• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.435-437
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• 2016

Hadoop Distributed File System(HDFS) is a file system for distributed processing of big data by replicating data to distributed data nodes. HDFS cluster shows a great scalability up to thousands of nodes, but it assumes a exclusive node cluster with numerous nodes for the big data processing. Various operational-purpose worker systems used by office are hardly considered as a part of cluster. This paper discusses this problem and proposes a dynamic cluster management technique to increase storage capability and analytic performance of hadoop cluster. The propsed technique can add legacy systems to the cluster and can remove them from the cluster dynamically depending on their availability.

• Journal of Korea Water Resources Association
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• v.43 no.1
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• pp.67-79
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• 2010

Korea water resources corporation (K-Water) has developed the real-time water resources management system for the Nakdong and the Geum River basin to efficiently operate multi-purpose dams in the basins. This study has extended to the Han River basin for providing an effective ending target storage of a month to the real-time water resources management system using Sampling Stochastic Dynamic Programming (SSDP), consequently increasing the efficiency of the reservoir system. The optimization model were developed for three reservoirs, named Soyang, Chungju, and Hwacheon, with high priority in terms of the amounts of effective capacity and water supply for the basin. The number of storage state variable for each dam to set an optimization problem has been assigned from the results of sensitivity analysis. Compared with the K-water operating policy with the target water supply elevations, the optimization model suggested in this study showed that the shortfalls are decreased by 37.22 MCM/year for the required water demands in the basin, even increasing 171 GWh in hydro electronic power generation. In addition, the result of a reservoir operating system during the drawdown period applied to real situation demonstrates that additional releases for water quality or hydro electronic power generation would be possible during the drawdown period between 2007 and 2008. On the basis of these simulation results, the applicability of the SSDP model and the reservoir operating system is proved. Therefore, the more efficient reservoir operation can be achieved if the reservoir operating system is extended further to other Korean basins.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.3
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• pp.259-266
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• 2015

Among many energy resources, natural gas has recently received a remarkable amount of attention, particularly from the electrical generation industry. This is in part due to increasing shale gas production, providing an environment-friendly fossil fuel, and high risk of nuclear power. Because South Korea, the world's second largest LNG importing nation after Japan, has no international natural gas pipelines and relies on imports in the form of LNG, the natural gas has been traditionally procured by long term LNG contracts at relatively high price. Thus, there is a need of developing an Asian LNG trading hub, where LNG can be traded at more competitive spot prices. In a natural gas spot market, the amount of natural gas to be bought should be carefully determined considering a limited storage capacity and future pricing dynamics. In this work, the problem to find the optimal amount of natural gas in a spot market is formulated as a Markov decision process (MDP) in risk neutral environment and the optimal base stock policy which depends on a stage and price is established. Taking into account price and demand uncertainties, the basestock target levels are simply approximated from dynamic programming. The simulation results show that the basestock policy can be one of effective ways for procurement of LNG in a spot market.

• Journal of Information Science Theory and Practice
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• v.11 no.2
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• pp.67-81
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• 2023

This paper presents a dynamic development of an ontology-based statistical information system supporting the collection, storage, processing, analysis, and the presentation of statistical knowledge at the national scale. To accomplish this, we propose a data mining technique to dynamically collect data relating to citizens from publicly available data sources; the collected data will then be structured, classified, categorized, and integrated into an ontology. Moreover, an intelligent platform is proposed in order to generate quantitative and qualitative statistical information based on the knowledge stored in the ontology. The main aims of our proposed system are to digitize administrative tasks and to provide reliable statistical information to governmental, economic, and social actors. The authorities will use the ontology-based statistical information system for strategic decision-making as it easily collects, produces, analyzes, and provides both quantitative and qualitative knowledge that will help to improve the administration and management of national political, social, and economic life.

