WO2018233139A1

WO2018233139A1 - Method, base station, and storage medium for selecting cluster head node

Info

Publication number: WO2018233139A1
Application number: PCT/CN2017/104997
Authority: WO
Inventors: 马路娟; 刘宏举; 吕叶青; 张传欣
Original assignee: 海信集团有限公司
Priority date: 2017-06-20
Filing date: 2017-09-30
Publication date: 2018-12-27
Also published as: CN107071849B; CN107071849A

Abstract

The present disclosure relates to the technical field of communications, and relates to a method, base station, and storage medium for selecting a cluster head node. The method comprises: determining, according to position information of nodes in a target house and an area of a target region in the target house, nodes contained in the target region of the target house; determining, according to region attribute information of the target region, a cluster head node number corresponding to the target region; and selecting, according to competition values of the nodes in the target region, a cluster head node number of cluster head nodes from the nodes in the target region. For target regions having different areas, the target regions have different region attributes and different region attribute information, and therefore, a determined cluster head node number varies according to an attribute of a target region. In this way, the present invention enables a dynamic cluster head node number to better adapt to target regions having different areas than a fixed cluster head node number.

Description

Method, base station and storage medium for electing cluster head node

The present application claims priority to Chinese Patent Application No. JP-A No. No. No. No. No. No. No. No. No. No. No. No. No. No. No. No. No No No No No No No No No No No No No No No No No No No No No No No No No No No No No No No No No No No No No In this application.

Technical field

The present disclosure relates to the field of communications technologies, and in particular, to a method, a base station, and a storage medium for electing a cluster head node.

Background technique

A local area network can be divided into multiple areas, and nodes (ie, devices) in each area form a cluster, and each cluster can include one or more nodes, and all nodes in each area form a cluster. The nodes in the cluster can be further divided into cluster head nodes and cluster member nodes. Cluster head nodes can be used to manage or control cluster member nodes throughout the cluster, as well as to coordinate work between cluster member nodes.

Summary of the invention

According to a first aspect of an embodiment of the present disclosure, a method of electing a cluster head node is provided, the method comprising:

Determining a node included in the target area according to location information of a node in the target house and a range of the target area in the target house;

Determining, according to the area attribute information of the target area, the number of cluster head nodes corresponding to the target area;

And selecting, according to a contention value of a node in the target area, a cluster head node of the number of cluster head nodes among nodes of the target area.

Optionally, the area attribute information of the target area includes a number of nodes of the target area, a maximum side length, and an average distance of the node to the base station in the target area.

Optionally, the number of the cluster head nodes corresponding to the target area is positively correlated with the number of nodes of the target area, and is positively correlated with the maximum side length of the target area, and the average distance from each node to the base station in the target area. It is inversely related.

Optionally, the method for determining the number of cluster head nodes corresponding to the target area according to the area attribute information of the target area includes:

Determine the number of cluster head nodes corresponding to the target area according to the following calculation formula:

Where k _opt is the number of cluster head nodes corresponding to the target area, n is the number of nodes of the target area, M is the maximum side length of the target area, and the d _toBS is the node to the base station in the target area. Average distance.

Optionally, the target area is a room of the target house.

Optionally, the cluster head node that elects the number of cluster head nodes in the node of the target area according to the contention value of the node in the target area includes:

Sorting nodes in the target area according to a competition value of nodes in the target area from large to small;

The nodes ranked in the top N are elected as cluster head nodes, where N is the number of cluster head nodes.

Optionally, after the election of the cluster head node is completed, when a new node is detected to join the target area, the method further includes:

Selecting, in the new node and the cluster head node, a node ranked in the top N as a cluster head node according to a contention value of the new node and the cluster head node in the target area, where N is the cluster head node number.

According to a second aspect of the embodiments of the present disclosure, a base station is provided, the base station comprising:

a node determining module, configured to determine a node included in the target area according to location information of a node in the target house and a range of the target area in the target house;

a number determining module, configured to determine, according to the area attribute information of the target area, a number of cluster head nodes corresponding to the target area;

a first election module, configured to elect, according to a contention value of a node in the target area, a cluster head node of the number of cluster head nodes among nodes of the target area.

