• 사물인터넷융복합논문지
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• 제1권1호
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• pp.1-4
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• 2015

본 논문은 TCP 혼잡제어 메커니즘의 슬로우-스타트 단계에서 웹 객체의 평균전송 시간을 추정하기 위한 수학적 모델을 제안한다. 평균 지연은 네트워크의 종단 사용자가 필요로 하는 중요한 서비스 품질이다. 제안하는 모델의 적용대상은 작은 윈도우 크기로 인해 패킷손실이 슬로우-스타트 구간에서만 발생하는 멀티-홉 무선 네트워크와 대역폭이 작은 사물 인터넷을 대상으로 한다. 모델은 초기 윈도우 크기와 패킷 손실률을 고려하여 지연시간을 구한다. 제안한 모델은 주어진 패킷손실에 대해 라운드 트립 타임과 초기 윈도우 크기에 따라 주로 영향을 받게 되며, 종단 사용자가 사물 인터넷 응용 서비스에 요구하는 응답시간을 추정하는 데 적용될 수 있다.

• 전자통신동향분석
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• 제13권3호통권51호
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• pp.61-70
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• 1998

The obvious way to make a computer system more powerful is to make the processor as fast as possible. Furthermore, adopting a large number of such fast processors would be the next step. This multiprocessor system could be useful only if it distributes workload uniformly and if its processors are fully utilized. To achieve a higher processor utilization, memory access latency must be reduced as much as possible and even more the remaining latency must be hidden. The actual latency can be reduced by using fast logic and the effective latency can be reduced by using cache. This article discusses what the memory latency problem is, how serious it is by presenting analytical and simulation results, and existing techniques for coping with it; such as write-buffer, relaxed consistency model, multi-threading, data locality optimization, data forwarding, and data prefetching.

• 대한임베디드공학회논문지
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• 제14권5호
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• pp.227-237
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• 2019

Ultra-low latency control is one of the characteristics of 5G cellular network services, which means that the control loop is handled in milliseconds. To achieve this, it is necessary to identify time delay factors that occur in all components related to CPS control loop, including new 5G cellular network elements such as MEC, and to optimize CPS control loop in real time. In this paper, a novel CPS architecture for ultra-low latency control of CPS is designed. We first define the ultra-low latency characteristics of CPS and the CPS concept model, and then propose the design of the control loop performance monitor (CLPM) to manage the timing information of CPS control loop. Finally, a case study of MEC-based implementation of ultra-low latency CPS reviews the feasibility of future applications.

• ETRI Journal
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• 제43권5호
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• pp.775-786
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• 2021

To translate in real time, a simultaneous translation system should determine when to stop reading source tokens and generate target tokens corresponding to a partial source sentence read up to that point. However, conventional attention-based neural machine translation (NMT) models cannot produce translations with adequate latency in online scenarios because they wait until a source sentence is completed to compute alignment between the source and target tokens. To address this issue, we propose a reinforced learning (RL)-based attention mechanism, the reinforced attention mechanism, which allows a neural translation model to jointly train the stopping criterion and a partial translation model. The proposed attention mechanism comprises two modules, one to ensure translation quality and the other to address latency. Different from previous RL-based simultaneous translation systems, which learn the stopping criterion from a fixed NMT model, the modules can be trained jointly with a novel reward function. In our experiments, the proposed model has better translation quality and comparable latency compared to previous models.

• Safety and Health at Work
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• 제1권2호
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• pp.140-148
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• 2010

Objectives: Determining the work-relatedness of lung cancer developed through occupational exposures is very difficult. Aims of the present study are to develop a decision tree of occupational lung cancer. Methods: 153 cases of lung cancer surveyed by the Occupational Safety and Health Research Institute (OSHRI) from 1992-2007 were included. The target variable was whether the case was approved as work-related lung cancer, and independent variables were age, sex, pack-years of smoking, histological type, type of industry, latency, working period and exposure material in the workplace. The Classification and Regression Test (CART) model was used in searching for predictors of occupational lung cancer. Results: In the CART model, the best predictor was exposure to known lung carcinogens. The second best predictor was 8.6 years or higher latency and the third best predictor was smoking history of less than 11.25 pack-years. The CART model must be used sparingly in deciding the work-relatedness of lung cancer because it is not absolute. Conclusion: We found that exposure to lung carcinogens, latency and smoking history were predictive factors of approval for occupational lung cancer. Further studies for work-relatedness of occupational disease are needed.

