• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.237-244
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• 2021

Clustering is a most powerful un-supervised machine learning techniques for division of instances into homogenous group, which is called cluster. This Clustering is mainly used for generating a good quality of cluster through which we can discover hidden patterns and knowledge from the large datasets. It has huge application in different field like in medicine field, healthcare, gene-expression, image processing, agriculture, fraud detection, profitability analysis etc. The goal of this paper is to explore both hierarchical as well as partitioning clustering and understanding their problem with various approaches for their solution. Among different clustering K-means is better than other clustering due to its linear time complexity. Further this paper also focused on data mining that dealing with high-dimensional datasets with their problems and their existing approaches for their relevancy

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.121-129
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• 2011

One of the major challenges of minimum energy consumption for wireless sensor networks(WSN) environment. LEACH protocol is hierarchical routing protocol that obtains energy efficiency by using clustering. However, LEACH protocol in each round, because the new cluster configuration, cluster configuration, whenever the energy consumed shorten the life of the network. Therefore in this paper, the cluster is formed in WSN environment in early stage and the problems with energy waste have been solved by selecting C-node. In the initial round of proposed model uses 26 percent more than traditional LEACH energy consumption. However, as the round is ongoing, it has been proved by the network simulation tool that the waste of energy could be diminished up to 35%.

• Journal of Korea Multimedia Society
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• v.13 no.6
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• pp.911-923
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• 2010

In wireless sensor networks (WSNs), cluster based data routing protocols have the advantages of reducing energy consumption and link maintenance cost. Unfortunately, most of clustering protocols have been designed for uniformly distributed sensor networks. However, some urgent situations do not allow thousands of sensor nodes being deployed uniformly. For example, air vehicles or balloons may take the responsibility for deploying sensor nodes hence leading a normally distributed topology. In order to improve energy efficiency in such sensor networks, in this paper, we propose a new cluster formation algorithm named DAEEC (Density Aware Energy-Efficient Clustering). In this algorithm, we define two kinds of clusters: Low Density (LD) clusters and High Density (HD) clusters. They are determined by the number of nodes participated in one cluster. During the data routing period, the HD clusters help the neighbor LD clusters to forward the sensed data to the central base station. Thus, DAEEC can distribute the energy dissipation evenly among all sensor nodes by considering the deployment density to improve network lifetime and average energy savings. Moreover, because the HD clusters are densely deployed they can work in a manner of our former algorithm EEVAR (Energy Efficient Variable Area Routing Protocol) to save energy. According to the performance analysis result, DAEEC outperforms the conventional data routing schemes in terms of energy consumption and network lifetime.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10a
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• pp.490-493
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• 2006

본 논문은 Linux Cluster의 MPICH에서 MPI_Allgather Algorithm의 성능을 개선하고 실험을 통해 최대 30%의 성능향상을 증명하였다. MPICH의 기존 버전이 메시지의 크기와 실행 프로세스 수에 따라 Recursive Doubling, Bruck Algorithm, Ring Algorithm을 차등 적용했던 것을, 앞의 Algorithm을 개선하여 Double Bruck Algorithm, Double Ring Algorithm을 제안, 구현하였다.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.157-164
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• 2022

The proposed privacy preserving scheme has identified the drawbacks of existing schemes in Vehicular Networks. This prototype enhances the number of nodes by decreasing the cluster size. This algorithm is integrated with the whale optimization algorithm and Block Chain Technology. A set of results are done through the NS-2 simulator in the direction to check the effectiveness of proposed algorithm. The proposed method shows better results than with the existing techniques in terms of Delay, Drop, Delivery ratio, Overhead, throughout under the denial of attack.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.490-493
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• 2010

본 논문에서는 클러스터 측정(Cluster Measurement)과 유전자 알고리즘을 이용한 문서 클러스링 알고리즘을 제안한다. 유전자 알고리즘의 요소를 클러스터링에 대입하고 클러스터 측정을 적합도 함수에 대입하여 문서 클러스터링을 구현하였다. 성능 평가를 위하여 한국일보-20000/한국일보-40075 문서범주화 실험문서집합의 데이터 셋을 이용하였다. 클러스터링 성능 평가 결과 AS Index가 DB Index, RS Index 보다 좋은 성능을 보여준다. 또한 제안한 알고리즘이 K-means 클러스터링 알고리즘에 비교해 안정적으로 좋은 성능을 보여준다.

• Journal of IKEEE
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• v.13 no.1
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• pp.71-76
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• 2009

As one of the most important requirements for wireless sensor networks, prolonging network lifetime can be realized by minimizing energy consumption in cluster heads as well as sensor nodes. While most of the previous researches have focused on the energy of sensor nodes, we devote our attention to cluster heads because they are most dominant source of power consumption in the cluster-based sensor networks. Therefore, we seek to minimize energy consumption by minimizing the maximum(MINMAX) energy dissipation at each cluster heads. This work requires energy-efficient clustering of the sensor nodes while satisfying given energy constraints. In this paper, we present a constraint satisfaction modeling of cluster-based routing in a heterogeneous sensor networks because mixed integer programming cannot provide solutions to this MINMAX problem. Computational experiments show that substantial energy savings can be obtained with the MINMAX algorithm in comparison with a minimum total energy(MTE) strategy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.2
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• pp.680-699
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• 2015

The use of web service has been increased rapidly, with an increase in the number of available services, finding the exact service is the challenging task. Service discovery is the most significant job to complete the service discoverers needs. In order to achieve the efficient service discovery, we focus on designing a cluster based service discovery model for service registering and service provisioning among all mobile nodes in a mobile ad hoc network (MANETs). A dynamic backbone of nodes (i.e. cluster heads) that forms a service repository to which MANET nodes can publish their services and/or send their service queries. The designed model is based on storing services with their service description on cluster head nodes that are found in accordance with the proposed cluster head election model. In addition to identifying and analyzing the system parameters for finding the effectiveness of our model, this paper studies the stability analysis of the network, overhead of the cluster, and bandwidth utilization and network traffic is evaluated using analytic derivations and experimental evaluation has been done.

• Journal of Korea Multimedia Society
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• v.8 no.12
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• pp.1623-1630
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• 2005

Adaptive modulation and coding (AMC), which has a number of variation levels in accordance with the fading channel variation, is a promising technique for communication systems. In this paper, we present an AMC method using the cluster in OFDM system for bandwidth efficiency and performance improvement. The AMC schemes applied into each cluster or some clusters are determined by the minimum or the average SNR value among all the sub carriers within the corresponding cluster. It is important to find the optimal information on cluster because AMC performance can be varied according to the number and position of cluster. It is shown by computer simulation that the AMC method outperforms the fixed modulation in terms of bandwidth efficiency and its performance can be determined by the position and number of clusters.

• Journal of Communications and Networks
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• v.14 no.4
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• pp.443-450
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• 2012

As for cluster-based wireless sensor networks (WSNs), cluster lifetime is one of the most important subjects in recent researches. Besides reducing the energy consumptions of the clusters, it is necessary to make the clusters achieve equal lifetimes so that the whole network can survive longer. In this paper, we focus on the cluster lifetimes in multi-hop WSNs with cooperative multi-input single-output scheme. With a simplified model of multi-hop WSNs, we change the transmission schemes, the sizes and transmission distances of clusters to investigate their effects on the cluster lifetimes. Furthermore, linear and uniform data aggregations are considered in our model. As a result, we analyze the cluster lifetimes in different situations and discuss the requirements on the sizes and transmission distances of clusters for equal lifetimes.