• Title/Summary/Keyword: Online algorithm

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Interference-Prediction based Online Routing Aglorithm for MPLS Traffic Engineering (MPLS 트래픽 엔지니어링을 위한 간섭 예측 기반의 online 라우팅 알고리듬)

  • Lee, Dong-Hoon;Lee, Sung-Chang;Ye, Byung-Ho
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.42 no.12
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    • pp.9-16
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    • 2005
  • A new online routing algerian is proposed in this paper, which use the interference-prediction to solve the network congestion originated from extension of Internet scope and increasing amount of traffic. The end-to-end QoS has to be guaranteed in order to satisfy service level agreements (SLAs) in the integrated networks of next generation. For this purpose, bandwidth is allocated dynamically and effectively, moreover the path selection algorithm is required while considering the network performance. The proposed algorithm predicts the level of how much the amount of current demand interferes the future potential traffic, and then minimizes it. The proposed algorithm considers the bandwidth on demand, link state, and the information about ingress-egress pairs to maximize the network performance and to prevent the waste of the limited resources. In addition, the interference-prediction supports the bandwidth guarantee in dynamic network to accept more requests. In the result, the proposed algorithm performs the effective admission control and QoS routing. In this paper, we analyze the required conditions of routing algorithms, the aspect of recent research, and the representative algorithms to propose the optimized path selection algorithm adequate to Internet franc engineering. Based on these results, we analyze the problems of existing algorithms and propose our algorithm. The simulation shows improved performance by comparing with other algorithms and analyzing them.

Development of Coordinated Scheduling Algorithm and End-to-end Delay Analysis for CAN-based Distributed Control Systems (CAN기반 분산 제어시스템의 종단 간 지연시간 분석과 협조 스케줄링 알고리즘 개발)

  • 이희배;김홍열;김대원
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.53 no.7
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    • pp.501-508
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    • 2004
  • In this paper, a coordinated scheduling algorithm is proposed to reduce end-to-end delay in distributed control of systems. For the algorithm, the analysis of practical end-to-end delay in the worst case is performed priory with considering implementation of the systems. The end-to-end delay is composed of the delay caused by multi-task scheduling of operating systems, the delay caused by network communications, and the delay caused by asynchronous timing between operating systems and network communications. Through some simulation tests based on CAN(Controller Area Network), the proposed worst case end-to-end delay analysis is validated. Through the simulation tests, it is also shown that a real-time distributed control system designed to existing worst case delay cannot guarantee end-to-end time constraints. With the analysis, a coordinated scheduling algorithm is proposed here. The coordinated scheduling algorithm is focused on the reduction of the delay caused by asynchronous timing between operating systems and network communications. Online deadline assignment strategy is proposed for the scheduling. The performance enhancement of the distributed control systems by the scheduling algorithm is shown through simulation tests.

Online Trajectory Planning for a PUMA Robot

  • Kang, Chul-Goo
    • International Journal of Precision Engineering and Manufacturing
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    • v.8 no.4
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    • pp.16-21
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    • 2007
  • Robotic applications, such as automatic fish cutting, require online trajectory planning because the material properties of the object, such as the bone or flesh conditions, are not known in advance. Different trajectories are required when the material properties vary. An effective online trajectory-planning algorithm is proposed using quaternions to determine the position and orientation of a robot manipulator with a spherical wrist. Quaternions are free of representation singularities and permit computationally efficient orientation interpolations. To prevent singular configurations, the exact locations of the kinematic singularities of the PUMA 560 manipulator are derived and geometrically illustrated when a forearm offset exists and the third link length is not zero.

A Study on the Individual Authentication Using Facial Information For Online Lecture (가상강의에 적용을 위한 얼굴영상정보를 이용한 개인 인증 방법에 관한 연구)

  • 김동현;권중장
    • Proceedings of the IEEK Conference
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    • 2000.11c
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    • pp.117-120
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    • 2000
  • In this paper, we suggest an authentication system for online lecture using facial information and a face recognition algorithm base on relation of face. First, a facial area on complex background is detected using color information. Second, features are extracted with edge profile. Third, compare it with the value of original facial image in database. By experiments, we know that the proposed system is an useful method for online lecture authentication system.

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A Study on the Classic Theory-Driven Predictors of Adolescent Online and Offline Delinquency using the Random Forest Machine Learning Algorithm (랜덤포레스트 머신러닝 기법을 활용한 전통적 비행이론기반 청소년 온·오프라인 비행 예측요인 연구)

  • TaekHo, Lee;SeonYeong, Kim;YoonSun, Han
    • Korean Journal of Culture and Social Issue
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    • v.28 no.4
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    • pp.661-690
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    • 2022
  • Adolescent delinquency is a substantial social problem that occurs in both offline and online domains. The current study utilized random forest algorithms to identify predictors of adolescents' online and offline delinquency. Further, we explored the applicability of classic delinquency theories (social learning, strain, social control, routine activities, and labeling theory). We used the first-grade and fourth-grade elementary school panels as well as the first-grade middle school panel (N=4,137) among the sixth wave of the nationally-representative Korean Children and Youth Panel Survey 2010 for analysis. Random forest algorithms were used instead of the conventional regression analysis to improve the predictive performance of the model and possibly consider many predictors in the model. Random forest algorithm results showed that classic delinquency theories designed to explain offline delinquency were also applicable to online delinquency. Specifically, salient predictors of online delinquency were closely related to individual factors(routine activities and labeling theory). Social factors(social control and social learning theory) were particularly important for understanding offline delinquency. General strain theory was the commonly important theoretical framework that predicted both offline and online delinquency. Findings may provide evidence for more tailored prevention and intervention strategies against offline and online adolescent delinquency.

