• Title/Summary/Keyword: 분산알고리즘

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Design and Evaluation of a VOD Buffer Management Algorithm Using Fixed Prefetch and Drop Strategics (고정 선반입과 Drop 정책을 이용한 VOD 버퍼 관리 알고리즘 설계 및 평가)

  • 박규석;문병철
    • Journal of Korea Multimedia Society
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    • v.3 no.2
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    • pp.101-111
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    • 2000
  • Resource managing is very difficult because the multimedia data compressed by a VBR shows a bit rate change within high range, Therefore, the VOD server should use the prefetch method in order to improve system utilization, such as prefetching data in the overload period by a meta table that is the reference pattern of MPEG data which is analyzed off line. This prefetch method will not result in a failure to display at overload, however, this method can not keep a minimum loading time and low costs, because the prefetched section is being maximizes. In this paper, we suggest another method that the system utilization can be improved using the fixed prefetched section to keep loading time and costs under a constant range at overload. But this technique will result in a failure to display, due to fixed prefetched section. Rut, in this paper we suggest a drop module that drops only the B frame in the GOP, consistently distributes a lower drop in media quality for the user.

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A Nonblocking $Multi-Log_2N$ Multiconnection Network : Theoretical Characterization and Design Example for a Photonic Switching System (넌블럭킹 $Multi-Log_2N$다중 접속망 : 이론적 특성 및 광 교환시스템을 위한 설계예)

  • Yeong Hwan TSCHA;Kyoon Ha LEE
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.16 no.7
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    • pp.680-695
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    • 1991
  • In this paper, the conditions on the number of required copies of a self-routing network with and without extra stages in back-to-back manner are presented respectively for a nonblocking $Multi-Log_2N$ multiconnection network. Actually the obained results hold regardless of connection patterns, i.e., whether a network deploys on-to-one connections or multiconnections. Thus open problems on the nonblocking condition for a multi $Multi-Log_2N$ multiconnection network are solved. Interestingly some of the given formulas comprise the Benes network and the Canto network as a special case repectively. A novel switching system architecture deploying a distributed calls-distribution algorithm is provided to design a nonblocking $Multi-Log_2N$ photonic switching network using a directional coupler. And a directional couplex based call holding demultiplexer is introduced to hold a call until blocking disappears in a switching network and let it enter to a network, provided that the number of switching networks is less than that of required switching networks for a nonblocking $Multi-Log_2N$ network.

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Noise Band Extraction of Hyperion Image using Quadtree Structure and Fractal Characteristic (Quadtree 구조 및 프랙탈 특성을 이용한 Hyperion 영상의 노이즈 밴드 추출)

  • Chang, An-Jin;Kim, Yong-Il
    • Korean Journal of Remote Sensing
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    • v.26 no.5
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    • pp.489-495
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    • 2010
  • Hyperspectral imaging obtains information with a wider wavelength range a large number of bands. However, a high correlation between each band, computation cost, and noise causes inaccurate results in cases of no pre-processing. The noises of band extraction and elimination positively necessary in hyperspectral imaging. Since the previous studies have used a characteristic the whole image, a local characteristic of the image is considered for the noise band extraction. In this study, the Quadtree, which is a data structure algorithm. and the fractal dimension are adopted for noise band extraction in Hyperion images. The fractal dimensions of the segments divided by the Quadtree structure are calculated, and variation is used. We focused on the extraction of random noise bands in Hyperion images and compared them with the reference data made by visual decisions. The proposed algorithm extracts the most bands, including random noises. It is possible to eliminate more than 30 noise bands, regardless of images.

Big Data Processing and Performance Improvement for Ship Trajectory using MapReduce Technique

  • Kim, Kwang-Il;Kim, Joo-Sung
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.10
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    • pp.65-70
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    • 2019
  • In recently, ship trajectory data consisting of ship position, speed, course, and so on can be obtained from the Automatic Identification System device with which all ships should be equipped. These data are gathered more than 2GB every day at a crowed sea port and used for analysis of ship traffic statistic and patterns. In this study, we propose a method to process ship trajectory data efficiently with distributed computing resources using MapReduce algorithm. In data preprocessing phase, ship dynamic and static data are integrated into target dataset and filtered out ship trajectory that is not of interest. In mapping phase, we convert ship's position to Geohash code, and assign Geohash and ship MMSI to key and value. In reducing phase, key-value pairs are sorted according to the same key value and counted the ship traffic number in a grid cell. To evaluate the proposed method, we implemented it and compared it with IALA waterway risk assessment program(IWRAP) in their performance. The data processing performance improve 1 to 4 times that of the existing ship trajectory analysis program.

