• Title/Summary/Keyword: Real-time computing

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Design and Implementation of Cloud Computing Monitoring System Based on Android (안드로이드 기반의 클라우드 컴퓨팅 모니터링 시스템 설계 및 구현)

  • Kim, Bong-Hyun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.17 no.7
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    • pp.1627-1632
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    • 2013
  • Cloud computing technology for the company's IT infrastructure, reduce the maintenance burden and the company's IT technology to achieve cost savings through innovation in the high field of economic expectations. In particular, cloud computing monitoring system based on the Android is maturing necessary operational solutions in the IT infrastructure environments. Therefore, in this paper, cloud computing environment in terms of user management and real-time server check the situation in case of abnormalities Android phones are sent through the reality of sulfur and this situation of the server administrator to remotely diagnose and treatment system and to development a viable technology is applied.

Study on Education Content Delivery System in Hybrid P2P based Computing Environment (혼합형 P2P 기반 컴퓨팅환경에서의 교육 컨텐츠 전송 시스템에 대한 연구)

  • Kim, Jin-Il
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • v.9 no.2
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    • pp.658-661
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    • 2005
  • Internet-based client/server architecture of Contents Delivery System suffers from frequent disconnections and security treats caused by dependency of the server or overload. But, We reached the limit to the increase of the server because a contents quality enhance and Internet user explosively increase. Therefore, a P2P based computing methods are used for sloving these issues. In this paper, We implement and design the Education Content Delivery System for cyber education system using idle Computing Power in P2P computing to share computing resources. We implement not only Internet infrastructure but also satellite infrastructure system, and designed to transfer real-time or non real-time contents.

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Adjusting Transmission Power for Real-Time Communications in Wireless Sensor Networks

  • Kim, Ki-Il
    • Journal of information and communication convergence engineering
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    • v.10 no.1
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    • pp.21-26
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    • 2012
  • As the new requirements for wireless sensor networks are emerging, real-time communications is becoming a major research challenge because resource-constrained sensor nodes are not powerful enough to accommodate the complexity of the protocol. In addition, an efficient energy management scheme has naturally been a concern in wireless sensor networks for a long time. However, the existing schemes are limited to meeting one of these two requirements. To address the two factors together, we propose real-time communications with two approaches, a protocol for satisfied conditions and one for unsatisfied. Under the satisfied requirement, existing real-time protocol is employed. On the other hand, for the unsatisfied requirement, the newly developed scheme replaces the existing scheme by adjusting the transmission range of some surplus nodes. By expanding the transmission range, the end-to-end delay is shortened because the number of intermediate nodes decreases. These nodes conserve their energy for real-time communications by avoiding other activities such as sensing, forwarding, and computing. Finally, simulation results are given to demonstrate the feasibility of the proposed scheme in high traffic environments.

An Optimal Sorting Algorithm for Auto IC Test Handler (IC 테스트 핸들러의 최적분류 알고리즘 개발)

  • 김종관;최동훈
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.18 no.10
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    • pp.2606-2615
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    • 1994
  • Sorting time is one of the most important issues for auto IC test handling systems. In actual system, because of too much path, reducing the computing time for finding a sorting path is the key way to enhancing the system performance. The exhaustive path search technique can not be used for real systems. This paper proposes heuristic sorting algorithm to find the minimal sorting time. The suggested algorithm is basically based on the best-first search technique and multi-level search technique. The results are close to the optimal solutions and computing time is greately reduced also. Therefore the proposed algorthm can be effectively used for real-time sorting process in auto IC test handling systems.

Deep Learning-Based Dynamic Scheduling with Multi-Agents Supporting Scalability in Edge Computing Environments (멀티 에이전트 에지 컴퓨팅 환경에서 확장성을 지원하는 딥러닝 기반 동적 스케줄링)

  • JongBeom Lim
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.9
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    • pp.399-406
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    • 2023
  • Cloud computing has been evolved to support edge computing architecture that combines fog management layer with edge servers. The main reason why it is received much attention is low communication latency for real-time IoT applications. At the same time, various cloud task scheduling techniques based on artificial intelligence have been proposed. Artificial intelligence-based cloud task scheduling techniques show better performance in comparison to existing methods, but it has relatively high scheduling time. In this paper, we propose a deep learning-based dynamic scheduling with multi-agents supporting scalability in edge computing environments. The proposed method shows low scheduling time than previous artificial intelligence-based scheduling techniques. To show the effectiveness of the proposed method, we compare the performance between previous and proposed methods in a scalable experimental environment. The results show that our method supports real-time IoT applications with low scheduling time, and shows better performance in terms of the number of completed cloud tasks in a scalable experimental environment.