Cooperative Detection of Moving Source Signals in Sensor Networks (센서 네트워크 환경에서 움직이는 소스 신호의 협업 검출 기법)

  • Nguyen, Minh N.H.;Chuan, Pham;Hong, Choong Seon
    • Journal of KIISE
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    • v.44 no.7
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    • pp.726-732
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    • 2017
  • In practical distributed sensing and prediction applications over wireless sensor networks (WSN), environmental sensing activities are highly dynamic because of noisy sensory information from moving source signals. The recent distributed online convex optimization frameworks have been developed as promising approaches for solving approximately stochastic learning problems over network of sensors in a distributed manner. Negligence of mobility consequence in the original distributed saddle point algorithm (DSPA) could strongly affect the convergence rate and stability of learning results. In this paper, we propose an integrated sliding windows mechanism in order to stabilize predictions and achieve better convergence rates in cooperative detection of a moving source signal scenario.

Online Signature Verification using Extreme Points and Writer-dependent Features (변곡점과 필자고유특징을 이용한 온라인 서명 인증)

  • Son, Ki-Hyoung;Park, Jae-Hyun;Cha, Eui-Young
    • Journal of Korea Multimedia Society
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    • v.10 no.9
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    • pp.1220-1228
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    • 2007
  • This paper presents a new system for online signature verification, approaching for finding gaps between a point-to-point matching and a segment-to-segment matching. Each matching algorithm has been separately used in previous studies. Various features with respect to each matching algorithm have been extracted for solving two-class classification problem. We combined advantages of the two algorithms to implement an efficient system for online signature verification. In the proposed method, extreme feints are used to extract writer-dependent features. In addition, using the writer-dependent features proves to be more adaptive than using writer-independent features in terms of efficiency of classification and verification in this paper.

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Online blind source separation and dereverberation of speech based on a joint diagonalizability constraint (공동 행렬대각화 조건 기반 온라인 음원 신호 분리 및 잔향제거)

  • Yu, Ho-Gun;Kim, Do-Hui;Song, Min-Hwan;Park, Hyung-Min
    • The Journal of the Acoustical Society of Korea
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    • v.40 no.5
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    • pp.503-514
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    • 2021
  • Reverberation in speech signals tends to significantly degrade the performance of the Blind Source Separation (BSS) system. Especially in online systems, the performance degradation becomes severe. Methods based on joint diagonalizability constraints have been recently developed to tackle the problem. To improve the quality of separated speech, in this paper, we add the proposed de-reverberation method to the online BSS algorithm based on the constraints in reverberant environments. Through experiments on the WSJCAM0 corpus, the proposed method was compared with the existing online BSS algorithm. The performance evaluation by the Signal-to-Distortion Ratio and the Perceptual Evaluation of Speech Quality demonstrated that SDR improved from 1.23 dB to 3.76 dB and PESQ improved from 1.15 to 2.12 on average.

High-revenue Online Provisioning for Virtual Clusters in Multi-tenant Cloud Data Center Network

  • Lu, Shuaibing;Fang, Zhiyi;Wu, Jie
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.3
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    • pp.1164-1183
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    • 2019
  • The rapid development of cloud computing and high requirements of operators requires strong support from the underlying Data Center Networks. Therefore, the effectiveness of using resources in the data center networks becomes a point of concern for operators and material for research. In this paper, we discuss the online virtual-cluster provision problem for multiple tenants with an aim to decide when and where the virtual cluster should be placed in a data center network. Our objective is maximizing the total revenue for the data center networks under the constraints. In order to solve this problem, this paper divides it into two parts: online multi-tenancy scheduling and virtual cluster placement. The first part aims to determine the scheduling orders for the multiple tenants, and the second part aims to determine the locations of virtual machines. We first approach the problem by using the variational inequality model and discuss the existence of the optimal solution. After that, we prove that provisioning virtual clusters for a multi-tenant data center network that maximizes revenue is NP-hard. Due to the complexity of this problem, an efficient heuristic algorithm OMS (Online Multi-tenancy Scheduling) is proposed to solve the online multi-tenancy scheduling problem. We further explore the virtual cluster placement problem based on the OMS and propose a novel algorithm during the virtual machine placement. We evaluate our algorithms through a series of simulations, and the simulations results demonstrate that OMS can significantly increase the efficiency and total revenue for the data centers.

Offline Deduplication for Solid State Disk Using a Lightweight Hash Algorithm

  • Park, Eunsoo;Shin, Dongkun
    • JSTS:Journal of Semiconductor Technology and Science
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    • v.15 no.5
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    • pp.539-545
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    • 2015
  • Deduplication technique can expand the lifespan and capacity of flash memory-based storage devices by eliminating duplicated write operations. The deduplication techniques can be classified into two approaches, i.e., online and offline approaches. We propose an offline deduplication technique that uses a lightweight hash algorithm, whereas the previous offline technique uses a high-cost hash algorithm. Therefore, the memory space for caching hash values can be reduced, and more pages can be examined for deduplication during short idle intervals. As a result, it can provide shorter write latencies compared to the online approach, and can show low garbage collection costs compared to the previous offline deduplication technique.