• The Journal of the Korea Contents Association
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• v.8 no.12
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• pp.441-448
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• 2008

The molecular docking system needs a large amount of computation and requires super-computing power. Since the experiment requires a large amount of time, the experiment is conducted in the distributed environment or in the grid environment. Recently, researches on using parallel GPU of far higher performance than that of CPU in scientific computing have been very actively conducted. CUDA is an open technique by which a parallel GPU programming is made possible. This study proposes the molecular docking system using CUDA. It also proposes algorithm that parallels energy-minimizing-computation. To verify such experiments, this study conducted a comparative analysis on the time required for experimenting molecular docking in general CPU and the time and performance of the parallel GPU-based molecular docking which is proposed in this study.

• Journal of Korea Spatial Information System Society
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• v.11 no.3
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• pp.55-62
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• 2009

Location based Services in the ubiquitous computing environment, namely u-LBS, use very large and skewed spatial objects that are closely related to locational information. It is especially essential to achieve fast search, which is looking for POI(Point of Interest) related to the location of users. This paper examines how to search large and skewed POI efficiently in the u-LBS environment. We propose the Dynamic-level Grid based R-Tree(DGR-Tree), which is an index for point data that can reduce the cost of stationary POI search. DGR-Tree uses both R-Tree as a primary index and Dynamic-level Grid as a secondary index. DGR-Tree is optimized to be suitable for point data and solves the overlapping problem among leaf nodes. Dynamic-level Grid of DGR-Tree is created dynamically according to the density of POI. Each cell in Dynamic-level Grid has a leaf node pointer for direct access with the leaf node of the primary index. Therefore, the index access performance is improved greatly by accessing the leaf node directly through Dynamic-level Grid. We also propose a K-Nearest Neighbor(KNN) algorithm for DGR-Tree, which utilizes Dynamic-level Grid for fast access to candidate cells. The KNN algorithm for DGR-Tree provides the mechanism, which can access directly to cells enclosing given query point and adjacent cells without tree traversal. The KNN algorithm minimizes sorting cost about candidate lists with minimum distance and provides NEB(Non Extensible Boundary), which need not consider the extension of candidate nodes for KNN search.

• Journal of the Korea Society of Computer and Information
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• v.13 no.4
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• pp.31-37
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• 2008

In this paper, we propose a dynamic job relocation strategy that considering application's characteristics in multiple grid sites. This scheme classifies application to execute in multiple grid sites by their characteristics : computing intensive application, network intensive application. Also, it eliminates the communication between sites by allocating the network intensive application in single site, thus reducing the total job execution time. But if a number of free nodes to execute the network intensive application aren't found in single site, the proposed scheme the first allocates the network intensive application in multiple sites to minimize network latency. Then if the network intensive application being executed in multiple sites suitable free nodes are found in single site. the proposed scheme relocates the application being executed in multiple sites to another single site. This results in reducing the total job execution time. Through simulation, we show that the proposed dynamic job reallocation strategy improves the performance of Data Grid environment compared with previous strategies.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.8
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• pp.525-533
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• 2009

Staging technique is used to provide files for a job in the Grid. If a staged file has large volume, the start time of the job is delayed and the throughput of job in the Grid may decrease. Therefore, removal of staging overhead helps the Grid operate more efficiently. In this paper, we present two methods for efficient file provisioning to clear the overhead. First, we propose RA-RFT, which extends RFT of Globus Toolkit and enables it to utilize RLS with replica information. RA-RFT can reduce file transfer time by doing partial transfer for each replica in parallel. Second, we suggest Remote Link that uses remote I/O instead of file transfer. Remote link is able to save storage of computational nodes and enables fast file provisioning via prefetching. Through various experiments, we argue that our two methods have an advantage over existing staging techniques.

• Journal of Digital Contents Society
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• v.17 no.1
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• pp.51-57
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• 2016

Distributed Computing attempts to harness a massive computing power using a great numbers of idle PCs resource distributed linked to the internet and processes a variety of applications parallel way such as bio, climate, cryptology, and astronomy. In this paper, we develop internet-distributed computing environment, so that we can analyze High Resolution Rainfall Prediction application in meteorological field. For analyze the rainfall forecast in Korea peninsula, we used QPM(Quantitative Precipitation Model) that is a mesoscale forecasting model. It needs to a lot of time to construct model which consisted of 27KM grid spacing, also the efficiency is degraded. On the other hand, based on this model it is easy to understand the distribution of rainfall calculated in accordance with the detailed topography of the area represented by a small terrain model reflecting the effects 3km radius of detail and terrain can improve the computational efficiency. The model is broken down into detailed area greater the required parallelism and increases the number of compute nodes that efficiency is increased linearly.. This model is distributed divided in two sub-grid distributed units of work to be done in the domain of $20{\times}20$ is networked computing resources.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2310-2345
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• 2017

