Byungsang Kim

Korea Institute of Science and Technology Information (KISTI), Daiden, Daejeon, South Korea

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Publications (8)1.89 Total impact

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    ABSTRACT: The cloud environment makes it possible to analyze large data sets in a scalable computing infrastructure. In the bioinformatics field, the applications are composed of the complex workflow tasks, which require huge data storage as well as a computing-intensive parallel workload. Many approaches have been introduced in distributed solutions. However, they focus on static resource provisioning with a batch-processing scheme in a local computing farm and data storage. In the case of a large-scale workflow system, it is inevitable and valuable to outsource the entire or a part of their tasks to public clouds for reducing resource costs. The problems, however, occurred at the transfer time for huge dataset as well as there being an unbalanced completion time of different problem sizes. In this paper, we propose an adaptive resource-provisioning scheme that includes run-time data distribution and collection services for hiding the data transfer time. The proposed adaptive resource-provisioning scheme optimizes the allocation ratio of computing elements to the different datasets in order to minimize the total makespan under resource constraints. We conducted the experiments with a well-known sequence alignment algorithm and the results showed that the proposed scheme is efficient for the cloud environment.
    Journal of Information Processing Systems 12/2012; 8(4). DOI:10.3745/JIPS.2012.8.4.555
  • Byungsang Kim, Chan-Hyun Youn
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    ABSTRACT: For widely distributed data analysis applications over that run the Internet, both the instability of the data transfer time and the dynamics of data processing rate require a more sophisticated data provisioning scheme to maximize parallel efficiency, in particular, under conditions in which real-time and limited data buffer (storage) constraints are given. In this letter, we propose a synchronized data provisioning scheme that implicitly avoids the data buffer overflow as well as explicitly controls the data buffer underflow by optimally adjusting the buffer resilience. In order to guarantee the designated quality of service, we further exploit an adaptive buffer resilience control algorithm based on sample path analysis of the state of the data buffer and the demand queue. The simulation results show that the proposed scheme is suitably efficient to apply to an environment that can not postulate the stochastic characteristics of the data transfer time and data processing rate.
    IEEE Communications Letters 04/2012; 16(4):557-559. DOI:10.1109/LCOMM.2012.030512.112324 · 1.46 Impact Factor
  • Byungsang Kim, Yougjoo Han, Chan-Hyun Youn
    Annual International Conference on Advances in Distributed and Parallel Computing ADPC 2010; 11/2010
  • Journal- Korean Physical Society 11/2009; 55(52). DOI:10.3938/jkps.55.2229 · 0.43 Impact Factor
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    ABSTRACT: To utilize an e-Science application service which is built on a grid computing environment efficiently, it is vital to develop technologies for integrating each e- Science application service into a workflow and to execute the workflow in a cooperative environment. In this paper, the required workflow in e-Science is analyzed using a conceptual scenario and categorized into three types of workflows: simulations, experiments, and collaborative work. Additionally, the workflow of the aerospace research community, an e-Science environment is shown. The necessary applications and functionalities for the required workflow are then proposed.
    Computer and Information Science, 2008. ICIS 08. Seventh IEEE/ACIS International Conference on; 06/2008
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    ABSTRACT: In e-science environments, scientists need to execute a scientific application with various parameters multiple times to simulate and experiment complicated problems on the grid. For this, they should write every single job description with distinct parameters even if this is a troublesome task. To provide the flexibility and adaptability for parameter study, we propose an application parameter description language (APDL) and a service oriented parameter study scheme, called a parametric study service (PSS), for parameterized simulations on the grid. The APDL extends the job submission description language (JSDL) to generate parameters for multiple jobs. The proposed PSS provides a unified interface to submit jobs into various middleware platforms such as gLite, Globus, etc. The problem solving environment (PSE) assists a parameter study for their applications and every research fields tend to construct individual own PSE., The proposed PSS can be easily adapted into the specific PSE because of being implemented as Web services. In practice, we apply the APDL and the PSS into aerospace research PSE which carry out the three-dimensional turbulent analysis for compressible flow.
    e-Science and Grid Computing, IEEE International Conference on; 01/2008
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    ABSTRACT: This paper describes a parametric study service (PSS) that enables parameterized simulations on the grid. Scientific and engineering problems often require the large amount of computing resources to conduct a large-scale simulations with a wide range of input parameters and files, namely parametric study. Conducting parametric studies on the grid is a great challenge because it involves the allocation, scheduling and monitoring of jobs over the highly heterogeneous, distributed and failure-prone grid environments. The system exploits the grid computing technology to establish an integrated Web service environment which supports distributed computational simulations and remote executions. The proposed system provides an easy-to-use parametric study service that prevents users from being exposed to the complexity of the underlying grid. To demonstrate the usefulness of our PSS system, we have carried out thousands of protein folding simulations in the grid testbed, namely the KMI testbed, which consists of Linux clusters distributed across the nation.
    Advanced Communication Technology, The 9th International Conference on; 03/2007
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    ABSTRACT: Recently, there are many paradigms for supporting convergence for both networks and computing. Grid computing offers high levels of computational, storage and network capacity on the wide area environment. Optic based network is a good candidate for supporting the grid application. In this paper, we proposed a novel contention resolution scheme which is differentiated by specific application and their job type for supporting grid services in the OBS network
    Advanced Communication Technology, 2006. ICACT 2006. The 8th International Conference; 03/2006