• Title/Summary/Keyword: AIS 네트워크

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Development of Distributed Autonomous Robotic Systerrt Based on Classifier System and Artificial Immune Network (분류자 시스템과 인공면역네트워크를 이용한 자율 분산 로봇시스템 개발)

  • Sim, Kwee-Bo;Hwang, Chul-Min
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.6
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    • pp.699-704
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    • 2004
  • This paper proposes a Distributed Autonomous Robotic System(DARS) based on an Artificial Immune System(AIS) and a Classifier System(CS). The behaviors of robots in the system are divided into global behaviors and local behaviors. The global behaviors are actions to search tasks in environment. These actions are composed of two types: aggregation and dispersion. AIS decides one among these two actions, which robot should select and act on in the global. The local behaviors are actions to execute searched tasks. The robots learn the cooperative actions in these behaviors by the CS in the local. The proposed system is more adaptive than the existing system at the viewpoint that the robots learn and adapt the changing of tasks.

자율운항선박의 운항 경로 예측 및 운항 해역 항적 정보 기반의 비상상황인식 프레임워크 설계

  • 박정홍;최진우;김채원;홍성훈;김혜진
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2022.11a
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    • pp.73-75
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    • 2022
  • 본 논문에서는 자율운항선박의 예측 가능한 운항 경로 상에 잠재된 비상상황을 인식하기 위하여 운항 해역의 항적 정보를 활용한 방안과 이를 기반으로 충돌 위험과 같은 비상위험을 식별하는 프레임워크를 설계하였다. 설계한 프레임워크는 크게 항적 특성 분석 모듈, 항로예측 모듈, 위험 식별 모듈로 구성된다. 항적 특성 분석 모듈에서는 자율운항선박의 운항 해역에 관한 선박들의 항적 정보를 활용하기 위하여, 대상 VTS 관제 영역 내에서 취합된 누적 선박자동식별장치(AIS) 데이터를 이용하여 선박의 항적 특성을 분석하여 데이터베이스(DB)를 생성하였다. 그리고 운항 경로 예측 모듈에서는 누적된 항적 정보와 자율운항선박의 현재 운항 정보를 기반으로 특정 시간 동안의 운항 경로를 예측하기 위한 학습 네트워크 모델을 구성하였다. 마지막으로, 위험 식별 모듈에서는 예측한 운항 경로 상에 최근접점과 최근접점 거리 정보를 이용하여 충돌 위험 가능성이 있는 충돌위험영역을 식별하였다. 설계한 프레임워크는 자율운항선박의 육상 관제소에서 원격 제어를 통해 위험상황을 인지하고 회피할 수 있는 정보를 제공할 수 있음을 실제 항적 데이터를 활용하여 그 결과를 검증하였다.

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Spatiotemporal Analysis of Vessel Trajectory Data using Network Analysis (네트워크 분석 기법을 이용한 항적 데이터의 시공간적 특징 분석)

  • Oh, Jaeyong;Kim, Hye-Jin
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.26 no.7
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    • pp.759-766
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    • 2020
  • In recent years, the maritime traffic environment has been changing in various ways, and the traffic volume has been increasing constantly. Accordingly, the requirements for maritime traffic analysis have become diversified. To this end, traffic characteristics must first be analyzed using vessel trajectory data. However, as the conventional method is mostly manual, it requires a considerable amount of time and effort, and errors may occur during data processing. In addition, ensuring the reliability of the analysis results is difficult, because this method considers the subjective opinion of analysts. Therefore, in this paper, we propose an automated method of traffic network generation for maritime traffic analysis. In the experiment, spatiotemporal features are analyzed using data collected at Mokpo Harbor over six months. The proposed method can automatically generate a traffic network reflecting the traffic characteristics of the experimental area. In addition, it can be applied to a large amount of trajectory data. Finally, as the spatiotemporal characteristics can be analyzed using the traffic network, the proposed method is expected to be used in various maritime traffic analyses.

Throughput Analysis of ASO-TDMA in Multi-hop Maritime Communication Network (다중-홉 선박 통신 네트워크를 위한 애드혹 자율 구성 TDMA 방식의 수율 성능 분석)

  • Cho, Kumin;Yun, Changho;Kang, Chung G.
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.37B no.9
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    • pp.741-749
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    • 2012
  • Ad Hoc Self-Organizing TDMA (ASO-TDMA) has been proposed as a specification to support the multi-hop data communication service for ships over VHF band. It allows for organizing a multi-hop ad-hoc network in a distributed manner by sharing the radio resources among the ships navigating along the route. In this paper, Markov chain analysis is given to provide the average throughput performance for ASO-TDMA protocol Furthermore, the analytical results are verified with computer simulation, which shows that there exists the optimal transmission rate to maximize the average throughput as the subframe size and the number of ships are varying in each hop region.

Congestion Control Mechanism using Real Time Signaling Information in ATM based MPLS Network (ATM 기반 MPLS 망에서 실시간 신호정보를 이용한 체증 제어 기법)

  • Ahn, Gwi-Im
    • Journal of Korea Multimedia Society
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    • v.10 no.4
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    • pp.462-469
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    • 2007
  • ATM protocol has the techniques such as cell discarding priority, traffic shaping and traffic policing. ATM based MPLS(Multiprotocol Label Switching) is discussed for its provisioning QoS commitment capabilities, traffic engineering and smooth migration for BcN using conventional ATM infra in Korea. This paper proposes preventive congestion control mechanism for detecting HTR(Hard To Reach) LSP(Label Switched Path) in ATM based MPLS systems. In particular, we decide HTR LSP using real time signaling information(etc., PTI,AIS/RDI) for applying HTR concept in circuit switching to ATM based MPLS systems and use those session gap and percentage based control algorithm that were used in conventional PSTN call controls. We concluded that it maximized the efficiency of network resources by restricting ineffective machine attempts. Proposed control can handle 208% call processing and more than 147% success call, than those without control. It can handle 187% BHCA(Busy Hour Call Attempts) with 100 times less than use of exchange memory.

