• 한국정보통신학회논문지
• /
• 제10권9호
• /
• pp.1558-1564
• /
• 2006

본 논문에서는 유비쿼터스 컴퓨팅의 핵심 기술인 MANET 환경에서 발생 할 수 있는 보안 요구사항을 도출하고, MANET을 구성하는 멤버 노드들의 협력적인 부분 인증서 관리 서비스에 의해 인증서 관리 및 멤버 노드들의 동적인 변화에 즉각적으로 적응할 수 있는 시스템 모델을 제안한다. 제안한 모델을 통하여 MAMT환경에서 발생되는 부하 집중 문제를 해결하고, 클러스터 내에서 통신하고 있는 기존의 노드들이 새로운 노드의 유입에 영향을 받지 않고 능동적으로 인증 서비스를 수행 할 수 있도록 높은 확장성과, 보안 위협을 방지 할 수 있는 모델을 제안하도록 한다. 아울러 제안한 시스템을 시뮬레이션을 통해 안정성 및 효율성과 견고성을 평가해 보도록 한다

• 유체기계공업학회:학술대회논문집
• /
• 유체기계공업학회 2006년 제4회 한국유체공학학술대회 논문집
• /
• pp.383-386
• /
• 2006

In this study, we propose a new fast algorithm for calculating short range forces in molecular dynamics, This algorithm uses a new hierarchical tree data structure which has a high adaptiveness to the particle distribution. It can divide a parent cell into k daughter cells and the tree structure is independent of the coordinate system and particle distribution. We investigated the characteristics and the performance of the tree structure according to k. For parallel computation, we used orthogonal recursive bisection method for domain decomposition to distribute particles to each processor, and the numerical experiments were performed on a 32-node Linux cluster. We compared the performance of the oct-tree and developed new algorithm according to the particle distributions, problem sizes and the number of processors. The comparison was performed sing tree-independent method and the results are independent of computing platform, parallelization, or programming language. It was found that the new algorithm can reduce computing cost for a large problem which has a short search range compared to the computational domain. But there are only small differences in wall-clock time because the proposed algorithm requires much time to construct tree structure than the oct-tree and he performance gain is small compared to the time for single time step calculation.

• 방송공학회논문지
• /
• 제20권5호
• /
• pp.774-777
• /
• 2015

본 논문에서는 8K(7680x4320) UHD(Ultra High Definition) TV에서의 화질 향상을 위한 영상신호 처리용 프로그래머블 비디오 프로세싱 플랫폼을 세계 최초로 제안하였다. 8K 영상을 초당 60 프레임으로 처리하기 위해서는 고성능 컴퓨팅 능력과 대용량의 메모리 대역폭이 지원되어야 한다. 제안한 아키텍처에서는 입력 영상의 병렬처리를 위한 멀티 클러스터 구조, 클러스터 간이 데이터 파이프라이닝을 위한 링 데이터 패스 구조 및 필터링 연산을 위한 하드웨어 가속기로 구성되었다. 재구성형 프로세서(Reconfigurable Processor) 기반의 제안된 플랫폼은 다양한 화질향상 알고리즘을 구동할 수 있으며, UHD 방송 표준 및 디스플레이 패널 변동성에 알고리즘의 업데이트만으로 대응이 가능한 큰 장점을 갖고 있다.

• 대한기계학회논문집A
• /
• 제26권9호
• /
• pp.1806-1813
• /
• 2002

It is well known that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a classical optimization technique was adopted by previous researchers. That technique overcame the difficulty of finding the intersection point of the superposed contours that correspond to the eigenfrequency caused by the crack presence. However, it is hard to select a trial solution initially for optimization because the defined objective function is heavily multimodal. A method is presented in this paper, which uses continuous evolutionary algorithms(CEAs). CEAs are effective for solving inverse problems and implemented on PC clusters to shorten calculation time. With finite element model of the structure to calculate eigenfrequencies, it is possible to formulate the inverse problem in optimization format. CEAs are used to identify the crack location and depth minimizing the difference from the measured frequencies. We have tried this new idea on a simple beam structure and the results are promising with high parallel efficiency over about 94%.

• 한국항공우주학회지
• /
• 제31권10호
• /
• pp.1-9
• /
• 2003

컴퓨팅 그리드 환경에서는 컴퓨팅 그리드 시스템을 구성하는 단위 시스템들의 성능이 균일하지 않기 때문에, 영역을 균등하게 분할하는 일반적인 로드밸런싱 기법을 적용하기가 적절하지 않다. 본 연구에서는 그래프 분할기법을 기반으로 하여, 컴퓨팅 그리드 시스템을 구성하는 단위 시스템들의 성능가중치를 계산하여 분할하는 2단계 영역 분할 기법을 제시하였다. 2단계 영역 분할 기법 시 발생하는 통신량의 증가는 그래프 분할기법인 WEVM을 적용하여 최소화 할 수 있었으며, 멀티 클러스터 환경과 WAN에서 타당성과 효율성을 검증해 보았다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제6권9호
• /
• pp.2405-2423
• /
• 2012

