• Title/Summary/Keyword: Distributed Processing environment

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Verification Model for Object Integration in Heterogeneous Distributed Database (이질의 분산 데이타베이스에서 객체 통합을 위한 검증 모델)

  • Kim, Yong-Won
    • The Transactions of the Korea Information Processing Society
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    • v.2 no.1
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    • pp.12-22
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    • 1995
  • When we integrate schema of distributed local databases, we mean entity integration as central concept of schema integration, and semantic of entity affects several factors. Thus the schema integration in distributed database environment starts from definition of domain relation among entity types of local schemas. Moreover, the domain relation defined by designer needs some works for confidence and validation of schema integration system. But this work was not presented in previous integration system. In this paper, we define object oriented integration for schema integration of local databases in distributed system environment, present models to verify validation on its integration, and implement the validation system.

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Performance Factor of Distributed Processing of Machine Learning using Spark (스파크를 이용한 머신러닝의 분산 처리 성능 요인)

  • Ryu, Woo-Seok
    • The Journal of the Korea institute of electronic communication sciences
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    • v.16 no.1
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    • pp.19-24
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    • 2021
  • In this paper, we study performance factor of machine learning in the distributed environment using Apache Spark and presents an efficient distributed processing method through experiments. This work firstly presents performance factor when performing machine learning in a distributed cluster by classifying cluster performance, data size, and configuration of spark engine. In addition, performance study of regression analysis using Spark MLlib running on the Hadoop cluster is performed while changing the configuration of the node and the Spark Executor. As a result of the experiment, it was confirmed that the effective number of executors was affected by the number of data blocks, but depending on the cluster size, the maximum and minimum values were limited by the number of cores and the number of worker nodes, respectively.

Data Transmission Processing System Design for Real-Time Distributed Simulation by Using Software Design Patterns (소프트웨어 디자인 패턴을 적용한 실시간 분산 시뮬레이션을 위한 데이터 전달처리 시스템 설계)

  • Suk, Jin-Weon;Ryoo, In-Tae
    • 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.

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The Design and Implementation of On-Line Performance Monitor for JaNeC (JaNeC을 위한 온라인 성능감시기의 설계 및 구현)

  • Kim, Myung-Ho;Kim, Nam-Hoon;Choi, Jae-young
    • The KIPS Transactions:PartA
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    • v.9A no.4
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    • pp.563-572
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    • 2002
  • A performance monitor is indispensable to trace and evaluate performance of a program under distributed processing environment. A performance monitor il classified as off-line and on-line according to its output method. An off-line performance monitor analyzes its performance after a program terminates, and an on-line performance monitor analyzes its one while a program runs. Therefore, the on-line function is essential to analyzing and debugging the program fast. JaNeC, distributed processing environment that is implemented in Java, contains an off-line performance monitor for this. However, this performance monitor may not analyze the program running on JaNeC efficiently. Consequently, this paper explains that an on-line performance monitor is designed and implemented for fast analysis and debugging of the program running on JaNeC. This on-line performance monitor is designed to minimize effects on a program to analyze, and provides various forms of graphic output, to analyze the program effectively. In addition, even after a program terminates, it provides interface with the off-line performance monitor, to analyze again.

Outlier Detection Based on MapReduce for Analyzing Big Data (대용량 데이터 분석을 위한 맵리듀스 기반의 이상치 탐지)

  • Hong, Yejin;Na, Eunhee;Jung, Yonghwan;Kim, Yangwoo
    • Journal of Internet Computing and Services
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    • v.18 no.1
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    • pp.27-35
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    • 2017
  • In near future, IoT data is expected to be a major portion of Big Data. Moreover, sensor data is expected to be major portion of IoT data, and its' research is actively carried out currently. However, processed results may not be trusted and used if outlier data is included in the processing of sensor data. Therefore, method for detection and deletion of those outlier data before processing is studied in this paper. Moreover, we used Spark which is memory based distributed processing environment for fast processing of big sensor data. The detection and deletion of outlier data consist of four stages, and each stage is implemented with Mapper and Reducer operation. The proposed method is compared in three different processing environments, and it is expected that the outlier detection and deletion performance is best in the distributed Spark environment as data volume is increasing.

Design and Implementation of Distributed Object Framework Supporting Audio/Video Streaming (오디오/비디오 스트리밍을 지원하는 분산 객체 프레임 워크 설계 및 구현)