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Adaptive Intrusion Detection Algorithm based on Artificial Immune System (인공 면역계를 기반으로 하는 적응형 침입탐지 알고리즘)

  • Sim, Kwee-Bo;Yang, Jae-Won
    • Journal of the Korean Institute of Intelligent Systems
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    • v.13 no.2
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    • pp.169-174
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    • 2003
  • The trial and success of malicious cyber attacks has been increased rapidly with spreading of Internet and the activation of a internet shopping mall and the supply of an online, or an offline internet, so it is expected to make a problem more and more. The goal of intrusion detection is to identify unauthorized use, misuse, and abuse of computer systems by both system insiders and external penetrators in real time. In fact, the general security system based on Internet couldn't cope with the attack properly, if ever. other regular systems have depended on common vaccine softwares to cope with the attack. But in this paper, we will use the positive selection and negative selection mechanism of T-cell, which is the biologically distributed autonomous system, to develop the self/nonself recognition algorithm and AIS (Artificial Immune System) that is easy to be concrete on the artificial system. For making it come true, we will apply AIS to the network environment, which is a computer security system.

A Hybrid Course-Based Routing Protocol Suitable for Vessel Ad Hoc Networks (선박 애드 혹 네트워크에 적합한 복합적 항로기반 경로배정 프로토콜)

  • Son, Joo-Young;Mun, Seong-Mi
    • Journal of Advanced Marine Engineering and Technology
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    • v.32 no.5
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    • pp.775-784
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    • 2008
  • It is not easy to access very high speed Internet services at sea due to some technical and economical problems. In order to realize the very high speed Internet services at sea like on land, new communication network models based on MANET should be adopted. In this paper, a new MANET model at sea is provided, which considered the ocean environments, and the characteristics and movement of vessels. On the basis of the fact that most vessels navigate on the predetermined courses, which are the shortest paths between source and destination ports in most cases, a type of location oriented routing protocol is proposed in this paper. The Hybrid Course-Based Routing Protocol(HCBR) makes use of the static information such as courses and positions of ports to proactively find the shortest paths not only among ports but also the cross points of courses. HCBR also makes use of the locational information of vessels obtained via GPS and AIS systems to reactively discover the shortest route by which data packets are delivered between them. We have simulated the comparison of the performance of HCBR with those of LAR scheme 1 and scheme2, the most typical protocols using geographical information. The simulation results show that HCBR guarantees the route discovery even without using any control packet. They also show that HCBR is more reliable(40%) and is able to obtain more optimal routes(10%) than LAR scheme1 and scheme2 protocols.

The Efficient Ship Wireless Sensor Network Using Drone (드론을 활용한 효율적인 선박 센서 네트워크)

  • Hong, Sung-Hwa;Kim, Byoung-Kug
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.1
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    • pp.122-127
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    • 2022
  • Currently, the drone is considered as a mobile base station of USN as a method to act as a base station using USN in existing LTE-M and LTE networks for data transmission in unmanned ships. Therefore, the drone, which is a mobile base station, is a sink node equipped with an LTE modem or a short-range communication modem, and can collect safety information of ship operation from the sensor node and transmit the safety information to the ship or transmit the information between the ships. As, if a short-range network is formed by using drones, it will form a communication network around unmanned ships and will be advantageous for collecting information using security and environmental sensors. In this paper, we propose a method to transmit environmental sensor data and to utilize communication between ships using drones to secure the surrounding information necessary for AI operation of unmanned ships in the future.

Navigational Anomaly Detection using a Traffic Network Model (교통 네트워크 모델 기반 이상 운항 선박 식별에 관한 연구)

  • Jaeyong Oh;Hye-Jin Kim
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.29 no.7
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    • pp.828-835
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    • 2023
  • Vessel traffic service operators (VTSOs) need to quickly and accurately analyze the maritime traffic situation in the vessel traffic service (VTS) area and provide information to the vessels. However, if traf ic increases rapidly, the workload of VTSOs increases, and they may not be able to provide adequate information. Therefore, it is essential to develop VTSO support technologies that can reduce their workload and provide consistent information. In this paper, we propose a model for automatically detecting abnormal vessels in the VTS area. The proposed model consists of a positional model and a contextual model and is specifically optimized for the traffic characteristics of the target area. The implemented model was tested by using real-world data collected at a test center (Daesan Port VTS). Our experiments confirmed that the model could automatically detect various abnormal situations, and the results were validated through expert evaluation.

Intrusion Detection System of Network Based on Biological Immune System (생체 면역계를 이용한 네트워크 침입탐지 시스템)

  • Sim, Kwee-Bo;Yang, Jae-Won;Lee, Dong-Wook;Seo, Dong-Il;Choi, Yang-Seo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.12 no.5
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    • pp.411-416
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    • 2002
  • Recently, the trial and success of malicious cyber attacks has been increased rapidly with spreading of Internet and the activation of a internet shopping mall and the supply of an online internet, so it is expected to make a problem more and more. Currently, the general security system based on Internet couldn't cope with the attack properly, if ever, other regular systems have depended on common softwares to cope with the attack. In this paper, we propose the positive selection mechanism and negative selection mechanism of T-cell, which is the biological distributed autonomous system, to develop the self/non-self recognition algorithm, the anomalous behavior detection algorithm, and AIS (Artificial Immune System) that is easy to be concrete on the artificial system. The proposed algorithm can cope with new intrusion as well as existing one to intrusion detection system in the network environment.