• Title/Summary/Keyword: intelligent network

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A Receiver-Driven Loss Recovery Mechanism for Video Dissemination over Information-Centric VANET

  • Han, Longzhe;Bao, Xuecai;Wang, Wenfeng;Feng, Xiangsheng;Liu, Zuhan;Tan, Wenqun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.7
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    • pp.3465-3479
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    • 2017
  • Information-Centric Vehicular Ad Hoc Network (IC-VANET) is a promising network architecture for the future intelligent transport system. Video streaming applications over IC-VANET not only enrich infotainment services, but also provide the drivers and pedestrians real-time visual information to make proper decisions. However, due to the characteristics of wireless link and frequent change of the network topology, the packet loss seriously affects the quality of video streaming applications. In this paper, we propose a REceiver-Driven loss reCOvery Mechanism (REDCOM) to enhance video dissemination over IC-VANET. A Markov chain based estimation model is introduced to capture the real-time network condition. Based on the estimation result, the proposed REDCOM recovers the lost packets by requesting additional forward error correction packets. The REDCOM follows the receiver-driven model of IC-VANET and does not require the infrastructure support to efficiently overcome packet losses. Experimental results demonstrate that the proposed REDCOM improves video quality under various network conditions.

Mobility-Based Clustering Algorithm for Multimedia Broadcasting over IEEE 802.11p-LTE-enabled VANET

  • Syfullah, Mohammad;Lim, Joanne Mun-Yee;Siaw, Fei Lu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.3
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    • pp.1213-1237
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    • 2019
  • Vehicular Ad-hoc Network (VANET) facilities envision future Intelligent Transporting Systems (ITSs) by providing inter-vehicle communication for metrics such as road surveillance, traffic information, and road condition. In recent years, vehicle manufacturers, researchers and academicians have devoted significant attention to vehicular communication technology because of its highly dynamic connectivity and self-organized, decentralized networking characteristics. However, due to VANET's high mobility, dynamic network topology and low communication coverage, dissemination of large data packets (e.g. multimedia content) is challenging. Clustering enhances network performance by maintaining communication link stability, sharing network resources and efficiently using bandwidth among nodes. This paper proposes a mobility-based, multi-hop clustering algorithm, (MBCA) for multimedia content broadcasting over an IEEE 802.11p-LTE-enabled hybrid VANET architecture. The OMNeT++ network simulator and a SUMO traffic generator are used to simulate a network scenario. The simulation results indicate that the proposed clustering algorithm over a hybrid VANET architecture improves the overall network stability and performance, resulting in an overall 20% increased cluster head duration, 20% increased cluster member duration, lower cluster overhead, 15% improved data packet delivery ratio and lower network delay from the referenced schemes [46], [47] and [50] during multimedia content dissemination over VANET.

Ubiquitous Network and Wireless Embedded System with Intelligent Channel Scheduling Method (지능형 채널 할당 기법의 유비쿼터스 네트워크 및 무선 임베디드 시스템)

  • Park, Hyoung-Keun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.12 no.3
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    • pp.1336-1340
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    • 2011
  • In this paper, the efficient prevention of cross talk technique for basically avoiding the confusion problem between the overlapped ubiquitous network of the other object is developed within the same area. The intelligent unified wireless network remote meter reading system of the ubiquitous ZigBee base is developed based on this technology. Therefore, in this paper, each meter reading equipments managed the information of its own adjacent ZigBee channel. The intelligent network system steadily transmitting data a relay was developed based upon this information in each region through the flexible channel conversion technique.

A Real-time Intelligent Home Network Control System (실시간 지능형 홈 네트워크 제어 시스템)

  • Kim, Yong-Soo;Jung, Hee
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.10 no.11
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    • pp.3193-3199
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    • 2009
  • The real-time intelligent home network control system is the system which can control and monitor intelligent home network anytime and anywhere with mobile devices. In this study, to embody the real-time control system for intelligent home network, I designed the sub-module which can control various USN senses with using ZigBee, and organized the GUI environment into the client module to drive by users with mobiles devices.

