• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.10
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• pp.1-9
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• 2003

In GRID environments, an efficient load balancing algorithm should be adopted since the system performances of GRID system are not homogeneous. In this work, a new two-step mesh-partitioning scheme based on the graph-partitioning scheme was introduced to consider the difference of system performance. In the two-step mesh-partitioning scheme, the system performance weights were calculated to reflect the effect of heterogeneous system performances and WEVM(Weighted Edge and vertex Method) was adopted to minimize the increase' of communications. Numerical experiments were carried out in multi-cluster environment and WAN (Wide Area Network) environment to investigate the effectiveness of the two-step mesh-partitioning scheme.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.1-9
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• 2017

Recently, the active research into wireless sensor networks has led to the development of sensor nodes with improved performance, including their mobility and location awareness. One of the most important goals of such sensor networks is to transmit the data generated by mobile sensors nodes. Since these sensor nodes move in the mobile wireless sensor networks (MWSNs), the energy consumption required for them to transmit the sensed data to the fixed sink is increased. In order to solve this problem, the use of mobile sinks to collect the data while moving inside the network is studied herein. The important issues are the mobility and energy consumption in MWSNs. Because of the sensor nodes' limited energy, their energy consumption for data transmission affects the lifetime of the network. In this paper, a mobile-sink based energy-efficient clustering scheme is proposed for use in mobile wireless sensor networks (MECMs). The proposed scheme improves the energy efficiency when selecting a new cluster head according to the mobility of the mobile sensor nodes. In order to take into consideration the mobility problem, this method divides the entire network into several cluster groups based on mobile sinks, thereby decreasing the overall energy consumption. Through both analysis and simulation, it was shown that the proposed MECM is better than previous clustering methods in mobile sensor networks from the viewpoint of the network energy efficiency.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.5
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• pp.479-485
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• 2011

A number of case studies that find distribution of longevity population and influencing factors through the spatial data fusion using GIS techniques are growing. The majority cases of these studies are adopt census administrative boundary data for the spatial analysis. However, these methods cannot fully explain the phenomenon of longevity because there are a variety of spatial characteristics within the census administrative boundaries. Therefore, studies of spatial unit are required that realistically reflect the phenomenon of human longevity. The dasymetric mapping method enables to product of spatial unit more realistic than census administrative boundary map and statistic estimates of small area utilizing diversity spatial information. In this study, elderly population of small area has been estimated within statistically significant level that applied the vector based dasymetric mapping method. Also, the cluster analysis confirmed that the variation of local spatial relationship within census administrative boundary. The result of this study implied that the need for local-level studies of the human longevity and the validity of the dashmetric mapping techniques.

• Convergence Security Journal
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• v.14 no.7
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• pp.53-58
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• 2014

MANET can quickly build a network because it is configured with only the mobile node and it is very popular today due to its various application range. However, MANET should solve vulnerable security problem that dynamic topology, limited resources of each nodes, and wireless communication by the frequent movement of nodes have. In this paper, we propose a domain-based distributed cooperative intrusion detection techniques that can perform accurate intrusion detection by reducing overhead. In the proposed intrusion detection techniques, the local detection and global detection is performed after network is divided into certain size. The local detection performs on all the nodes to detect abnormal behavior of the nodes and the global detection performs signature-based attack detection on gateway node. Signature DB managed by the gateway node accomplishes periodic update by configuring neighboring gateway node and honeynet and maintains the reliability of nodes in the domain by the trust management module. The excellent performance is confirmed through comparative experiments of a multi-layer cluster technique and proposed technique in order to confirm intrusion detection performance of the proposed technique.