• IEIE Transactions on Smart Processing and Computing
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• 제3권1호
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• pp.1-9
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• 2014

This paper proposes a low-latency Sample Adaptive Offset filter (SAO) architecture and its Single Instruction Multiple Data (SIMD) optimization scheme to achieve fast High Efficiency Video Coding (HEVC) decoding in a multi-core environment. According to the HEVC standard and its Test Model (HM), SAO operation is performed only at the picture level. Most realtime decoders, however, execute their sub-modules on a Coding Tree Unit (CTU) basis to reduce the latency and memory bandwidth. The proposed low-latency SAO architecture has the following advantages over picture-based SAO: 1) significantly less memory requirements, and 2) low-latency property enabling efficient pipelined multi-core decoding. In addition, SIMD optimization of SAO filtering can reduce the SAO filtering time significantly. The simulation results showed that the proposed low-latency SAO architecture with significantly less memory usage, produces a similar decoding time as a picture-based SAO in single-core decoding. Furthermore, the SIMD optimization scheme reduces the SAO filtering time by approximately 509% and increases the total decoding speed by approximately 7% compared to the existing look-up table approach of HM.

• 사물인터넷융복합논문지
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• 제6권3호
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• pp.1-6
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• 2020

본 논문은 평균 객체 전송 지연 시간에 대한 기존의 모델들을 하나의 프레임워크로 통합하고 실제 계산 경험을 통해 결과를 분석하는 것을 목표로 한다. 해석적 객체 전송 지연 시간 모델은 다중 패킷 손실과 작은 혼잡제어 윈도우로 인해 빠른 재전송이 불가능한 멀티홉 무선 네트워크를 위시한 사물 인터넷(IoT) 환경을 가정한다. 이 모델은 또한 초기 혼잡 윈도우 크기와 하나의 혼잡 윈도우에서의 다중 패킷 손실을 고려한다. 성능평가에 의하면, 전송 객체 크기와 패킷 손실률이 작은 경우 평균 객체 전송 지연의 하한값과 상한값은 거의 동일하다. 그러나 패킷 손실률이 커지면 초기 혼잡 윈도우의 크기와 왕복 시간이 평균 객체 전송 지연의 상·하한값에 영향을 미치는 것으로 나타났다.

• 정보과학회 컴퓨팅의 실제 논문지
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• 제23권3호
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• pp.165-170
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• 2017

GPGPU의 높은 연산 처리 능력을 활용하여 길고 복잡한 계산을 하려는 시도가 많이 있다. GPGPU 프로그램의 특성상 host와 device 사이에 메모리 복사가 필요하다. 해당 메모리 복사 latency가 길 경우 프로그램의 성능에 많은 영향을 준다. 그래서 GPGPU를 활용한 프로그래밍은 최적화에 따른 성능 차이가 크다. 여러 개의 GPGPU 프로그램을 동시에 실행시키면 메모리 복사와 GPGPU 컴퓨팅이 중첩이 되어 메모리 복사 latency hiding 효과를 기대할 수 있다. 이 논문에서는 메모리 복사 latency hiding을 분석한다. 또 메모리 복사의 성능을 높이기 위해 pinned memory를 사용했을 경우의 제약 조건에 따른 성능 예측 모델링 및 알고리즘을 제안하고 이를 바탕으로 실행할 워크로드를 선택하면 41%의 성능 향상을 보인다.

• 한국산학기술학회논문지
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• 제4권4호
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• pp.329-333
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• 2003

본 논문에서는 컴퓨터 시뮬레이션을 이용하여 모바일 IP에서 사용하는 낮은 지연을 갖는 사전 등록 핸드오프 방식의 성능을 분석한다. 시스템의 이용률에 따라서 패킷 손실과 지연을 평가한다. 사전 등록 핸드오프 방식에 참여하는 외부 에이전트는 입력 및 출력포트를 갖는 큐로써 모델링 할 수 있으므로 본 논문에서는 오픈 큐잉 네트워크 모델을 이용하여 사전등록 핸드오프 방식의 지연 시간값과 시스템내에 있는 패킷수를 얻기 위한 해석적 모델을 제시한다. 해석적 모델과 컴퓨터 시뮬레이션으로 얻은 값이 거의 일치함을 알 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권2호
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• pp.473-493
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• 2019

5G vehicular communication is one of key enablers in next generation intelligent transportation system (ITS), that require ultra-reliable and low latency communication (URLLC). To meet this requirement, a new hybrid vehicular network structure which supports both centralized network structure and distributed structure is proposed in this paper. Based on the proposed network structure, a new vehicular network utility model considering the latency and reliability in vehicular networks is developed based on Euclidean norm theory. Building on the Pareto improvement theory in economics, a vehicular network uplink optimization algorithm is proposed to optimize the uplink utility of vehicles on the roads. Simulation results show that the proposed scheme can significantly improve the uplink vehicular network utility in vehicular networks to meet the URLLC requirements.