• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제2권2호
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• pp.91-96
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• 2013

바이오 응용과 같은 대용량 데이터 처리와 고성능 계산을 동시에 지원하는 발판으로 슈퍼컴퓨팅 시스템의 활용 분야가 변화하고 있다. 이러한 응용에서는 발생하는 대용량의 데이터를 고속으로 처리하고 효율적으로 저장 관리하기 위한 고성능의 분산 파일 시스템이 요구된다. 본 논문에서는 대용량의 데이터 처리와 고성능 계산을 동시에 지원하는 슈퍼컴퓨팅 시스템을 위해 우수한 메타데이터 연산 성능 및 입출력 성능을 제공하는 MAHA-FS를 소개한다. 아울러 성능 분석을 통해 MAHA-FS가 메타데이터 연산 처리 성능 및 random 입출력 성능이 우수함을 보인다.

• 인터넷정보학회논문지
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• 제24권6호
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• pp.1-11
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• 2023

Federated learning (FL) is a ground breaking machine learning paradigm that allow smultiple participants to collaboratively train models in a cloud environment, all while maintaining the privacy of their raw data. This approach is in valuable in applications involving sensitive or geographically distributed data. However, one of the challenges in FL is dealing with heterogeneous and non-independent and identically distributed (non-IID) data across participants, which can result in suboptimal model performance compared to traditionalmachine learning methods. To tackle this, we introduce FedGCD, a novel FL algorithm that employs Graph Neural Network (GNN)-based community detection to enhance model convergence in federated settings. In our experiments, FedGCD consistently outperformed existing FL algorithms in various scenarios: for instance, in a non-IID environment, it achieved an accuracy of 0.9113, a precision of 0.8798,and an F1-Score of 0.8972. In a semi-IID setting, it demonstrated the highest accuracy at 0.9315 and an impressive F1-Score of 0.9312. We also introduce a new metric, nonIIDness, to quantitatively measure the degree of data heterogeneity. Our results indicate that FedGCD not only addresses the challenges of data heterogeneity and non-IIDness but also sets new benchmarks for FL algorithms. The community detection approach adopted in FedGCD has broader implications, suggesting that it could be adapted for other distributed machine learning scenarios, thereby improving model performance and convergence across a range of applications.

• International Journal of CAD/CAM
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• 제3권1_2호
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• pp.51-60
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• 2003

The growth of the World Wide Web and the advances in high-speed network access have greatly changed existing CAD/CAE environment. The WWW has enabled us to share various distributed product data and to collaborate in the design process. An international standard for the product model data, STEP, and a standard for the distributed object technology, CORBA, are very important technological components for the interoperability in the advanced design and manufacturing environment. These two technologies provide background for the sharing of product data and the integration of applications on the network. This paper describes a distributed CAD/CAE environment that is integrated on the network by CORBA and product model data standard STEP. Several prototype application modules were implemented to verify the proposed concept and the test result is discussed. Finite element analysis server are further distributed into several frontal servers for the implementation of distributed parallel solution of finite element system equations. Distributed computation of analysis server is also implemented by using CORBA for the generalization of the proposed method.

• 정보과학회 논문지
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• 제44권7호
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• pp.726-732
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• 2017

무선 센서 네트워크의 분산 센싱 및 예측에 대한 실제 Application에서 네트워크 환경 센싱 기능은 움직이는 소스 신호의 잡음 및 많은 센싱 정보들 때문에 매우 동적인 기능을 요구한다. 최근의 Distributed Online Convex Optimization 프레임워크는 분산된 방식으로 센서 네트워크를 통해 확률적인 학습 문제를 해결하기 위한 유망한 접근법으로 개발되었다. 기존의 Distributed Saddle Point Algorithm (DSPA)의 학습 결과에서 수렴 속도와 안정성은 이동성의 영향을 받을 수 있다. 이에 본 논문에서는 움직이는 소스 신호 시나리오의 동시 검출에서 예측을 안정화하고 보다 나은 수렵 속도를 달성하기 위해 통합 Sliding Windows 메커니즘을 제안한다.

• 한국시뮬레이션학회논문지
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• 제18권1호
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• pp.35-40
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• 2009

분산 네트워크의 사용이 증가함에 따라 분산 작업을 신뢰성 있게 수행하기 위한 연구가 중요한 이슈로 등장하고 있다. 분산 네트워크에서의 작업의 수행은 인터넷 상의 유효자원에서 수행되므로, 가용한 자원에까지 효율적으로 접근할 수 있는가와 수행된 결과가 안정적으로 요청자에게 전달되는 것은 중요한 문제이다. 그래서 본 논문에서는 작업의 수행을 요청하는 곳에서 실제 작업이 실행되는 위치의 자원까지 데이터를 안전하게 전송하기 위한 생존성 인자를 설정하고, 생존성 인자의 값에 따른 데이터 전송속도를 측정하기 위한 성능평가를 수행하였다. 또한 제시한 생존성 인자를 활용한 안전한 전송을 보장할 수 있는 전송 알고리즘을 제시하였다.