The development network based on motor driver for modular robot implementation (모듈로봇 구현을 위한 네트워크기반 모터제어드라이버 개발)

  • Moon, Yong-Seon;Lee, Gwang-Seok;Seo, Dong-Jin;Lee, Sung-Ho;Bae, Young-Chul
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.7
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    • pp.887-892
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    • 2007
  • In this paper, we design, implement and apply network physical layer to 100 BaseFx optical cable interface module based on industrial ethernet protocol EtherCAT that has ensure its open standard ethernet compatibility which haying been provided with real time of control in network of intelligent service robot, can process numerous data to sensor and motor control system. Through various tests, we try to propose suitability as internal network of intelligent service robot.

A Note for Speed-Up of Interval Regression Neural Network (구간회귀 신경망의 속도개선)

  • 이중우;권순학
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2001.05a
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    • pp.101-104
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    • 2001
  • This paper deals with the speed-up of interval regression neural network. We propose an improved method of adjusting the parameter alpha used in the interval regression neural network to improve the learning speed and regression performance. Finally, we provide numerical examples to evaluate the performance of the proposed method.

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Implementation of Open & Distributed Intelligent Control Network for BAS (빌딩자동화용 개방.지능 분산제어 네트워크 구축에 관한 연구)

  • Hong, Won-Pyo;Lee, Sung-Hak
    • Proceedings of the KIEE Conference
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    • 2000.07d
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    • pp.2446-2451
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    • 2000
  • This paper presents the conceptual model of open & distributed intelligent control network for BAS. The characteristics and definition of this network also is proposed from theoretical study of LonWorks and a comparison between LonWorks and conventional network.

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Intelligent Modeling of Nuclear Power Plant Steam Generator (원자력발전소 증기발생기의 인공지능 모델링에 관한 연구)

  • Choi, Jin-Young;Lee, Jae-Gi
    • Proceedings of the KIEE Conference
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    • 1997.11a
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    • pp.675-678
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    • 1997
  • In this research we continue the study of nuclear power plant steam generator's intelligent modeling. This model represents the input-output behavior and is a preliminary stage for intelligent control. Among many intelligent models available, we study neural network models that have been proven as universal function approximators. We select multilayer perceptrons, circular backpropagation networks, piecewise linearly trained networks and recurrent neural networks as the candidates for the steam generator's intelligent models. We take the input-output pairs from steam generator's reference model and train the neural network models. We validate trained neural network models as intelligent models of steam generator.

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An Immune-Fuzzy Neural Network For Dynamic System

  • Kim, Dong-Hwa;Cho, Jae-Hoon
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2004.10a
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    • pp.303-308
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    • 2004
  • Fuzzy logic, neural network, fuzzy-neural network play an important as the key technology of linguistic modeling for intelligent control and decision making in complex systems. The fuzzy-neural network (FNN) learning represents one of the most effective algorithms to build such linguistic models. This paper proposes learning approach of fuzzy-neural network by immune algorithm. The proposed learning model is presented in an immune based fuzzy-neural network (FNN) form which can handle linguistic knowledge by immune algorithm. The learning algorithm of an immune based FNN is composed of two phases. The first phase used to find the initial membership functions of the fuzzy neural network model. In the second phase, a new immune algorithm based optimization is proposed for tuning of membership functions and structure of the proposed model.

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A many-objective optimization WSN energy balance model

  • Wu, Di;Geng, Shaojin;Cai, Xingjuan;Zhang, Guoyou;Xue, Fei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.2
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    • pp.514-537
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    • 2020
  • Wireless sensor network (WSN) is a distributed network composed of many sensory nodes. It is precisely due to the clustering unevenness and cluster head election randomness that the energy consumption of WSN is excessive. Therefore, a many-objective optimization WSN energy balance model is proposed for the first time in the clustering stage of LEACH protocol. The four objective is considered that the cluster distance, the sink node distance, the overall energy consumption of the network and the network energy consumption balance to select the cluster head, which to better balance the energy consumption of the WSN network and extend the network lifetime. A many-objective optimization algorithm to optimize the model (LEACH-ABF) is designed, which combines adaptive balanced function strategy with penalty-based boundary selection intersection strategy to optimize the clustering method of LEACH. The experimental results show that LEACH-ABF can balance network energy consumption effectively and extend the network lifetime when compared with other algorithms.