With the emergence of the Internet of Things (IoT) the world is projecting towards a scenario where every object in the world (including humans) acts as a sender and receiver of data and if we were to see that concept mature we would soon be talking of billions more users of the cloud networks. The cloud technology is a very apt alternative to permanent storage when it comes to bulk storage and reporting. It has however shown weaknesses concerning real-time data accessibility and processing. The bandwidth availability of the cloud networks is limited and combined with the highly centralized storage structure and geographical vastness of the network in terms of distance from the end user the cloud just does not seem like a friendly environment for real-time IOT data. This paper aims at highlighting the importance of Flavio Bonomi's idea of Fog Computing which has been glamorized and marketed by Cisco but has not yet been given a proper service architecture that would explain how it would be used in terms of various service models i-e IaaS, PaaS and SaaS, of the Cloud. The main contribution of the paper would be models for IaaS, PaaS and SaaS for Fog environments. The paper would conclude by highlighting the importance of the presented models and giving a consolidated overview of how they would work. It would also calculate the respective latencies for fog and cloud to prove that our models would work. We have used CloudSim and iFogSim to show the effectiveness of the paradigm shift from traditional cloud architecture to our Fog architecture.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.406-434
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• 2019

In general, an information security approach estimates the risk, where the risk is to occur due to an unusual event, and the associated consequences for cloud organization. Information Security and Risk Management (ISRA) practices vary among cloud organizations and disciplines. There are several approaches to compare existing risk management methods for cloud organizations but their scope is limited considering stereo type criteria, rather than developing an agent based task that considers all aspects of the associated risk. It is the lack of considering all existing renowned risk management frameworks, their proper comparison, and agent techniques that motivates this research. This paper proposes Agent Based Information Security Framework for Hybrid Cloud Computing as an all-inclusive method including cloud related methods to review and compare existing different renowned methods for cloud computing risk issues and by adding new tasks from surveyed methods. The concepts of software agent and intelligent agent have been introduced that fetch/collect accurate information used in framework and to develop a decision system that facilitates the organization to take decision against threat agent on the basis of information provided by the security agents. The scope of this research primarily considers risk assessment methods that focus on assets, potential threats, vulnerabilities and their associated measures to calculate consequences. After in-depth comparison of renowned ISRA methods with ABISF, we have found that ISO/IEC 27005:2011 is the most appropriate approach among existing ISRA methods. The proposed framework was implemented using fuzzy inference system based upon fuzzy set theory, and MATLAB(R) fuzzy logic rules were used to test the framework. The fuzzy results confirm that proposed framework could be used for information security in cloud computing environment.

• Journal of Internet Computing and Services
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• v.13 no.1
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• pp.37-44
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• 2012

Numerous scientists who are engaged in compute-intensive researches require more computing facilities than before, while the computing resource and techniques are increasingly becoming more advanced. For this reason, many works for e-Science environment have been actively invested and established around the world, but still the scientists look for an intuitive experimental environment, which is guaranteed the improved environmental facilities without additional configurations or installations. In this paper, we present an integrated scientific workflow execution environment for Scientific applications supporting workflow design with high performance computing infrastructure and accessibility for web browser. This portal supports automated consecutive execution of computation jobs in order of the form defined by workflow design tool and execution service concerning characteristics of each job to batch over distributed grid resources. Workflow editor of the portal presents a high-level frontend and easy-to-use interface with monitoring service, which shows the status of workflow execution in real time so that user can check the intermediate data during experiments. Therefore, the scientists can take advantages of the environment to improve the productivity of study based on HTC.

• Journal of Internet Computing and Services
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• v.9 no.1
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• pp.79-90
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• 2008

In the ubiquitous environment sensor network technologies have advanced for collecting information of the environment. With the rapid growth of sensor network technology, it is necessary and important to share the collected sensor data with a large base of diverse users. In order to provide dissemination of sensor data, we design an information dissemination system using an independent disseminator between provider and consumer. This paper describes how we designed the information dissemination system using one of the possible dissemination patterns for sensor networks, and an efficient matching algorithm called CGIM (Classed Grouping Index Matching) which employs a dynamic re-grouping scheme.

• Journal of the Korea Society of Computer and Information
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• v.11 no.1 s.39
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• pp.71-85
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• 2006

The environment of computational grid is composed of the LAN/WAN each of which has different efficiency and heterogeneous network conditions, and where various programs are running. In this environment, the role of the resource selection broker is very important because the work of each node is performed by considering heterogeneous network environment and the computing power of each node according to the characteristics of a program. In this paper, a new resource selection broker is presented that decides the number of work processes to be allocated at each node by considering network state information and the performance of each node according to the characteristics of a program in the environment of computational grid. The proposed resource selection broker has three steps as follows. First, the performance ratio of each node is computed using latency-bandwidth-cpu mixture information reflecting the characteristics of a program, and the number of work processes that will be performed at each node are decided by this ratio. Second, RSL file is automatically made based on the number of work processes decided at the previous step. Finally, each node creates work processes by using that RSL file and performs the work which has been allocated to itself. As experimental results, the proposed method reflecting characteristics of a program, compared with the existing (uniformity) and latency-bandwidth method is improved $278%\sim316%,\;524%\sim595%,\;924%\sim954%$ in the point of work amount, work process number, and node number respectively.