• Advances in aircraft and spacecraft science
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• 제4권3호
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• pp.317-334
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• 2017

With rapid growth in the complexity of large scale engineering systems, the application of multidisciplinary analysis and design optimization (MDO) in the engineering design process has garnered much attention. MDO addresses the challenge of integrating several different disciplines into the design process. Primary challenges of MDO include computational expense and poor scalability. The introduction of a distributed, collaborative computational environment results in better utilization of available computational resources, reducing the time to solution, and enhancing scalability. SORCER, a Java-based network-centric computing platform, enables analyses and design studies in a distributed collaborative computing environment. Two different optimization algorithms widely used in multidisciplinary engineering design-VTDIRECT95 and QNSTOP-are implemented on a SORCER grid. VTDIRECT95, a Fortran 95 implementation of D. R. Jones' algorithm DIRECT, is a highly parallelizable derivative-free deterministic global optimization algorithm. QNSTOP is a parallel quasi-Newton algorithm for stochastic optimization problems. The purpose of integrating VTDIRECT95 and QNSTOP into the SORCER framework is to provide load balancing among computational resources, resulting in a dynamically scalable process. Further, the federated computing paradigm implemented by SORCER manages distributed services in real time, thereby significantly speeding up the design process. Part 1 covers SORCER and the algorithms, Part 2 presents results for aircraft panel design with curvilinear stiffeners.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권11호
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• pp.3030-3049
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• 2023

With the development and wide application of hybrid network computing modes like cloud computing, edge computing and fog computing, the customer service requests and the collaborative optimization of various computing resources face huge challenges. Considering the characteristics of network environment resources, the optimized deployment of service resources is a feasible solution. So, in this paper, the optimal goals for deploying service resources are customer experience and service cost. The focus is on the system impact of deploying services on load, fault tolerance, service cost, and quality of service (QoS). Therefore, the alternate node filtering algorithm (ANF) and the adjustment factor of cost matrix are proposed in this paper to enhance the system service performance without changing the minimum total service cost, and corresponding theoretical proof has been provided. In addition, for improving the fault tolerance of system, the alternate node preference factor and algorithm (ANP) are presented, which can effectively reduce the probability of data copy loss, based on which an improved cost-efficient replica deployment strategy named ICERD is given. Finally, by simulating the random occurrence of cloud node failures in the experiments and comparing the ICERD strategy with representative strategies, it has been validated that the ICERD strategy proposed in this paper not only effectively reduces customer access latency, meets customers' QoS requests, and improves system service quality, but also maintains the load balancing of the entire system, reduces service cost, enhances system fault tolerance, which further confirm the effectiveness and reliability of the ICERD strategy.

• International Journal of Contents
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• 제2권4호
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• pp.25-30
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• 2006

The mutual exclusion (MX) paradigm can be used as a building block in many practical problems such as group communication, atomic commitment and replicated data management where the exclusive use of an object might be useful. The problem has been widely studied in the research community since one reason for this wide interest is that many distributed protocols need a mutual exclusion protocol. However, despite its usefulness, to our knowledge there is no work that has been devoted to this problem in a mobile computing environment. In this paper, we describe a solution to the mutual exclusion problem from mobile computing systems. This solution is based on the token-based mutual exclusion algorithm.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2008년도 학술대회 1부
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• pp.309-313
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• 2008

지능적인 사용자 중심의 서비스 제공 실현은 현재 여러 분야에서 활발히 진행 중인 유비쿼터스 컴퓨팅의 최종 목표이다. [1] 이와 같은 지능적 환경 구성의 목표 실현을 위하여 상황인지 기법은 핵심 요소로써 간주 되고 있으며 각 연구 기관에서 심도 높게 진행되고 있다. 이에 본 연구에서는 상황인지 기반 동적 환경 구성 및 사용자 중심의 서비스 제공 기법으로써 커뮤니티 컴퓨팅을 소개 하고 이를 구현하기 워하여 OSSGi(Open Services Gateway Initiative) 기반의 커뮤니티 컴퓨팅 통합 플랫폼을 제안한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권12호
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• pp.5780-5802
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• 2017

Cloud computing system consists of distributed resources in a dynamic and decentralized environment. Therefore, using cloud computing resources efficiently and getting the maximum profits are still challenging problems to the cloud service providers and cloud service users. It is important to provide the efficient scheduling. To schedule cloud resources, numerous heuristic algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Cuckoo Search (CS) algorithms have been adopted. The paper proposes a Modified Particle Swarm Optimization (MPSO) algorithm to solve the above mentioned issues. We first formulate an optimization problem and propose a Modified PSO optimization technique. The performance of MPSO was evaluated against PSO, and GA. Our experimental results show that the proposed MPSO minimizes the task execution time, and maximizes the resource utilization rate.

