• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.329-332
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• 2000

Research interests on temporal data have been almost focused on data models. There has been relatively less research in the area of temporal data management. In this paper, we propose two data migration strategies based on time-segmented storage structure: the migration strategy by Time Granularity, the migration strategy by LST-GET. We describe the criterion for data migration and moving process. We simulated the performance of the migration strategy by Time Granularity in order to compare it with non-segmentation method. We compared and analyzed two data migration strategies for temporal data.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2005.10a
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• pp.456-460
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• 2005

The purpose of this study is to develop a estimation model of migration with only population data using the cohort-survival model which has been used for forecasting future population. The fluctuation of population can be bisected to the natural change which can be occurred by birth and death and the social change which means migration. The factors of the social change are usually very important for establishing rural policies. However, researches using migration data has limitations because the usage of them are restricted. For verifying a estimation model of migration, comparing estimated population in 2000 year and migration quantity between 1996 and 2000 of 25 gu with real values, using population data and death ratio from 1995 to 2000 of the 25 gu in Seoul. Result shows a reliable data that R-square of forecating population model is 0.9755 and migration is 0.9180. So these model are worth to estimate a population and migration quantity to restricted migration data.

• The Transactions of the Korea Information Processing Society
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• v.6 no.4
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• pp.851-867
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• 1999

Numerous proposals for extending the relational data model as well as conceptual and object-oriented data models have been suggested. However, there has been relatively less research in the area of defining segmented storage structure and data migration strategies for temporal data. This paper presents the segmented storage structure in order to increment search performance and the two data migration strategies for segmented storage structure. this paper presents the two data migration strategies : the migration strategy by Time granularity, the migration strategy by LST-GET. In the migration strategy by Time Granularity, the dividing time point to assign the entity versions to the past segment, the current segment, and future segment is defined and the searching and moving process for data validity at a granularity level are described. In the migration strategy by LST-GET, we describe the process how to compute the value of dividing criterion. searching and moving processes are described for migration on the future segment and the current segment and entity versions 새 assign on each segment are defined. We simulate the search performance of the segmented storage structure in order to compare it with conventional storage structure in relational database system. And extensive simulation studies are performed in order to compare the search performance of the migration strategies with the segmented storage structure.

• The KIPS Transactions:PartD
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• v.8D no.6
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• pp.813-822
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• 2001

In this paper we proposed four data migration methods based on time segmented storage structure including past segment, current segment, and future segment. The migration methods proposed in this paper are the Time Granularity migration method, the LST-GET (Least valid Start Time-Greatest valid End Time) migration method, the AST-AET (Average valid Start Time-Average valid End Time) migration method, and the Min-Overlap migration method. In the each data migration method we define the dividing criterion among segments and entity versions to store on each segment. We measured the response time of queries for the proposed migration methods. When there are no LLTs (Long Lived Tuples), the average response time of AST-AET migration method and LST-GET migration method are smaller than that of Time Granularity migration method. In case of existing LLT, the performance of the LST-GET migration method decreased. The AST-AET migration method resulted in better performance for queries than the Time Granularity migration method and the LST-GET migration method. The Min-Overlap migration method resulted in the almost equal performance for queries compared with the AST-AET migration method, in case of storage utilization more efficient than the AST-AET.

• Journal of Information Processing Systems
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• v.11 no.1
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• pp.148-164
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• 2015

The use of mobile agents for collaborative processing in wireless sensor network has gained considerable attention. This is when mobile agents are used for data aggregation to exploit redundant and correlated data. The efficiency of agent-based data aggregation depends on the agent migration scheme. However, in general, most of the proposed schemes are centralized approach-based schemes where the sink node determines the migration paths for the agents before dispatching them in the sensor network. The main limitations with such schemes are that they need global network topology information for deriving the migration paths of the agents, which incurs additional communication overhead, since each node has a very limited communication range. In addition, a centralized approach does not provide fault tolerant and adaptive migration paths. In order to solve such problems, we have proposed a distributed approach-based scheme for determining the migration path of the agents where at each hop, the local information is used to decide the migration of the agents. In addition, we also propose a local repair mechanism for dealing with the faulty nodes. The simulation results show that the proposed scheme performs better than existing schemes in the presence of faulty nodes within the networks, and manages to report the aggregated data to the sink faster.

