Earticle

This paper proposes a design method for a driving simulator and driver assistance system in a vehicle network environment. Each module is on the same Controller Area Network(CAN) bus line for vehicle network configuration. To compose hardware in the loop simulation (HILS), a testbed similar to the actual vehicle environment is configured, and a virtual city and vehicle objects are created using a driving simulator. In particular, the vehicle network was configured by modularity and CAN ID applied from the modules according to the priority order. In the experiment, the possibility of using the vehicle control module was confirmed through the vehicle driving scenario in terms of the driver’s various emotions and situations. By acquisition of bio signal data from attached electrodes on the driver’s hand, the response time for changing the vehicle control mode and the control response time was measured in the manual driving mode, and it was confirmed that the control latency time is less than the commercialized response time of 830ms in autonomous vehicle control.

Existing simulators for performance analysis of resource management techniques in edge computing have a limitation: they lack horizontal management features such as inter-server clustering and container registry placement. To address this issue, this paper proposes EdgeNet, a new simulator specialized for modeling of network overhead and server clustering algorithm in edge computing environments. EdgeNet provides a Python library that can be used to develop leader election algorithms for clustered server groups, facilitating research into horizontal resource management approaches that were previously difficult to study.

ICT와 network의 발달로 규모가 커진 IT 인프라의 보안 관리가 매우 어려워지고 있다. 많은 회사나 공공기관에서 시스템과 네트워크 보안 관리에 어려움을 겪고 있다. 또한 하드웨어와 소프트웨어의 복잡함이 커짐에 따라 사람이 모든 보안을 관리한다는 것은 불가능에 가까워지고 있다. 따라서 네트워크 보안 관리에 AI가 필수적이다. 하지만 실제 네트워크 환경에 공격 모델을 구동하는 것은 매우 위험하기에 실제와 유사한 네트워크 환경을 구현하여 강화학습을 통해 사이버 보안 시뮬레이션 연구를 진행하였다. 이를 위해 본 연구는 강화학습을 네트워크 환경에 적용하였고, 에이전트는 학습이 진행될수록 해당 네트워크의 취약점을 정확하게 찾아냈다. AI를 통해 네트워크의 취약점을 발견하면, 자동화된 맞춤 대응이 가능해진다.

With the development of ICT and network, security management of IT infrastructure that has grown in size is becoming very difficult. Many companies and public institutions are having difficulty managing system and network security. In addition, as the complexity of hardware and software grows, it is becoming almost impossible for a person to manage all security. Therefore, AI is essential for network security management. However, since it is very dangerous to operate an attack model in a real network environment, cybersecurity emulation research was conducted through reinforcement learning by implementing a real-life network environment. To this end, this study applied reinforcement learning to the network environment, and as the learning progressed, the agent accurately identified the vulnerability of the network. When a network vulnerability is detected through AI, automated customized response becomes possible.

The competition between companies for prior occupation of the market is becoming fierce. In this highly competitive situation, it is important for companies to differentiate themselves if they are going to have a chance at success. And the competition to create the best solution method possible is higher than ever. Increased competition is forcing companies to lower costs and improve efficiency. A supply chain management(SCM) has become one of the most important solution methods of competitive advantage. This study has developed a simulator for the supply chain network problem. The simulator is designed to simulate the conditions of an actual supply chain network considering uncertainties. The simulator developed using commercial simulation tool ARENA and the results of computational experiments for a simple example were given and discussed to validate the developed simulator. Further research is needed, but using the simulator could become a useful tool for decision making in the supply chain network area.

본 논문에서는 기존의 차별화된 서비스 제공과 달리 보장형 서비스품질 제공 방안을 제시하고, NS-2를 이용한 시뮬레이션 결과를 제시한다. 한정된 자원을 요구하는 가입자별로 공정하게 나누어 가지는 경우 각각의 가입자들은 서비스품질의 저하를 느끼게 되어 전체적으로 가입자의 만족이 줄어든다. 따라서 보장형 서비스품질 제공 기법을 이용하여 제한된 자원내에서만 가입자를 서비스하고 이후에 요구하는 서비스 플로우에 대하여 서비스 제공을 거절함으로서 기존의 가입자의 만족을 증대시킬 수 있음을 알 수 있다.

For the efficient business, the telecommunication providers should have an attention for the minimization of the basic setup cost to implement the network infrastructure. Furthermore, the provision of the quality of service (QoS) to the service users is crucial for the service providers and vendors. In this paper, we propose the new algorithm to provide the user’s QoS under the various traffic in the broadband convergence network. Using the NS-2 network simulator, we evaluate the QoS for the proposed algorithm, and compare those with the results of the previous differentiated service network.