• 한국국방경영분석학회지
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• 제24권1호
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• pp.18-40
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• 1998

This paper is aimed to design an intelligent military decision aiding system in a network computing environment, especially focusing on designing an intelligent analytic system that has data mining tools and inference engine. Through this study, we concluded that the intelligent analytic system can aid military decision making processes. Highlights of the proposed system are as follows : 1) Decision making time can be reduced by the On-line and Real-time analysis ; 2) Intelligent analysis on military decision problems in network computing environments in enabled; 3) The WWW-based implementation models, which provide a standard user interface with seamless information sharing and integration capability and knowledge repository.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2007년도 정기 학술대회 논문집
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• pp.719-724
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• 2007

Many engineering problems often require the large amount of computing resources for iterative simulations of problems treating many parameters and input files. In order to overcome the situation, this paper proposes an e-Science based computational system. The system exploits the Grid computing technology to establish an integrated web service environment which supports distributed high throughput computational simulations and remote executions. The proposed system provides an easy-to-use parametric study service where a computational service includes real time monitoring. To verify usability of the proposed system, two kinds of applications were introduced. The first application is an Aerospace Integrated Research System (e-AIRS). The e-AIRS adapts the proposed computational system to solve CFD problems. The second one is design and optimization of protein 3-dimensional structures.

• 한국컴퓨터정보학회논문지
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• 제11권3호
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• pp.239-248
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• 2006

유비쿼터스 컴퓨팅 환경에서 현재의 상황 인식 어플리케이션은 다루고 있는 상황 정보가 정확하다고 가정하지만, 실제로 센서로 입력되고 해석된 상황 정보들은 종종 모호하거나 불확실하다. 본 논문에서는 상황 정보의 모호성을 해결하기 위하여 베이지안 네트워크를 사용하고 상황 정보를 표현하기 위해 온톨로지 기반 모델을 확장한 확률 모델을 제안한다. 이 논문에서 제시한 확률 확장 온톨로지 기반 상황 인식 미들웨어는 유비쿼터스 환경에서 요구되는 다양한 상황 인식 서비스의 개발 및 운용을 효과적으로 지원 할 수 있다.

• 인터넷정보학회논문지
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• 제22권5호
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• pp.57-67
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• 2021

Modern cloud computing is rapidly changing from traditional hypervisor-based virtual machines to container-based cloud-native environments. Due to limitations in I/O performance required for both virtual machines and containers, the use of high-speed storage (SSD, NVMe, etc.) is increasing, and in-memory computing using main memory is also emerging. Running a virtual environment on main memory gives better performance compared to other storage arrays. However, RAM used as main memory is expensive and due to its volatile characteristics, data is lost when the system goes down. Therefore, additional work is required to run the virtual environment in main memory. In this paper, we propose a hybrid in-memory storage that combines a block storage such as a high-speed SSD with main memory to safely operate virtual machines and containers on main memory. In addition, the proposed storage showed 6 times faster write speed and 42 times faster read operation compared to regular disks for virtual machines, and showed the average 12% improvement of container's performance tests.

• International Journal of Computer Science & Network Security
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• 제23권7호
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• pp.119-130
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• 2023

Worldwide organizations use the benefits offered by Cloud Computing (CC) to store data, software and programs. While running hugely complicated and sophisticated software on cloud requires more energy that causes global warming and affects environment. Most of the time energy consumption is wasted and it is required to explore opportunities to reduce emission of carbon in CC environment to save energy. Many improvements can be done in regard to energy efficiency from the software perspective by considering and paying attention on the energy consumption aspects of software's that run on cloud infrastructure. The aim of the current research is to propose a framework with an additional phase called parameterized development phase to be incorporated along with the traditional Software Development Life cycle (SDLC) where the developers need to consider the suggested techniques during software implementation to utilize low energy for running software on the cloud and contribute in green computing. Experiments have been carried out and the results prove that the suggested techniques and methods has enabled in achieving energy consumption.