• Journal of KIISE
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• v.41 no.11
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• pp.958-966
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• 2014

Wireless sensor networks offer a distributed processing environment. Many sensor nodes are deployed in fields that have limited resources such as computing power, network bandwidth, and electric power. The sensor nodes construct their own networks automatically, and the collected data are sent to the sink node. In these traditional wireless sensor networks, network congestion due to packet flooding through the networks shortens the network life time. Clustering or in-network technologies help reduce packet flooding in the networks. Many studies have been focused on saving energy in the sensor nodes because the limited available power leads to an important problem of extending the operation of sensor networks as long as possible. However, we focus on the execution time because clustering and local distributed processing already contribute to saving energy by local decision-making. In this paper, we present a cooperative processing model based on the processing timeline. Our processing model includes validation of the processing, prediction of the total execution time, and determination of the optimal number of processing nodes for distributed processing in wireless sensor networks. The experiments demonstrate the accuracy of the proposed model, and a case study shows that our model can be used for the distributed application.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.2
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• pp.116-120
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• 2008

Clustering is a method for unsupervised learning. General clustering tools have been depended on statistical methods and machine learning algorithms. One of the popular clustering algorithms based on machine learning is the self organizing map(SOM). SOM is a neural networks model for clustering. SOM and extended SOM have been used in diverse classification and clustering fields such as data mining. But, SOM has had a problem determining optimal number of clusters. In this paper, we propose an improvement of SOM using gap statistic and probability distribution. The gap statistic was introduced to estimate the number of clusters in a dataset. We use gap statistic for settling the problem of SOM. Also, in our research, weights of feature nodes are updated by probability distribution. After complete updating according to prior and posterior distributions, the weights of SOM have probability distributions for optima clustering. To verify improved performance of our work, we make experiments compared with other learning algorithms using simulation data sets.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.2B
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• pp.76-81
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• 2008

LEACH (Low Energy Adaptive Clustering Hierarchy) has been proposed as a routing protocol with a hierarchical structure, in order to achieve the energy efficiency that is of primary importance in the wireless sensor networks. A wireless sensor network adopting LEACH is composed of a few clusters, each of which consists of member nodes that sense the data, and head nodes that deliver the collected data from member nodes to a sink node that is connected to a backbone network. A head node in a cluster allocates TDMA slots to its member nodes without taking into account whether they have data to transmit or not, thus resulting in inefficiency of energy usage of head node that remains in active mode during the entire round time. This motivates us to propose a scheme to improve the energy efficiency of LEACH, by assigning TDMA slots only to those member nodes who have data to send. As a result, the head node can remain sleep during the period of no data transmission from member nodes, leading to the substantial energy saving. By using the ns-2 simulator, we evaluate the performance of the proposed scheme in comparison with the original LEACH. Experimental results validate our scheme, showing a better performance than original LEACH in terms of the number of outliving nodes and the quantity of energy consumption as time evolves.

• Journal of Advanced Navigation Technology
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• v.13 no.4
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• pp.551-558
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• 2009

Most of clustering schemes focusing on the energy efficiency have only a cluster head in each cluster, thus the energy consumption of cluster head in a cluster can rapidly increase. To reduce the energy consumption, recently, the dual-layered clustering which is separated a cluster ranges into two parts, i.e., data aggregation layer and data transmission layer, based on a sensor equipped with geographical positioning system (GPS), was proposed. However, the logical regions existing within the dual-layered clustering range can not distinguish efficiently. This scheme leads to many messages collision and transmission delay among member nodes. In this paper, to solve these problems, we propose a separated dual-layered routing scheme using the position information and the cluster radius. Proposed scheme clearly distinguish the dual-layered clustering range and gets the balanced number of member nodes in each cluster. Therefore, the proposed routing scheme could prolong the overall network life time about 10% compared to the previous two layered clustering scheme and LEACH.