Optionally, the number determining module is specifically configured to determine, according to the following calculation formula, a number of cluster head nodes corresponding to the target area:

Optionally, the target area is a room of the target house.

Optionally, the first election module includes:

a sorting unit, configured to sort nodes in the target area according to a competition value of nodes in the target area from large to small;

An election unit is configured to elect a node ranked in the top N as a cluster head node, where N is the number of cluster head nodes.

Optionally, after the base station elects the cluster head node, when the new node is detected to join the target area, the base station further includes:

a second election module, configured to select a node ranked in the top N as a cluster head node in the new node and the cluster head node according to a competition value of the new node and the cluster head node in the target area, where N is the number of cluster head nodes.

According to a third aspect of the embodiments of the present disclosure, a base station is provided, the base station including:

a node determiner configured to determine a node included in the target area according to location information of a node in the target house and a range of the target area in the target house;

a number determining unit, configured to determine, according to the area attribute information of the target area, a number of cluster head nodes corresponding to the target area;

The first electoral device is configured to elect a cluster head node of the number of cluster head nodes among nodes of the target area according to a contention value of a node in the target area.

Optionally, the number determiner is specifically configured to determine a number of cluster head nodes corresponding to the target area according to the following calculation formula:

Optionally, the target area is a room of the target house.

Optionally, the first electoralator includes:

a sorter configured to sort nodes in the target area according to a competition value of nodes in the target area from large to small;

The elector is configured to elect a node ranked in the top N as a cluster head node, where N is the number of cluster head nodes.

a second arbitrator configured to select a node ranked in the top N as a cluster head node in the new node and the cluster head node according to a contention value of the new node and the cluster head node in the target area, where N is the number of cluster head nodes.

According to a fourth aspect of an embodiment of the present disclosure, there is provided a base station including a processor and a memory, wherein the memory stores computer instructions executed by the processor to implement the first aspect or A method of electing a cluster head node as shown in its alternative implementation.

According to a fifth aspect of embodiments of the present disclosure, there is provided a computer readable storage medium having stored therein computer instructions executed by a processor to implement the first aspect described above or an alternative implementation thereof The method of electing a cluster head node is shown.

Optionally, the computer readable storage medium may be a non-volatile storage medium.

According to a sixth aspect of an embodiment of the present disclosure, a computer program product is provided, in which computer instructions are stored, the computer instructions being executed by a processor to implement the first aspect described above or an alternative implementation thereof The method of electing a cluster head node.

The above general description and the following detailed description are intended to be illustrative and not restrictive.

DRAWINGS

The accompanying drawings, which are incorporated in the specification In the drawing:

FIG. 1 is a flowchart of a method for electing a cluster head node according to an exemplary embodiment;

FIG. 2 is a schematic diagram showing a region division according to an exemplary embodiment; FIG.

FIG. 3 is a flowchart of a method for electing a cluster head node according to an exemplary embodiment;

4 is a schematic diagram of a cluster connection, according to an exemplary embodiment;

FIG. 5 is a schematic diagram of a data transmission link according to an exemplary embodiment; FIG.

FIG. 6 is a schematic diagram of a base station according to an exemplary embodiment;

FIG. 7 is a schematic diagram of a base station according to an exemplary embodiment;

FIG. 8 is a schematic structural diagram of a base station according to an exemplary embodiment.

The embodiments of the present disclosure have been shown by the above-described drawings, which will be described in more detail later. The drawings and the text are not intended to limit the scope of the present disclosure in any way, and the description of the present disclosure will be described by those skilled in the art by reference to the specific embodiments.

Detailed ways

Exemplary embodiments will be described in detail herein, examples of which are illustrated in the accompanying drawings. The following description refers to the same or similar elements in the different figures unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with aspects of the present disclosure as detailed in the appended claims.