• Journal of Advanced Navigation Technology
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• v.14 no.5
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• pp.767-774
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• 2010

Due to advantages of NAND flash memory such as non-volatility, low access latency, low energy consumption, light weight, small size and shock resistance, it has become a better alternative over traditional magnetic disk drives, and has been widely used. Traditional DBMSs including mobile DBMSs may run on flash memory without any modification by using Flash Translation Layer (FTL), which emulates a random access block device to hide the characteristics of flash memory such as "erase-before-update". However, most existing FTLs are optimized for file systems, not for DBMSs, and traditional DBMSs are not aware of them. Also, traditional DBMSs do not consider the characteristics of flash memory. In this paper, we propose a flash-conscious storage system for DBMSs that utilizes flash memory as a main storage medium, and carefully put the characteristics of flash memory into considerations. The proposed flash-conscious storage system exploits log records to avoid costly update operations. It is shown that the proposed storage system outperforms the state.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1998.10a
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• pp.63-66
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• 1998

In the implementation of the simplex method program, the representation and the maintenance of basis matrix is very important, In the experimental study, we investigates Suhl's idea in the LU factorization and LU update of basis matrix. First, the triangularization of basis matrix is implemented and its efficiency is shown. Second, various technique in the dynamic Markowitz's ordering and threshold pivoting are presented. Third, modified Forrest-Tomlin LU update method exploiting sparsity is presented. Fourth, as a storage scheme of LU factors, Gustavson data structure is explained. Fifth, efficient timing of reinversion is developed. Finally, we show that modified Forrest-Tomlin method with Gustavson data structure is superior more than 30% to the Reid method with linked list data structure.

• Korean Management Science Review
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• v.12 no.3
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• pp.1-15
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• 1995

The Pusan Container Terminal faces a rapid increase in berthing time of container ships as well as in waiting time of external trucks, which is due to an absolute lack of yard space. This research is focused on the development of a decision support system for the planning of the container terminal yard assignment so that the yard space would be utilized most effectively. Efforts should be given to the reasonable assignment of the yard storage and the dynamic adaptation to the ever changing environment. The software introduced here is based on the know-how of the field exports and its framework takes the approach of the hierarchical decision making.

• Journal of the Korean Institute of Telematics and Electronics
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• v.22 no.6
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• pp.114-123
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• 1985

This is the second part of the four-part paper describing the development of a packet-switched computer network named the cORNET In this paper, following the first par paper that describes the concepts of the KORNET and the development of the network management center (NMC), wc present the design of the KORNET and the development of the network node processor (NNP) The initial configuration of the KORNET consists of three NNP's and one NMC. We have developed each NNP as a microprocessor-based (Mc68000) multiprocessor system, and implemented the NMC using a super-mini computer (Mv/8000) For the KORNET we use the virtual circuit (VC) method as the packet service strategy and the distributed adaptive routing algorithm to adapt efficiently the variation of node and link status. Also, we use a dynamic buffer management algorithm for efficient storage management. Thc hardware of the NNP system has been designed with emphasis on modularity so that it may be expanded esily . Also, the software of the NNP system has been developed according to the CCITT recommendations X.25, X.3, X.28 and X.29.

• The Journal of the Korea institute of electronic communication sciences
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• v.2 no.2
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• pp.83-91
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• 2007

The purpose of this paper is developing a PML server which is capable of saving and managing effectively the information of vehicles using RFID technology in the logistical and distributive environment. The PML server logs and manages the real-time static and dynamic information about the vehicles in EPC code format which is represented by XML schema and transmitted by the RFID reader to the server. It receives information from SAVANT the RFID middleware and transmits the data to the traffic information management application The main system we developed consists of the EPC data registry, query processor, data converter, vehicle product and instance data storage, system management tool and application API parts.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.4
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• pp.153-161
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• 2021

Real-time access is required to handle continuous and unstructured data and should be flexible in management under dynamic state. Platform can be built to allow data collection, storage, and processing from local-server or multi-server. Although the former centralize method is easy to control, it creates an overload problem because it proceeds all the processing in one unit, and the latter distributed method performs parallel processing, so it is fast to respond and can easily scale system capacity, but the design is complex. This paper provides data collection and processing on one platform to derive significant insights from various data held by an enterprise or agency in the latter manner, which is intuitively available on dashboards and utilizes Spark to improve distributed processing performance. All service utilize dockers to distribute and management. The data used in this study was 100% collected from Kafka, showing that when the file size is 4.4 gigabytes, the data processing speed in spark cluster mode is 2 minute 15 seconds, about 3 minutes 19 seconds faster than the local mode.