인공위성은 현대 사회에서 대부분의 IT 기술과 생활 전반의 바탕이 되며, 많은 연구가 진행되고 있다. 그러나 인공위성 기술의 발전과 함께 인공위성 통신망에 대한 사이버 공격도 다양화되어가고 있어 이를 대비하기 위해 인공위성 통신망의 가상 환경을 구축하는 연구의 필요성이 대두되고 있다. 본 논문에서는 가상 인공위성 통신망 구축을 통한 사이버훈련 환경을 개발하기 위한 연구의 선행 과정으로서. NASA에 서 개발한 공개 소프트웨어인 NOS3 (Operational Simulator for Small Satellites)의 구조를 분석한다. 또한, 분석 결과를 바탕으로 가상 인공위성 통신망 환경의 활용방안을 제시한다.

It is generally known that network simulator is a program used to verify new or existing network architecture and its activities. Basically network simulator helps to implement the virtual part of network research. This has save a lot of cost on analysis as the results of a network simulator is very close to real network cases. In recent researches, new models and prototypes are introduced to enable latest technologies support on network simulators. Some well-known network simulators are NS2, NS3, OMNET++ and QUALNET. As network research continues to grow rapidly, there is a need to analyze the supports and services offered by each network simulators. The objective of this paper is to investigate and analyze these network simulators in term of network mobility supports. This is because network mobility management has become a crucial topic in networking research. In selecting the right network simulators, issues such as CPU utilization, memory usage, computation time, feasibility, scalability and affordability need to be wisely studied. Using qualitative analysis this paper highlights the strengths and the limitations of these network simulators. The qualitative evaluations of these simulators are hereby presented.

The walking beam furnace (WBF) plays a critical role in a steel production factory, and has complex nonlinear dynamic behaviour. Thus, using the conventional physical principles to build a model of the process leads to a time-consuming modeling procedure and when the number of operating set-points in walking beam furnace increases the conventional modeling problem difficultly will be solved, indeed analytical models cannot be applied or can not give satisfactory results. This paper proposes intelligent nonlinear simulator model for a real walking beam furnace in a steel production factory using nonlinear sub-system identification technique based on the recurrent local linear neuro-fuzzy (RLLNF) network. This model is trained using the local linear model tree (LOLIMOT) algorithm, which is a tree-structure divide-and-conquer algorithm. It is the first time that such nonlinear simulator (recurrent) model for a real WBF based on locally linear neuro-fuzzy modelling is developed. The recorded data of Iran Alloy Steel Company are used to identify and evaluate the RLLNF simulator model of walking beam furnace.

본 논문은 NS-2 에서의 새로운 네트워크 요소 모듈 개발에 관한 연구를 목적으로 한다. 현재 대부분의 새로운 네트워크 요소들은 경제적인 이유와 네트워크의 환경적인 제약으로 인해서 시뮬레이터 환경에서 실험 되어지고 컴퓨터 공학에서 가장 많이 알려진 시뮬레이션툴 중의 하나로 NS-2 가 많이 사용되어 지고 있다 이러한 NS-2 는 Otcl 이라는 MIT 에서 개발한 언어와 C++ 가 상호 연동 되어져서 이벤트 처리 부분은 OTcl 이 담당하고 패킷 처리 부분은 C++가 담당 하고 있지만 새로운 네트워크 요소를 추가 하는 부분을 이해 하기에는 현재 공개된 문서 만으로는 이해하기 어려운 부분이 많다. 본 논문에서는 NS-2 에 새로운 네트워크 요소를 추가 하는대 있어서 필요한 NS-2 의 기술적인 부분을 설명함을 목적으로 하였다.

In this paper we introduce a software package, the Very long baseline interferometry Network SIMulator (VNSIM), which provides an integrated platform assisting radio astronomers to design Very Long Baseline Interferometry (VLBI) experiments and evaluate the network performance, with a user-friendly interface. Though VNSIM is primarily motivated by the East Asia VLBI Network, it can also be used for other VLBI networks and generic interferometers. The software package not only integrates the functionality of plotting (u, v) coverage, scheduling the observation, and displaying the dirty and CLEAN images, but also adds new features including sensitivity calculations for a given VLBI network. VNSIM provides flexible interactions on both command line and graphical user interface and offers friendly support for log reports and database management. Multi-processing acceleration is also supported, enabling users to handle large survey data. To facilitate future developments and updates, all simulation functions are encapsulated in separate Python modules, allowing independent invoking and testing. In order to verify the performance of VNSIM, we performed simulations and compared the results with other simulation tools, showing good agreement.

The power infrastructure defense system monitor and control a power system with parameters of a power system such as voltage, phasor angle, frequency and power flow which are measured at the same instance. For this, synchronized phasor measurement based on the GPS(Global Positioning System) is necessary. PMU(Phasor Measurement Unit) measures synchrophasor and transmits it to the power infrastructure defense system. For this communication, IEEE H37.118 defines a communication message format and measurement concept and we extend the protocol to transmit disturbance data. The synchrophasor data can be sent at various rates and there are several options for phasor information sent in the synchrophasor message. In this paper, we develop software that simulate communication between the power infrastructure defense system and PMU to annalize the traffic.

