• Journal of KIISE
• /
• v.43 no.4
• /
• pp.470-479
• /
• 2016

As the number of various types of media data such as UCC (User Created Contents) increases, research is actively being carried out in many different fields so as to provide meaningful media services. Amidst these studies, a semantic web-based media classification approach has been proposed; however, it encounters some limitations in video classification because of its underlying ontology derived from meta-information such as video tag and title. In this paper, we define recognized objects in a video and activity that is composed of video objects in a shot, and introduce a reasoning approach based on description logic. We define sequential rules for a sequence of shots in a video and describe how to classify it. For processing the large amount of increasing media data, we utilize Spark streaming, and a distributed in-memory big data processing framework, and describe how to classify media data in parallel. To evaluate the efficiency of the proposed approach, we conducted an experiment using a large amount of media ontology extracted from Youtube videos.

• Journal of the Korea Society of Computer and Information
• /
• v.13 no.3
• /
• pp.161-168
• /
• 2008

A standard Web server or web application servers require the Web Servlet container to execute SOAP messages. But it requires additional process to make web service modules and need communication port. Also, Recently many web applications is becoming increasingly demand against the dynamic document than the static documnet. But a recent study has found that Apache Web Server always does not show the better performance. The more it have the dynamic documents, rather it can show worse performance. To solve this problem, we propose a new High-Speed Message Processing System, in which the SOAP_MP and the WSDL builder are used. The WSDL builder convert HTML/XML to WSDL files automatically and the SOAP_MP minimize SOAP massage processing time by eliminating the Tomcat Servlet container in the mobile Web Services implementation. We compare and analyze the System, which was proposed by us, with the standard Web Service system.

• KIPS Transactions on Software and Data Engineering
• /
• v.3 no.9
• /
• pp.349-354
• /
• 2014

Since Hadoop which is the Big-data processing platform was announced, SQL-on-Hadoop is the spotlight as the technique to analyze data using SQL on Hadoop. Tajo created by Korean programmers has recently been promoted to Top-Level-Project status by the Apache in April and has been paid attention all around world. Despite a sensible change caused by Hadoop's appearance in DW market, researches of those performance is insufficient. Thus, this study has been conducted to help choose a DW solution based on SQL-on-Hadoop as progressing the test on comparison analysis of RDBMS and Tajo. It has shown that Tajo based on Hadoop is more superior than RDBMS if it is used with accurate strategy. In addition, open-source project Tajo is expected not only to achieve improvements in technique due to active participation of many developers but also to be in charge of an important role of DW in the filed of data analysis.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• v.9 no.1
• /
• pp.898-901
• /
• 2005

In this paper, we design an authorization policy module which provides the safty and reliable authorization of the user to provide the resolution for authorization in distributed environments. PKI have been utilized much by an information security-based structure for Internet electronic commerce, it is developing X.509-based in various application field such as a network security. Especially, it provides good resolution for the authentication of the user in the situation not to meet each other, but it is not enough to provide the resolution of the authorization in distributed computing environments. In this paper, We provide AAS model, which can be used distributed resources by distributed users, and design AAS model which is an authorization policy module in the Linux-based Apache Web server.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.14 no.2
• /
• pp.343-350
• /
• 2010

In the existing design of web server architecture, data encryption technique is used to keep the reliability, stability, and safety of web service. But the use of data encryption technique wastes the work of cpu while decreasing throughput of web server and increasing average response time so that it shows negative effect on the capacity of web application server. Also, the latest web applications require security and safety for the safe internet communication. Therefore, this paper suggests the improved web server which uses thread pool and Non-blocking I/O adding new web service modules to the existing web server for the safe web service, provides reliability and safety to show the safe web service capacity. And we compare and evaluate the safety and capacity through experiment on the existing traditional Tomcat based web server and the proposed system to evaluate the safety and capacity of the proposed web server system.

