KR100932922B1 - Clustering-based Location Awareness in Wireless Sensor Networks - Google Patents

Abstract

Clustering-based location recognition method in a wireless sensor network according to the present invention comprises the steps of recognizing the mutual location between the cluster head; Selecting, by the sensor node, a cluster head to govern itself; And acquiring the location information of the sensor node by the cluster head, and using the first and second location recognition processes, a structure using only the minimum communication overhead for location recognition is possible. In particular, the secondary location recognition process executes the location inference engine of the corresponding sensor node only when necessary according to the application scenario, thereby minimizing the power consumption of the entire network required for location recognition.

Wireless Sensor Networks, Clusters, Location Awareness

Description

Method for recognizing location based on clustering in wireless sensor network}

The present invention is a location recognition for a low-power wireless sensor network that can reduce the communication overhead between each node and minimize the power consumption of the sensor node when performing the routing and location-aware technique using a clustering structure in a dense environment of sensor nodes It is about a method.

The present invention is derived from the research conducted as part of the IT growth engine technology development project of the Ministry of Information and Communication and the Ministry of Information and Communication Research and Development. [Task No.:2005-S-106-03, Task name: Node technology development].

A wireless sensor network (WSN) refers to a wireless network system consisting of a sensor node that provides a communication function to a sensor that senses various information and a sink node that collects and delivers the information to a user. In recent years, research has been actively conducted to integrate not only home networks and telematics systems, but also control and management of industrial facilities, hospitals, military, disaster prevention, and security. As the application environment of WSN is extended from indoor to outdoor environment, research on sensor node location, mobility, routing technique and low power is becoming an important issue.

In general, the position recognition technology can recognize the position even in indoor or shadowed areas and requires precision within several tens of centimeters in a relatively narrow area. These technologies include wireless sensor networks for logistics automation, security, industrial automation and control, building automation, robotics, child protection, soldier location in combat, rescue of firefighters isolated or missing during evolution, and medical care. Application is possible.

In the conventional position recognition technology, when a reference node in a network broadcasts periodically, sensor nodes that do not know the position determine their own position by estimating the distance based on this information. Although the increase in the amount of communication and power consumption between the sensor nodes due to the location recognition engine is unavoidable, it is never desirable to accelerate the increase in resource consumption as the number of sensor nodes increases.

In addition, the conventional wireless sensor network-based location recognition technique aims to increase the accuracy of the location recognition algorithm. Power consumption is significant because it has the same computing power between sensor nodes and exchanges information with all sensor nodes that want to know the position as the number of reference nodes to use for location recognition. There are improvements, but they are not very efficient in terms of power limitations.

Another prior art location-based service providing system using a geographic code presents a location sensor node-centric routing by assigning a geographic code GGC, such as GPS, to a non-location sensor node.

   Since the location sensor node knows exactly the location of the next sensor node to which information should be conveyed, if one routing path of the existing tree structure is blocked, all the paths below will be paralyzed. It can compensate for the so-called looping problem in which the routing path of the structure only hoveres within a certain area.

However, this structure is not suitable for recognizing the exact location of the non-position sensor node, and the burden of the non-position sensor node should always have GGC code in the flash memory, and the sensor node may not read and write to the flash memory which consumes a lot of power when moving. It is not efficient in terms of power consumption because it is repeated.

The technical problem to be solved by the present invention is to provide a location-aware method that can reduce the efficient routing, low power, and communication overload by using a cluster-based location recognition method in a wireless sensor network environment including a location recognition engine. It is.

In order to solve the above technical problem, a clustering-based location recognition method in a wireless sensor network according to the present invention includes: recognizing mutual positions between cluster heads; Selecting, by the sensor node, a cluster head to govern itself; And acquiring position information of the sensor node by the cluster head.

In order to solve the above technical problem, a clustering-based location recognition method in a wireless sensor network according to the present invention includes: recognizing mutual positions between cluster heads; Selecting, by the sensor node, a cluster head to govern itself; Acquiring position information of the sensor node by the cluster head; And performing a handover by exchanging information with cluster heads of a cluster that the sensor node passes when the sensor node moves.

