• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.3900-3916
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• 2019

The modern mobile devices are typically equipped with multiple network interfaces, e.g., 4G LTE, Wi-Fi, Bluetooth, but the current implementation of TCP can support only a single path at the same time. The Multipath TCP (MPTCP) leverages the multipath feature and provides (i) robust connection by utilizing another interface if the current connection is lost and (ii) higher throughput than single path TCP by simultaneously leveraging multiple network paths. However, if the performance between the multiple paths are significantly diverse, the receiver may have to wait for packets from the slower path, causing reordering and buffering problems. To solve this problem, previous MPTCP schedulers mainly focused on predicting the latency of the path beforehand. Recent studies, however, have shown that the path latency varies by a large margin over time, thus the MPTCP scheduler may wrongly predict the path latency, causing performance degradation. In this paper, we propose a new MPTCP scheduler called, choose fastest subflow (CFS) scheduler to solve this problem. Rather than predicting the path latency, CFS utilizes the characteristics of these paths to reduce the overall flow completion time by redundantly sending the last part of the flow to both paths. We compare the performance through real testbed experiments that implements CFS. The experimental results on both synthetic packet generation and actual Web page requests, show that CFS consistently outperforms the previous proposals in all cases.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.1
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• pp.19-24
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• 2023

In traditional fish farming way, the workers have to observe all of the pools every time and every day to feed at the right timing. This method causes tremendous stress on workers and wastes time. To solve this problem, we implemented an automatic detection system for feeding time using deep neural network. The detection system consists of two steps: classification of the presence or absence of feed and checking DO (Dissolved Oxygen) of the pool. For the classification, the pretrained ResNet18 model and transfer learning with custom dataset are used. DO is obtained from the DO sensor in the pool through HTTP in real time. For better accuracy, the next step, checking DO proceeds when the result of the classification is absence of feed several times in a row. DO is checked if it is higher than a DO reference value that is set by the workers. These actions are performed automatically in the UI programs developed with LabVIEW.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.1695-1700
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• 2011

In this paper, we introduce the network infrastructure in an advanced emu test line in Deabul. New technology has been applied to advanced EMU(DMU, integrated broadcasting system, black box and etc). In order to efficient and safely test of new developed train, failure, operation, status of test line and weather information should be monitored in real time. We has implemented a wireless and optical network infrastructure for reliability and scalability. The wireless communication capability between a car and ground is 20Mbps and back-hole network has 50Mbps of the communication performance. The network between test tracks and control office was established in the optical network. That can improve communication reliability.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.7
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• pp.9-18
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• 1997

In this paper, we implemented the communication module in the Telephone Network Access Subsystem(TNAS) of the Advanced Communications Processing System(ACPS). We defined some kinds of communication tasks and related resources like several queues which are executed in real-time operating system, and implemented the procedures for processing the user information. Through traffic modeling and simulation, the performance of the Service Processing board Assembly(SPA) is evaluated in the aspets of system utilization and buffer size. The ACPS should accommodate various public networks such as public switch telephone network, packet switchen data network, frame realy netork, and ATM network. The communications module proposed in this paper could be used inthe interface beween the SPA and the High Speed Network Adaptor of other network interface subsystems.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.11
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• pp.918-926
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• 2001

In this paper, intelligent control method using neural network as a nonlinear controller is presented. Simulation studies for three link rotary robot are performed. Neural network controller is implemented on DSP board in PC to make real time computing possible. On-line training algorithms for neural network control are proposed. As a test-bed, a large x-y table was build and interface with PC has been implemented. Experiments such as inverted pendulum control and large x-y table position control are performed. The results for different PD controller gains with neural network show excellent position tracking for circular trajectory compared with those for PD controller only. Neural control scheme also works better for controlling inverted pendulum on x-y table.

• Journal of Korea Multimedia Society
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• v.6 no.7
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• pp.1209-1218
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• 2003

To guarantee client buffer stabilization and visual quality, the VOD service that provides real time video titles on requirements of numerous users, needs a mechanism which transfers frames with dropping or skipping algorithm by network condition. In this paper, we show an algorithm that transfers withdrawed skipped MPEG frames(I, P, B frame) from disk to client dependent on network load. Moreover, we verify through a simulation that adaptive dealing on network load can reduce the network load and stabilize client receiving buffer.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.5
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• pp.791-796
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• 2013

Advent of the brain wave health care system is considered as an important issues in the industrial and research area in these days. It is necessary to detect EEG signals in real-time in order to support the medical emergency service for the epileptic or brain infarct patients. Since the efficient network support is an essential factor for the system, several topologies using sensor node based wireless body area network is suggested and simulated in this paper. Finally the Opnet simulation result is evaluated for the efficient topology of the body area network.

• Proceedings of the KWS Conference
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• 2000.04a
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• pp.251-255
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• 2000

Recently, the improvement of computer capacities and artificial intelligence ware caused to employ for prediction of residual stresses and strength evaluation. There are a lot of researches regarding the measurement and prediction of residual stresses for weldment using a neural network in the advanced countries, but in our country, a neural network as a technical part, has only been used on the possibilities of employment for welding area. Furthermore, the relationship between residual stress and process parameters using a neural network was wholly lacking. Therefore development of a new technical method for the optimized process parameters on the reduction of residual stress and applyment of real-time production line should be developed. The objectives of this paper is to measure the residual stress of butt welded specimen using strain gage sectioning method and to apply them to a neural network for prediction of residual stresses on a given process parameter. Also, the assessment of the developed system using a neural network was carried out

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.566-571
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• 1994

This paper presents in image-based visual servo control scheme for tracking a workpiece with a hand-eye coordinated robotic system using the fuzzy-neural-network. The goal is to control the relative position and orientation between the end-effector and a moving workpiece using a single camera mounted on the end-effector of robot manipulator. We developed a fuzzy-neural-network that consists of a network-model fuzzy system and supervised learning rules. Fuzzy-neural-network is applied to approximate the nonlinear mapping which transforms the features and theire change into the desired camera motion. In addition a control strategy for real-time relative motion control based on this approximation is presented. Computer simulation results are illustrated to show the effectiveness of the fuzzy-neural-network method for visual servoing of robot manipulator.

• Journal of information and communication convergence engineering
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• v.18 no.3
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• pp.183-187
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• 2020

The general Wi-Fi network connection structure is that a number of IoT (Internet of Things) sensor nodes are directly connected to one AP (Access Point) node. In this structure, the range of the network that can be established within the specified specifications such as the range of signal strength (RSSI) to which the AP node can connect and the maximum connection capacity is limited. To overcome these limitations, multiple middleware bridge technologies for dynamic scalability and load balancing were studied. However, these network expansion technologies have difficulties in terms of the rules and conditions of AP nodes installed during the initial network deployment phase In this paper, an intelligent edge computing IoT device is developed for constructing an intelligent autonomous cluster edge computing network and applying it to real-time road danger context aware and notification system through an intelligent risk situation recognition algorithm.