• Journal of KIISE:Computing Practices and Letters
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• v.14 no.1
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• pp.76-80
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• 2008

In order to reduce a product life cycle and to improve productivity, it is required to automate the design/analysis processes. In general, since the design/analysis processes need a lot of time and resources, the various engineering resources should be integrated and utilized effectively in the distributed environments. KIMM (Korea Institute of Machinery and Materials) constructed the SOA-based e-Engineering framework to automate the execution of the design/analysis processes and to integrate the engineering resources in the distributed environments. This paper presents the concepts and the structures of the e-Engineering framework. Also it classifies the exceptional cases that will be able to occur in the e-Engineering framework and suggests the recovery techniques from the exceptional cases with viewpoints of the engineering process and the task, respectively.

• Journal of Korea Multimedia Society
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• v.14 no.2
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• pp.153-170
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• 2011

OMTP (Open Mobile Terminal Platform) is a global forum made by telecommunications providers to promote user-oriented mobile services and data business. Devised by OMTP, BONDI is a browser-based application or a mobile web run-time platform to help widgets make good use of functions of mobile devices in a secure way. BONDI enables applications programmed with web standard technologies such as HTML, JavaScript, CSS, and AJAX to reach the internal functions of mobile devices. Since BONDI, which is not just a simple network application, can reach the internal resources of devices in standard ways, it enables the application and widgets to be developed regardless of tile OS or platform. Web browser-based widgets are vulnerable to the network environment, and their exeeution speed can be slowed as the operations of the widgets or applications become heavy. However, those web widgets will be continuously used thanks to the user-friendly simple interface and the faster speed in using web resources more than the native widgets inside the device. This study suggested a method to effectively operate and manage the resource of OMTP BONDI web widget and then provided an improved result based on a running performance evaluation experiment. The experiment was carried to improve the entire operating time by enhancing the module-loading speed. In this regard, only indispensable modules were allowed to be loaded while the BONDI widget was underway. For the purpose, the widget resource list, able to make the operating speed of the BONDI widget faster, was redefined while a widget cache was employed. In addition, the widget box, a management tool for removed widgets, was devised to store temporarily idle widgets.

• The KIPS Transactions:PartC
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• v.9C no.3
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• pp.413-420
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• 2002

With the rapid development of computer networks, how to speed up network services and to guarantee QoS (Quality-of-Service) for users has drawn much attention from computer scientists. So has the need to manage network application services in order to manage network resources more effectively and meet the users' demands. In this paper, we present methodology of determining the traffic of application services on the network, so as to manage network resources effectively and thus to make application services more user-oriented. On the basis of this methodology and by using RMON MIB we develop analysis parameters and their algorithm to manage the traffic of application services on the network, thus realizing Web-based Application Management System which allows network managers to extract and analyze the Internet application service traffic beyond the limitation of time and space.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.113-120
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• 2022

Information technologies in higher education are the basis for solving the tasks set by monitoring the quality of higher education. The directions of aplying information technologies which are used the most nowadays have been listed. The issues that should be addressed by monitoring the quality of higher education with the use of information technology have been listed. The functional basis for building a monitoring system is the cyclical stages: Observation; Orientation; Decision; Action. The monitoring system's considered cyclicity ensures that the concept of independent functioning of the monitoring system's subsystems is implemented.. It also ensures real-time task execution and information availability for all levels of the system's hierarchy of vertical and horizontal links, with the ability to restrict access. The educational branch uses information and computer technologies to monitor research results, which are realized in: scientific, reference, and educational output; electronic resources; state standards of education; analytical materials; materials for state reports; expert inferences on current issues of education and science; normative legal documents; state and sectoral programs; conference recommendations; informational, bibliographic, abstract, review publications; digests. The quality of Ukrainian scientists' scientific work is measured using a variety of bibliographic markers. The most common is the citation index. In order to carry out high-quality systematization of information and computer monitoring technologies, the classification has been carried out on the basis of certain features: (processual support for implementation by publishing, distributing and using the results of research work). The advantages and disadvantages of using web-based resources and services as information technology tools have been discussed. A set of indicators disclosed in the article evaluates the effectiveness of any means or method of observation and control over the object of monitoring. The use of information technology for monitoring and evaluating higher education is feasible and widespread in Ukrainian education, and it encourages the adoption of e-learning. The functional elements that stand out in the information-analytical monitoring system have been disclosed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.1C
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• pp.21-35
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• 2002