Calculation of Non-revenue Water Ratio through the Artificial Neural Network of Water Distribution System (인공신경망을 이용한 상수관망 내 무수율 산정)

  • Jang, Dong Woo;Choi, Gye Woon;Park, Hyo Seon;Jo, Hyoung Geun
    • Proceedings of the Korea Water Resources Association Conference
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    • 2017.05a
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    • pp.120-120
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    • 2017
  • 인천지역의 상수도공급은 팔당댐을 취수원으로 하여 도수, 송수관을 거쳐 인천지역 내 정수장을 통하여 각 급수지역까지 일원화된 관로시스템으로 공급되고 있다. 관망에서의 적절한 수압관리, 노후관로 교체사업 등은 급수관망 내 관로 사고위험을 줄일 수 있고, 누수량을 저감하여 무수율의 감소로 이어질 수 있다. 상수관망 내 누수에 영향을 주는 물리적, 운영적 요소를 파악하고, 이를 이용하여 누수해결을 위한 방법론을 제시하는 것은 매우 중요하다. 본 연구에서는 인천시 배수관망 데이터를 활용하여 통계분석 및 인공신경망을 통하여 무수율에 영향을 미치는 인자를 선별하고, 무수율과의 연관성을 분석하고자 하였다. 이를 위해 대상지역에 대한 시설현황 및 운영자료를 취득하고, 무수율 분석에 활용하였다. 인천시의 소블럭을 대상으로 관로노후도, 배수관연장, 평균관경, 급수전당 공급량, 누수발생 횟수, 용도지역, 관망구성 형태 등을 고려하여 무수율과의 관계분석을 위한 통계분석을 수행하였다. 특히 급수에 필요한 최소에너지와 관망에서 공급되는 에너지를 비교하기 위하여 관망해석 프로그램인 EPANET을 이용하여 관망내 절점에서의 수압과 수요량이 적용된 최소공급에너지를 활용하였고, 이를 통하여 블록 내 과잉공급에너지와 무수율의 영향성을 비교하였다. 최종적으로 산출된 주요인자에 대한 주성분분석, 분산분석, 다중회귀분석 등의 통계분석과 인공신경망에 의해 학습된 알고리즘을 통하여 산정된 무수율을 실측 무수율과 비교, 분석하였다. 인공신경망에 의해 산정된 무수율과 실측 무수율의 정확도를 평가하기 위하여 MAE, MSE, PBIAS 등의 정확도 평가와 산점도 분석을 수행하고, 상관계수를 도출하여 가장 정확한 방법을 결정하였다. 분석 결과 통계분석에 의한 다중회귀식으로 산출된 무수율 보다 인공신경망에 의한 무수율이 실측값에 더욱 근접한 것으로 나타났으며 이용된 뉴런의 수의 따라 산출결과가 상이하기 때문에 최적 뉴런의 수를 산정해야 할 필요가 있음을 확인하였다. 특히 사용된 상수관망 주요인자 중 주성분분석을 통하여 선정된 각 성분을 인공신경망에 적용시 더욱 정확한 무수율 예측이 가능한 것으로 나타났다.

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A Model for Self-Authentication Based on Decentralized Identifier (탈중앙화 신원증명에 기반한 본인 인증 모델)

  • Kim, Ho-Yoon;Han, Kun-Hee;Shin, Seung-Soo
    • Journal of Convergence for Information Technology
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    • v.11 no.11
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    • pp.66-74
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    • 2021
  • With the development of the Internet, user authentication technology that proves me online is improving. Existing ID methods pose a threat of personal information leakage if the service provider manages personal information and security is weak, and the information subject is to the service provider. In this study, as online identification technology develops, we propose a DID-based self-authentication model to prevent the threat of leakage of personal information from a centralized format and strengthen sovereignty. The proposed model allows users to directly manage personal information and strengthen their sovereignty over information topics through VC issued by the issuing agency. As a research method, a self-authentication model that guarantees security and integrity is presented using a decentralized identifier method based on distributed ledger technology, and the security of the attack method is analyzed. Because it authenticates through DID Auth using public key encryption algorithms, it is safe from sniffing, man in the middle attack, and the proposed model can replace real identity card.

