• Journal of the Korea Society for Simulation
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• v.15 no.1
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• pp.35-42
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• 2006

Sensor network, that is an infrastructure of ubiquitous computing, consists of a number of sensor nodes of which hardware is very small. The network topology and routing scheme of the network should be determined according to its purpose, and its hardware and software may have to be changed as needed from time to time. Thus, the sensor network simulator being capable of verifying its behavior and estimating performance is required for better design. Sensor network simulators currently existing have been developed for specific hardwares or operating systems, so that they can only be used for such systems and do not provide any means to estimate the amount of power consumption and program execution time which are major issues for system design. In this study, we develop the sensor network simulator that can be used to design and verify various sensor networks without regarding to types of applications or operating systems, and also has the capability of predicting the amount of power consumption and program execution time. For this purpose, the simulator is developed by using machine instruction-level discrete-event simulation scheme. As a result, the simulator can be used to analyze program execution timings and related system behaviors in the actual sensor nodes in detail. Instruction traces used as workload for simulations are executable images produced by the cross-compiler for ATmega128L microcontroller.

• Journal of IKEEE
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• v.7 no.2 s.13
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• pp.127-134
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• 2003

Ad Hoc Networks, autonomous distributed network using routing scheme, does not operate properly owing to multi flow service when network load increases at specific network node. In this paper, we suggest traffic management routing protocol in Ad Hoc Network to reduce network traffic congestion and distribute network load in data transmission. Through test results of proposed algorithm under NS(Network Simulator)simulator environments . we acquired reduced network load and increased data transmission rate.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1745-1748
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• 2003

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

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.741-742
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• 2011

In this paper, an over-current relay algorithm module for a network-based protective relay simulator is proposed. The proposed protective simulator is based on the client-sever paradigm. The module composed of a server and user interface provides a network-based simulation environment.

• Proceedings of the KIEE Conference
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• 2003.07b
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• pp.1329-1331
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• 2003

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.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.13 no.1
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• pp.48-53
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• 2017

We diagnosed the defect using the data obtained from the nuclear power plant simulator. In this paper, we diagnosed faults in the nuclear power plant system for discovery instead of the traditional single-component or device unit. We created the six fault scenarios and used a fault simulator to obtain the fault data. It was extracted pattern from acquired failure data. Neural network model was trained and simple pattern matching algorithm was applied. We presented a simulation result and confirmed that the applied algorithm works correctly.

• Journal of the Semiconductor & Display Technology
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• v.16 no.3
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• pp.127-130
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• 2017

In this research, we present a path planning method for an autonomous flight of unmanned aerial vehicles (UAVs) through reinforcement learning under simulated environment. We design the simulator for reinforcement learning of uav. Also we implement interface for compatibility of Deep Q-Network(DQN) and simulator. In this paper, we perform reinforcement learning through the simulator and DQN, and use Q-learning algorithm, which is a kind of reinforcement learning algorithms. Through experimentation, we verify performance of DQN-simulator. Finally, we evaluated the learning results and suggest path planning strategy using reinforcement learning.

• Journal of the Korea Society of Computer and Information
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• v.15 no.2
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• pp.155-162
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• 2010

To ensure accurate measurements of wireless network performance, it should be collected real-time data which are transmitted between a large number of nodes in the actual network environment. Therefore, it is necessary to develop simulation tool for finding optimal network system design method such as media access control, routing technique, ad-hoc algorithm of node deployment while overcoming spatial and temporal constraints. Our research attempts to provide an improved architecture and design method of simulation tool for wireless network is an application of multi-threading technique in these issues. We finally show that usability of the proposed simulator by comparing results derived from same test environment in the wireless LAN model of our simulator and widely used network simulation package, NS-2.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.2
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• pp.132-140
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• 2002

A momentum backpropagation neural network is prepared to carry out real-time dynamics simulations of a passenger car. A full-car model of fifteen degrees of freedom was constructed for vehicle dynamics analysis. Human body dynamics analysis was performed for a male driver(50 percentile Korean adult) restrained by a three point seatbelt system. The trained data using the neural network were obtained using a dynamic solver, ADAMS . The neural network were formed based on the dynamics of the simulator. The optimized hidden layer was obtained by selecting the optimal number of hidden layers. The driving scenario including bump passing and lane changing has been used for the estimation of the proposed neural network. A comparison between the trained data and neural network outputs is found to be satisfactory to show the applicability of the suggested approach.

• Journal of information and communication convergence engineering
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• v.9 no.4
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• pp.396-400
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• 2011

P2P(peer to Peer) network is a distributed network architecture composed of participants that make a portion of their resources directly available to other network participants, without the need for a central server. Currently, convergence network industry using wired and mobile are grows rapidly. So P2P protocols will be used between mobile and wired network. But current P2P protocols are focused on the wired networks only and there are no simulators for performance analysis of mobile P2P. In this paper, we design a P2P simulation system for performance analysis of P2P protocols in mobile, wired and convergence networks. It is constructed by a well-known mobile network simulator and wired based P2P protocol simulator. Finally we have implemented a smart TV test-bed using our P2P test-bed for convergence networks.