In a traditional Single Sign-On (SSO) scheme, the user and the Service Providers (SPs) have given their trust to the Identity Provider (IdP) or Authentication Service Provider (ASP) for the authentication and correct assertion. However, we still need a better solution for the local/native true SSO to gain user confidence, whereby the trusted entity must play the role of the ASP between distinct SPs. This technical gap has been filled by Trusted Computing (TC), where the remote attestation approach introduced by the Trusted Computing Group (TCG) is to attest whether the remote platform integrity is indeed trusted or not. In this paper, we demonstrate a Trustworthy Mutual Attestation (TMutualA) protocol as a proof of concept implementation for a local true SSO using the Integrity Measurement Architecture (IMA) with the Trusted Platform Module (TPM). In our proposed protocol, firstly, the user and SP platform integrity are checked (i.e., hardware and software integrity state verification) before allowing access to a protected resource sited at the SP and releasing a user authentication token to the SP. We evaluated the performance of the proposed TMutualA protocol, in particular, the client and server attestation time and the round trip of the mutual attestation time.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제13권12호
• /
• pp.5972-5989
• /
• 2019

With the onset of the big data age, data is growing exponentially, and the issue of how to optimize large-scale data processing is especially significant. Large-scale global optimization (LSGO) is a research topic with great interest in academia and industry. Spark is a popular cloud computing framework that can cluster large-scale data, and it can effectively support the functions of iterative calculation through resilient distributed datasets (RDD). In this paper, we propose a hybrid mechanism of particle swarm optimization (PSO) and differential evolution (DE) algorithms based on Spark (SparkPSODE). The SparkPSODE algorithm is a parallel algorithm, in which the RDD and island models are employed. The island model is used to divide the global population into several subpopulations, which are applied to reduce the computational time by corresponding to RDD's partitions. To preserve population diversity and avoid premature convergence, the evolutionary strategy of DE is integrated into SparkPSODE. Finally, SparkPSODE is conducted on a set of benchmark problems on LSGO and show that, in comparison with several algorithms, the proposed SparkPSODE algorithm obtains better optimization performance through experimental results.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제13권6호
• /
• pp.2824-2837
• /
• 2019

Container technologies are widely used in infrastructures to deploy and manage applications in cloud computing environment. As containers are light-weight software, the cluster of cloud applications can easily scale up or down to provide Internet-based services. Container-based applications can well deal with fluctuate workloads by dynamically adjusting physical resources. Current works of scheduling applications often construct applications' performance models with collected historical training data, but these works with static models cannot self-adjust physical resources to meet the dynamic requirements of cloud computing. Thus, we propose a self-adaptive automatic container scheduling framework AutoScale for cloud applications, which uses a feedback-based approach to adjust physical resources by extending, contracting and migrating containers. First, a queue-based performance model for cloud applications is proposed to correlate performance and workloads. Second, a fuzzy Kalman filter is used to adjust the performance model's parameters to accurately predict applications' response time. Third, extension, contraction and migration strategies based on predicted response time are designed to schedule containers at runtime. Furthermore, we have implemented a framework AutoScale with container scheduling strategies. By comparing with current approaches in an experiment environment deployed with typical applications, we observe that AutoScale has advantages in predicting response time, and scheduling containers to guarantee that response time keeps stable in fluctuant workloads.

• 한국정보통신학회:학술대회논문집
• /
• 한국정보통신학회 2014년도 추계학술대회
• /
• pp.93-95
• /
• 2014

본 논문은 계층적 클러스터 구조에서, 상황인식 이동성 예측모델을 통해 예측된 이동성으로 효율적인 포워딩 경로를 산출하는 기법을 제안한다. 이동성으로 인하여 노드 간 연결이 쉽게 변화하는 환경에서 통신의 불안정성을 극복하기 위해, 제안하는 알고리즘은 상황인식 이동성 예측모델을 통해 얻은 클러스터의 예측된 속성정보를 활용한다. 예측정보를 통해 클러스터간의 연결성을 매트릭스의 형태로 정리하며, 마스킹 기법을 응용한 포워딩 경로 산출 기법을 통해 효율적인 경로를 도출한다. 모의실험 결과, 제안하는 알고리즘으로 클러스터의 이동성을 고려하여 노드 간의 연결이 오래 지속될 수 있는 포워딩 경로를 선택 후에 전송함으로써 지연시간이 줄어드는 결과가 기대된다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제15권5호
• /
• pp.1649-1665
• /
• 2021

In view of the low accuracy of the traditional FunkSVD algorithm, and in order to improve the computational efficiency of the algorithm, this paper proposes a parallel algorithm of improved FunkSVD based on Spark (SP-FD). Using RMSProp algorithm to improve the traditional FunkSVD algorithm. The improved FunkSVD algorithm can not only solve the problem of decreased accuracy caused by iterative oscillations but also alleviate the impact of data sparseness on the accuracy of the algorithm, thereby achieving the effect of improving the accuracy of the algorithm. And using the Spark big data computing framework to realize the parallelization of the improved algorithm, to use RDD for iterative calculation, and to store calculation data in the iterative process in distributed memory to speed up the iteration. The Cartesian product operation in the improved FunkSVD algorithm is divided into blocks to realize parallel calculation, thereby improving the calculation speed of the algorithm. Experiments on three standard data sets in terms of accuracy, execution time, and speedup show that the SP-FD algorithm not only improves the recommendation accuracy, shortens the calculation interval compared to the traditional FunkSVD and several other algorithms but also shows good parallel performance in a cluster environment with multiple nodes. The analysis of experimental results shows that the SP-FD algorithm improves the accuracy and parallel computing capability of the algorithm, which is better than the traditional FunkSVD algorithm.