• Title/Summary/Keyword: network based replication model

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FPGA-based Hardware Implementation of Cryptography Algorithm ARIA (암호화 알고리즘 ARIA의 FPGA기반 하드웨어 구현)

  • Kim Young-Soo;Cho Sun-Gu
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.7
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    • pp.1229-1236
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    • 2006
  • Group oriented multicast service is a prerequisite for the current application system for remote lecture and customer service. IP multicast is used to be generally accepted as an internet standard. IP multicast which is designed to support network based replication model can efficiently use host and network resource, however it has some weak points that it has to support IP multicast in the internet by adding multicast-capable internet infrastructure such as router and is vulnerable to security by using public IP address for group identifier. Therefore we propose the trigger based application level multicast model that can enhance both scalability and security by separating the functions, which send and receive message to solve these problems. Our suggested model is expected to ensure the promotion of quality of service and reliability.

File Replication and Workload Allocation for a Locally Distributed Database

  • Gil sang Jang
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.24 no.64
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    • pp.1-20
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    • 2001
  • In distributed databases, file replication and workload allocation are important design issues. This paper solves these two issues simultaneously, The primary objective is to minimize the system response time that consists of local processing and communication overhead on a local area network. Workload (query transactions) is assigned among any sites in proportion to the remaining file request service rate of the each server The problem is presented in the form of a nonlinear integer programming model. The problem is proved to be NP-complete and thus an efficient heuristic is developed by employing its special structure. To illustrate its effectiveness, it is shown that the proposed heuristic is based on the heuristic of a non-redundant allocation that was provided to be effective. The model and heuristics are likely to provide more effective distributed database designs.

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Torus Network Based Distributed Storage System for Massive Multimedia Contents (토러스 연결망 기반의 대용량 멀티미디어용 분산 스토리지 시스템)

  • Kim, Cheiyol;Kim, Dongoh;Kim, Hongyeon;Kim, Youngkyun;Seo, Daewha
    • Journal of Korea Multimedia Society
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    • v.19 no.8
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    • pp.1487-1497
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    • 2016
  • Explosively growing service of digital multimedia data increases the need for highly scalable low-cost storage. This paper proposes the new storage architecture based on torus network which does not need network switch and erasure coding for efficient storage usage for high scalability and efficient disk utilization. The proposed model has to compensate for the disadvantage of long network latency and network processing overhead of torus network. The proposed storage model was compared to two most popular distributed file system, GlusterFS and Ceph distributed file systems through a prototype implementation. The performance of prototype system shows outstanding results than erasure coding policy of two file systems and mostly even better results than replication policy of them.

An ORB Extension for support of Fault-Tolerant CORBA (고장감내 CORBA를 지원하기 위한 객체중개자의 확장)

  • Shin, Bum-Joo;Son, Duk-Joo;Kim, Myung-Joon
    • Journal of KIISE:Computing Practices and Letters
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    • v.7 no.2
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    • pp.121-131
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    • 2001
  • The failure of network and/or node on which server object is executed is a single point of system failure in the CORBA application. One of the possible ways to overcome such problem is to replicate server objects to several independent nodes. The replicated objects executing same tasks are called object group. In order to provide fault tolerance of server object, this paper proposes and implements new CORBA model that supports the object group based on active replication. The proposed model not only provides interoperability with existing CORBA application but also minimizes additional application interface required to support object group because it uses nop to exchange messages between client and server. And this paper extends IDL structure. Depending to application logic, it makes possible to prevent performance degradation caused by consistency maintenance. At present, this paper supports only active replication. But it can be easily extended to provide warm ancVor cold passive replication without modification of architecture required for active replication.

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Deep Learning based Raw Audio Signal Bandwidth Extension System (딥러닝 기반 음향 신호 대역 확장 시스템)

  • Kim, Yun-Su;Seok, Jong-Won
    • Journal of IKEEE
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    • v.24 no.4
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    • pp.1122-1128
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    • 2020
  • Bandwidth Extension refers to restoring and expanding a narrow band signal(NB) that is damaged or damaged in the encoding and decoding process due to the lack of channel capacity or the characteristics of the codec installed in the mobile communication device. It means converting to a wideband signal(WB). Bandwidth extension research mainly focuses on voice signals and converts high bands into frequency domains, such as SBR (Spectral Band Replication) and IGF (Intelligent Gap Filling), and restores disappeared or damaged high bands based on complex feature extraction processes. In this paper, we propose a model that outputs an bandwidth extended signal based on an autoencoder among deep learning models, using the residual connection of one-dimensional convolutional neural networks (CNN), the bandwidth is extended by inputting a time domain signal of a certain length without complicated pre-processing. In addition, it was confirmed that the damaged high band can be restored even by training on a dataset containing various types of sound sources including music that is not limited to the speech.

A Deep Learning-based Automatic Modulation Classification Method on SDR Platforms (SDR 플랫폼을 위한 딥러닝 기반의 무선 자동 변조 분류 기술 연구)

  • Jung-Ik, Jang;Jaehyuk, Choi;Young-Il, Yoon
    • Journal of IKEEE
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    • v.26 no.4
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    • pp.568-576
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    • 2022
  • Automatic modulation classification(AMC) is a core technique in Software Defined Radio(SDR) platform that enables smart and flexible spectrum sensing and access in a wide frequency band. In this study, we propose a simple yet accurate deep learning-based method that allows AMC for variable-size radio signals. To this end, we design a classification architecture consisting of two Convolutional Neural Network(CNN)-based models, namely main and small models, which were trained on radio signal datasets with two different signal sizes, respectively. Then, for a received signal input with an arbitrary length, modulation classification is performed by augmenting the input samples using a self-replicating padding technique to fit the input layer size of our model. Experiments using the RadioML 2018.01A dataset demonstrated that the proposed method provides higher accuracy than the existing methods in all signal-to-noise ratio(SNR) domains with less computation overhead.