• Journal of KIISE
• /
• v.43 no.7
• /
• pp.820-826
• /
• 2016

There is a growing requirement for big data processing which extracts valuable information from a large amount of data. The Hadoop system employs the MapReduce framework to process big data. However, MapReduce has limitations such as inflexible and slow data processing. To overcome these drawbacks, SQL query processing techniques known as SQL-on-Hadoop were developed. Apache Tajo, one of the SQL-on-Hadoop techniques, was developed by a Korean development group. External merge sort is one of the heavily used algorithms in Tajo for query processing. The performance of external merge sort in Tajo is influenced by two parameters, sort buffer size and fanout. In this paper, we analyzed the performance of external merge sort in Tajo with various sort buffer sizes and fanouts. In addition, we figured out that there are two major causes of differences in the performance of external merge sort: CPU cache misses which increase as the sort buffer size grows; and the number of merge passes determined by fanout.

• KIPS Transactions on Software and Data Engineering
• /
• v.9 no.1
• /
• pp.11-16
• /
• 2020

3D printing is one of the emerging technologies and getting a lot of attention. To do 3D printing, 3D model is first generated, and then converted to G-code which is 3D printer's operations. Facet, which is a small triangle, represents a small surface of 3D model. Depending on the height or precision of the 3D model, the number of facets becomes very large and so the conversion time from 3D model to G-code takes longer. Apach Hadoop is a software framework to support distributed processing for large data set and its application range gets widening. In this paper, Hadoop is used to do the conversion works time-efficient way. 2-phase distributed algorithm is developed first. In the algorithm, all facets are sorted according to its lowest Z-value, divided into N parts, and converted on several nodes independently. The algorithm is implemented in four steps; preprocessing - Map - Shuffling - Reduce of Hadoop. Finally, to show the performance evaluation, Hadoop systems are set up and converts testing 3D model while changing the height or precision.

• Journal of the Korea Society of Computer and Information
• /
• v.24 no.11
• /
• pp.51-59
• /
• 2019

Due to the exponential growth of access information on the web, the need for predicting web users' next access has increased. Various models such as markov models, deep neural networks, support vector machines, and fuzzy inference models were proposed to handle web access prediction. For deep learning based on neural network models, training time on large-scale web usage data is very huge. To address this problem, deep neural network models are trained on cluster of computers in parallel. In this paper, we investigated impact of several important spark parameters related to data partitions, shuffling, compression, and locality (basic spark parameters) for training Multi-Layer Perceptron model on Spark standalone cluster. Then based on the investigation, we tuned basic spark parameters for training Multi-Layer Perceptron model and used it for tuning Spark when training Multi-Layer Perceptron model for web access prediction. Through experiments, we showed the accuracy of web access prediction based on our proposed web access prediction model. In addition, we also showed performance improvement in training time based on our spark basic parameters tuning for training Multi-Layer Perceptron model over default spark parameters configuration.

• Journal of the Korea Society of Computer and Information
• /
• v.13 no.5
• /
• pp.135-142
• /
• 2008

Recently, the mobile Internet is rapidly changing environment in a user's web server performance requires frequent connection is difficult because the proper response is needed to improve the performance of web services engine. Therefore, the goal of this paper is to improve the performance of web services for the installation of additional access to users regardless of tomcat servlet container and process the request and to shorten processing time of SOAP (Simple Object Access Protocol) message of the server structure to of for web mobile services. The web-sever structure is consists of user demand receiver, web document processor, SOAP protocol processor, NBTM(Non-Blocking and Thread Manager) manager, session manager. The system fully supports a standard web-service protocol, reduces the message processing time and communication overhead of mobile web-service system in Web 2.0 and overhead of server, and confirms the improvement of capability by comparing and evaluating Web 2.0 standard mobile web-service system through delaying achievement evaluation by the experiment of realization in Web 2.0 environment.

• Journal of Creative Information Culture
• /
• v.6 no.1
• /
• pp.15-21
• /
• 2020

In order to utilize big data in general industrial sites, the structured big data collected from facilities, processes, and environments of industrial sites must first be processed and stored, and in the case of unstructured data, it must be stored as unstructured data or converted into structured data and stored in a database. In this paper, we study a method of collecting big data based on open IoT standards that can converge and utilize measurement information, environmental information of industrial sites to collect big data. The platform for collecting big data proposed in this paper is capable of collecting, processing, and storing big data at industrial sites to process real-time sensing information. For processing and analyzing data according to the purpose of the stored industrial, various big data technologies also can be applied.