The clustering-based location recognition method in the wireless sensor network according to the present invention proposes a concept and a detailed method of the clustering-based location recognition method as a method for minimizing the overall traffic load and power consumption between the ubiquitous wireless sensor network and the sensor node. .

Through the first and second location recognition process proposed in the present invention, a structure using only the minimum communication overhead for location recognition is possible. In particular, the second location recognition process may be performed only when necessary according to an application scenario. Running a location inference engine minimizes the power consumption of the entire network for location awareness.

In addition, by using the position information of the cluster heads obtained in the first position recognition process and by limiting the routing path of the end sensor nodes in the cluster to the cluster head, it is possible to implement a simple and efficient routing algorithm.

In the present invention, it is assumed that system resources of the cluster head and the terminal sensor node are inequality. In other words, it is assumed that the cluster head has superior power, memory, and computing power with respect to the end sensor node. Therefore, most of the computational complexity of the location-aware technique itself is transferred to the cluster head, thereby maximizing the lifetime of the network for a given system resource.

Finally, by using the simple location recognition process and the beacon signal for the mobile sensor node, the mobile node actively performs the handover between clusters, thereby efficiently updating the local information according to the mobility. .

Before describing an embodiment of the present invention in detail, the necessity of the present invention in a wireless sensor network will be briefly described. The present invention proposes an efficient technique of a location recognition engine that has emerged as a core technology for various applications in a wireless sensor network. The clustering-based location-aware technology proposed in the present invention reduces the communication load of the wireless sensor node to maximize the lifespan, enable efficient routing, and consider the mobility of the nodes by lowering the power of the wireless sensor node. Sensor nodes are themselves self-contained technologies that relate to their structure and operation technology. Efficient routing refers to a technique that overcomes the problems of the topology by using a hierarchical structure with two different topologies and establishes a new routing path with low power when the sensor node moves.

Meanwhile, in order to transmit information in a multihop from a source node to a sink node, routing is required. If the location of nodes in a wireless sensor network is known, routing paths can be easily determined through local information using the nodes. This local information based routing technique can reduce the complexity of the routing algorithm. In this case, rather than requiring a high level of location accuracy, the local information may reduce complexity by only direction information of a node to be targeted from the reference node. The location recognition scheme proposed in the present invention can reduce power consumption and lead to a reduction in communication between nodes by simplifying the execution of the location recognition engine as necessary. There is a need to minimize network power consumption to obtain location information of sensors in a wireless sensor network. This is in the same context as minimizing the amount of communication overhead needed to obtain location information.

In addition, by using the acquired location information, it overcomes the disadvantages of the routing of the existing tree and mesh networks, enables low-power low-load communication, and enables low-power low-load communication even when the sensor node moves. There is also a need to provide efficient routing techniques that can be easily incorporated into new clusters to quickly set up routing paths.

In particular, the conventional technology assumes that all nodes in the sensor network are devices with equivalent system resources, so that the location-aware engine is operated, resulting in not only traffic overload and power consumption, but also inefficient routing paths caused by location-aware errors. Will be set. In order to solve this problem, the present invention provides a clustering-based location recognition technique, thereby pursuing low power and reducing traffic overload.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. However, descriptions of technical matters that are easily understood by those skilled in the art will be omitted. 1 is a diagram conceptually illustrating a configuration of a clustering-based low power sensor network. 2 is a flowchart illustrating a clustering-based location recognition method in the wireless sensor network according to the present invention, and FIG. 3 is a flowchart illustrating a first location recognition process (a location recognition process between cluster heads). 4 is a view showing the concept of a secondary position recognition process (position recognition process of the terminal sensor node). 5 is a flowchart illustrating a position recognition process with a clustering of a mobile sensor node, and FIG. 6 is a diagram illustrating a concept of position recognition with a clustering of a mobile thin wire node.

