The advent of Science Clouds enables scientists to facilitate large-scale scientific computational experiments over cloud environment besides specialized supercomputers in diverse science domains. Cloud computing service elicits efficiency on on-demand resource usage and timely execution at any given time depending on experimental requirements. Hybrid clouds, composing of private and public clouds, even extend research opportunities on resource selection for further complicated experiments but increase the needs of dynamic resource management to maximize its utilization. At existing public cloud providers for commercial use, rule-based and schedule-based mechanisms have been tried for automatic resource allocation to provide resources for processing dynamic workload of modern applications. However, most of the auto-scaling methods just simply support performance metric such as CPU utilization but rarely are aware of Service Level Agreements (SLA) including execution deadline or cost. In this paper, we propose an auto-scaling method that automatically allocates resources depending on variable resource requirements in hybrid clouds satisfying a user's requirements on SLA. We present experimental results which show that the proposed auto-scaling can minimize SLA violations and acceptable cost if needed.

전 세계적으로 다양한 응용과학 분야의 연구자들은 그들의 연구 개발에 필수적인 고성능 컴퓨팅 자원의 확보와 복잡한 수치 해석 기법 개발을 위해 막대한 연구를 수행해 왔다. 특히 항공 우주 분야에서는 공력 최적 설계를 위해 소요되는 시간과 비용을 상당 부분 줄이기 위해 진보적인 수치기법을 개발하고 컴퓨팅 기술의 발전에 의존해왔으나, 여전히 1회의 실험에 막대한 비용 지출과 수개월의 소요 기간을 감수하고 있는 실정이다. 본 논문에서는 항공 우주 분야 연구자들의 연구 개발 편의성을 도모하고자 다양한 컴퓨팅 자원 인프라를 제공하는 통합 공학 교육 실험 환경을 소개하고 그 우수성을 보인다. 다양한 컴퓨팅 인프라구조로의 연결을 통해 산재되어 있는 다수의 컴퓨팅 자원 활용이 가능하므로 다수의 교육 대상자 및 연구자들에게 장소에 제한 없는 실험 시도를 가능케 함으로써 연구 개발의 복잡성을 줄이고 생산성을 높일 수 있다. 또한 통합 환경을 교육에 활용하여 교육 효율성을 극대화시킬 수 있다. All around the world, numerous scientists have been carried out researches of e-Science to improve performance of computations and accessibility of their experimental flexibilities for a long times. However, they still have been in difficulty securing high-performance computing facilities. In case of Aerodynamics, for example, a single experiment costs a tremendous amount of budget and requires a span of more than 6 months even though researchers have been developed diverse improved mathematical methods as well as relied on advanced computing technologies to reduce runtime and costs. In this paper, we proposed a multiple infrastructure-based scientific workflow environments for engineering education in fields of design optimization of aircraft and demonstrated the superiority. Since it offers diverse kind of computing resources, it can offer elastic resources regardless of the number of tasks for experiments and limitations of spaces. Also, it can improve education efficiency by using this environment to engineering education.

—The analytical experiments for numerical analysis lead a sequence of complex scientific computations composing of numerical equations and require enormous computing re- sources with appropriate management tools. Currently most studies on e-Science environments for numerical studies focus on solving specific problems to drag out the best performance of matters and have less interest in providing a uniform framework to apply for diverse numerical domains, especially for fluid dynamics. This paper presents an integrated e-Science experiment framework which could be easily applicable to solve various numerical analyses in fluid dynamics. As a proof- of-concept, an integrated e-Science framework with diverse numerical analyses has been designed and implemented over UNICORE that runs over grid computing environment.

As computing technologies develop, various studies for e-Science have been actively developed for many years. The advent of Cloud computing, for example, enables scientists to expand their research environments over supercomputers to on-demand and scalable resources. However, several performance drawbacks on the cloud computing can cause considerable obstacles in scientific domains, despite its strong merits. A hybrid infrastructure which consists of the existing and cloud architecture thus can produce a synergy effect for utilizing resources efficiently. In this paper, we proposed hybrid infrastructure-supported a scientific workflow environment for Aerodynamics design and demonstrated its superiority. Hybrid infrastructure covers grid and private cloud computing in this paper. Especially, we focused on improving performance by supporting hybrid infrastructure and efficient usages of physical resources. Since it offers diverse types of computing infrastructures including cloud computing, it can serve elastic resources regardless of the number of tasks for experiments or limitations of space and can reduce costs of time as well as budget during simulations.

The analytical experiments for fluid dynamics lead a sequence of complex scientifical computations composing of numerical equations and require enormous computing resources with appropriate management tools with them. Currently, most studies on experimental environments for numerical study and fluid dynamics on e-Science focus on solving specific problems to drag out the best performance of the matters and have less interests on providing a common framework to apply for various numerical domains easily, especially for fluid dynamics. This paper presents an e-Science experiment framework for various numerical analysis in fluid dynamics. As a proof-of-concept, an integrated e-Science framework with three numerical analysis has been implemented over Unicore Rich Client (URC), which provides a basic experiment interface over a Grid environment.

As increasing complexity of scientific computational applications that embrace multiple physical models and require a large range of scales on computing power, demands for interoperable infrastructures steadily have been increasing. Even though heterogeneity of computational resource including large-scale computing power, storage and networks gives difficulty of management on extending resource availability in e-Science environment, researchers, especially who have limited knowledge of managing computing resource, desire to have uniform and easy-to-use access interface to those diverse computational resources. However, no problem solving environment (PSE) is capable of solving all problems in diverse application domains as their execution requirement are so various. Depending on application characteristics, it is meaningful to provide a proper PSE to solve specific application patterns for e-Science environment and manage life cycle of an application for designing, executing, analyzing, and profiling. In this paper, we present a common and integrated framework providing a problem solving environment among multi application domains, especially, in scientific numerical study, running over e-Science environment fostering interoperability in Grid infrastructure. The proposed framework, based on UNICORE, provides seamless, secure, and intuitive access to distributed Grid resources. It also speeds up developing new numerical study with existing application patterns, which are easily shared, reusable, and extendable.

Due to diverse characteristics of application domains, most experts dealing with scientific computational simulations require a specialized and customized Problem Solving Environment (PSE) with easy-to-use graphical user interfaces integrated with large-scale computing resources for their experiments. It is also important to provide adequate middleware support to drag out best performance of an application from the environment. To fulfill these requirements, we propose a workflow-enabled integrated e-Science portal system supporting interactivities for aerodynamic computing simulations, which are driven to diverse multiple execution stages depending on convergence status of variables. The portal allows scientists to manage whole life-cycle of experiments from designing, deploying, executing, and monitoring a scientific application in aerodynamic research on e-Science environment. Scientists easily extend various types of their experiments with less risk of design errors and save their time for learning curve to handle computing resources to optimize the performance of experiments. Workflow editor presents interactive, high-level web-based front end to scientist and monitoring service shows the step of the execution of workflow in real-time so that scientists in any level of expertise can check the intermediate data during experiments.