KR20140044626A

KR20140044626A - Method of clustering ship usn using location attribute and residual energy of sensors

Info

Publication number: KR20140044626A
Application number: KR1020120110834A
Authority: KR
Inventors: 이성호; 박희만; 오일환; 양후열; 김경호; 정민아; 이성로
Original assignee: 목포대학교산학협력단
Priority date: 2012-10-05
Filing date: 2012-10-05
Publication date: 2014-04-15

Abstract

The present invention relates to a method of clustering a ship USN using location attributes and residual energy of sensors in a USN system including multiple sensors. The method comprises the steps of: establishing an attribute hierarchy based on locations of the sensors; forming a cluster comprising one cluster head and multiple nodes having an identical location attribute using location attributes of the nodes; selecting a cluster head from among the nodes; transmitting catalog information from the former cluster head to the selected cluster head; and transmitting the updated catalog information from the selected cluster head to an upper level cluster head. According to the present invention, energy consumption for communications among nodes can be reduced by using the location attributes and residual energy of the sensors. Moreover, a cluster head is not replaced with another frequently since residual energy is considered when a cluster head is selected, thereby providing economic feasibility and stable communications among nodes. [Reference numerals] (AA) Start; (BB) End; (S210) Establishing an attribute hierarchy; (S220) Forming a cluster; (S230) Selecting a cluster head; (S240) Transmitting catalog information; (S250) Transmitting updated catalog information

Description

Method of clustering ship USN using location attribute and residual energy of sensors}

The present invention relates to a ship USN clustering method, and more particularly to a ship USN clustering method using sensor position properties and remaining energy.

Wireless Sensor Networks (WSNs) have become an important technology of considerable interest. Recent advances in wireless communications and electronics have made it possible to develop sensors that are low cost, low power and perform multiple functions. Typically, these sensors are small in size and perform short-range communications. Inexpensive and smart sensors are networked over the wireless link and a large number of sensors are deployed to run the application. Wireless sensor networks monitor and control homes, cities, and the environment. In addition, networked sensors perform a wide range of tasks in tactical applications, as well as in traditional defense areas such as reconnaissance and surveillance.

Most WSN applications use a fairly large number of sensors because the area to be covered is large, the short lifespan of battery-powered sensors, and the potential for damaging sensor nodes in deployment. Therefore, designing and operating a wireless sensor network requires a scalable architecture strategy and management strategy. In addition, sensors in such an environment are energy constrained, and the battery of the sensor is often not rechargeable. For this reason, clustering techniques have been actively studied in which sensor nodes are grouped into clusters and cluster heads representing clusters transfer data within the cluster.

Clustering has many other advantages besides supporting network scalability. You can localize routing settings within the cluster, so that you can reduce the size of routing tables stored on individual nodes. In addition, clustering conserves communication bandwidth because it limits the range of intercluster interactions to clusters and avoids redundant message exchanges between sensor nodes. In addition, clustering can stabilize the network topology at the sensor level and reduce topology maintenance overhead. That is, the sensor is only interested in connecting to its cluster head and will not be affected by changes in the hierarchy levels between cluster heads.

When forming clusters, several methods have been invented to achieve energy efficiency, with HEED and Attribute-Based Clustering (ABC) representative. After the sensor node is deployed, the HEED elects a cluster head and forms a cluster in consideration of the combination of energy and communication cost among the deployed sensors. HEED is a distributed clustering scheme that is selected from the sensors on which the cluster head is located. HEED considers the combination of energy and communication costs when choosing a cluster head. Unlike LEACH, HEED does not randomly select a cell-head node. Only sensors with high residual energy can be cell-head nodes. HEED has three characteristics:

1) The probability that two nodes within the transmission range of each other will be the cluster head is small. Unlike LEACH, this means that cluster heads are well distributed across the network.

2) Energy consumption is not assumed to be equal for all nodes.

3) For the delivery range of a given sensor, the cluster head election probability can be adjusted to ensure connectivity between cluster heads.

ABC (Attribute-Based Clustering) is a method of clustering WSNs based on attributes of queries and data. This method proposes a method of clustering WSNs based on attributes of queries and data. The main motivation is the efficient dissemination of data in the network. The concept is similar to the data-centric design model of WSN. Clustering is established by mapping a layer of data attributes to the network.

1 is a block diagram of a conventional attribute hierarchy. Referring to Figure 1, the approach is based on the well-known leader election algorithm. The base station begins the process by asking the nodes to form a cluster. The node receiving the request decides whether to designate itself as the cluster head based on the energy. After receiving the base station request, the sensor node intending to be the cluster head waits for an arbitrary time based on the remaining battery amount. Nodes with more energy wait longer. If a node appoints itself, the node broadcasts an announcement from node to node. The node later joins the cluster head, which can be reached via the minimum number of hops. During the waiting time, when a node hears a cluster head assertion packet from a neighboring node, it relinquishes its received packet after giving up its cluster head bid and incrementing 1 by the hop count in the packet. As soon as the cluster receives a cluster head announcement from another node, the receiving node establishes a new cluster for that attribute and becomes the cluster head.

However, HEED, which is a conventional technology, does not consider the sensor position, so when communicating between nodes, more energy may be consumed, and ABC does not consider the remaining energy of the sensor node, so that the cluster head may be frequently replaced. there was.

An object of the present invention is to provide a ship USN clustering method capable of stable energy communication with excellent energy efficiency in inter-node communication by using sensor position attributes and remaining energy.

According to an aspect of the present invention, there is provided a vessel USN clustering method using a sensor position attribute and remaining energy, comprising: establishing an attribute hierarchy based on a position of the sensor; Forming a cluster comprising a cluster head and a plurality of nodes of the same location property using the location property of the sensor; Electing a cluster head among the nodes; Transmitting catalog information from a pre-selected cluster head to the elected cluster head; And transmitting the updated catalog information from the elected cluster head to a higher cluster head.