Deep Learning Model for Incomplete Data (불완전한 데이터를 위한 딥러닝 모델)

  • Lee, Jong Chan
    • Journal of the Korea Convergence Society
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    • v.10 no.2
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    • pp.1-6
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    • 2019
  • The proposed model is developed to minimize the loss of information in incomplete data including missing data. The first step is to transform the learning data to compensate for the loss information using the data extension technique. In this conversion process, the attribute values of the data are filled with binary or probability values in one-hot encoding. Next, this conversion data is input to the deep learning model, where the number of entries is not constant depending on the cardinality of each attribute. Then, the entry values of each attribute are assigned to the respective input nodes, and learning proceeds. This is different from existing learning models, and has an unusual structure in which arbitrary attribute values are distributedly input to multiple nodes in the input layer. In order to evaluate the learning performance of the proposed model, various experiments are performed on the missing data and it shows that it is superior in terms of performance. The proposed model will be useful as an algorithm to minimize the loss in the ubiquitous environment.

Heterogeneous Network Gateway Architecture and Simulation for Tactical MANET (전술 에드혹 환경에서 이종망 게이트웨이 구조 및 시뮬레이션 연구)

  • Roh, Bong Soo;Han, Myoung Hun;Kwon, Dae Hoon;Ham, Jae Hyun;Yun, Seon Hui;Ha, Jae Kyoung;Kim, Ki Il
    • Journal of the Korea Society for Simulation
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    • v.28 no.2
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    • pp.97-105
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    • 2019
  • The tactical mobile ad-hoc network(MANET) consists of distributed autonomous networks between individual ground nodes, which is effective in terms of network survivability and flexibility. However, due to constraints such as limited power, terrain, and mobility, frequent link disconnection and shadow area may occur in communication. On the other hand, the satellite network has the advantage of providing a wide-area wireless link overcoming terrain and mobility, but has limited bandwidth and high-latency characteristic. In the future battlefield, an integrated network architecture for interworking multi-layer networks through a heterogeneous network gateway (HNG) is required to overcome the limitations of the existing individual networks and increase reliability and efficiency of communication. In this paper, we propose a new HNG architecture and detailed algorithm that integrates satellite network and the tactical MANET and enables reliable data transfer based on flow characteristics of traffic. The simulations validated the proposed architecture using Riverbed Modeler, a network-level simulator.

Performance Improvement of Distributed Consensus Algorithms for Blockchain through Suggestion and Analysis of Assessment Items (평가항목 제안 및 분석을 통한 블록체인 분산합의 알고리즘 성능 개선)

  • Kim, Do Gyun;Choi, Jin Young;Kim, Kiyoung;Oh, Jintae
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.41 no.4
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    • pp.179-188
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    • 2018
  • Recently, blockchain technology has been recognized as one of the most important issues for the 4th Industrial Revolution which can be represented by Artificial Intelligence and Internet of Things. Cryptocurrency, named Bitcoin, was the first successful implementation of blockchain, and it triggered the emergence of various cryptocurrencies. In addition, blockchain technology has been applied to various applications such as finance, healthcare, manufacturing, logistics as well as public services. Distributed consensus algorithm is an essential component in blockchain, and it enables all nodes belonging to blockchain network to make an agreement, which means all nodes have the same information. For example, Bitcoin uses a consensus algorithm called Proof-of-Work (PoW) that gives possession of block generation based on the computational volume committed by nodes. However, energy consumption for block generation in PoW has drastically increased due to the growth of computational performance to prove the possession of block. Although many other distributed consensus algorithms including Proof-of-Stake are suggested, they have their own advantages and limitations, and new research works should be proposed to overcome these limitations. For doing this, above all things, we need to establish an evaluation method existing distributed consensus algorithms. Based on this motivation, in this work, we suggest and analyze assessment items by classifying them as efficiency and safety perspectives for investigating existing distributed consensus algorithms. Furthermore, we suggest new assessment criteria and their implementation methods, which can be used for a baseline for improving performance of existing distributed consensus algorithms and designing new consensus algorithm in future.

Mobile-based Big Data Processing and Monitoring Technology in IoT Environment (IoT 환경에서 모바일 기반 빅데이터 처리 및 모니터링 기술)

  • Lee, Seung-Hae;Kim, Ju-Ho;Shin, Dong-Youn;Shin, Dong-Jin;Park, Jeong-Min;Kim, Jeong-Joon
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.18 no.6
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    • pp.1-9
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    • 2018
  • In the fourth industrial revolution, which has become an issue now, we have been able to receive instant analysis results faster than the existing slow speed through various Big Data technologies, and to conduct real-time monitoring on mobile and web. First, various irregular sensor Data is generated using IoT device, Raspberry Pi. Sensor Data is collected in real time, and the collected data is distributed and stored using several nodes. Then, the stored Sensor Data is processed and refined. Visualize and output the analysis result after analysis. By using these methods, we can train the human resources required for Big Data and mobile related fields using IoT, and process data efficiently and quickly. We also provide information that can confirm the reliability of research results through real time monitoring.