• 한국정보처리학회논문지
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• 제7권4호
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• pp.1050-1061
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• 2000

This paper presents a new object model, LOM(Lightweight Object Model) and an implementation method for the distributed trader in heterogeneous distributed computing environment including mobile network. Trader is third party object that enables clients to find suitable servers, which provide the most appropriate services to client in distributed environment including dynamic reconfiguration of services and servers. Trading service requires simpler and more specific object model than genetic object models which provide richer multimedia data types and semantic characteristics with complex data structures. LOM supports a new reference attribute type instead of the relationship, inheritance and composite attribute types of the general object oriented models and so LOM has simple data structures. Also in LOM, the modelling step includes specifying of the information about users and the access right to objects for security in the mobile environment and development of the distributed storage for trading service. Also, we propose and implementation method of the distributed trader, which integrates the LOM-information object model and the OMG (object Management Group) computational object model.

• International Journal of Computer Science & Network Security
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• 제23권5호
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• pp.207-211
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• 2023

Traditional methods for datamining typically assume that the data is small, centralized, memory resident and static. But this assumption is no longer acceptable, because datasets are growing very fast hence becoming huge from time to time. There is fast growing need to manage data with efficient mining algorithms. In such a scenario it is inevitable to carry out data mining in a distributed environment and Frequent Itemset Mining (FIM) is no exception. Thus, the need of an efficient incremental mining algorithm arises. We propose the Distributed Incremental Approximate Frequent Itemset Mining (DIAFIM) which is an incremental FIM algorithm and works on the distributed parallel MapReduce environment. The key contribution of this research is devising an incremental mining algorithm that works on the distributed parallel MapReduce environment.

• 한국정보전자통신기술학회논문지
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• 제11권1호
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• pp.70-75
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• 2018

스마트 팩토리는 설계 개발, 제조, 유통 물류 등 생산 전체 과정에 정보 통신 기술을 적용하여 생산성, 품질, 고객만족도 등을 향상시킬 수 있는 지능형 공장이다. 스마트 팩토리에서 발생되는 데이터의 양은 공장의 규모 및 시설 수준에 따라 많은 차이를 보이지만, 기존의 생산관리시스템을 활용하여 방대한 양의 데이터를 발생시키는 스마트 팩토리 환경에 적용하기에 어려움이 있다. 이로 인해 방대한 양의 빅데이터 처리할 수 있는 빅데이터 분산 처리 시스템의 필요성이 요구되고 있다. 따라서 본 논문에서는 스마트 팩토리 환경에서의 GlusterFS 기반 빅데이터 분산 처리 시스템 설계하였다. 제안하는 빅데이터 분산 처리 시스템은 기존 분산 처리 시스템에 비해 네트워크 트래픽 분산 및 관리를 통해 부하와 데이터 소실 위험도를 감소시켰다.

• 정보기술과데이타베이스저널
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• 제3권2호
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• pp.3-24
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• 1996

In this paper a data replicator scheme with a distributed join architecture is suggested with its cost functions and the performance results. The contribution of this scheme is not only minimizing the number of base relation locks in distributed database tables but also reducing the remote transmission amount remarkably, which will be able to embellish the distributed databse system practical. The differential files that are derived from the active log of the DBMS are mainly forcing the scheme to reduce the number of base relation locks. The amount of transportation between relevant sites could be curtailed by the tuple reduction procedures. Then we prescribe an algorithm of data replicator with its cost function and show the performance results compared with the semi-join scheme in their distributed environments.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2007년도 한국컴퓨터종합학술대회논문집 Vol.34 No.1 (C)
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• pp.336-340
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• 2007

We envisage that grid computing environments allow us to implement distributed data mining services, that is, those applications which analyze large sets of geographically distributed databases and information using the computational power and resources of a grid environment. This paper describes an experimental framework towards such a distributed data mining approach, including design considerations and a prototype implementation. Based on the "Knowledge Grid" architecture suggested by Cannataro et al., we identify four major components - user node, broker node, data node, and computation node - and define their individual roles. For implementing the prototype, we have investigated methods for utilizing distributed resources within a grid computing environment, e.g., communication and coordination among the various resources available.

