• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.1
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• pp.23-32
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• 2009

Although the web is becoming a widely accepted medium, it provides relatively poor performance and low availability. A cluster consists of a collection of interconnected stand-alone computers working together and provides a high-availability solution in application area such as web services or information systems. Web server clusters require a high-availability service with a proactive and practical fault management. However, as the system complexity grows, it is not easy to meet the requirement. Therefore, web server clusters must have self-fault management capability for meeting high-availability requirement. In this paper, we propose high availability web server clusters using self-healing technique with a minimal human intervention. Our experimental results show that a proposed method can be used to improve the availability of web server clusters.

• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.177-180
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• 2002

This paper introduces a new distributed QoS (Quality of Service) control system for clusters of web servers. The proposed system can employ not only network bandwidth but also other metrics such as processor load, memory usage, and storage access load that affect the overall system performance. Moreover, it controls over clustered\ulcorner workstations in of-der to utilize idle resources among workstations. This architecture maximizes overall usage of cluster of web servers while it provides predictable and differentiated performance for each contents volume. We implemented a prototype of introduced system, and the test results showed the proposed method can control QoS in a cluster server system.

• Proceedings of the IEEK Conference
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• 2003.11b
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• pp.65-68
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• 2003

In this paper, we consider issues related to the autonomous management of a server cluster Server clustering technique is widely used for high available Internet servers such as a web server, because it provides very scalable and reliable service. However, it is very burden-some to manage the cluster system. For instance, installation or configuration of a new node requires skilled administrators. Also, when a node is failed, it should be recognized and recovered by a human. The management complexity gets higher while increasing the number of machines for higher throughput. Here, we are going to alleviate the management complexity by building an autonomous cluster server with Jini $_{TM}$ technology from Sun Microsystems.

• Journal of KIISE:Software and Applications
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• v.31 no.5
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• pp.586-594
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• 2004

Because web documents become creation and disappearance rapidly, users require the recommend system that offers users to browse the web document conveniently and correctly. One largely untapped source of knowledge about large data collections is contained in the cumulative experiences of individuals finding useful information in the collection. Recommendation systems attempt to extract such useful information by capturing and mining one or more measures of the usefulness of the data. The existing Information Filtering system has the shortcoming that it must have user's profile. And Collaborative Filtering system has the shortcoming that users have to rate each web document first and in high-quantity, low-quality environments, users may cover only a tiny percentage of documents available. And dynamic recommendation system using the user browsing pattern also provides users with unrelated web documents. This paper classifies these web documents using the similarity between the web documents under the web document type and extracts the user browsing sequential pattern DB using the users' session information based on the web server log file. When user approaches the web document, the proposed Dynamic recommendation system recommends Top N-associated web documents set that has high similarity between current web document and other web documents and recommends set that has sequential specificity using the extracted informations and users' session information.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.669-678
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• 2018

This study developed information technology infrastructures for building a driving environment analysis platform using various big data, such as vehicle sensing data, public data, etc. First, a small platform server with a parallel structure for big data distribution processing was developed with H/W technology. Next, programs for big data collection/storage, processing/analysis, and information visualization were developed with S/W technology. The collection S/W was developed as a collection interface using Kafka, Flume, and Sqoop. The storage S/W was developed to be divided into a Hadoop distributed file system and Cassandra DB according to the utilization of data. Processing S/W was developed for spatial unit matching and time interval interpolation/aggregation of the collected data by applying the grid index method. An analysis S/W was developed as an analytical tool based on the Zeppelin notebook for the application and evaluation of a development algorithm. Finally, Information Visualization S/W was developed as a Web GIS engine program for providing various driving environment information and visualization. As a result of the performance evaluation, the number of executors, the optimal memory capacity, and number of cores for the development server were derived, and the computation performance was superior to that of the other cloud computing.

• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.547-550
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• 2008

Recently, changes in the environment of user-centric internet service such as blog, UCC and IPTV and ubiquitous computing based on web service are needed to high availability system platform. High availability system is to provide safe service continuously even if system failure occurs in clustering system at the network. And it is necessary to synchronize data for reliable service in high availability system. In this paper, I implement DRBD(Disk Replicated Block Device) which is synchronization technique for data of local disks in high availability system.

• KIISE Transactions on Computing Practices
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• v.22 no.12
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• pp.663-674
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• 2016

Traditional supercomputing services suffer from limited accessibility and low utilization in that users(researchers) may perform computational executions only using terminal-based command line interfaces. To address this problem, in this paper, we provide the design and implementation details of National supercomputing service framework. The proposed framework supports all the fundamental primitive functions such as user management/authentication, heterogeneous computing resource management, HPC (High Performance Computing) job management, etc. so that it enables various 3rd-party applications to be newly built on top of the proposed framework. Our framework also provides Web-based RESTful OpenAPIs and the abstraction interfaces of job schedulers (as well as bundle scheduler plug-ins, for example, LoadLeveler, Open Grid Scheduler, TORQUE) in order to easily integrate the broad spectrum of heterogeneous computing clusters. To show and validate the effectiveness of the proposed framework, we describe the best practice scenario of high energy physics Lattice-QCD as an example application.