Parallel Integration for Real-Time Simulation (실시간 시뮬레이션을 위한 병렬적분)

  • Lee, W.S.;Samson, J.
    • Transactions of the Korean Society of Automotive Engineers
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    • v.2 no.1
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    • pp.106-115
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    • 1994
  • A parallel integration approach is proposed for real-time simulation of controlled mechanical systems. The proposed approach, which employs the dual-rate integration method in a parallel computing environment, is developed to deal with stiffness and high frequency characteristics of the controlled mechanical systems effectively. Numerical experiments are performed to demonstrate the effectiveness of the approach in shared memory multiprocessors, Alliant FX/8 and Alliant FX/80.

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Video Transcoding Scheme for N-Screen Service Based on Cloud Computing (클라우드 컴퓨팅에서 N-스크린 서비스를 위한 동영상 트랜스 코딩 기법)

  • Lim, Heon-Yong;Lee, Won-Joo;Jeon, Chang-Ho
    • Journal of the Korea Society of Computer and Information
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    • v.19 no.9
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    • pp.11-19
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    • 2014
  • In this paper, we propose a real-time video transcoding scheme for N-Screen service based on cloud computing. This scheme creates an intro-block and several playback blocks by splitting the original video. And there is the first service request, after transmitting the intro-block, transmits the playback blocks that converting the blocks on real-time. In order to completing trans-coding within playback time of each block, we split and allocate the block to node according to performance of each node. Also, in order to provide real-time video playback service, the previous scheme convert original video into all format and resolution. However we show that the proposed scheme can reduce storage usage by converting original video into format with proper resolution suitable to device and platform of client. Through simulation, we show that it is more effective to real-time video playback for N-screen service than the previous method. We also show that the proposed scheme uses less storage usage than previous method.

An Efficient Deep Learning Based Image Recognition Service System Using AWS Lambda Serverless Computing Technology (AWS Lambda Serverless Computing 기술을 활용한 효율적인 딥러닝 기반 이미지 인식 서비스 시스템)

  • Lee, Hyunchul;Lee, Sungmin;Kim, Kangseok
    • KIPS Transactions on Software and Data Engineering
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    • v.9 no.6
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    • pp.177-186
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    • 2020
  • Recent advances in deep learning technology have improved image recognition performance in the field of computer vision, and serverless computing is emerging as the next generation cloud computing technology for event-based cloud application development and services. Attempts to use deep learning and serverless computing technology to increase the number of real-world image recognition services are increasing. Therefore, this paper describes how to develop an efficient deep learning based image recognition service system using serverless computing technology. The proposed system suggests a method that can serve large neural network model to users at low cost by using AWS Lambda Server based on serverless computing. We also show that we can effectively build a serverless computing system that uses a large neural network model by addressing the shortcomings of AWS Lambda Server, cold start time and capacity limitation. Through experiments, we confirmed that the proposed system, using AWS Lambda Serverless Computing technology, is efficient for servicing large neural network models by solving processing time and capacity limitations as well as cost reduction.

Efficient Implementing of DNA Computing-inspired Pattern Classifier Using GPU (GPU를 이용한 DNA 컴퓨팅 기반 패턴 분류기의 효율적 구현)

  • Choi, Sun-Wook;Lee, Chong-Ho
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.58 no.7
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    • pp.1424-1434
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    • 2009
  • DNA computing-inspired pattern classification based on the hypernetwork model is a novel approach to pattern classification problems. The hypernetwork model has been shown to be a powerful tool for multi-class data analysis. However, the ordinary hypernetwork model has limitations, such as operating sequentially only. In this paper, we propose a efficient implementing method of DNA computing-inspired pattern classifier using GPU. We show simulation results of multi-class pattern classification from hand-written digit data, DNA microarray data and 8 category scene data for performance evaluation. and we also compare of operation time of the proposed DNA computing-inspired pattern classifier on each operating environments such as CPU and GPU. Experiment results show competitive diagnosis results over other conventional machine learning algorithms. We could confirm the proposed DNA computing-inspired pattern classifier, designed on GPU using CUDA platform, which is suitable for multi-class data classification. And its operating speed is fast enough to comply point-of-care diagnostic purpose and real-time scene categorization and hand-written digit data classification.

The Real-Time Constructive Simulation With the RM scheduling and Lock-free Shared Objects (RM 스케쥴링과 Lock-Free 공유개체에 의한 실시간 시뮬레이션)

  • 박현규
    • Proceedings of the IEEK Conference
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    • 1998.10a
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    • pp.519-522
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    • 1998
  • The Constructive Battle simulation Model is very important to the recent military training for the substitution of the field training. However, real battlefield systems operate under rea-time conditions, they are inherently distributed, concurrent and dynamic. In order to reflect these properties by the computer-based simulation systems which represent real world processes, we have been developing constructive simulation model for several years. The constructive simulation system is one of the famous real-time system software, nd the one common feature of all real-time systems is defined as the correctness of the system depend not only on the logical result of computation, but also on the time at which the results are produced. Conventionally, scheduling and resource allocation activities which have timing constraints are major problem of real-time computing systems. To overcome these constraints, we elaborated on these issues and developed the simulation system on commercially available hardware and operating system with lock-free resource allocation scheme and rae monotonic scheduling.

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