• Proceedings of the Korea Database Society Conference
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• 1997.10a
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• pp.302-318
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• 1997

인터넷 환경하의 어플리케이션 구축이 확산되면서 기존시스템의 정보 (Legacy sources)를 새롭게 전개되는 분산객체 환경의 시스템에서 접근이 가능하도록 하는 요구가 증대되게 되었으며, 이를 해결하기 위하여 WWW, 분산객체 미들웨어, 특수목적 미들웨어를 사용할 수 가 있다. 본 논문에서는 특수목적 미들웨어로서의 객체포장(Object Wrapping) 방법에 대해서 논한다. 기존시스템의 객체포장은 기존시스템에 대한 깊은 이해 없이 접근을 숨기는 (Information Hiding) 방법이다. 기존시스템의 내용은 데이타와 기능을 포함하며 잘 정의된 인터페이스를 제공하므로써 기존시스템을 이용하려는 어떠한 클라이언트나 타 시스템에서 이용할 수 있도록 해준다. 객체포장은 기존시스템에 대한 깊은 이해 없이도 인터넷상에서 기존시스템의 서비스를 개발위험은 최소로 하면서 서비스의 중복이나 불일치 (Inconsistency)를 회피하며 구현하는 대안이다. 한 번 객체포장이 된 기존시스템은 그 서비스를 필요로 하는 어떠한 종류나 클라이언트의 숫자와 관계없이 클라이언트에 대하여 표준 인터페이스를 제공하는 미들웨어로서 인터페이스 외부의 환경에 대하여 다양한 융통성을 가지게 된다.

• Journal of the Korea Computer Industry Society
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• v.5 no.9
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• pp.841-850
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• 2004

In this paper under the distributed system for efficient distribution resource to system's each node must be designed to get right decision making. Thus we considered computing time to estimate fault such as delay on communication network, communication period and other decision making. Aiso, using direct communitation mode improve the availity of total system.

• Asia pacific journal of information systems
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• v.5 no.2
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• pp.51-78
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• 1995

This paper suggests a contingent perspective for analyzing information systems issues of the Korean firms. The contingent perspective includes such corporate characteristics as industry, organizational size, strategy, and value-added application function. This research surveyed 119 corporations in manufacturing, banking, distribution, and construction industries. Among those samples 104 data of corporate IS managers turned out to be statistically valid. As a result, those issues are ranked as the most urgent and important IS issues: strategic IS planning, system integration, application of database, process standardization, and network planning and implementation. Furthermore, factor analysis says that thirty issues to be surveyed are to be grouped into seven factors such as IS planning, user/education, database, applications of IT, system management, distributed computing technology, and network applications. It also found through Pearson correlation and ANOVA that organizational characteristics highly influences the IS issues the corporations face.

• Journal of Information Processing Systems
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• v.17 no.1
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• pp.37-50
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• 2021

Query applications based on nested data, the most commonly used form of data representation on the web, especially precise query, is becoming more extensively used. MapReduce, a distributed architecture with parallel computing power, provides a good solution for big data processing. However, in practical application, query requests are usually concurrent, which causes bottlenecks in server processing. To solve this problem, this paper first combines a column storage structure and an inverted index to build index for nested data on MapReduce. On this basis, this paper puts forward an optimization strategy which combines query execution service tree and frequent sub-query trajectory to reduce the response time of frequent queries and further improve the efficiency of multi-user concurrent queries on large scale nested data. Experiments show that this method greatly improves the efficiency of nested data query.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1807-1824
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• 2015

As the technologies advance, mobile peer-to-peer (MP2P) networks or systems become one of the major ways to share resources and information. On such a system, the information retrieval (IR), including the development of scalable infrastructures for indexing, becomes more complicated due to a huge increase on the amount of information and rapid information change. To keep the systems on MP2P networks more reliable and consistent, the index structures need to be updated frequently. For a semantic IR system, the index structure is even more complicated than a classic IR system and generally has higher update cost. The most well-known indexing technique used in semantic IR systems is Latent Semantic Indexing (LSI), of which the index structure is generated by singular value decomposition (SVD). Although LSI performs well, updating the index structure is not easy and time consuming. In an MP2P environment, which is fully distributed and dynamic, the update becomes more challenging. In this work, we consider how to update the sematic index generated by LSI and keep the index consistent in the whole MP2P network. The proposed Concept Space Update (CSU) protocol, based on distributed 2-Phase locking strategy, can effectively achieve the objectives in terms of two measurements: coverage speed and update cost. Using the proposed effective synchronization mechanism with the efficient updates on the SVD, re-computing the whole index on the P2P overlay can be avoided and the consistency can be achieved. Simulated experiments are also performed to validate our analysis on the proposed CSU protocol. The experimental results indicate that CSU is effective on updating the concept space with LSI/SVD index structure in MP2P semantic IR systems.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.5
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• pp.598-606
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• 2002