According to the present invention, less energy is consumed when communicating between nodes by using sensor position properties and remaining energy, and the cluster head is not frequently replaced in consideration of the remaining energy of the node when the cluster head is selected, and thus economic efficiency is recognized and stable. Can provide communication between nodes.

1 is a block diagram of an attribute hierarchy in the prior art.
2 is a flow chart of a ship USN clustering method according to an embodiment of the present invention.

BRIEF DESCRIPTION OF THE DRAWINGS The advantages and features of the present invention and the manner of achieving them will become apparent with reference to the embodiments described in detail below with reference to the accompanying drawings. The present invention may, however, be embodied in many different forms and should not be construed as being limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the invention to those skilled in the art. To fully disclose the scope of the invention to a person skilled in the art, and the invention is defined by the scope of the claims. It is to be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. In the present specification, the singular form includes plural forms unless otherwise specified in the specification. As used herein, the terms " comprises, " and / or "comprising" refer to the presence or absence of one or more other components, steps, operations, and / Or additions.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

If you rely on data flooding to spread the query within the ship USN, the sensor will be affected whenever the query requests a different kind of data. This results in energy inefficiencies in the sensor network. In order to save energy, we propose a method of clustering sensors according to attributes that are meaningful to query and can be used to reduce unnecessary traffic.

2 is a flow chart of a ship USN clustering method according to an embodiment of the present invention. Referring to FIG. 2, first, an attribute layer is established based on the position of the sensor (S210).

Specifically, the higher level hierarchy includes the lower level hierarchy. The reason for selecting the location attribute as the clustering criterion is as follows. First, location properties are general enough to be used in most environments. Second, the hierarchy can be easily achieved. For example, the cabin belongs to the floor and the floor belongs to the ship.

In other words, an attribute hierarchy is established from cabin to floor to ship.

Subsequently, a cluster including one cluster head and a plurality of nodes having the same position attribute is formed using the position attribute of the sensor (S220). Specifically, the algorithm forms a cluster of nodes of the same property having one cluster head, and performs a cluster head function between the cluster members. The cluster head gathers information from the members so that it can decide whether to flood the query within the cluster or discard it. Cluster size is constrained to avoid managing disproportionately large clusters.

Next, the cluster head is selected from the nodes (S230). After the cluster is formed based on the location attribute, the cluster head is prepared to be elected among the nodes in the cluster. Every node announces its remaining energy to neighboring nodes. The neighbor node recommends the node with the highest remaining energy among its neighbors as the cluster head. It compares the node recommended by itself with the node recommended by the neighbor, and recommends the node having the higher remaining energy as the final candidate. In this way the cluster head is elected.

The cluster head rotation is intended to ensure that no one node suffers from energy exhaustion. This is due to the fact that acting as a cluster head requires a lot of energy. The rotation period can be determined depending on the application or determined after a certain number of data collections.

The criteria for selecting a new cluster head is also determined by the remaining energy of the node. The cluster head rotation step is as follows. After the timeout period, the sensor node with the highest energy remaining in the cluster announces its intention to be the cluster head. If multiple candidates come up, the most suitable candidate is determined as the cluster head.

Subsequently, catalog information is transmitted from the preselected cluster head to the selected cluster head (S240). Specifically, upon timeout, the old cluster head forwards its catalog information to the newly elected cluster head in unicast.

The updated catalog information is transmitted from the elected cluster head to the upper cluster head (S250). Specifically, the new cluster head delivers the updated catalog information to its parent cluster head. This update establishes a unicast path from the new cluster head to the higher level cluster head.

The newly elected sensor may attempt to join the best neighbor cluster with the same attribute value. The sensor may broadcast a request for a membership packet. If no answer is received for the N broadcasts, the sensor remains isolated and can only form a cluster when a cluster-forming packet arrives.

However, if there are nearby clustered sensors, they can respond to membership requests by sending their cluster head instance information as well as their cluster information. If the attributes match or attempt to form a new cluster, the new sensor can join the best cluster.

If there is an addition of the cluster head level, the sensor that receives the cluster head update is effectively a new headerless sensor in the already deployed network. The sensor requests membership, but will receive cluster information without any matching cluster head level instance. This new cluster head is in contact with higher and lower level heads and can reestablish a unicast communication architecture between neighboring level cluster heads.

The foregoing description is merely illustrative of the technical idea of the present invention and various changes and modifications may be made without departing from the essential characteristics of the present invention. Therefore, the embodiments described in the present invention are not intended to limit the scope of the present invention, but are intended to be illustrative, and the scope of the present invention is not limited by these embodiments. It is intended that the present invention cover the modifications and variations of this invention provided they come within the scope of the appended claims and their equivalents, which fall within the scope of the present invention as claimed.

Claims

In a ship USN system comprising a plurality of sensors,
Establishing an attribute hierarchy based on the location of the sensor;
Forming a cluster comprising a cluster head and a plurality of nodes of the same location property using the location property of the sensor;
Electing a cluster head among the nodes;
Transmitting catalog information from a pre-selected cluster head to the elected cluster head; And
Transmitting the updated catalog information from the elected cluster head to a higher cluster head.
Ship USN clustering method using the sensor position attribute and the remaining energy comprising a.

The method according to claim 1,
Electing the cluster head is
Electing the node with the highest remaining energy as the cluster head in a cluster containing a plurality of nodes of the same positional attribute
Vessel USN Clustering Method Using Phosphor Sensor Position Attributes and Residual Energy.