Computer devices in a local area network are often referred to as nodes in a local area network. Illustratively, the computer device (ie, the node) in the embodiments of the present disclosure may be a device such as a desktop computer, a laptop computer, a tablet computer, a mobile phone, a refrigerator, a television, a washing machine, an air conditioner, or a sensor.

Currently in the related art, a local area network can be divided into a plurality of clusters, and each cluster can include a plurality of nodes (for example, computer devices). The number of cluster head nodes in each area contained in a local area network (for example, a local area network) is one. This may result in too many or too few cluster member nodes carried by a cluster head node in some areas, thereby affecting communication efficiency within the cluster.

In order to solve the above problem, the embodiment of the present disclosure provides a method for electing a cluster head node, in which, before electing a cluster head node, first, it is necessary to determine the number of cluster head nodes corresponding to the target area according to the area attribute information of the target area, thereby The number of corresponding cluster head nodes can be flexibly determined for each area according to the attribute information of the target area.

The method for electing a cluster head node provided by an embodiment of the present disclosure may be implemented by a base station.

A base station in an embodiment of the present disclosure may include components such as a processor, a memory, a transceiver, and the like. The processor may be a CPU (Central Processing Unit) or the like, and may be used for calculating the number of cluster head nodes in the target area and calculating the contention value of each node. The memory may be a RAM (Random Access Memory), a Flash (Flash Memory), or the like, and may be used to store received data, data required for processing, data generated during processing, and the like. The transceiver can be used for data transmission with nodes and other base stations. The transceiver can include an antenna, a matching circuit, a radio frequency circuit, and the like.

An exemplary embodiment of the present disclosure provides a method for electing a cluster head node. As shown in FIG. 1 , the processing flow of the method may include the following steps:

Step S110: Determine a node included in the target area according to the location information of the node in the target house and the range of the target area in the target house.

In an implementation, first, the base station may pre-store a floor plan of the target house, where the floor plan includes location information and size of each room. Then, the base station can receive each node The location information of each node passed. Then, the base station may determine, according to the floor plan of the target house and the location information of each node, which locations in each of the target houses are specifically located. Finally, determine the nodes included in the target area in the target house. For example, as shown in Figure 2, the target house includes a bathroom, a kitchen, two bedrooms, and a living room. If the living room in the target house is the target area, the area 6 corresponding to the living room includes six nodes, and it can be determined that they are node A, node B, node C, node D, node E, and node F, respectively.

Optionally, the target area may be a room of the target house.

In the implementation, in the process of dividing the area, the division is performed in units of rooms in the target house, for example, dividing the bathroom into one area and dividing the living room into another area. This ensures that there is no wall penetration in any area that is divided, and the internal communication of the cluster in any area will not pass through the wall, thus avoiding signal attenuation and communication caused by communication through the wall. The problem of performance degradation.

Step S120: Determine the number of cluster head nodes corresponding to the target area according to the area attribute information of the target area.

In the implementation, since the process of dividing the area is based on the room in the target house, the size of the divided area may be different, so it is possible to elect a cluster head node in the area to make a cluster head. The node member nodes carried by the node are too many or too few, which affects the communication efficiency within the cluster. In the method provided in this embodiment, before electing a cluster head node, first, it is necessary to determine the number of cluster head nodes corresponding to the target area according to the area attribute information of the target area.

Optionally, the number of cluster head nodes corresponding to the target area is positively correlated with the number of nodes in the target area, and is positively correlated with the maximum side length of the target area, and inversely related to the average distance of each node to the base station in the target area.

The number of cluster head nodes corresponding to the target area is positively correlated with the number of nodes in the target area and positively correlated with the maximum side length of the target area. It can be understood that the number of nodes in the target area and/or the maximum side length of the target area increases, and the target The number of cluster head nodes corresponding to the region increases accordingly; the number of cluster head nodes corresponding to the target region is inversely related to the average distance from each node to the base station in the target region, which can be understood as the average distance from each node to the base station in the target region. Small, the number of cluster head nodes corresponding to the target area decreases. Optionally, the number of nodes in the target area is also available. The maximum side length of the target area and the average distance from each node to the base station in the target area are set to a constant weight, or the number of nodes in the target area, the maximum side length of the target area, or the average distance from each node to the base station in the target area may be performed. Square or square and so on.