• 한국연소학회:학술대회논문집
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• 한국연소학회 제26회 KOSCO SYMPOSIUM 논문집
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• pp.75-83
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• 2003

Diode laser absorption system is advantageous of their non-invasive nature, fast response time, high sensitivity and real-time measurement capability. Furthermore, recent advances in room-temperature, near-IR and visible diode laser sources for telecommunication, optical data storage applications are enabling combustion diagnostics system based on diode laser absorption spectroscopy. So, combined with fiber-optics and high sensitive detection strategies, compact and portable sensor system are now appearing for a variety of applications. The objective of this research is to take advantage of distributed feed-back diode laser and develope new gas sensing system. It experimentally found out that the wavelength, power characteristics as a function of injection current and temperature. In addition to direct absorption and wavelength modulation spectroscopy have been demonstrated in these experiments and have a bright prospect to this diode laser system.

• ETRI Journal
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• 제27권1호
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• pp.13-21
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• 2005

Many multicast applications, such as video-on-demand and video conferencing, desire quality of service (QoS) support from an underlying network. The differentiated services (DiffServ) approach will bring benefits for theses applications. However, difficulties arise while integrating native IP multicasting with DiffServ, such as multicast group states in the core routers and a heterogeneous QoS requirement within the same multicast group. In addition, a missing per-flow reservation in DiffServ and a dynamic join/leave in the group introduce heavier and uncontrollable traffic in a network. In this paper, we propose a distributed and stateless admission control in the edge routers. We also use a mobile agents-based approach for dynamic resource availability checking. In this approach, mobile agents act in a parallel and distributed fashion and cooperate with each other in order to construct the multicast tree satisfying the QoS requirements.

• 한국정보기술응용학회:학술대회논문집
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• 한국정보기술응용학회 2007년도 춘계학술대회
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• pp.84-102
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• 2007

Security is crucial for the successful deployment of large distributed systems. Many of these systems provide services to people across different administrative domains. The traditional identity-based access control mechanisms are un scalable and difficult to manage. Unlike the closed systems, open systems provide services to people from different security domains. Healthcare systems need to be highly available in order for the patients to get a timely treatment. The health care information should be available to authorized users both inside the administrative domain and outside the domain, such as pharmacies and insurance companies. In this paper, we first analyzed the necessities and advantages of importing attribute-based trust-management models into open distributed systems. Then we reviewed traditional access-control models and presented the basic elements of the new trust-management model.

• 한국통신학회논문지
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• 제22권6호
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• pp.1356-1364
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• 1997

This paper presents a modelling and implementation scheme of a multi directory which provides location and supplementary information of multiple applications in distributed environments. An extrended directory schema and extended DIT(Directory Information Tree) model is proposed for the multi directory. For implementation scheme, an implementation example adapted for the DFR(Document Filing and Retrieval) is shown. In addition, a configuration model for interworking between the DFR and the multi directory, an association mechanisms between two application's operations are also described. In a distributed environment, the interworking between the DFR and a multi directory implemented by using QUIPU 8.0 of ISODE(ISO Development Environment) directory system is tested. Based on the result of this paper, an extended model ofthe directory system is proposed for providing search operation of various application' objects.

• Journal of Electrical Engineering and Technology
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• 제6권4호
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• pp.573-579
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• 2011

To meet the scalability and performance requirements of data analyses, which often involve voluminous data, efficient parallel or concurrent algorithms and frameworks are essential. We present a high-performance Korean morphological analyzer which employs the MapReduce framework on the graphics processing unit (GPU). MapReduce is a programming framework introduced by Google to aid the development of web search applications on a large number of central processing units (CPUs). GPUs are designed as a special-purpose co-processor. Their programming interfaces are typically formulated for graphics applications. Compared to CPUs, GPUs have greater computation power and memory bandwidth; however, GPUs are more difficult to program because of the design of their architectures. The performance of the Korean morphological analyzer using the MapReduce framework on the GPU is evaluated in comparison with the CPU-based model. The proposed Korean Morphological analyzer shows promising scalable performance on distributed computing with the GPU.