  • Ban, Deok-Hun;Kim, Dong-Seong;Park, Yeon-Sang;Lee, Heon-Ju
    • Journal of KIISE:Computing Practices and Letters
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    • v.5 no.4
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    • pp.440-448
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    • 1999
  • 본 논문은 객체지향형 분산처리 환경 하에서 오디오나 비디오 등과 같은 실시간(real-time) 스트림(stream) 데이타를 처리하는 데 필요한 소프트웨어 기반구조를 설계하고 구현한 내용을 기술한다. 본 논문에서 제시한 DAViS(Distributed Object Framework supporting Audio/Video Streaming)는, 오디오/비디오 데이타의 처리와 관련된 여러 소프트웨어 구성요소들을 분산객체로 추상화하고, 그 객체들간의 제어정보 교환경로와 오디오/비디오 데이타 전송경로를 서로 분리하여 처리한다. 분산응용프로그램 작성자는 DAViS에서 제공하는 서비스들을 이용하여, 기존의 분산프로그래밍 환경이 제공하는 것과 동일한 수준에서 오디오/비디오 데이타에 대한 처리를 표현할 수 있다. DAViS는, 새로운 형식의 오디오/비디오 데이타를 처리하는 부분을 손쉽게 통합하고, 하부 네트워크의 전송기술이나 컴퓨터시스템 관련 기술의 진보를 신속하고 자연스럽게 수용할 수 있도록 하는 유연한 구조를 가지고 있다. Abstract This paper describes the design and implementation of software framework which supports the processing of real-time stream data like audio and video in distributed object-oriented computing environment. DAViS(Distributed Object Framework supporting Audio/Video Streaming), proposed in this paper, abstracts software components concerning the processing of audio/video data as distributed objects and separates the transmission path of data between them from that of control information. Based on DAViS, distributed applications can be written in the same abstract level as is provided by the existing distributed environment in handling audio/video data. DAViS has a flexible internal structure enough to easily incorporate new types of audio/video data and to rapidly accommodate the progress of underlying network and computer system technology with very little modifications.

Study of In-Memory based Hybrid Big Data Processing Scheme for Improve the Big Data Processing Rate (빅데이터 처리율 향상을 위한 인-메모리 기반 하이브리드 빅데이터 처리 기법 연구)

  • Lee, Hyeopgeon;Kim, Young-Woon;Kim, Ki-Young
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.12 no.2
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    • pp.127-134
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    • 2019
  • With the advancement of IT technology, the amount of data generated has been growing exponentially every year. As an alternative to this, research on distributed systems and in-memory based big data processing schemes has been actively underway. The processing power of traditional big data processing schemes enables big data to be processed as fast as the number of nodes and memory capacity increases. However, the increase in the number of nodes inevitably raises the frequency of failures in a big data infrastructure environment, and infrastructure management points and infrastructure operating costs also increase accordingly. In addition, the increase in memory capacity raises infrastructure costs for a node configuration. Therefore, this paper proposes an in-memory-based hybrid big data processing scheme for improve the big data processing rate. The proposed scheme reduces the number of nodes compared to traditional big data processing schemes based on distributed systems by adding a combiner step to a distributed system processing scheme and applying an in-memory based processing technology at that step. It decreases the big data processing time by approximately 22%. In the future, realistic performance evaluation in a big data infrastructure environment consisting of more nodes will be required for practical verification of the proposed scheme.

On the Current Status and Future Trend of Distributed Object System (분산 객체 시스템의 현찰과 기술 전망)

  • 윤석환;김평중
    • Journal of the Korean Professional Engineers Association
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    • v.30 no.2
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    • pp.79-86
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    • 1997
  • As network has high speed and wide communication capability, users demand diverse and new software to satisfy their needs. To meet users needs, the softwares for multimedia or groupware or distributed virtual environments can communicate the widely distributed information fast and accurately. Even though the technology for this is under development, it is deficient to support the reliable computer communication. Distributed Object System aims, as the new paradigm of distributed system software development to overcome this problem, to obtain in distributed environment the easiness of development and management, expandability, reusability which object oriented technologies support by solving the complexity of communication processing through the object oriented methods. This paper aims to introduce distributed object system, its technological properties and the current status and trend of technology development related to its standardization. Additionally, with explaining the Replicated Shared Object System(RSOS) which is developed in our country as one of the distributed object systems, its future prospects and technical issues are discussed.

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Data-Hiding Method using Digital Watermark in the Public Multimedia Network

  • Seo, Jung-Hee;Park, Hung-Bog
    • Journal of Information Processing Systems
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    • v.2 no.2
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    • pp.82-87
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    • 2006
  • In spite of the rapid development of the public network, the variety of network-based developments currently raises numerous risks factors regarding copyright violation, the prohibition and distribution of digital media utilization, safe communication, and network security. Among these problems, multimedia data tend to increase in the distributed network environment. Hence, most image information has been transmitted in the form of digitalization. Therefore, the need for multimedia contents protection must be addressed. This paper is focused on possible solutions for multimedia contents security in the public network in order to prevent data modification by non-owners and to ensure safe communication in the distributed network environment. Accordingly, the Orthogonal Forward Wavelet Transform-based Scalable Digital Watermarking technique is proposed in this paper.

High Rate Denial-of-Service Attack Detection System for Cloud Environment Using Flume and Spark

  • Gutierrez, Janitza Punto;Lee, Kilhung
    • Journal of Information Processing Systems
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    • v.17 no.4
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    • pp.675-689
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    • 2021
  • Nowadays, cloud computing is being adopted for more organizations. However, since cloud computing has a virtualized, volatile, scalable and multi-tenancy distributed nature, it is challenging task to perform attack detection in the cloud following conventional processes. This work proposes a solution which aims to collect web server logs by using Flume and filter them through Spark Streaming in order to only consider suspicious data or data related to denial-of-service attacks and reduce the data that will be stored in Hadoop Distributed File System for posterior analysis with the frequent pattern (FP)-Growth algorithm. With the proposed system, we can address some of the difficulties in security for cloud environment, facilitating the data collection, reducing detection time and consequently enabling an almost real-time attack detection.