Optionally, step S120 may include: determining a number of cluster head nodes corresponding to the target area according to the following calculation formula:

Where k _opt is the number of cluster head nodes corresponding to the target area, n is the number of nodes of the target area, M is the maximum side length of the target area, and d _toBS is the average distance of each node in the target area to the base station. It should be noted that M may be the maximum side length in the boundary line of the target area.

It should be noted that the above formula 1 can be adjusted in other forms. For example, weights can be set for M and d _toBS , and the above formula 1 is adjusted to:

Where a and b are the constant weights of M and d _toBS , respectively; or, the weight is set in the part of n, and the above formula 1 is adjusted to:

Where c is the weight of the number of nodes in the target area. Optionally, the values of the above-mentioned constants a, b, and c may be determined according to actual conditions, for example, may be obtained from multiple test data, or obtained according to experience, and are not limited in the embodiment of the present invention.

For example, as shown in FIG. 2, the living room corresponding to the area 6 is 10 meters long and 5 meters wide, and the maximum side length is 10 meters. d _toBS is a statistical data. Specifically, in planning and erecting a base station, the distance from the surrounding location to the base station is counted. For example, if a residential X cell is 5 kilometers away from the base station, it can be in the memory of the base station. The identifier corresponding to a certain residential X cell is stored in the distance list corresponding to the distance between the base station and a residential X cell. When the base station obtains an identifier corresponding to a residential X-cell, it may perform an inquiry according to the identifier corresponding to a residential X-cell in the distance list to determine a base station corresponding to a certain residential X-cell and a certain residential X. The distance of the cell. When the base station acquires the location information of each node, it can roughly determine which location the nodes are from, and roughly determine the average distance d _{toBS of} the location to the base station.

The above formula 1 can be obtained by combining the following formulas 2 to 6, and performing a first-order derivation of the parameter k therein, and making the derivation result 0.

Equation 2 is as follows:

Where E _CH is the total energy consumed by all cluster head nodes in a cluster in the target area, n is the number of nodes in the target area, k is the number of cluster head nodes corresponding to the target area, and E _DA is required for data fusion of the cluster head node energy _consumption, d toBS each node as a target area from the base station to the average, E _elec circuit to transmit or receive circuitry of each cluster head transmits 1-bit data or receive energy consumed, ε _fs depending transmit circuitry or The signal amplifier model in the receiving circuit, L is the number of bits of data that needs to be transmitted. Among them, E _CH , k, L are unknown parameters. E _DA and _Elec are test data. Generally, at the stage of designing the node circuit, the performance of the node can be tested, including testing of the nodes E _DA and _Elec . After multiple tests, the test values of E _DA and _Elec will be obtained. When applied to the test values of E _DA and _Elec , the user's manual can be directly queried to know E _DA and _Elec. . In the present embodiment, values corresponding to the respective E _DA and _Elec can be stored in advance in the memory of each node. When the base station needs to obtain these values, it can be directly sent to the base station.

Equation 3 is as follows:

E _nonCH =L·E _elec +L·ε _fs ·d ² _tocH (Equation 3)

Where E _nonCH is the total energy consumed by all cluster member nodes in a cluster in the target area, and d _toCH is the distance from the cluster member node to the cluster head node. Where E _nonCH , L, and d _toCH are unknown parameters. The formula for calculating d _toCH can be seen in Equation 4:

Where ρ(x, y) is the distribution density function of the node, and x and y are the position coordinates of each node in the target area. It should be noted that in the process of deriving the formula 1, the formula 4 can be substituted into the formula 3, and the d ^{2 to} _CH in the formula 3 can be directly eliminated.