This paper presents an operator training simulator for power system restoration against massive blackout. The system is designed especially focused on the generality and convenient setting up for initial condition of simulation. The former is accomplished by using power flow calculation methodology, and PSS/E data is used to set up the initial state for easy setting. The proposed simulator consists of three major components-a power flow(PF), a data conversion(CONV), and, a GUI module. The PF module calculates power flow, and then checks over-voltages of buses and overloads of lines. The CONV module composes a Y-Bus array and a database at each restoration action. The initial Y-Bus array is composed from PSS/E data. A user friendly GUI module is developed including a graphic editor and a built-in operation manual. The maximum processing time for one step operation is 15 seconds, which is adequate for training purpose.

This paper presents a Train Communication Network simulator (TCNS) that can be used to evaluate the performance of TCN. TCN was accepted as the standard of the protocol for the communication network in trains. We carry out some simulation tests using the TCNS to show practical uses of the simulator. Results of some simulation tests are also reported.

A simulated network protocol provides the capability of distributed simulation to a generic simulator. Through this, full coverage of management of data and service handling among separated simulators is achieved. The distributed simulation environment is much more conducive to handling simulation load balancing and hazard treatment than a standalone computer. According to the simulated network protocol, one simulator takes on the role of server and the other simulators take on the role of client, and client is controlled by server. The purpose of the simulated network protocol is to seamlessly connect multiple simulator instances into a single simulation environment. This paper presents the development of a simulated network (simNetwork) that provides the capability of distributed simulation to a generic simulator (GenSim), which is a software simulator of satellites that has been developed by the Korea Aerospace Research Institute since 2010, to use as a flight software validation bench for future satellite development.

V2X 협력통신 시스템은 차량 운전을 쉽고 안전하게 할 수 있도록 도와주는 융합기술로 실제 교통상황에서 이러한 기술을 평가하고 효과를 예상하기 위해서는 실차 기반의 도로 구축과 통신 장비 구축, 검증 전문 인력 투입을 필요로 하며 많은 비용과 시간을 투입해야한다. 위와 같은 이유로 연구소 및 대학에서는 개발한 시스템을 테스트 하는데 어려움을 겪고 있으며, V2X 장비 개발이 가속화됨에 따라 차량 안전 어플리케이션과 V2X 통신기술을 테스트 할 수 있는 신뢰성 있는 테스트베드 구축에 대한 필요성이 증가하고 있다. 본 논문에서는 위와 같은 문제점들을 해결하기 위해 시뮬레이션을 기반으로 하는 테스팅 환경을 구성하기 위하여 External 인터페이스 구현을 통하여 트래픽 시뮬레이터와 네트워크 시뮬레이터를 연동하는 시스템을 구현하였다.

The V2X cooperative communication system is fusion technology which makes vehicle manuver safer. To evaluate and anticipate effect of these kind of technology, it requires real-car based road construction, implementation of communication devices, hiring inspection specialized personnel. For this reason, many laboratories and universities experience difficulties to test their technology results. Also, the need of implementing reliable testbed for testing vehicle safety applications and V2X communication technology is increasing as V2X device development is being accelerated. In this paper, we implemented a system which synchronizes traffic and network simulators via developing External interface to set simulation based testing environment in order to solve the difficulties.

최근 차량 네트워크를 통한 각종 서비스가 주목 받고 있으며 그 중 안전 서비스나 안전 서비스 어플리케이션 등의 테스트와 테스트를 위한 테스트베드에 대한 필요성이 생기고 있다. 본 논문은 네트워크 시뮬레이터와 교통 시뮬레이터 간의 연동을 통하여 실제 차량 통신 환경과 유사한 시나리오를 시뮬레이션 할 수 있도록 구현 하였다. 네트워크 시뮬레이터에서는 실제 차량의 이동성을 충분히 반영하기가 어렵고 대단위의 시나리오를 생성하기 어렵기 때문에 네트워크 시뮬레이터에 차량 이동성 정보 생성을 위하여 교통 시뮬레이터에서 생성 된 정보를 사용 할 수 있도록 하였다. 이러한 서로 다른 시뮬레이터간의 연동은 동기화의 문제가 존재하게 되는데 본 논문에서는 이를 해결하기 위한 각기 다른 세 가지의 동기화 방식을 연구 하였다.

네트워크 연구 분야에서 실시간 시나리오로 네트워크를 구성하는 것은 제약 사항이 많다. 단 하나의 테스트 베드도 비용과 시간을 굉장히 많이 소모하기 때문에 실제로 네트워크 전체를 구성하는 것 또한 쉽지 않으며 비용소모가 크다. 시뮬레이터는 이러한 실제 비용과 시간의 제약사항을 완화하여 시스템이 어떻게 동작 할지 알아보는데 도움을 준다. 본 논문에서는 서로 다른 몇 가지 네트워크 시뮬레이터의 주요 기능을 소개하고 장점과 단점을 도출해냈다.