• Journal of Digital Contents Society
• /
• v.9 no.2
• /
• pp.277-284
• /
• 2008

As the increasing of users' request about internet web service, the importance of ontology to construct semantic web is increasing now. Early Internet data processing was studied in the form of data integration through centralized ontology construction. However, because of distributed environment of internet, when integrating data of distributed site, it is required to integrate data of each site in terms of peer-to-peer data processing for corresponding to fast change of internet. In this paper, in distributed environment, we propose data processing method which construct ontology in each site with ontology language OWL. Furthermore, through relational representation of OWL, we propose the system containing distributed query processing for data constructed in different site with different method.

• Journal of Korean Society for Quality Management
• /
• v.48 no.4
• /
• pp.553-566
• /
• 2020

Purpose: The purpose of this study was to design a framework for generating one-class classification algorithm based on Hyper-Rectangle(H-RTGL) in a distributed environment connected by network. Methods: At first, we devised one-class classifier based on H-RTGL which can be performed by distributed computing nodes considering model and data parallelism. Then, we also designed facilitating components for execution of distributed processing. In the end, we validate both effectiveness and efficiency of the classifier obtained from the proposed framework by a numerical experiment using data set obtained from UCI machine learning repository. Results: We designed distributed processing framework capable of one-class classification based on H-RTGL in distributed environment consisting of physically separated computing nodes. It includes components for implementation of model and data parallelism, which enables distributed generation of classifier. From a numerical experiment, we could observe that there was no significant change of classification performance assessed by statistical test and elapsed time was reduced due to application of distributed processing in dataset with considerable size. Conclusion: Based on such result, we can conclude that application of distributed processing for generating classifier can preserve classification performance and it can improve the efficiency of classification algorithms. In addition, we suggested an idea for future research directions of this paper as well as limitation of our work.

• The Journal of the Korea Contents Association
• /
• v.16 no.7
• /
• pp.667-680
• /
• 2016

As distributed computing platforms like Hadoop MapReduce have been developed, it is necessary to perform the conventional query processing techniques, which have been executed in a single computing machine, in distributed computing environments efficiently. Especially, studies on similarity join query processing in distributed computing environments have been done where similarity join means retrieving all data pairs with high similarity between given two data sets. But the existing similarity join query processing schemes for distributed computing environments have a problem of skewed computing load balance between clusters because they consider only the data transmission cost. In this paper, we propose Matrix-based Load-balancing Algorithm for efficient similarity join query processing in distributed computing environment. In order to uniform load balancing of clusters, the proposed algorithm estimates expected computing cost by using matrix and generates partitions based on the estimated cost. In addition, it can reduce computing loads by filtering out data which are not used in query processing in clusters. Finally, it is shown from our performance evaluation that the proposed algorithm is better on query processing performance than the existing one.

• The Transactions of the Korea Information Processing Society
• /
• v.7 no.4
• /
• pp.1050-1061
• /
• 2000

This paper presents a new object model, LOM(Lightweight Object Model) and an implementation method for the distributed trader in heterogeneous distributed computing environment including mobile network. Trader is third party object that enables clients to find suitable servers, which provide the most appropriate services to client in distributed environment including dynamic reconfiguration of services and servers. Trading service requires simpler and more specific object model than genetic object models which provide richer multimedia data types and semantic characteristics with complex data structures. LOM supports a new reference attribute type instead of the relationship, inheritance and composite attribute types of the general object oriented models and so LOM has simple data structures. Also in LOM, the modelling step includes specifying of the information about users and the access right to objects for security in the mobile environment and development of the distributed storage for trading service. Also, we propose and implementation method of the distributed trader, which integrates the LOM-information object model and the OMG (object Management Group) computational object model.

• Journal of Korea Multimedia Society
• /
• v.20 no.9
• /
• pp.1559-1566
• /
• 2017

Recently in the IoT(Internet of Things) environment, a data collection in real-time through device's sensor has increased with an emergence of various devices. Collected data from IoT environment shows a large scale, non-uniform generation cycle and atypical. For this reason, the distributed processing technique is required to analyze the IoT sensor data. However if you do not consider the optimal scheduling for data and the processor of IoT in a distributed processing environment complexity increase the amount in assigning a task, the user is difficult to guarantee the QoS(Quality of Service) for the sensor data. In this paper, we propose APQTA(Adaptive Priority Queue-driven Task Allocation method for sensor data processing) to efficiently process the sensor data generated by the IoT environment. APQTA is to separate the data into job and by applying the priority allocation scheduling based on the deadline to ensure that guarantee the QoS at the same time increasing the efficiency of the data processing.