Equation 5 is as follows:

Where E _cluster is the total energy consumed by all nodes in a cluster in the target area.

Equation 6 is as follows:

E _tot = L(2nE _elec +nE _DA +ε _fs (kd ² _toBS +nd ² _toCH )) (Equation 6)

Where E _tot is the total energy consumed by all nodes in the target area.

By synthesizing the above formulas 2 to 6, the unknown parameters that can be eliminated are eliminated, and the first-order derivation of the parameter k is performed, and then the derivation result is 0, and the expression of the above k _opt is obtained (formula 1) .

Step S130, selecting a cluster head node of the number of cluster head nodes in the nodes of the target area according to the contention value of the nodes in the target area.

In an implementation, the embodiment may provide a contention value algorithm for calculating the contention value of each node in the target area. There are a plurality of algorithms for the calculation of the competition value, which are not exemplified in this embodiment.

Optionally, before calculating the contention value of the node in the target area, it may first confirm which nodes participate in the election of the cluster head node, and do not perform the calculation of the contention value for the nodes that do not need to participate in the election of the cluster head node. Specifically, it may be first determined whether the node is a node with strong communication capability. A node that uses cellular communication can be used as a node with strong communication capabilities, such as a mobile phone using a SIM card communication. In addition, the remaining nodes that use WiFi, Bluetooth, Zigbee, and D2D (Device-to-Device Communication) communication can be used as nodes with weak communication capabilities. The above distinctions for the communication capabilities of the nodes are mainly based on the distance of their communication. For example, a mobile phone can be connected to a base station outside of a kilometer via a cellular network, however, the tablet can only be connected to a router within 30 meters via WiFi. Obviously, the communication capacity of mobile phones is far greater than the communication capabilities of tablet computers. The node having strong communication capability included in the target area is determined according to the judgment result of the communication capability of the node. Then, it can be determined whether these nodes with strong communication capabilities have established a connection with the base station. If so, it is determined that the node that has established a connection with the base station participates in the election of the cluster head node.

Then, the contention value of the nodes participating in the election of the cluster head node in the target area is calculated. Specifically, the contention value of the node may be calculated by the signal connection strength of the node and the base station, and the node link information. The signal connection strength between the node and the base station can be obtained by directly receiving the strength information sent by the node. The node link information includes the connectivity, the load size, the remaining energy of the node, the remaining bandwidth of the node, and the lifetime of the node. Wherein, the degree of connectivity may be one of neighboring nodes of the node The number of hop nodes. The remaining energy of the node and the remaining bandwidth of the node can be obtained directly from the node. The node lifetime represents the time at which the moving node can exist in the target area. Firstly, the position information of the node can be determined by the position information of the node, and then the time required for the node to move out of the target area according to the motion speed of the node is the node survival time. The formula for calculating the load size can be seen in Equation 7:

Where Δt is the measurement time, Q _max is the largest data queue length in node i in the target area that needs to be transmitted, and Q _avg (t) is the average data to be transmitted by node i in the target area from t-Δt to t time. Queue size.

The method for calculating the contention value of a node by the signal connection strength of the node and the base station and the link information of the node can be seen in Equation 8:

Where N is the number of nodes participating in the election of the cluster head node, and p _j is the normalized value of each parameter included in the link information of the node, such as the degree of connectivity, the size of the load, the remaining energy of the node, the remaining bandwidth of the node, and the lifetime of the node, w Indicates the weight corresponding to each parameter. Among them, different parameters and their weights can be determined according to different application environments.

Optionally, the node in the target area may also send the network topology map of the neighboring node to the base station. The base station can obtain a network topology diagram of the entire target house according to the network topology map of the node in the target area and the neighboring neighbor nodes.

Optionally, the method for electing a cluster head node may be as follows. As shown in FIG. 3, step S130 may include: step S310, sorting nodes in the target area according to the contention value of the nodes in the target area from large to small; and step S320, selecting the node ranked in the top N as the cluster head node. Where N is the number of cluster head nodes and N is an integer greater than or equal to 1.