• 한국산학기술학회논문지
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• 제13권6호
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• pp.2713-2719
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• 2012

위치를 기반으로 하는 서비스가 다양해짐에 따라 고가용성과 고확장성을 제공하기 위한 분산 데이터 스트림 처리 기법에 대한 연구가 널리 수행되고 있다. 기존 연구는 분산된 노드들에서 부하의 균형을 유지하기 위해 공간 데이터 스트림의 지리적인 특성을 고려하지 않고 있어 공간적으로 인접한 연산을 수행함에 있어 전체 시스템의 부하를 증가시키고 있다. 본 논문에서는 분산 환경의 공간 데이터 스트림을 처리하기 위해 공간 영역의 겹침을 고려한 연산배치 기법을 제안한다. 제안 기법에서는 인접한 공간 영역을 대상으로 하는 연산을 효율적으로 분리하기 위해 질의 영역이 겹치는 부분의 연산을 우선적으로 동일 노드에 분배하여 중복 영역에 대한 공유의 최대화를 보장한다.

• 한국멀티미디어학회논문지
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• 제15권8호
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• pp.1048-1058
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• 2012

본 논문은 클라우딩 환경에서 클라이언트와 저장 서버, 검증 서버로 구성하여 자가 조직 저장 매체의 데이터 손실을 방지하고, 보안을 유지하기 위한 DDMPF( Distributed Data Management Protocol using FAT)을 제안한다. DDMPF는 클라우드 컴퓨팅 환경에서 자가 조직 저장 서버를 구축하고, 데이터를 분할하여 저장 서버에 분산 저장함으로써 기존의 클라우딩 저장 매체의 중앙 집중화 문제와 저장 서버 문제로 인한 데이터 손실 문제를 해결하였고, 파일할당테이블을 이용해 분산 저장된 데이터 관리의 효율성도 향상시켰다. 그리고 DDMPF는 저장 서버의 데이터 무결성을 검증 서버가 검증함으로써 데이터의 신뢰성을 향상시키고, 클라이언트의 비밀키와 EC-DH 알고리즘을 이용하여 생성된 시스템 마스터 키로 이중 암호화하여 전송함으로써 보안을 강화시켰다. 또한, 자가 조직 저장 매체를 구성할 때, 검증서버의 개수를 제한하고, 검증요청메시지에 대한 TS(Time Stamp)을 설정함으로써 플러딩 공격 탐지하였고, 검증을 요청할 때마다 새롭게 생성된 nonce 값을 이용하여 재전송 공격을 탐지하도록 하였다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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• pp.145-150
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• 2002

Web GIS (Geographic Information Systems) service systems provide the various GIS services of analyzing and displaying the spatial data with friendly user-interface. These services are expanding the business domain and many users want to access the distributed various spatial data. But, it is difficult to access diverse data sources because of different spatial data format and data access methods. In this paper, we design and implement web GIS services based on the inter-operability and GML (Geography Markup Language) of OGC(Open GIS Consortium) in web distributed environment. Inter-operability provides unique accessing method to distributed data sources based on OLE DB technology of Microsoft. In addition, GML support web GIS services based on XML. We design these GIS services as components using UML (Unified Modeling Language) of an object-oriented modeling language for specifying, visualizing, constructing, and documenting the artifacts of software system. In addition, they also were developed in object-oriented computing environment, and it provides the interoperability, language-independent, easy developing environment as well as re-usability.

• Journal of the Korean Data and Information Science Society
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• 제22권5호
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• pp.989-998
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• 2011

Cloud computing provides computation, software, data access, and storage services that do not require end-user knowledge of the physical location and configuration of the system that delivers the services. Cloud computing providers have setup several data centers at different geographical locations over the Internet in order to optimally serve needs of their customers around the world. One of the fundamental challenges in geographically distributed clouds is to provide efficient algorithms for supporting inter-cloud data management and dissemination. In this paper, we propose a group quorum system (GQS)-based dissemination for improving the interoperability of inter-cloud in time-critical event dissemination service, such as computing policy updating, message sharing, event notification and so forth. The proposed GQS-based method organizes these distributed clouds into a group quorum ring overlay to support a constant event dissemination latency. Our numerical results show that the GQS-based method improves the efficiency as compared with Chord-based and Plume methods.

• Journal of Communications and Networks
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• 제16권4호
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• pp.430-435
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• 2014

The performance of a distributed database system depends particularly on the site-allocation of the fragments. Queries access different fragments among the sites, and an originating site exists for each query. A data allocation algorithm should distribute the fragments to minimize the transfer and settlement costs of executing the query plans. The primary cost for a data allocation algorithm is the cost of the data transmission across the network. The data allocation problem in a distributed database is NP-complete, and scalable evolutionary algorithms were developed to minimize the execution costs of the query plans. In this paper, quadratic assignment problem heuristics were designed and implemented for the data allocation problem. The proposed algorithms find near-optimal solutions for the data allocation problem. In addition to the fast ant colony, robust tabu search, and genetic algorithm solutions to this problem, we propose a fast and scalable hybrid genetic multi-start tabu search algorithm that outperforms the other well-known heuristics in terms of execution time and solution quality.