A tool development for forced striation and delineation of river network from digital elevation model based on ModelBuilder (모델빌더 기반 하천망의 DEM 각인 및 추출 툴 개발)

  • Choi, Seungsoo;Kim, Dongsu;You, Hojun
    • Journal of Korea Water Resources Association
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    • v.52 no.8
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    • pp.515-529
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    • 2019
  • Geospatial information for river network and watershed boundary have played a fundamental roles in terms of river management, planning and design, hydrological and hydraulic analysis. Irrespective of their importance, the lack of punctual update and improper maintenance in currently available river-related geospatial information systems has revealed inconsistency issues between individual systems and spatial inaccuracy with regard to reflecting dynamically transferring riverine geography. Given that digital elevation models (DEMs) of high spatial resolution enabling to reproduce precise river network are only available adjacent to national rivers, DEMs with poor spatial resolution lead to generate unreliable river network information and thereby reduce their extensible applicabilities. This study first of all evaluated published spatial information available in Korea with respect to their spatial accuracy and consistency, and also provides a methodology and tool to modify existing low resolution of DEMs by means of striation of conventional or digitized river network to replicate input river network in various degree of further delineation. The tool named FSND was designed to be operated in ArcGIS ModelBuilder which ensures to automatically simulate river network striation to DEMs and delineation with different flow accumulation threshold. The FNSD was successfully validated in Seom River basin to identify its replication of given river network manually digitized based on recent aerial photograph in conjunction with a DEM with 30 meter spatial resolution. With the derived accuracy of reproducibility, substantiation of a various order of river network and watershed boundary from the striated DEM posed tangible possibility for highly extending DEMs with low resolution to be capable of producing reliable riverine spatial information subsequently.

An Enhanced University Registration Model Using Distributed Database Schema

  • Maabreh, Khaled Saleh
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.7
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    • pp.3533-3549
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    • 2019
  • A big database utilizes the establishing network technology, and it became an emerging trend in the computing field. Therefore, there is a necessity for an optimal and effective data distribution approach to deal with this trend. This research presents the practical perspective of designing and implementing distributed database features. The proposed system has been establishing the satisfying, reliable, scalable, and standardized use of information. Furthermore, the proposed scheme reduces the vast and recurring efforts for designing an individual system for each university, as well as it is effectively participating in solving the course equivalence problem. The empirical finding in this study shows the superiority of the distributed system performance based on the average response time and the average waiting time than the centralized system. The system throughput also overcomes the centralized system because of data distribution and replication. Therefore, the analyzed data shows that the centralized system thrashes when the workload exceeds 60%, while the distributed system becomes thrashes after 81% workload.

Construction of an Agent-based Fault-Tolerant Object Group Model (에이전트 기반의 고장허용 객체그룹 모델 구축)

  • Kang, Myung-Seok;Kim, Hag-Bae
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.1B
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    • pp.74-85
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    • 2009
  • We propose an Agent-based Fault Tolerant Object Group model based on the agent technology and FTOG model with replication mechanism for effective object management and fault recovery. We define the five kind of agents - internal processing agent, registration agent, state handling agent, user interface agent, and service agent - that extend the functions of the FTOG model. The roles of the agents in the proposed model are to reduce the remote interactions between distributed objects and provide more effective service execution. To verify the effectiveness of the proposed model, we implemented the Intelligent Home Network Simulator (IHNS) which virtually provides general home networking services. Through the simulations, it is validated that the proposed model decreases the interactions of the object components and supports the effective fault recovery, while providing more stable and reliable services.

Calibration of a Network Link Travel Cost Function with the Harmony Search Algorithm (화음탐색법을 이용한 교통망 링크 통행비용함수 정산기법 개발)

  • Kim, Hyun Myung;Hwang, Yong Hwan;Yang, In Chul
    • Journal of Korean Society of Transportation
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    • v.30 no.5
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    • pp.71-82
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    • 2012
  • Some previous studies adopted a method statistically based on the observed traffic volumes and travel times to estimate the parameters. Others tried to find an optimal set of parameters to minimize the gap between the observed and estimated traffic volumes using, for instance, a combined optimization model with a traffic assignment model. The latter is frequently used in a large-scale network that has a capability to find a set of optimal parameter values, but its appropriateness has never been demonstrated. Thus, we developed a methodology to estimate a set of parameter values of BPR(Bureau of Public Road) function using Harmony Search (HS) method. HS was developed in early 2000, and is a global search method proven to be superior to other global search methods (e.g. Genetic Algorithm or Tabu search). However, it has rarely been adopted in transportation research arena yet. The HS based transportation network calibration algorithm developed in this study is tested using a grid network, and its outcomes are compared to those from incremental method (Incre) and Golden Section (GS) method. It is found that the HS algorithm outperforms Incre and GS for copying the given observed link traffic counts, and it is also pointed out that the popular optimal network calibration techniques based on an objective function of traffic volume replication are lacking the capability to find appropriate free flow travel speed and ${\alpha}$ value.