In the implementation, as shown in FIG. 2, for example, the target area is the area 6, and the nodes are sorted according to the competition value of each node in the area 6 from large to small, and the ranking result is: node C, node E, node F, Node A, Node D, Node B. If the number of cluster head nodes is 2, node C and node E ranked in the top 2 positions can be elected as cluster head nodes.

Optionally, after the cluster head node is elected, for example, by connecting the example, the cluster head node C can be The surrounding nodes A and B serve as their cluster member nodes, and node D and node F around the cluster head node E can be used as their cluster member nodes. Alternatively, clustering may be performed according to the size of data transmitted by other nodes than the cluster head node. For example, node A is a television, node B is a temperature sensor, node D is a computer, and node F is a humidity sensor. Generally speaking, the amount of data that TVs and computers need to transmit is large, and the amount of data that temperature sensors and humidity sensors need to transmit is small. Therefore, nodes with a large amount of data can be separated according to the amount of data to be transmitted, so that they are in a cluster at the same time, and the cluster head node cannot effectively process the data of the cluster member nodes in the cluster. For example, a television and a temperature sensor around the cluster head node C can be used as its cluster member node, and a computer and a humidity sensor around the cluster head node E can be used as its cluster member node. Of course, it can also be clustered by the algorithm of the reservation. Finally, after the cluster head node is elected and the cluster node nodes are carried by the cluster head node, the base station sends the election result and the clustering result to the nodes participating in the election of the cluster head node. The unsuccessful node can disconnect from the base station and connect to its cluster head node instead. The node that selects the cluster head node can notify its cluster member node to establish a connection with itself.

Optionally, the optimal node can also be continuously updated as a cluster head node. Correspondingly, after the election of the cluster head node is completed, when a new node is detected to join the target area, the method provided by the embodiment further includes: according to the competition value of the new node and the cluster head node in the target area, the new node and The cluster head node elects the node ranked in the first N bits as the cluster head node, where N is the number of cluster head nodes.

In the implementation, when it is detected that a new node is opened and added to the local area network, the contention value of the new node may be calculated, according to the new node in the target area and the competition value of each cluster head node, in the new node and each cluster. The node in the top N position is elected as the cluster head node.

Optionally, in addition to the foregoing method of updating an optimal node as a cluster head node, another method of updating an optimal node as a cluster head node may be provided. After each predetermined time T, the competition value of the nodes in the target area is recalculated, and the election of the cluster head nodes is performed again according to the new competition value.

After the cluster head node is elected and clustering is completed, as shown in Figure 4, a complete network can be established. The base station can be connected to the cluster head node, and the cluster head node can be connected to its cluster member node. Communication can also take place between cluster head nodes.

Optionally, after the cluster head node is elected and the clustering is completed, the base station may send the network topology map of the entire target house to each node, and each node may be based on the network topology of the entire target house. The graph calculates the routing table. If the node is communicating within the local area network of the home, each node can determine how to send data from the source node to the destination node by querying the routing table. It should be noted that, in the local area network, in addition to the cluster member nodes directly connected to the cluster head node, there are secondary cluster member nodes that cannot be directly connected to the cluster head node, and they need to pass between them. Communication and transmission of data with communication between cluster member nodes that can be directly connected to the cluster head node. Therefore, there may be multiple paths from the source node to the destination node.

