• 제목/요약/키워드: Dynamic Network

검색결과 3,200건 처리시간 0.025초

A Dynamic Offset and Delay Differential Assembly Method for OBS Network

  • Sui Zhicheng;Xiao Shilin;Zeng Qingji
    • Journal of Communications and Networks
    • /
    • 제8권2호
    • /
    • pp.234-240
    • /
    • 2006
  • We study the dynamic burst assembly based on traffic prediction and offset and delay differentiation in optical burst switching network. To improve existing burst assembly mechanism and build an adaptive flexible optical burst switching network, an approach called quality of service (QoS) based adaptive dynamic assembly (QADA) is proposed in this paper. QADA method takes into account current arrival traffic in prediction time adequately and performs adaptive dynamic assembly in limited burst assembly time (BAT) range. By the simulation of burst length error, the QADA method is proved better than the existing method and can achieve the small enough predictive error for real scenarios. Then the different dynamic ranges of BAT for four traffic classes are introduced to make delay differentiation. According to the limitation of BAT range, the burst assembly is classified into one-dimension limit and two-dimension limit. We draw a comparison between one-dimension and two-dimension limit with different prediction time under QoS based offset time and find that the one-dimensional approach offers better network performance, while the two-dimensional approach provides strict inter-class differentiation. Furthermore, the final simulation results in our network condition show that QADA can execute adaptive flexible burst assembly with dynamic BAT and achieve a latency reduction, delay fairness, and offset time QoS guarantee for different traffic classes.

Link Stability aware Reinforcement Learning based Network Path Planning

  • Quach, Hong-Nam;Jo, Hyeonjun;Yeom, Sungwoong;Kim, Kyungbaek
    • 스마트미디어저널
    • /
    • 제11권5호
    • /
    • pp.82-90
    • /
    • 2022
  • Along with the growing popularity of 5G technology, providing flexible and personalized network services suitable for requirements of customers has also become a lucrative venture and business key for network service providers. Therefore, dynamic network provisioning is needed to help network service providers. Moreover, increasing user demand for network services meets specific requirements of users, including location, usage duration, and QoS. In this paper, a routing algorithm, which makes routing decisions using Reinforcement Learning (RL) based on the information about link stability, is proposed and called Link Stability aware Reinforcement Learning (LSRL) routing. To evaluate this algorithm, several mininet-based experiments with various network settings were conducted. As a result, it was observed that the proposed method accepts more requests through the evaluation than the past link annotated shorted path algorithm and it was demonstrated that the proposed approach is an appealing solution for dynamic network provisioning routing.

Dynamic data Path Prediction in Network Virtual Environment

  • Jeoung, You-Sun;Ra, Sang-Dong
    • Journal of information and communication convergence engineering
    • /
    • 제5권2호
    • /
    • pp.83-87
    • /
    • 2007
  • This research studies real time interaction and dynamic data shared through 3D scenes in virtual network environments. In a distributed virtual environment of client-server structure, consistency is maintained by the static information exchange; as jerks occur by packet delay when updating messages of dynamic data exchanges are broadcasted disorderly, the network bottleneck is reduced by predicting the movement path by using the Dead-reckoning algorithm. In Dead-reckoning path prediction, the error between the estimated and the actual static values which is over the threshold based on the shared object location requires interpolation and multicasting of the previous location by the ESPDU of DIS. The shared dynamic data of the 3D virtual environment is implementation using the VRML.

HSFE Network and Fusion Model based Dynamic Hand Gesture Recognition

  • Tai, Do Nhu;Na, In Seop;Kim, Soo Hyung
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • 제14권9호
    • /
    • pp.3924-3940
    • /
    • 2020
  • Dynamic hand gesture recognition(d-HGR) plays an important role in human-computer interaction(HCI) system. With the growth of hand-pose estimation as well as 3D depth sensors, depth, and the hand-skeleton dataset is proposed to bring much research in depth and 3D hand skeleton approaches. However, it is still a challenging problem due to the low resolution, higher complexity, and self-occlusion. In this paper, we propose a hand-shape feature extraction(HSFE) network to produce robust hand-shapes. We build a hand-shape model, and hand-skeleton based on LSTM to exploit the temporal information from hand-shape and motion changes. Fusion between two models brings the best accuracy in dynamic hand gesture (DHG) dataset.

동적 QoS 적응을 고려한 계층적 미디어 데이터의 전송 기법 (Layered Media Data Transmission Mechanism Of Considering Adaptive Dynamic QoS Control)

  • 나윤주;이승하;박준호;남지승;마평수
    • 대한전자공학회:학술대회논문집
    • /
    • 대한전자공학회 2001년도 하계종합학술대회 논문집(3)
    • /
    • pp.97-100
    • /
    • 2001
  • A common network such as internet does not provide a guaranteed network bandwidth to accommodate multimedia service in a reliable fashion. In this paper, we propose a new rate control mechanism for multimedia service on the internet which is adaptive to the dynamic QoS in real-time. Also we adapt an QoS monitoring module and real-time transmission control module to adapt dynamic network bandwidth. To do this, we used layer attribution of media data and also considered loss rate and buffer threshold in receiver side for measurement of dynamic QoS.