• Journal of KIISE:Databases
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• v.31 no.1
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• pp.30-38
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• 2004

In many scientific and commercial applications such as Earth Observation System (EOSDIS) and mobile Phone services tracking a large number of clients, it is a daunting task to archive and index ever increasing volume of complex data that are continuously added to databases. To efficiently manage multidimensional data in scientific and data warehousing environments, R-tree based index structures have been widely used. In this paper, we propose a scalable technique called seeded clustering that allows us to maintain R-tree indexes by bulk insertion while keeping pace with high data arrival rates. Our approach uses a seed tree, which is copied from the top k levels of a target R-tree, to classify input data objects into clusters. We then build an R-tree for each of the clusters and insert the input R-trees into the target R-tree in bulk one at a time. We present detailed algorithms for the seeded clustering and bulk insertion as well as the results from our extensive experimental study. The experimental results show that the bulk insertion by seeded clustering outperforms the previously known methods in terms of insertion cost and the quality of target R-trees measured by their query performance.

• Convergence Security Journal
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• v.13 no.3
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• pp.33-38
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• 2013

Security between mobile nodes and efficient communication is one of the most important parts of the MANET. In particular, the wireless network is significantly higher for the attack threats because of collaborative structure for open communication media and communication. However, application of existing security mechanisms and intrusion detection system is not easy due to the characteristics of MANET. It is because collection and integration of adult data by the dynamic topology due to the mobility of nodes and many network sensors is difficult. In this study, we propose cooperative security system technique that can improve the reliability based on authentication assessing confidence about the whole nodes which joins to network and detect effectively this when intrusion occurs. Cluster head which manages the cluster performs CA role for the certificate issue and the gateway node performs role of intrusion detection system. Intrusion detection is performed by cooperating with neighboring nodes when attack is not detected in one intrusion detection node. The performance of the proposed method was confirmed through experiments comparing with the SRP technique.

• Journal of Digital Convergence
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• v.13 no.9
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• pp.235-242
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• 2015

Social network technology has been increasing interest in the big data service and development. However, the data stored in the distributed server and not on the central server technology is easy enough to find and extract. In this paper, we propose a big data management techniques to minimize the processing time of information you want from the content server and the management server that provides big data services. The proposed method is to link the in-group data, classified data and groups according to the type, feature, characteristic of big data and the attribute information applied to a hash chain. Further, the data generated to extract the stored data in the distributed server to record time for improving the data index information processing speed of the data classification of the multi-attribute information imparted to the data. As experimental result, The average seek time of the data through the number of cluster groups was increased an average of 14.6% and the data processing time through the number of keywords was reduced an average of 13%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.114-121
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• 2022

In this paper, we consider a user centric clustering in order to guarantee the performance of the users in cell free multiple-input multiple-output (MIMO) network. In the user centric clustering scheme, by using large scale fading coefficients of the connected access points (APs), each user decides own cluster with the APs having the higher the large scale fading coefficients than threshold value compared to the highest large scale fading coefficient. In the determined user centric clusters, the APs design the beamformers and power allocations in the distributed manner and the APs cooperatively transmit data to users by using beamformers and power allocations. In the simulation results, we verify the performance of user centric clustering in terms of the spectral efficiency and we also find the optimal threshold value in the given configuration.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.253-258
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• 2014

In smartphone sensing which monitors various social phenomena of the individuals by using embedded sensors, managing metadata is one of the important issue to process large-scale data, improve the data quality, and share collected data. In this paper, we proposed a document clustering scheme for the large-scale metadata management architecture which is designed as a hybrid back-end consisting of a cluster head and member nodes to reduce the server-side overhead. we also verified that the proposed scheme is more efficient than the distance based clustering scheme in terms of the server-side overhead through simulation results.

• Journal of KIISE:Computer Systems and Theory
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• v.28 no.9
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• pp.461-468
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• 2001

Though shared virtual memory (SVM) system promise low cost solutions for high performance computing they suffer from long memory latencies. These latencies are usually caused by repetitive invalidations on shared data. Since shared data are accessed through synchronization and the patterns by which threads synchronizes are repetitive, a prefetching scheme bases on such repetitiveness would reduce memory latencies. Based on this observation, we propose a prefetching technique which predicts future access behavior by analyzing access history per synchronization variable. Our technique was evaluated on an 8-node SVM system using the SPLASH-2 benchmark. The results show the our technique could achieve 34%~45% reduction in memory access latencies.