• The KIPS Transactions:PartC
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• v.17C no.1
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• pp.69-80
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• 2010

Wireless sensor networks (WSN) consisting of a large number of sensors aim to gather data in a variety of environments and are being used and applied to many different fields. The sensor nodes composing a sensor network operate on battery of limited power and as a result, high energy efficiency and long network lifetime are major goals of research in the WSN. In this paper we propose a novel tree-based clustering approach for energy efficient wireless sensor networks. The proposed scheme forms the cluster and the nodes in a cluster construct a tree with the root of the cluster-head., The height of the tree is the distance of the member nodes to the cluster-head. Computer simulation shows that the proposed scheme enhances energy efficiency and balances the energy consumption among the nodes, and thus significantly extends the network lifetime compared to the existing schemes such as LEACH, PEGASIS, and TREEPSI.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.9
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• pp.3472-3480
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• 2010

The Clustering technology of Energy efficiency wireless sensor network gets the energy efficiency by reducing the number of communication between sensor nodes and sink node. In this paper, First analyzed on the clustering technique of the distributed clustering protocol routing scheme LEACH (Low Energy Adaptive Clustering Hierarchy) and HEED (Hybrid, Energy-Efficient Distributed Clustering Approach), and based on this, new energy-efficient clustering technique is proposed for the cause the maximum delay of dead nodes and to increase the lifetime of the network. In the proposed method, the cluster head is elect the optimal efficiency node based on the residual energy information of each member node and located information between sink node and cluster node, and elected a node in the cluster head since the data transfer process from the data been sent to the sink node to form a network by sending the energy consumption of individual nodes evenly to increase the network's entire life is the purpose of this study. To verify the performance of the proposed method through simulation and compared with existing clustering techniques. As a result, compared to the existing method of the network life cycle is approximately 5-10% improvement could be confirmed.

• International Journal of Contents
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• v.8 no.2
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• pp.13-18
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• 2012

In wireless sensor networks, an energy efficient data gathering scheme is one of core technologies to process a query. The cluster-based data gathering methods minimize the energy consumption of sensor nodes by maximizing the efficiency of data aggregation. However, since the existing clustering methods consider only uniform network environments, they are not suitable for the real world applications that sensor nodes can be distributed unevenly. To solve such a problem, we propose a balanced multi-hop clustering scheme in non-uniform wireless sensor networks. The proposed scheme constructs a cluster based on the logical distance to the cluster head using a min-distance hop count. To show the superiority of our proposed scheme, we compare it with the existing clustering schemes in sensor networks. Our experimental results show that our proposed scheme prolongs about 48% lifetime over the existing methods on average.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.4
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• pp.665-683
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• 2011

Wireless sensor networks (WSN) consist of a large amount of sensor nodes distributed in a certain region. Due to the limited battery power of a sensor node, lots of energy-efficient schemes have been studied. Clustering is primarily used for energy efficiency purpose. However, clustering in WSNs faces several unattained issues, such as ensuring connectivity and scheduling inter-cluster transmissions. In this paper, we propose a location-based spiral clustering (LBSC) algorithm for improving connectivity and avoiding inter-cluster collisions. It also provides reliable location aware routing paths from all cluster heads to a sink node during cluster formation. Proposed algorithm can simultaneously make clusters in four spiral directions from the center of sensor field by using the location information and residual energy level of neighbor sensor nodes. Three logical addresses are used for categorizing the clusters into four global groups and scheduling the intra- and inter-cluster transmission time for each cluster. We evaluated the performance with simulations and compared it with other algorithms.

