• Ocean Systems Engineering
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• v.10 no.4
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• pp.435-449
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• 2020

This paper proposes a method to estimate the underwater target object's yaw angle using a sonar image. A simulator modeling imaging mechanism of a sonar sensor and a generative adversarial network for style transfer generates realistic template images of the target object by predicting shapes according to the viewing angles. Then, the target object's yaw angle can be estimated by comparing the template images and a shape taken in real sonar images. We verified the proposed method by conducting water tank experiments. The proposed method was also applied to AUV in field experiments. The proposed method, which provides bearing information between underwater objects and the sonar sensor, can be applied to algorithms such as underwater localization or multi-view-based underwater object recognition.

• Journal of Information Processing Systems
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• v.6 no.4
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• pp.501-510
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• 2010

Wireless sensor networks consist of sensor nodes which are expected to be battery-powered and are hard to replace or recharge. Thus, reducing the energy consumption of sensor nodes is an important design consideration in wireless sensor networks. For the implementation of an energy-efficient MAC protocol, a Sensor-MAC based on the IEEE 802.11 protocol, which has energy efficient scheduling, has been proposed. In this paper, we propose a Dynamic S-MAC that adapts dynamically to the network-traffic state. The dynamic S-MAC protocol improves the energy consumption of the S-MAC by changing the frame length according to the network-traffic state. Using an NS-2 Simulator, we compare the performance of the Dynamic S-MAC with that of the S-MAC protocol.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.1
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• pp.47-53
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• 2012

Sensor networks and car networks that have different structure from that of conventional TCP/IP network require extreme network environment due to frequent change of connectivity. Because such extreme network environment has characteristics like unreliable link connectivity, long delay time, asymmetrical data transfer rate, and high error rate, etc., it is difficult to perform normally with the conventional TCP/P-based routing. DTNs (delay and disruption tolerant network) was designed to support data transfer in extreme network environment with long delay time and no guarantee for continuous connectivity between terminals. This study suggests an algorithm that limits the maximum number of copying transferred message to L by improving the spray and wait routing protocol, which is one of the conventional DTNs routing protocols, and using the azimuth and density data of the mobile nods. The suggested algorithm was examined by using ONE, a DTNs simulator. As a result, it could reduce the delay time and overhead of unnecessary packets compared to the conventional spray and wait routing protocol.

• Structural Engineering and Mechanics
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• v.49 no.4
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• pp.509-521
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• 2014

In this paper two protocols of Wireless Sensor Networks (WSN) are examined through both a simulation and a case study. The simulation was performed with the optimized network (OPNET) simulator while comparing the performance of the Ad-Hoc on demand Distance Vector (AODV) and the Dynamic Source Routing (DSR) protocols. This is compared and shown with real-world measurement of deflection from eight wireless sensor nodes. The wireless sensor response results were compared with accelerometer sensors for validation purposes. It was found that although the computer simulation suggests the AODV protocol is more accurate, in the case study no distinct difference was found. However, it was shown that AODV is still more beneficial in the field as it has a longer battery life enabling longer surveying times. This is a significant finding as a large factor in determining the use of wireless network sensors as a method of assessing structural response has been their short battery life. Thus if protocols which enhance battery life, such as the AODV protocol, are employed it may be possible in the future to couple wireless networks with solar power extending their monitoring periods.

• Journal of KIISE:Information Networking
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• v.34 no.4
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• pp.262-268
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• 2007

The efficient node-energy utilization in wireless sensor networks has been studied because sensor nodes operate with limited power based on battery. To extend the lifetime of the wireless sensor networks, maintaining balanced power consumption between sensor nodes is more important than reducing total energy consumption of the overall network. Since a large number of sensor nodes are densely deployed and collect data by cooperation in wireless sensor network, keeping more sensor nodes alive as possible is important to extend the lifetime of the sensor network. In this paper, we submit an efficient energy aware routing protocol based on AODV ad hoc routing protocol for wireless sensor networks to increase its lifetime without degrading network performance. The proposed protocol is designed to avoid traffic congestion on minor specific nodes at data transfer and to make the node power consumption be widely distributed to increase the lifetime of the network. The performance of the proposed protocol has been examined and evaluated with the NS-2 simulator in terms of network lifetime and end-to-end delay.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.169-178
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• 2023

Wireless sensor network is wieldy use for IoT application. The sensor node consider as physical device in IoT architecture. This all sensor node are operated with battery so the power consumption is very high during the data communication and low during the sensing the environment. Without proper planning of data communication the network might be dead very early so primary objective of the cluster based routing protocol is to enhance the battery life and run the application for longer time. In this paper we have comprehensive of twenty research paper related with clustering based routing protocol. We have taken basic information, network simulation parameters and performance parameters for the comparison. In particular, we have taken clustering manner, node deployment, scalability, data aggregation, power consumption and implementation cost many more points for the comparison of all 20 protocol. Along with basic information we also consider the network simulation parameters like number of nodes, simulation time, simulator name, initial energy and communication range as well energy consumption, throughput, network lifetime, packet delivery ration, jitter and fault tolerance parameters about the performance parameters. Finally we have summarize the technical aspect and few common parameter must be fulfill or consider for the design energy efficient cluster based routing protocol.