  • PDF

신경회로망을 이용한 동적 문턱값에 의한 비선형 시스템의 고장진단 (Fault Diagnosis of Nonlinear Systems Based on Dynamic Threshold Using Neural Network)

  • 소병석;이인수;전기준
    • 제어로봇시스템학회논문지
    • /
    • 제6권11호
    • /
    • pp.968-973
    • /
    • 2000
  • Fault diagnosis plays an important role in the performance and safe operation of many modern engineering plants. This paper investigates the problem of fault detection using neural networks in dynamic systems. A general framework for constructing a nonlinear fault detection scheme for nonlinear dynamic systems containing modeling uncertaintly is proposed. The main idea behind the proposed approach is to monitor the physical system with an off -line learning neural network and then to approximate the upper and lower thresholds of acceleration of the nominal system with the model-based threshold(ThMB) method, The performance of the proposed fault detection scheme is investigated through simulations of a pendulum with uncertainty.

  • PDF

셀룰러 네트워크의 동적채널에서 빠른 분산 전력 제어 기법의 특성에 대한 연구 (A Study on the Characteristics of Fast Distributed Power Control Schemes in Cellular Network under Dynamic Channel)

  • 이영대;박현숙
    • 한국인터넷방송통신학회논문지
    • /
    • 제8권2호
    • /
    • pp.49-55
    • /
    • 2008
  • To address the convergence issue of power control algorithms, a number of algorithms have been developed hat shape the dynamics of up-link power control for cellular network. Power algorithms based on fixed point iterations can be accelerated by the use of various methods, one of the simplest being the use of Newton iterations, however, this method has the disadvantage which not only needs derivatives of the cost function but also may be weak to noisy environment. we showed performance of the power control schemes to solve the fixed point problem under static or stationary channel. They proved goof performance to solve the fixed point problem due to their predictor based optimal control and quadratic convergence rate. Here, we apply the proposed power control schemes to the problem of the dynamic channel or to dynamic time varying link gains. The rigorous simulation results demonstrated the validity of our approach.

  • PDF

Lactic Acid Bacteria의 동역학 네트워크 모델을 이용한 in Silico 모사방법 연구 (Study of in Silico Simulation Method for Dynamic Network Model in Lactic Acid Bacteria)

  • 정의섭;이혜원;이진원
    • 제어로봇시스템학회논문지
    • /
    • 제11권10호
    • /
    • pp.823-829
    • /
    • 2005
  • We have newly constructed an in silico model of fermentative metabolism for Lactococcus lactis in order to analyze the characteristics of metabolite flux for dynamic network. A rigorous mathematical model for metabolic flux has been developed and simulation researches have been performed by using GEPASI program. In this simulation task, we were able to predict the whole flux distribution trend for lactate metabolism and analyze the flux ratio on the pyruvate branch point by using metabolic flux analysis(MFA). And we have studied flux control coefficients of key reaction steps in the model by using metabolic control analysis(MCA). The role of pyruvate branch seems to be essential for the secretion of lactate and other organic byproducts. Then we have made an effort to elucidate its metabolic regulation characteristics and key reaction steps, and find an optimal condition for the production of lactate.

Dynamic Routing and Spectrum Allocation with Traffic Differentiation to Reduce Fragmentation in Multifiber Elastic Optical Networks

  • ZOUNEME, Boris Stephane;ADEPO, Joel;DIEDIE, Herve Gokou;OUMTANAGA, Souleymane
    • International Journal of Computer Science & Network Security
    • /
    • 제21권3호
    • /
    • pp.1-10
    • /
    • 2021
  • In recent decades, the heterogeneous and dynamic behavior of Internet traffic has placed new demands on the adaptive resource allocation of the optical network infrastructure. However, the advent of multifiber elastic optical networks has led to a higher degree of spectrum fragmentation than conventional flexible grid networks due to the dynamic and random establishment and removal of optical connections. In this paper, we propose heuristic routing and dynamic slot allocation algorithms to minimize spectrum fragmentation and reduce the probability of blocking future connection requests by considering the power consumption in elastic multifiber elastic optical networks.

액중 방전 성형과 인공신경망 기법을 활용한 Cowper-Symonds 구성 방정식의 변형률 속도 파라메터 역추정 (Estimating Strain Rate Dependent Parameters of Cowper-Symonds Model Using Electrohydraulic Forming and Artificial Neural Network)

  • 변한비;김정
    • 소성∙가공
    • /
    • 제31권2호
    • /
    • pp.81-88
    • /
    • 2022
  • Numerical analysis and dynamic material properties are required to analyze the behavior of workpiece during an electrohydraulic forming (EHF) process. In this study, EHF experiments were conducted under three conditions (6, 7, 8 kV). Dynamic material properties of Al 5052-H34 were inversely estimated through an ANN (Artificial Neural Network) model constructed based on LS-Dyna analysis results. Parameters of Cowper-Symonds constitutive equation, C and p, were used to implement dynamic material properties. By comparing experimental results of three conditions with ANN model results, optimized parameters were obtained. To determine the reliability of the derived parameters, experimental results, LS-Dyna analysis results, and ANN results of three conditions were compared using MSE and SMAPE. Valid parameters were obtained because values of indicators were within confidence intervals.