1 shows an example of a configuration of a ubiquitous sensor network for applying a location recognition structure and method of a clustering-based wireless sensor node according to the present invention. The cluster head knows the location information of cluster heads and is collected by cluster heads. The gateway 101 connects the information to the external network and the cluster head 103 which determines the location of the sensor nodes or relays the information collected from the sensor nodes to the gateway, and transmits the collected information with the position recognition engine in the dormant state. Or, if necessary, a plurality of sensor nodes 105 in a position aware engine operating state. In addition, as shown in FIG. 1, the cluster is connected to the cluster in a mesh structure through each head, and the cluster head and the terminal sensor nodes in the cluster form a star structure topology.

The data collected from the end node 105 is sent to the cluster head 103, which sends the information to the gateway 101 or receives information from the gateway 101 in a multi-hop via routing. By doing so, the sensor node 105 is managed, and the gateway 101 manages the cluster head 103 and the sensor node 105 and the data collected therefrom while connecting and transmitting information to and from an external network.

2 shows the overall flow of the present invention. The position recognition method according to the present invention is largely a first position recognition process (step S201) for estimating position recognition information between cluster heads and an association in which end sensor nodes select and join a cluster head to form a cluster. Process (steps S203 to S20), and a second position recognition process (step S209) to obtain position information of the terminal sensor nodes.

The flow for the first location recognition process is shown in more detail in FIG. 3. It is assumed that a plurality of cluster heads exist in a network for multi-hop relaying of sensing information, and all or some of them know their location. The remaining cluster heads that do not know their position receive an RF signal from the neighboring cluster head (reference cluster head) to determine their position, and determine their relative position. (Step S301 to step S305) The cluster head having determined its own location information transmits its own local information to the adjacent cluster head, gateway, and sensor node (step S307). It can be used as geographic information to use location-based routing in wireless sensor networks.

As such, after the position information of the cluster heads is estimated through the primary position recognition process, the cluster heads broadcast a control signal such as a beacon signal to form a cluster. After listening to these control signals, the end nodes select the cluster head having the largest signal-to-noise ratio (S / N ratio) and become a member of the cluster (steps S203 to S203). If it is necessary to recognize the location of the sensor node or only routing (step S207), and if it is necessary to recognize the position of the end node, that is, the sensor node, the process proceeds to the second location recognition process as shown in FIG.

4 shows a secondary position recognition process. The end sensor node 401 receives an RF signal from three adjacent cluster heads 402, 403, 404 to determine its position, and then employs a ranging-based or ranging-free algorithm. Estimate the location of use. After the estimation of the position is finished, the end sensor nodes in the cluster transmit their position information to the head 404 of the cluster to which they belong. The secondary position recognition process is a process for obtaining the position information of the end sensor node in the cluster, and does not need to be repeated every time when a communication frame is transmitted or the position recognition information needs to be updated. The location of the end node can be replaced with local information of the corresponding cluster head, if not needed. In other words, the location information of the end sensor node is performed when there is an application level request for the location of the corresponding node (see step S207). Otherwise, the second recognition process is not performed. This can extend sensor network life by consuming no power or increasing communication overhead for all nodes for location awareness.

5 is a flowchart illustrating a location recognition process for a case where a sensor node collects and transmits information while moving. The mobile sensor node must attempt to connect to the cluster to which it currently belongs and the new cluster to be handed over because of the move. To this end, the mobile node generates a beacon signal (step S501) and requests a response signal from an adjacent cluster head (step S503), and uses this to determine the cluster to which it belongs (step S505). The mobile node periodically sends a beacon signal to the cluster head to request a response signal from the new cluster heads to which it belongs, while the routing node establishes a routing path (step S507) or recognizes the position according to the command of the cluster head to which it belongs. In step S509, information is collected and received.