Optionally, as shown in FIG. 5, the data to be transmitted may be divided into three parts, and data transmission is performed through three preferred paths. For any node in the transmission, when the node receives any data packet, it can determine whether it is the destination node, and if so, unpack the data packet, if not, determine whether it is the first time to receive the data packet. If the packet is received for the first time, the packet is directly forwarded. If the packet is not received for the first time, it is determined whether the path of the second transmission of the packet intersects with the path of the first transmission, and if so, the packet is discarded. For example, as shown in FIG. 5, the source node sends the data packet Bag from the node A to the node B, and the node B determines that the data packet is received for the first time, and the source node sends the data packet Bag again from the node C to the node B. When the Node B determines that the data packet is not received for the first time, it determines whether the path of the second transmission intersects with the path of the first transmission. Specifically, the data packet Bag is sent from the source node to the node A for the first time and then to the node B and then to the node D. The data packet Bag is sent from the source node to the node C and then to the node B and then to the node. D, the two paths are intersected, and the intersection point is the node B, so the packet of the packet can be discarded to avoid repeatedly sending the packet to the destination node and wasting the communication resources of the local area network. In addition, when the source node is an internal node of the local area network and the destination node is an external node of the local area network, the cluster head node of the source node needs to forward the data to the base station, and then the base station forwards the data to the network where the destination node is located.

According to the method provided in this embodiment, the number of cluster head nodes corresponding to the target area is determined according to the area attribute information of the target area, and the number of the cluster head nodes is determined according to the area attribute information of the target area, and the target area is determined for different ranges. If there are different area attributes, the area attribute information is also different, and then the number of cluster head nodes obtained is determined according to the target area attribute. The number of dynamically changing cluster head nodes is more suitable than the fixed number of cluster head nodes. Target areas in different ranges.

A further exemplary embodiment of the present disclosure provides a base station, as shown in FIG. 6, the base station includes:

a node determining module 610, configured to determine, according to location information of a node in the target house and a range of the target area in the target house, a node included in the target area;

The number determining module 620 is configured to determine, according to the area attribute information of the target area, the number of cluster head nodes corresponding to the target area;

The first election module 630 is configured to elect, according to a contention value of a node in the target area, a cluster head node of the number of cluster head nodes among nodes of the target area.

Optionally, the number determining module 620 is specifically configured to determine, according to the following calculation formula, a number of cluster head nodes corresponding to the target area:

Optionally, the target area is a room of the target house.

Optionally, as shown in FIG. 7, the first election module 630 includes:

a sorting unit 731, configured to sort nodes in the target area according to a competition value of nodes in the target area from large to small;

The election unit 732 is configured to elect a node ranked in the top N as a cluster head node, where N is the number of cluster head nodes.

Regarding the base station in the above embodiment, the specific manner in which each module performs an operation has been A detailed description of the embodiment of the method will not be described in detail herein.

It should be noted that the method for electing a cluster head node provided by the foregoing embodiment is only exemplified by the division of the foregoing functional modules when the cluster head node is elected. In actual applications, the foregoing functions may be allocated differently according to requirements. The function module is completed, that is, the internal structure of the base station is divided into different functional modules to complete all or part of the functions described above. In addition, the method for the base station and the method for electing the cluster head node in the foregoing embodiment are the same. The specific implementation process is described in the method embodiment, and details are not described herein again.

The embodiment of the present disclosure further provides a base station, where the base station includes:

Optionally, the target area is a room of the target house.

Optionally, the first electoralator includes:

Embodiments of the present disclosure provide a base station including a processor and a memory, where the computer instructions are stored in the memory, and the computer instructions are executed by the processor to implement the method for electing the cluster head node shown in the above disclosed embodiments.

As shown in FIG. 8, it is a schematic structural diagram of a base station 900, which includes a processor 902 and a memory 904.

The processor 902 typically controls the overall operation of the base station 900, and the processor 902 can be used to execute computer instructions to perform all or part of the steps of the method of electing a cluster head node as disclosed in the above-described disclosed embodiments. Exemplary. The processor 902 can be a central processing unit, a general purpose processor, a digital signal processor, an application specific integrated circuit, a field programmable gate array or other programmable logic device, a transistor logic device, a hardware component, or any combination thereof. It is possible to implement or perform various illustrative logical blocks, modules and circuits described in connection with the embodiments of the present disclosure. The processor can also be a combination of computing functions, for example, including one or more microprocessor combinations, a combination of a DSP and a microprocessor, and the like.