• Bulletin of the Korean Space Science Society
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• 2008.10a
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• pp.35.3-36
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• 2008

The ground-based spacecraft simulator is a useful tool to realize various space missions and satellite formation flying in the future. Also, the spacecraft simulator can be used to develop and verify new control laws required by modern spacecraft applications. In this research, therefore, Hardware-in-the-loop (HIL) simulator which can be demonstrated the experimental validation of the theoretical results is designed and developed. The main components of the HIL simulator which we focused on are the thruster system to attitude control and automatic mass-balancing for elimination of gravity torques. To control the attitude of the spacecraft simulator, 8 thrusters which using the cold gas (N2) are aligned with roll, pitch and yaw axis. Also Linear actuators are applied to the HIL simulator for automatic mass balancing system to compensate for the center of mass offset from the center of rotation. Addition to the thruster control system and Linear actuators, the HIL simulator for spacecraft attitude control includes an embedded computer (Onboard PC) for simulator system control, Host PC for simulator health monitoring, command and post analysis, wireless adapter for wireless network, rate gyro sensor to measure 3-axis attitude of the simulator, inclinometer to measure horizontality and battery sets to independently supply power only for the simulator. Finally, we present some experimental results from the application of the controller on the spacecraft simulator.

• ETRI Journal
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• v.30 no.1
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• pp.47-58
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• 2008

In sensor networks, analyzing power consumption before actual deployment is crucial for maximizing service lifetime. This paper proposes an instruction-level power estimator (IPEN) for sensor networks. IPEN is an accurate and fine grain power estimation tool, using an instruction-level simulator. It is independent of the operating system, so many different kinds of sensor node software can be simulated for estimation. We have developed the power model of a Micaz-compatible mote. The power consumption of the ATmega128L microcontroller is modeled with the base energy cost and the instruction overheads. The CC2420 communication component and other peripherals are modeled according to their operation states. The energy consumption estimation module profiles peripheral accesses and function calls while an application is running. IPEN has shown excellent power estimation accuracy, with less than 5% estimation error compared to real sensor network implementation. With IPEN's high precision instruction-level energy prediction, users can accurately estimate a sensor network's energy consumption and achieve fine-grained optimization of their software.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.196-196
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• 2000

This paper describes a lateral guidance system of an autonomous vehicle, using a neural network model of magneto-resistive sensor and magnetic fields. The model equation was compared with experimental sensing data. We found that the experimental result has a negligible difference from the modeling equation result. We verified that the modeling equation can be used in simulations. As the neural network controller acquires magnetic field values(B$\_$x/, B$\_$y/, B$\_$z/) from the three-axis, the controller outputs a steering angle. The controller uses the back-propagation algorithms of neural network. The learning pattern acquisition was obtained using computer simulation, which is more exact than human driving. The simulation program was developed in order to verify the acquisition of the teaming pattern, teaming itself, and the adequacy of the design controller. The performance of the controller can be verified through simulation. The real autonomous electric vehicle using neural network controller verified good results.

• Journal of Astronomy and Space Sciences
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• v.26 no.1
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• pp.47-58
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• 2009

In this study, a Hardware-In-the-Loop (HIL) simulator using thrusters is developed to validate the spacecraft attitude system. To control the attitude of the simulator, eight cold gas thrusters are aligned with roll, pitch and yaw axis. Also linear actuators are applied to the HIL simulator for automatic mass balancing to compensate the center of mass offset from the center of rotation. The HIL simulator consists of an embedded computer (Onboard PC) for simulator system control, a wireless adapter for wireless network, a rate gyro sensor to measure 3-axis attitude of the simulator, an inclinometer to measure horizontal attitude, and a battery set to supply power for the simulator independently. For the performance test of the HIL simulator, a bang-bang controller and Pulse-Width Pulse-Frequency (PWPF) modulator are evaluated successfully. The maneuver of 68 deg. in yaw axis is tested for the comparison of the both controllers. The settling time of the bang -bang controller is faster than that of the PWPF modulator by six seconds in the experiment. The required fuel of the PWPF modulator is used as much as 51% of bang-bang controller in the experiment. Overall, the HIL simulator is appropriately developed to validate the control algorithms using thrusters.