• Journal of Digital Contents Society
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• v.14 no.2
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• pp.171-178
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• 2013

Desktop grid computing is the computing paradigm that can execute large-scale computing jobs using the desktop resources with heterogeneity and volatility. However, such the computing environment can not guarantee the stability and reliability of task execution because the desktop resources with different performance can freely participate and leave in task execution. Therefore, in this paper, we design resource grouping scheme using k-means clustering algorithm with an aim to provide desktop grid computing with the stability and reliability of task execution. Moreover, we conduct resource grouping using the execution log data of actual desktop grid systems and present application methods of desktop resource groups to fault-tolerance.

• Journal of Information Processing Systems
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• v.7 no.4
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• pp.707-716
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• 2011

It is important that desktop grids should be able to aggressively deal with the dynamic properties that arise from the volatility and heterogeneity of resources. Therefore, it is required that task scheduling be able to positively consider the execution behavior that is characterized by an individual resource. In this paper, we implement a log analysis system with REST web services, which can analyze the execution behavior by utilizing the actual log data of desktop grid systems. To verify the log analysis system, we conducted simulations and showed that the resource group-based task scheduling, based on the analysis of the execution behavior, offers a faster turnaround time than the existing one even if few resources are used.

• The Journal of Korean Association of Computer Education
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• v.12 no.4
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• pp.65-75
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• 2009

The result verification is necessary to support a guarantee for the correctness of the task results be executed by any unspecified resources in desktop grid environments. Typically, voting-based and trust-based result verification schemes have been used in the environments. However, these suffer from two potential problems: waste of resources due to redundant replicas of each task and increase in turnaround time due to the inability to deal with a dynamic changeable execution environment. To overcome these problems, we propose a fuzzy inference-based replication scheme which can adaptively determine the number of replicas per task by using both trusty degree and result return probability of resources. Therefore our proposal can reduce waste of resources by determining the number of replicas meeting with a dynamic execution environment of desktop grids, not to mention an enhancement of turnaround time for entire asks. Simulation results show that our scheme is superior to other ones in terms of turnaround time, the waste of resources, and the number of re-replications per task.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.6
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• pp.628-646
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• 2009

Users want to browse and search various web contents with mobile devices which can be used anywhere and anytime without limitations, in the same manner as desktop. But mobile devices have limited resources compared to desktop in terms of computing performance, network bandwidth, screen size for full browsing, and etc, so there are many difficulties in providing support for mobile devices to fully use desktop-based web contents. Recently, mobile network bandwidth has been greatly improved, however, since mobile devices cannot provide the same environment as desktop, users still feel inconvenienced. To provide web contents optimized for each user device, there have been studies about analyzing code to extract blocks for adaptation to a mobile environment. But since web contents are divided into several items such as menu, login, news, shopping, etc, if the block dividing basis is limited only to code or segment size, it will be difficult for users to recognize and find the items they need. Also it is necessary to resolve interface issues, which are the biggest inconvenience for users browsing in a mobile environment. In this paper, we suggest a personalized adaptation system that extracts item blocks from desktop-based web contents based on user interests, layers them, and adapts them for users so they can see preferred contents first.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.7
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• pp.429-439
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• 2006

A desktop grid, which is a computing grid composed of idle computing resources in a large network of desktop computers, is a promising platform for compute-intensive distributed computing applications. However, due to reliability and unpredictability of computing resources, effective scheduling of parallel computing applications on such a platform is a difficult problem. This paper proposes a new scheduling method aimed at reducing the total execution time of a parallel application on a desktop grid. The proposed method is based on utilizing the histories of execution behavior of individual computing nodes in the scheduling algorithm. In order to test out the feasibility of this idea, execution trace data were collected from a set of 40 desktop workstations over a period of seven weeks. Then, based on this data, the execution of several representative parallel applications were simulated using trace-driven simulation. The simulation results showed that the proposed method improves the execution time of the target applications significantly when compared to previous desktop grid scheduling methods. In addition, there were fewer instances of application suspension and failure.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.1
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• pp.45-50
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• 2019