We suggest a distributed communication and management methodology using PC to PC Query multicasting strategy for efficient management of medical images produced by DICOM(Digital Imaging and Communications in Medicine) Modalities. It is absolutely necessary to reduce strict degradation of PACS system due to large sire of medical images and their very high transport rates. DICOM PC to PC Component is composed of a Service Manager to execute requested queries, a Communication Manager to take charge of file transmission, and a DICOM Manager to manage stored data and system behavior Each Manager itself is a component to search for requested file by interaction or to transmit the file to other PCs. Distributed management and transformation of medical information based on PC to PC Query multicasting methodology will enhance performance of central server and network capacity, reducing overload on both. We organize three major components for system operation. Each component is implemented as Agent. Communication between agents uses XML encoded Agent Communication Language.

• Smart Media Journal
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• v.10 no.1
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• pp.99-107
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• 2021

In addition to the 4th Industrial Revolution and Industry 4.0, the recent megatrends in the ICT field are Big-data, IoT, Cloud Computing, and Artificial Intelligence. Therefore, rapid digital transformation according to the convergence of various industrial areas and ICT fields is an ongoing trend that is due to the development of technology of AI services suitable for the era of the 4th industrial revolution and the development of subdivided technologies such as (Business Intelligence), IA (Intelligent Analytics, BI + AI), AIoT (Artificial Intelligence of Things), AIOPS (Artificial Intelligence for IT Operations), and RPA 2.0 (Robotic Process Automation + AI). This study aims to integrate and advance various machine learning services of infrastructure-side GPU, CDA (Connected Data Architecture) framework, and AI based on mass distributed Abyss storage in accordance with these technical situations. Also, we want to utilize AI business revenue model in various industries.

• Journal of Korea Spatial Information System Society
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• v.8 no.2 s.17
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• pp.75-89
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• 2006

LBS (Location-Based Service) systems have become a serious subject for research and development since recent rapid advances in wireless communication technologies and position measurement technologies such as global positioning system. The architecture named the GALIS (Gracefully Aging Location Information System) has been suggested which is a cluster-based distributed computing system architecture to overcome performance losses and to efficiently handle a large volume of data, at least millions. The GALIS consists of SLDS and LLDS. The SLDS manages current location information of moving objects and the LLDS manages past location information of moving objects. In this thesis, we implement a monitoring technique for the GALIS prototype, to allow dynamic load balancing among multiple computing nodes by keeping track of the load of each node in real-time during the location data management and spatio-temporal query processing. We also propose a buffering technique which efficiently manages the query results having overlapped query regions to improve query processing performance of the GALIS. The proposed scheme reduces query processing time by eliminating unnecessary query execution on the overlapped regions with the previous queries.

• Magazine of the Korean Society of Agricultural Engineers
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• v.35 no.2
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• pp.65-72
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• 1993

When a drought occurs in an area irrigated by multi-reservoirs, onerating a single reservoir separately to control the reservoir' storage is not a desirable solution. In order to reduce damages effectively for the areal drought, the storage of the reservoirs within the areal boundary should be managed as a group. Storage management procedures are as follows : 1. Collecting and checking the present storages of all reservoirs 2. Computing the drought frequency and depth; and finally, establishing a suitable storage saving strategy based on the estimated drought depth. For the purpose of this storage management, the RESTOMS(Reservoirs Storage Management System) was developed and the system was composed of the PRIME computer and the ORACLE as a distributed database management system, which was the host computer of Rural Development Corporation and would be on-lined with the regional offices throughout the country. Reservoirs operated by Farm Land Improvment Association were comprised in the DB system. Using the RESTOMS, the drought frequencies and drought depths were calculated with respect to the reservoir storage records(1967 to 1992). It was obvious that the results were closely corresponding to the real drought records.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.204-226
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• 2018

Big data processing applications have been migrated into cloud gradually, due to the advantages of cloud computing. Hadoop Distributed File System (HDFS) is one of the fundamental support systems for big data processing on MapReduce-like frameworks, such as Hadoop and Spark. Since HDFS is not aware of the co-location of virtual machines in the cloud, the default scheme of block allocation in HDFS does not fit well in the cloud environments behaving in two aspects: data reliability loss and performance degradation. In this paper, we present a novel location-aware data block allocation strategy (LDBAS). LDBAS jointly optimizes data reliability and performance for upper-layer applications by allocating data blocks according to the locations and different processing capacities of virtual nodes in the cloud. We apply LDBAS to two stages of data allocation of HDFS in the cloud (the initial data allocation and data recovery), and design the corresponding algorithms. Finally, we implement LDBAS into an actual Hadoop cluster and evaluate the performance with the benchmark suite BigDataBench. The experimental results show that LDBAS can guarantee the designed data reliability while reducing the job execution time of the I/O-intensive applications in Hadoop by 8.9% on average and up to 11.2% compared with the original Hadoop in the cloud.