• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.36
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• pp.143-152
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• 1995

This paper determines the allocation of computers and data files to minimize the sum of processing and communication costs which occur in processing jobs at each node. The problem of optimally configuring a distributed computer system belongs to the class of NP-Complete problems and the object function of this paper is nonlinear function and is hard to solve. This paper seeks the solution of distributed processing system by Tabu Search. Firstly, it presents the method of generating the starting solution proper to the distributed processing system. Secondly, it develops the method of searching neighborhood solutions. Finally, it determines the Tabu restriction appropriate to the distributed processing system. According to the experimental results, this algorithm solves a sized problems in reasonable time and is effective in the convergence of the solution. The algorithm developed in this paper is also applicable to the general allocation problems of the distributed processing system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.87-92
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• 2011

Server overload is directly proportional to requested image data size in a image processing. If request data are increase then system is overloaded in a image processing system. For the reduce of server bottle neck, we will be able to consider a distributed processing. Simple distributed processing system can solve server bottleneck and system overload but high cost system requirements. In this paper, Proposes a new distributed image processing system. Object activation technology are being grafted on to simple distributed processing system. It can optimize the user of system resources and can reuse idle system resources in network.

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

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.992-995
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• 1996

The major roles of Power SCADA System are continuous monitoring of electrical equipments state, real-time data processing and dispatching. Especially, SCADA system demands fast response time in heavy load condition, high reliability, fault tolerance, expansion capacity for the future. According to developing computer system technology, SCADA system is changing system configuration from centralized processing system to distributed processing system. This paper describes operational benefits, problems and improvement (which is studying in theory) in the application of Open System Architecture SCADA which has been installed since 1994, Seoul regional control center in KEPCO.

• Journal of Korean Society for Quality Management
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• v.39 no.3
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• pp.412-421
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• 2011

In this paper, we introduce Quality of Service(QoS) analytic model of a distributed system that decentralizes the process nodes performing each task and communicates through a network for cooperation. The model advances a service reliability model of Dai et a1.(2003) by means of considering the processing time. The service is assumed to be provided by a centralized heterogeneous distributed system which is composed of some subsystems managed by a control center. The QoS is defined as the probability that a service is provided successfully in an allowed time, we consider the hardware/software reliability and the processing time which include program execution time, data transfer time. We derive the processing time distribution for a required service through convolution of corresponding probability density function. An application example is used to explain the procedure of computing quality of service.

• Journal of Digital Contents Society
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• v.10 no.4
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• pp.649-657
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• 2009

Usually, The data transmission processing efficiency of the distributed system running on high speed networks depends on the system architecture and the data transmission processing system. In order to secure the real-time rate and the system reliability, the real-time distributed simulation system on the distributed environment has tried to satisfy the performance required by the data transmission processing system. However, the client/server-based data transmission processing system in the real-time simulation system has been difficult to satisfy the system stability, extensibility and maintenability, especially when system changes. So, it is natural to study another improved data transmission processing system to solve the problems at the existing real-time simulation system. After analyzing the existing real-time simulation system, this paper will propose the improved real-time data transmission system by using Software Design Pattern, which enhances extensibility, interoperability, reusability and maintenability of the system.

• The KIPS Transactions:PartA
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• v.11A no.3
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• pp.181-188
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• 2004

PDF(Parallel/Distributed Processing) is an internet-based parallel/distributed processing system that utilizes resources from hosts on the internet in idle state to perform large scale application through parallel processing, thus decreasing the total execution time. In this paper. do propose an adaptive method to be changed network environment at any time using realtime monitoring of host. It is found from experiments that parallel/distributed processing has better performance than its without monitoring as an adaptive strategy, which copy with task delay factor by overload and fault of network, be applicable to the cockpits of task allocation algorithm in PDP.

• Journal of Internet Computing and Services
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• v.18 no.6
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• pp.47-53
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• 2017

Recently, huge datasets have been generating rapidly in a variety of fields. Then, there is an urgent need for technologies that will allow efficient and effective processing of huge datasets. Therefore the problems of partitioning a huge dataset effectively and alleviating the processing overhead of the partitioned data efficiently have been a critical factor for scalability and performance in distributed database system. In our work we utilized multicore servers to provide scalable service to our distributed system. The partitioning of database over multicore servers have emerged from a need for new architectural design of distributed database system from scalability and performance concerns in today's data deluge. The system allows uniform access through a web service interface to concurrently distributed databases over multicore servers, using SQMD (Single Query Multiple Database) mechanism based on publish/subscribe paradigm. We will present performance results with the distributed database system built on multicore server, which is time intensive with traditional architectures. We will also discuss future works.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.1
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• pp.70-75
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• 2018

Smart Factory is an intelligent factory that can enhance productivity, quality, customer satisfaction, etc. by applying information and communications technology to the entire production process including design & development, manufacture, and distribution & logistics. The precise amount of data generated in a smart factory varies depending on the factory's size and state of facilities. Regardless, it would be difficult to apply traditional production management systems to a smart factory environment, as it generates vast amounts of data. For this reason, the need for a distributed big-data processing system has risen, which can process a large amount of data. Therefore, this article has designed a Gluster File System (GlusterFS)-based distributed big-data processing system that can be used in a smart factory environment. Compared to existing distributed processing systems, the proposed distributed big-data processing system reduces the system load and the risk of data loss through the distribution and management of network traffic.

• Asia pacific journal of information systems
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• v.6 no.1
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• pp.21-38
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• 1996

This paper investigates the performance improvement opportunities through a resiliency mechanism in the distributed primary/backup database system. Recognizing that a distributed transaction executes at several servers during its lifetime, we propose a resiliency mechanism which allows continuous transaction processing in distributed database server systems in the presence of a server failure. In order to perform continuous transaction processing despite failures, every state change of a transaction processing can be saved in the backup server. Obviously, this pessimistic synchronization may give more burdens than benefits to the system. Thus, the tracking needs not be done synchronously with the transaction progress. Instead, the state of all transaction processing in a system is saved periodically. This activity is referred to as a savepoint. Then, the question is how often the savepoint has to be done. We derive the optimal savepoint to identify the optimization parameters for the resilient transaction processing system.