Nowadays, in accordance with increasing expectations of multimedia stream service on the internet, a lot of distributed applications are being required and developed. But the models of the existing systems have the problems that cannot support the extensibility and the reusability, when the QoS relating functions are being developed as an integrated modules which are suited on the centralized controlled specific-purpose application services. To cope with these problems, it is suggested in this paper to a distributed QoS management system on CORBA, an object-oriented middleware compliance. This systems we suggested can provides not only for efficient control of resources, various service QoS, and QoS control functions as the existing functions, but also QoS control real-time negotiation and dynamic adaptation in addition. This system consists of QoS Control Management Module(QoS CMM) in client side and QoS Management Module(QoS MM) in server side, respectively. These distributed modules are interfacing with each other via CORBA on different systems for distributed QoS management while serving distributed streaming applications. In phase of design of our system, we use UML(Unified Modeling Language) for designing each component in modules, their method calls and various detailed functions for controlling QoS of stream services. For implementation of our system, we used OrbixWeb 3.1c following CORBA specification on Solaris 2.5/2.7, Java language, Java Media Framework API 2.0 beta2, Mini-SQL 1.0.16 and the multimedia equipments, such as SunVideoPlus/Sun Video capture board and Sun Camera. Finally, we showed a numerical data controlled by real-time negotiation and adaptation procedures based on QoS map information to GUIs on client and server dynamically, while our distributed QoS management system is executing a given streaming service.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.71-84
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• 2013

Log data, which record the multitude of information created when operating computer systems, are utilized in many processes, from carrying out computer system inspection and process optimization to providing customized user optimization. In this paper, we propose a MongoDB-based unstructured log processing system in a cloud environment for processing the massive amount of log data of banks. Most of the log data generated during banking operations come from handling a client's business. Therefore, in order to gather, store, categorize, and analyze the log data generated while processing the client's business, a separate log data processing system needs to be established. However, the realization of flexible storage expansion functions for processing a massive amount of unstructured log data and executing a considerable number of functions to categorize and analyze the stored unstructured log data is difficult in existing computer environments. Thus, in this study, we use cloud computing technology to realize a cloud-based log data processing system for processing unstructured log data that are difficult to process using the existing computing infrastructure's analysis tools and management system. The proposed system uses the IaaS (Infrastructure as a Service) cloud environment to provide a flexible expansion of computing resources and includes the ability to flexibly expand resources such as storage space and memory under conditions such as extended storage or rapid increase in log data. Moreover, to overcome the processing limits of the existing analysis tool when a real-time analysis of the aggregated unstructured log data is required, the proposed system includes a Hadoop-based analysis module for quick and reliable parallel-distributed processing of the massive amount of log data. Furthermore, because the HDFS (Hadoop Distributed File System) stores data by generating copies of the block units of the aggregated log data, the proposed system offers automatic restore functions for the system to continually operate after it recovers from a malfunction. Finally, by establishing a distributed database using the NoSQL-based Mongo DB, the proposed system provides methods of effectively processing unstructured log data. Relational databases such as the MySQL databases have complex schemas that are inappropriate for processing unstructured log data. Further, strict schemas like those of relational databases cannot expand nodes in the case wherein the stored data are distributed to various nodes when the amount of data rapidly increases. NoSQL does not provide the complex computations that relational databases may provide but can easily expand the database through node dispersion when the amount of data increases rapidly; it is a non-relational database with an appropriate structure for processing unstructured data. The data models of the NoSQL are usually classified as Key-Value, column-oriented, and document-oriented types. Of these, the representative document-oriented data model, MongoDB, which has a free schema structure, is used in the proposed system. MongoDB is introduced to the proposed system because it makes it easy to process unstructured log data through a flexible schema structure, facilitates flexible node expansion when the amount of data is rapidly increasing, and provides an Auto-Sharding function that automatically expands storage. The proposed system is composed of a log collector module, a log graph generator module, a MongoDB module, a Hadoop-based analysis module, and a MySQL module. When the log data generated over the entire client business process of each bank are sent to the cloud server, the log collector module collects and classifies data according to the type of log data and distributes it to the MongoDB module and the MySQL module. The log graph generator module generates the results of the log analysis of the MongoDB module, Hadoop-based analysis module, and the MySQL module per analysis time and type of the aggregated log data, and provides them to the user through a web interface. Log data that require a real-time log data analysis are stored in the MySQL module and provided real-time by the log graph generator module. The aggregated log data per unit time are stored in the MongoDB module and plotted in a graph according to the user's various analysis conditions. The aggregated log data in the MongoDB module are parallel-distributed and processed by the Hadoop-based analysis module. A comparative evaluation is carried out against a log data processing system that uses only MySQL for inserting log data and estimating query performance; this evaluation proves the proposed system's superiority. Moreover, an optimal chunk size is confirmed through the log data insert performance evaluation of MongoDB for various chunk sizes.