• Journal of KIISE:Information Networking
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• v.36 no.2
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• pp.98-107
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• 2009

In this paper, we propose a novel centralized energy-efficient clustering algorithm, called "MCCA : Max k-Cut based Clustering Algorithm for Wireless Sensor Networks." The algorithm does not use location information and constructs clusters via a distributive Max k-Cut based cluster-head election method, where only relative and approximate distance information with neighbor nodes is used and nodes, not having enough energy, are excluded for cluster-heads for a specific period. We show that the energy efficiency performance of MCCA is better than that of LEACH, EECS and similar to BCDCP's by simulation studies.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.6
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• pp.229-234
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• 2014

As association between sensor networks that collect environmental information by using numberous sensor nodes and smartphones that are equipped with various sensors, many applications understanding users' context have been developed to interact users and their environments. Collected data should be stored with XML formatted metadata containing semantic information to share the collected data. In case of distance based clustering schemes, the efficiency of data collection decreases because metadata files are extended and changed as the purpose of each system developer. In this paper, we proposed a clustering scheme considering the structural similarity of metadata to reduce clustering construction time and improve the similarity of metadata among member nodes in a cluster.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.4
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• pp.252-258
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• 2013

As WSN is energy constraint so energy efficiency of nodes is important. Because avoiding long distance communication, clustering operating in rounds is an efficient algorithm for prolonging the lifetime of WSN and its performance depends on duration of a round. A short round time leads to frequent re-clustering while a long round time increases energy consume of cluster heads more. So existing clustering schemes determine proper round time, based on the parameters of initial WSN. But it is not appropriate to apply the round time according to initial value throughout the whole network time because WSN is very dynamic networks nodes can be added or vanished. In this paper we propose a new algorithm which calculates the round time relying on the alive node number to adapt the dynamic WSN. Simulation results validate the proposed algorithm has better performance in terms of energy consumption of nodes and loss rate of data.

• Smart Media Journal
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• v.6 no.4
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• pp.24-31
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• 2017

In wireless sensor networks, sensor nodes are deployed in a remote, harsh environment. When the power of the sensor node is consumed in such a network, the sensor nodes become useless together with the deterioration of the quality and performance of the sensor network which may save human life. Although many clustering protocols have been proposed to improve the energy consumption and extend the life of the sensor network, most of the previous studies have shown that the overhead of the cluster head is quite large. It is important to design a routing protocol that minimizes the energy consumption of each node and maximizes the network lifetime because of the power limitations of the sensor nodes and the overhead of the cluster heads. Therefore, in this paper, we propose an efficient clustering scheme that reduces the burden of cluster heads, minimizes energy consumption, and uses algorithms that maximize network lifetime. Simulation results show that the proposed clustering scheme improves the energy balance and prolongs the network life when compared with similar techniques.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.12
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• pp.3675-3681
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• 2009

One of the most important factors in the lifetime of WSN(Wireless Sensor Network) is the limited resources and static control problem of the sensor nodes. In order to achieve energy efficiency and network utilities, sensor nodes can be well organized into one cluster and selected head node and normal node by dynamic conditions. Various clustering algorithms have been proposed as an efficient way to organize method based on LEACH algorithm. In this paper, we propose an efficient clustering algorithm using information entropy theory based on LEACH algorithm, which is able to recognize environmental differences according to changes from data of sensor nodes. To measure and analyze the changes of clusters, we simply compute the entropy of sensor data and applied it to probability based clustering algorithm. In experiments, we simulate the proposed method and LEACH algorithm. We have shown that our data balanced and energy efficient scheme, has high energy efficiency and network lifetime in two conditions.

• The Journal of the Acoustical Society of Korea
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• v.32 no.2
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• pp.174-180
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• 2013

This paper proposes a decision tree based context clustering algorithm for HMM-based speech synthesis systems using the cross likelihood ratio with a hierarchical prior (CLRHP). Conventional algorithms tie the context-dependent HMM states that have similar statistical characteristics, but they do not consider the statistical similarity of split child nodes, which does not guarantee the statistical difference between the final leaf nodes. The proposed CLRHP algorithm improves the reliability of model parameters by taking a criterion of minimizing the statistical similarity of split child nodes. Experimental results verify the superiority of the proposed approach to conventional ones.