• Annual Conference of KIPS
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• 2010.11a
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• pp.925-928
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• 2010

Wireless sensor networks are composed of a large number of sensor nodes with limited energy resources. One critical issue in wireless sensor networks is how to gather sensed information in an energy efficient way since the energy is limited. The clustering algorithm is a technique used to reduce energy consumption. It can improve the scalability and lifetime of wireless sensor network. In this paper, we introduce a clustering protocol with mode selection (CPMS) for wireless sensor networks. Our scheme improves the performance of BCDCP (Base Station Controlled Dynamic Clustering Protocol) and BIDRP (Base Station Initiated Dynamic Routing Protocol) routing protocol. In CPMS, the base station constructs clusters and makes the head node with highest residual energy send data to base station. Furthermore, we can save the energy of head nodes using modes selection method. The simulation results show that CPMS achieves longer lifetime and more data messages transmissions than current important clustering protocol in wireless sensor networks.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.12
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• pp.9-16
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• 2016

Wireless sensor networks (WSN) are composed of sensor nodes and a base station. The sensor nodes deploy a non-accessible area, receive critical information, and transmit it to the base station. The information received is applied to real-time monitoring, distribution, medical service, etc.. Recently, the WSN was extended to mobile wireless sensor networks (MWSN). The MWSN has been applied to wild animal tracking, marine ecology, etc.. The important issues are mobility and energy consumption in MWSN. Because of the limited energy of the sensor nodes, the energy consumption for data transmission affects the lifetime of the network. Therefore, efficient data transmission from the sensor nodes to the base station is necessary for sensing data. This paper, proposes an energy consumption model using two-tier clustering in mobile sensor networks (TTCM). This method divides the entire network into two layers. The mobility problem was considered, whole energy consumption was decreased and clustering methods of recent researches were analyzed for the proposed energy consumption model. Through analysis and simulation, the proposed TTCM was found to be better than the previous clustering method in mobile sensor networks at point of the network energy efficiency.

• Journal of Digital Contents Society
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• v.9 no.1
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• pp.33-39
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• 2008

Mobile Ad Hoc Network is easy to be attacked because nodes are distributed not network based infrastructure. Intrusion detection system perceives the trust values of neighboring nodes and receives inspection on local security of nodes and observation ability. This study applied clustering mechanism to reduce overhead in intrusion detection. And, in order to measure the trust values, it associates the trust information cluster head received from member nodes with its own value and evaluates the trust of neighboring nodes. Secure data transmission is received by proposed concept because the trust of nodes on network is achieved accurately.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.9
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• pp.3468-3495
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• 2015

In this paper, we present a multi-chain based hierarchical topology control algorithm (MCHTC) for wireless sensor networks. In this algorithm, the topology control process using static clustering is divided into sensing layer that is composed by sensor nodes and multi-hop data forwarding layer that is composed by leader nodes. The communication cost and residual energy of nodes are considered to organize nodes into a chain in each cluster, and leader nodes form a tree topology. Leader nodes are elected based on the residual energy and distance between themselves and the base station. Analysis and simulation results show that MCHTC outperforms LEACH, PEGASIS and IEEPB in terms of network lifetime, energy consumption and network energy balance.

• Journal of Internet Computing and Services
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• v.9 no.4
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• pp.43-50
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• 2008

Various studies are being conducted to achieve efficient routing and reduce energy consumption in wireless sensor networks where energy replacement is difficult. Among routing mechanisms, the clustering technique has been known to be most efficient. The clustering technique consists of the elements of cluster construction and data transmission. The elements that construct a cluster are repeated in regular intervals in order to equalize energy consumption among sensor nodes in the cluster. The algorithms for selecting a cluster head node and arranging cluster member nodes optimized for the cluster head node are complex and requires high energy consumption. Furthermore, energy consumption for the data transmission elements is proportional to $d^2$ and $d^4$ around the crossover region. This paper proposes a means of reducing energy consumption by increasing the efficiency of the cluster construction elements that are regularly repeated in the cluster technique. The proposed approach maintains the number of sensor nodes in a cluster at a constant level by equally partitioning the region where nodes with density considerations will be allocated in cluster construction, and reduces energy consumption by selecting head nodes near the center of the cluster. It was confirmed through simulation experiments that the proposed approach consumes less energy than the LEACH algorithm.

• The KIPS Transactions:PartC
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• v.8C no.6
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• pp.765-774
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• 2001

In this paper, we proposed the striping policy for the storage nodes in the Linux-based parallel media stream server. We newly developed a storage clustering architecture, and named it as a system RAID architecture. In this system, many storage cluster nodes are grouped to operate as a single server. This system uses unique striping policy to distribute multimedia files into the parallel storage nodes. If a service request occurs, each storage cluster node transmits striped files concurrently to the clients. This scheme can provide the fair distribution of the preprocessing load in all storage cluster nodes. The feature of this system is a relative striping policy based on the file types, service types, and the number of storage nodes to provide the best service.