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Ahn S.,Korea Institute of Science and Technology | Hwang S.,Korea Institute of Science and Technology | Jang J.-H.,Korea Institute of Science and Technology | Jang J.-H.,National Institute of Supercomputing and Networking NISN | And 2 more authors.
International Journal of Software Engineering and its Applications | Year: 2015

Objective of the long-term ecological research is to monitor environmental changes due to climate change and track the consequences, to cope with the environmental issues that may arise now and in the future. Long-term ecological research addresses the temporal gap between short-term studies by studying processes on time scales from months to decades. For long-term ecological researches, a system (Cyber Infrastructure) is essential, which can continuously harvest and manage the data about ecosystem changes. Requirements of a long-term ecological research system are very diverse; standardized interface, sharing and data integration, flexibility, standardized vocabulary, and so on. To deal with these issues, countries around the world have been building platforms that can harvest and manage the data about ecosystem changes for long-term ecological researches. This paper presents requirements and technologies for the long-term ecological research platform, and examines current technological trends in order to meet various requirements of the long-term ecological research. © 2015 SERSC. Source


Yu J.-L.,National Institute of Supercomputing and Networking NISN | Choi C.-H.,National Institute of Supercomputing and Networking NISN | Jin D.-S.,National Institute of Supercomputing and Networking NISN | Lee J.R.,National Institute of Supercomputing and Networking NISN | Byun H.-J.,University of Suwon
International Journal of Software Engineering and its Applications | Year: 2014

Virtualized Computing Cloud (VCC) is a well-known resource-provisioning and computing environment due to advantages such as maximized resource utilization, isolated performance, and customizable runtimes. Therefore, recently, VCC has been increasingly adopted in a broad spectrum of service domains, including internet-based application services and computational science. However, efficient resource (i.e., virtual machine; VM) allocation techniques are required to deliver higher-quality Internet and/or computing services. In this paper, we propose a novel dynamic, self-adaptive VMs allocation technique considering network resource contention in a Xen virtualization environment. In addition, we provide generic virtualized resources and job management framework to realize our proposed VM allocation technique. Using the virtualized resources and job management framework, we also practically analyze the impact of various system parameters and job characteristics on the performance of our technique. The results show that our approach outperforms others, reducing the average job response (by up to 37%) and execution (by up to 22.3%) times. © 2014 SERSC. Source

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