With the gradual advancement of IT, passive work processes are automated and the overall quality of life has greatly improved. This is made possible by the formation of an organic topology between a wide variety of real-life smart devices. To serve these diverse smart devices, businesses or users are using the cloud. The services in the cloud are divided into Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS). SaaS runs on PaaS, and PaaS runs on IaaS. Since IaaS is the basis of all services, an algorithm is required to operate virtualization resources efficiently. Among them, desktop resource virtualization is used for resource high availability of unused state time of existing desktop PC. Clustering of hierarchical structures is important for high availability of these resources. In addition, it is very important to select a suitable algorithm because many clustering algorithms are mainly used depending on the distribution ratio and environment of the desktop PC. If various attempts are made to find an algorithm suitable for desktop resource virtualization in an operating environment, a great deal of power, time, and manpower will be incurred. Therefore, this paper proposes a resource clustering simulator for cluster selection of desktop virtualization. This provides a clustering simulation to properly select clustering algorithms and apply elements in different environments of desktop PCs.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.933-937
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• 2010

This study aimed at the introduction of desktop method for assessment of environmental flows developed by IWMI(International Water Management Institute) recently and its application to Geum river basin. This scheme simulated the influence on aquatic ecosystem caused by watershed development and in turn the decrease of water quantity keeping the river's own flow regime. It was found to be as very effective method although it had simple structure. Flow duration curves for different environmental classes at Sutong and Gongjoo sites were estimated according to the natural conditional scenario of Geum river basin and the results were relatively compared well with the previous studies. The behaviors of monthly average runoff time series of both sites showed the level of A class. The results of this study would provide the fundamental data to establish the future plans of monitoring or management for aquatic ecosystem of Geum river basin.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.250-253
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• 2011

Chip manufacture nowadays turned their attention from accelerating uniprocessors to integrating multiple cores on a chip. Moreover desktop graphic hardware is now starting to support general purpose computation. Desktop users are able to use multi-core CPU and GPU as a high performance computing resources these days. However exploiting parallel computing resources are still challenging because of lack of higher programming abstraction for parallel programming. The 2-dimensional discrete cosine transform (2D-DCT) algorithms are most computational intensive part of JPEG encoding. There are many fast 2D-DCT algorithms already studied. We implemented several algorithms and estimated its runtime on multi-core CPU and GPU environments. Experiments show that data parallelism can be fully exploited on CPU and GPU architecture. We expect parallelized DCT bring performance benefit towards its applications such as JPEG and MPEG.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.12
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• pp.295-300
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• 2018

The rapid development of IT, many conventional passive jobs have been automated. This automation increases the leisure time of many people and various services are being developed for them. In addition, with the advent of smart devices that are compact and portable, it is possible to use various internet services without any time and place discretion. Various studies based on virtualization are under way to efficiently store and process large data generated by many devices and services. Desktop Storage Virtualization (DSV), which integrates and provides users with on-premise-based distributed desktop resources during these studies, uses virtualization to consolidate unused resources within distributed, legacy desktops. This DSV is very important for providing high reliability to users. In addition, research on hierarchical structure and resource integration for efficient data distribution storage processing in a distributed desktop-based resource integration environment is underway. However, there is a lack of research on efficient operation in case of server failure in on-premise resource integration environment. In this paper, we propose Non-disruptive Server Management (NSM) which can actively cope with the failure of desktop server in distributed desktop storage environment based on on-premise. NSM is easy to add and remove desktops in a desktop-based integrated environment. In addition, an alternative server is actively performed in response to a failure occurrence.

• KIISE Transactions on Computing Practices
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• v.22 no.8
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• pp.369-374
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• 2016

The growing demand of virtual computing and storage resources in the cloud computing environment has led to deduplication of storage system for effective reduction and utilization of storage space. In particular, large reduction in the storage space is made possible by preventing data with identical content as the virtual desktop images from being stored on the virtual desktop infrastructure. However, in order to provide reliable support of virtual desktop services, the storage system must address a variety of workloads by virtual desktop, such as performance overhead due to deduplication, periodic data I/O storms and frequent random I/O operations. In this paper, we designed and implemented a clustered file system to support virtual desktop and storage services in cloud computing environment. The proposed clustered file system provides low storage consumption by means of inline deduplication on virtual desktop images. In addition, it reduces performance overhead by deduplication process in the data server and not the virtual host on which virtual desktops are running.