6 is a diagram illustrating an example of exchanging position information with a cluster head while the sensor node 601 moves as shown in the operation flowchart of FIG. 5. The movement path of the sensor node 601 is like a straight line and passes through three cluster head regions from 602 to 604 through this path. Since the sensor node 601 periodically sends a signal to the cluster heads 602 to 604 for information on location recognition, the sensor node 601 has already moved to another area when the sensor node 601 passes from one area to another. Signaling may occur later. In this case, the sensor node 601 maintains the entire area as a routing path and receives no commands. In this case, if the cluster head of the previous region does not answer the command, the cluster head transmits the command to the adjacent cluster head so that the command is transmitted by the cluster head.

The invention can also be embodied as computer readable code on a computer readable recording medium. Computer-readable recording media include all kinds of recording devices that store data that can be read by a computer system. Examples of computer-readable recording media include ROM, RAM, CD-ROM, magnetic tape, floppy disks, optical data storage devices, and the like, which are also implemented in the form of carrier waves (for example, transmission over the Internet). Include. The computer readable recording medium can also be distributed over network coupled computer systems so that the computer readable code is stored and executed in a distributed fashion. In addition, functional programs, codes, and code segments for implementing the present invention can be easily inferred by programmers in the technical field to which the present invention belongs.

Although the present invention has been described with reference to the embodiments shown in the drawings, this is merely exemplary, and it will be understood by those skilled in the art that various modifications and equivalent other embodiments are possible. Therefore, the true scope of protection of the present invention should be defined only by the appended claims.

1 is a diagram conceptually illustrating a configuration of a clustering-based low power sensor network.

2 is a flowchart illustrating a process of a clustering-based location recognition method in a wireless sensor network according to the present invention.

3 is a flowchart showing a primary position recognition process (position recognition process between cluster heads).

4 is a view showing the concept of a secondary position recognition process (position recognition process of the terminal sensor node).

5 is a flowchart illustrating a location recognition process with clustering of a mobile sensor node.

6 is a diagram illustrating a concept of position recognition with a clustering of a mobile thin line node.

Claims (9)

(a) recognizing mutual positions between cluster heads; (b) the sensor node selecting a cluster head to govern itself; And (c) acquiring position information of the sensor node by the cluster head; Step (a) is (a1) receiving a radio frequency (RF) signal from a reference cluster head by a cluster head whose location is unknown; (a2) the cluster head receiving the RF signal to determine a location based on the RF signal; And (a3) transferring the location to an adjacent cluster head; Step (c) is (c1) Clustering-based location recognition method in a wireless sensor network, characterized in that the sensor node receives the RF signal from at least one or more cluster head adjacent to estimate its location. delete The method of claim 1, wherein step (b) (b1) the cluster head broadcasting a predetermined control signal; And (b2) a sensor node receiving the control signal selects a cluster head having the largest signal-to-noise ratio and becomes a member of a cluster controlled by the cluster head; clustering-based location in a wireless sensor network Recognition method. The method of claim 3, wherein the control signal Clustering-based location recognition method in the wireless sensor network, characterized in that the cluster head contains information indicating that the beacon (beacon) or the packet header in the header of the packet itself. delete The method of claim 1, wherein step (c1) If location information of the sensor node is not needed, the location information of the cluster head in charge of the sensor node is substituted for the location information estimation, and the location information is estimated only when necessary based on clustering in the wireless sensor network. Location recognition method. The method of claim 1, (d) performing a handover by exchanging information with cluster heads of a cluster which the sensor node passes through when moving; clustering-based location recognition method in a wireless sensor network, further comprising. The method of claim 7, wherein step (d) (d1) the mobile node transmitting a beacon signal to adjacent cluster heads; And (d2) receiving a response signal from the adjacent cluster heads and selecting the cluster head having the largest signal-to-noise ratio as the head of the cluster to which it belongs to; clustering-based location recognition method in a wireless sensor network. The method of claim 8, wherein step (d) Requesting an adjacent cluster head to transmit the information provision request to the sensor node if there is no response from the information provision request of the cluster head having jurisdiction over the sensor node; clustering in the wireless sensor network Based location recognition method.

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