• The Transactions of the Korea Information Processing Society
• /
• v.6 no.10
• /
• pp.2618-2629
• /
• 1999

In this paper, we describe the design and implementation of the FDRA(Fault Detection Recovery based on Agent) running on distributed multimedia environment. DOORAE is a good example for distributed multimedia and multimedia distance education system among students and teachers during lecture. It has primitive service agents. Service functions are implemented with objected oriented concept. FDRA is a multi-agent system. It has been environment, intelligent agents interact with each other, either collaboratively or non-collaboratively, to achieve their goals. The main idea is to detect an error by using polling method. This system detects an error by polling periodically the process with relation to session. And, it is to classify the type of error s automatically by using learning rules. The merit of this system is to use the same method to recovery it as it creates a session. FDRA is a system that is able to detect an error, to classify an error type, and to recover automatically a software error based on distributed multimedia environment.

• The KIPS Transactions:PartA
• /
• v.11A no.4
• /
• pp.251-256
• /
• 2004

By large quantity supply of high efficiency computers, various kind of distributed resource has been extravagant around. Use this distributed resource, if exclude concept of systems by each field, module, operation and administration then we can use it into minimum expense. Hereupon, accommodate some among contents that is proposed through 'Proposal of DVM and DESPL that have apply in distributed environment' and designs and implements SDVM. The user who use SDVM can use into minimum expense without concept of distributed environment.

• Proceedings of the Korea Database Society Conference
• /
• 1994.09a
• /
• pp.105-129
• /
• 1994

The information system of corporations are facing a new environment expressed by miniaturization, decentralization and Open System. It is therefore of utmost importance for corporations to adapt flexibly th such new environment by providing for corresponding changes to their existing information systems. The objectives of this study are to identify this new environment faced by today′s information system and develop effective methods for data resource management under this new environment. In this study, it is assumed that the new environment faced by information systems can be specified as Distributed Computing Environment, and in order to achieve such system, presents Client/server architecture as its representative computing structure, This study defines Client/server architecture as a computing architecture which specialize the fuctionality of the client system and the server system in order to have an application distribute and perform cooperative processing at the best platform. Furthermore, from among the five structures utilized in Client/server architecture for distribution and cooperative processing of application between server and client this study presents two different data management methods under the Client/server environment; one is "Remote Data Management Method" which uses file server or database server and. the other is "Distributed Data Management Method" using distributed database management system. The result of this study leads to the conclusion that in the client/server environment although distributed application is assumed, the data could become centralized (in the case of file server or database server) or decentralized (in the case of distributed database system) and the data management method through a distributed database system where complete responsibility and powers with respect to control of data used by the user are given not only is it more adaptable to modern flexible corporate environment, but in terms of system operation, it presents a more efficient data management alternative compared to existing data management methods in terms of cutting costs.

• Journal of Information Processing Systems
• /
• v.13 no.3
• /
• pp.518-532
• /
• 2017

Due to the rapid growth of the amount of data, research on bigdata processing has been highlighted. For bigdata processing, CUBRID Shard is able to support query processing in parallel way by dividing the database into a number of CUBRID servers. However, CUBRID Shard can answer a user's query only when the query is required to gain accesses to a single CUBRID server, instead of multiple ones. To solve the problem, in this paper we propose a CUBRID based distributed parallel query processing system that can answer a user's query in parallel and distributed manner. Finally, through the performance evaluation, we show that our proposed system provides 2-3 times better performance on query processing time than the existing CUBRID Shard.

• Journal of Korea Multimedia Society
• /
• v.9 no.4
• /
• pp.490-504
• /
• 2006

It needs to control each objects on various platform and transmit multimedia data to multiple receivers which are for developing a multimedia service with multimedia live streaming in a distributed environment. In this paper, we present a DLS (Distributed Live Streaming) package which support l:N multimedia live streaming in a distributed environment. Also, it has extended RMI which is a distributed object technology and JMF using multimedia transmission/processing. A java-based DLS package has been designed to separate a transmission and a control for more efficient distributed processing. It is possible to apply in development of multimedia service supported 1:N transmission and runned independently to any platform.