• Journal of the Korean association of regional geographers
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• v.16 no.5
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• pp.590-609
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• 2010

The purpose of the study is to propose and evaluate Exploratory Spatial Data Analysis(ESDA) methods for examining age-specific population migration characteristics. First, population migration pyramid which is a pyramid-shaped graph designed with in-migration, out-migration, and net migration by age (or age group), was developed as a tool exploring age-specific migration propensities and structures. Second, various spatial statistics techniques based on local indicators of spatial association(LISA) such as Local Moran''s $I_i$, Getis-Ord ${G_i}^*$, and AMOEBA were suggested as ways to detect spatial dusters of age-specific net migration rate. These ESDA techniques were applied to age-specific population migration of Daegu Metropolitan City. Application results demonstrated that suggested ESDA methods can effectively detect new information and patterns such as contribution of age-specific migration propensities to population changes in a given region, relationship among different age groups, hot and cold spot of age-specific net migration rate, and similarity between age-specific spatial clusters.

• Journal of Korean Society of Rural Planning
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• v.23 no.2
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• pp.43-54
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• 2017

When an age of low growth and population decline, population migration plays an important role in spatial structure of region. There have been many researches on migration and regional spatial structure. The purpose of this study is to examine the changes of Gwangju and Jeonnam region's spatial structure and central area using social network analysis methods. For analysis it was used that population and migration data and passenger OD(Origin and Destination) travel data released by Statistics Korea and Korea Transport Database(KTDB). Using Gephi 0.8.2, migration and passenger OD networks were visualized, and this describe network flow and density. The results of the network centrality analysis show that the most populated village is not always network center though population mass is an important factor of central places. The average eigenvector centrality of 2010 migration is the lowest during 2005-2015, and it means few regions have high centralities. When comparing migration and travel networks, travel data is more effective than migration data in determining the central location considering spatial functions.

• Journal of KIISE:Databases
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• v.28 no.3
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• pp.384-394
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• 2001

In this paper, we propose AST-AET(Average valid Start Time-Average valid End Time) data migration strategy based on the storage structure where temporal data is divided into a past segment, a current segment, and a future segment. We define AST and AET which are used in AST-AET data migration strategy and also define entity versions to be stored in each segment. We describe methods to compute AST and AET, and processes to search entity versions for migration and move them. We compare average response times for user queries between AST-AET data migration strategy and the existing LST-GET(Least valid Start Time-Greatest valid End Time) data migration strategy. The experimental results show that, when there are no LLTs(Long Lived Tuples), there is little difference in performance between the two migration strategies because the size of a current segment is nearly equal. However, when there are LLTs, the average response time of AST-AET data migration strategy is smaller than that of LST-GET data migration strategy because the size of a current segment of LST-GET data migration strategy becomes larger. In addition, when we change average interarrival times of temporal queries, generally the average response time of AST-AET data migration strategy is smaller than that of LST-GET data migration strategy.

• Journal of Information Processing Systems
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• v.13 no.3
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• pp.476-490
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• 2017

In the centralized cloud controlled environment, the decision-making and monitoring play crucial role where in the host controller (HC) manages the resources across hosts in data center (DC). HC does virtual machine (VM) and physical hosts management. The VM management includes VM creation, monitoring, and migration. If HC down, the services hosted by various hosts in DC can't be accessed outside the DC. Decentralized VM management avoids centralized failure by considering one of the hosts from DC as HC that helps in maintaining DC in running state. Each host in DC has many VM's with the threshold limit beyond which it can't provide service. To maintain threshold, the host's in DC does VM migration across various hosts. The data in migration is in the form of plaintext, the intruder can analyze packet movement and can control hosts traffic. The incorporation of security mechanism on hosts in DC helps protecting data in migration. This paper discusses an approach for dynamic HC selection, VM selection and secure VM migration over cloud environment.

• 한국신재생에너지학회:학술대회논문집
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• 2007.06a
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• pp.493-496
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• 2007

Korean Institute of Geosciences and Mineral Resources (KIGAM) has studied on gas hydrate in the Ulleung Basin, East sea of Korea since 1997. Most of all, a evidence for existence of gas hydrate, possible new energy resources, in seismic reflection data is bottom simulating reflection (BSR) which parallel to the sea bottom. Here we conducted the conventional data processing for gas hydrate data and Kirchhoff prestack depth migration. Kirchhoff migration is widely used for pre- and post-stack migration might be helpful to better image as well as to get the geological information. The processed stack image by GEOBIT showed some geological structures such as faults and shallow gas hydrate seeping area indicated by strong BSR. The BSR in the stack image showed at TWT 3.07s between shot gather No 3940 to No 4120. The estimated gas seeping area occurred at the shot point No 4187 to No 4203 and it seems to have some minor faults at shot point No 3735, 3791, 3947 and 4120. According to the result of depth migration, the BSR showed as 2.3km below the sea bottom.