-14 | 支付宝(杭州)信息技术有限公司 | Method and device for fragmenting block chain system |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20100057367A (en) * | 2008-11-21 | 2010-05-31 | 한국전자통신연구원 | Method for allocating resources for wireless network |
| CN109510763A (en) * | 2019-01-03 | 2019-03-22 | 中国联合网络通信集团有限公司 | A kind of node cluster head electoral machinery and system |
| CN109819497A (en) * | 2019-02-27 | 2019-05-28 | 中国联合网络通信集团有限公司 | A kind of cluster head selection method and device |
-
2020
- 2020-06-04 CN CN202010500545.4A patent/CN111711976A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20100057367A (en) * | 2008-11-21 | 2010-05-31 | 한국전자통신연구원 | Method for allocating resources for wireless network |
| CN109510763A (en) * | 2019-01-03 | 2019-03-22 | 中国联合网络通信集团有限公司 | A kind of node cluster head electoral machinery and system |
| CN109819497A (en) * | 2019-02-27 | 2019-05-28 | 中国联合网络通信集团有限公司 | A kind of cluster head selection method and device |
Non-Patent Citations (2)
| Title |
|---|
| 常铁原，刘伟娜，张炎，李会雅: "基于簇头距离和能量的优化LEACH协议", 《河北大学学报》 * |
| 方怡: "无线传感器网络的分簇算法研究", 《中国优秀硕士论文全文数据库》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113395357A (en) * | 2021-08-16 | 2021-09-14 | 支付宝(杭州)信息技术有限公司 | Method and device for fragmenting block chain system |
| CN113395357B (en) * | 2021-08-16 | 2021-11-12 | 支付宝(杭州)信息技术有限公司 | Method and device for fragmenting block chain system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US9723583B2 (en) | Masterless slot allocation | |
| US10230630B2 (en) | Determining network rank for communication to neighboring nodes | |
| US8788865B2 (en) | Method and system for redeploying powered devices from a power sourcing equipment with insufficient power capacity to another power sourcing equipment with excess power capacity | |
| US10602503B2 (en) | Control information format processing method, base station, and user equipment | |
| CN102291847A (en) | Dynamic connection management on mobile peer devices | |
| JP6521994B2 (en) | Technologies for Optimizing Mesh Networks | |
| CN103814601A (en) | Methods and apparatus for traffic contention resource allocation | |
| CN104918303B (en) | mobile terminal device and control method | |
| CN111601268A (en) | Cluster head selection method and device, terminal equipment and storage medium | |
| US9814052B2 (en) | Data distribution system, distribution device, terminal device, and data distribution method providing enhanced communication efficiency | |
| CN104683585B (en) | A kind of mobile terminal and its intelligent call transfer method | |
| CN111711976A (en) | Node clustering method, system, terminal equipment and computer readable storage medium | |
| CN113660687B (en) | Network difference cell processing method, device, equipment and storage medium | |
| EP4171128A1 (en) | Cell reselection method, network management device, base station, and storage medium | |
| CN111711930B (en) | Cluster head election method, system, terminal equipment and computer readable storage medium | |
| CN102984739A (en) | Breakdown information processing method and processing device | |
| CN112075102A (en) | Low-power Bluetooth networking method, electronic equipment, network and storage medium | |
| CN111757443A (en) | Node dormancy method, system, terminal device and computer readable storage medium | |
| CN110069274A (en) | Pond server ReDriver chip configures update method and device | |
| CN111383432B (en) | Information receiving method and device, and information reporting method, device and system | |
| CN111510989A (en) | Relay node selection method, data transmission method, terminal device, and storage medium | |
| CN111711975A (en) | Data transmission method, system, terminal device and computer readable storage medium | |
| CN111711977A (en) | Node clustering method, system, terminal equipment and computer readable storage medium | |
| CN112105071A (en) | Cluster head election method, system, terminal equipment and computer readable storage medium | |
| CN109104265A (en) | Channel arrangement method, base station and readable storage medium storing program for executing |
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 | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20200925 |