Memory 904 can be configured to store various types of data to support operation at base station 900. Examples of such data include instructions for any application or method operating on base station 900. Memory 904 can be implemented by any type of volatile or non-volatile storage device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Read Only Memory (PROM), Read Only Memory (ROM), Magnetic Memory, Flash Memory, Disk or Optical Disk.

Communication component 906 is configured to facilitate wired or wireless communication between base station 900 and other devices. The base station 900 can access a wireless network based on a communication standard, such as 2G, 3G or 4G, or a combination thereof.

In an exemplary embodiment, base station 900 may be implemented by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable A gate array (FPGA), controller, microcontroller, microprocessor or other electronic component implementation for performing the method of electing a cluster head node as described in the above embodiments of the present disclosure.

In an exemplary embodiment, there is also provided a computer readable storage medium having stored thereon computer instructions, wherein instructions in the storage medium are executed by a processor to perform electoral clusters as disclosed in the above disclosed embodiments The method of the head node. Illustratively, the computer readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device.

The embodiment of the present disclosure further provides a computer program product, wherein the computer program product stores a computer instruction, and the computer instruction is executed by a processor to implement the method for electing a cluster head node shown in the above disclosed embodiment.

Other embodiments of the present disclosure will be readily apparent to those skilled in the <RTIgt; The present application is intended to cover any variations, uses, or adaptations of the present disclosure, which are in accordance with the general principles of the disclosure and include common general knowledge or common technical means in the art that are not disclosed in the present disclosure. . The specification and examples are to be regarded as illustrative only,

It is to be understood that the invention is not limited to the details of the details and The scope of the disclosure is to be limited only by the appended claims.

Claims

A method for electing a cluster head node, the method comprising:

Determining a node included in the target area according to location information of a node in the target house and a range of the target area in the target house;

Determining, according to the area attribute information of the target area, the number of cluster head nodes corresponding to the target area;

And selecting, according to a contention value of a node in the target area, a cluster head node of the number of cluster head nodes among nodes of the target area.
The method according to claim 1, wherein the area attribute information of the target area comprises a number of nodes of the target area, a maximum side length, and an average distance of a node to a base station in the target area.
The method according to claim 2, wherein the number of cluster head nodes corresponding to the target area is positively correlated with the number of nodes of the target area, and is positively correlated with the maximum side length of the target area, and the target The average distance from each node to the base station in the area is inversely related.
The method according to claim 2 or 3, wherein the determining the number of cluster head nodes corresponding to the target area according to the area attribute information of the target area comprises:

Determine the number of cluster head nodes corresponding to the target area according to the following calculation formula:

Where k opt is the number of cluster head nodes corresponding to the target area, n is the number of nodes of the target area, M is the maximum side length of the target area, and the d toBS is the node to the base station in the target area. Average distance.
The method of claim 1 wherein said target area comprises a room of said target house.
The method according to claim 1, wherein the cluster head node that elects the number of the cluster head nodes in the nodes of the target area according to the contention value of the nodes in the target area comprises:

Sorting the nodes of the target area according to the competition value of the nodes in the target area from large to small;

Electing the nodes ranked in the top N as cluster head nodes, where N is the number of cluster head nodes, N is an integer greater than or equal to 1.
The method according to claim 1, wherein after the election of the cluster head node is completed, when it is detected that a new node is added to the target area, the method further includes:

Selecting, in the new node and the cluster head node, a node ranked in the top N as a cluster head node according to a contention value of the new node and the cluster head node in the target area, where N is the cluster head node The number, N is an integer greater than or equal to 1.
A base station, comprising: a processor and a memory; wherein the memory stores computer instructions, the computer instructions being executed by the processor to implement any of the above claims 1-7 The method of electing a cluster head node.
A computer readable storage medium, wherein the storage medium stores computer instructions, the computer instructions being executed by a processor to implement the method of electing a cluster head node according to any of claims 1-7.
A computer program product, wherein the computer program product stores computer instructions, the computer instructions being executed by a processor to implement the method of electing a cluster head node according to any of claims 1-7.