• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.2002-2019
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• 2017

RPL routing protocol for low-power and lossy networks is an Internet Engineering Task Force (IETF) recommended IPv6 based protocol for routing over Low power Lossy Networks (LLNs). RPL is proposed for networks with characteristics like small packet size, low bandwidth, low data rate, lossy wireless links and low power. RPL is a proactive routing protocol that creates a Directed Acyclic Graph (DAG) of the network topology. RPL is increasingly used for Internet of Things (IoT) which comprises of heterogeneous networks and applications. RPL proposes a single path routing strategy. The forwarding technique of RPL does not support multiple paths between source and destination. Multipath routing is an important strategy used in both sensor and ad-hoc network for performance enhancement. Multipath routing is also used to achieve multi-fold objectives including higher reliability, increase in throughput, fault tolerance, congestion mitigation and hole avoidance. In this paper, M-RPL (Multi-path extension of RPL) is proposed, which aims to provide temporary multiple paths during congestion over a single routing path. Congestion is primarily detected using buffer size and packet delivery ratio at forwarding nodes. Congestion is mitigated by creating partially disjoint multiple paths and by avoiding forwarding of packets through the congested node. Detailed simulation analysis of M-RPL against RPL in both grid and random topologies shows that M-RPL successfully mitigates congestion and it enhances overall network throughput.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.8
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• pp.643-650
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• 2014

Recently, the wireless communication applications are studied in various environment by the development of short range communication system like wireless sensor networks. This paper presents the analysis of localization schemes for ship application using received signal strength. The localization schemes using received signal strength from wireless networks are classified under two methods, which are Range based method and Range free method. Range based methods estimate the location with least square estimation based on estimated distance using path-loss model. Range free methods estimated the location with the information of anchor nodes linked to target. Simulation results show the appropriate localization scheme for each cabin environments based on the empirical path-loss model in warship's internal space.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.5
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• pp.1-7
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• 2009

When constructing various mobile networks including sensor networks, the problem of finding the layout or graph to interconnect the terminals or nodes of the network may come up. Providing a common scheme that can be applied to the kind of problems, and formulating the bounds of the run time and the result of the algorithm from the scheme, one may evaluate precisely the plan of constructing analogous network systems. This paper, dealing with EMST(Euclidean Minimum Spanning Tree) that represents such problems, provides the scheme for constructing EMST by parallel processing over distributed environments, and the ground for determining the maximum difference of the layout or the graph produced from the scheme: the difference from EMST. In addition, it provides the upper bound of the run time of the algorithm from the scheme.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.6
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• pp.261-268
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• 2014

This paper presents a electrocardiogram(ECG), electromyogram(EMG), and Photoplethysmography(PPG) signal wireless monitoring system based on Bluetooth Low Energy (BLE). ECG and EMG sensor interface analog front-end circuits are designed by using off-the-shelf parts. Texas Instruments(TI)'s CC2540DK is used for BLE-based communication. Two CC2540DK modules are used as Peripheral and Central nodes. In peripheral device, vital signals are acquired by the analog front-ends and fed to ADC for analog-to-digital conversion. The peripheral transmitts the data through the air to the central device. The central device receive the data and sends them to PC using UART. GUI is designed using Labview for displaying the acquired vital signals. The developed system can be used for future ubiquitous wireless healthcare system based on bluetooth 4.0.

• Journal of the Korea Society of Computer and Information
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• v.17 no.10
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• pp.89-98
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• 2012

In this paper, we proposed the efficient addressing scheme for improving the performance of routing algorithm by using ZigBee in Smart Grid environment. In a 16-bit address space and the network size of a few thousands, it is very unlikely to suffer from frequent address collisions. In response, we propose an elegant (x, y, z) coordinate axes addressing scheme from divided address space of 16 bit and its routing algorithm. One of disadvantages of (x, y) coordinate axes addressing, however, is that any router may not hold as many children as proposed, since sensor nodes tend to be connected to a geographically nearby router. We also present an adaptive routing algorithm for location-aware routing algorithms, using our addressing scheme. As a result, each node was reduced not only bitwise but also multi hop using the coordinate axes while routing and the effective address assignment and routing is to minimize the average energy consumption of each node in the network.

• Journal of Convergence for Information Technology
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• v.10 no.5
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• pp.1-7
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• 2020

This paper proposes a link adaptation method for Underwater Internet of Things (IoT), which reduces power consumption of sensor nodes and improves the throughput of network in underwater IoT network. Adaptive Modulation and Coding (AMC) technique is one of link adaptation methods. AMC uses the strong correlation between Signal Noise Rate (SNR) and Bit Error Rate (BER), but it is difficult to apply in underwater IoT as it is. Therefore, we propose the machine learning based AMC technique for underwater environments. The proposed Modulation Coding and Scheme (MCS) prediction model predicts transmission method to achieve target BER value in underwater channel environment. It is realistically difficult to apply the predicted transmission method in real underwater communication in reality. Thus, this paper uses the high accuracy BER prediction model to measure the performance of MCS prediction model. Consequently, the proposed AMC technique confirmed the applicability of machine learning by increase the probability of communication success.

• Journal of Convergence for Information Technology
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• v.10 no.6
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• pp.1-7
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• 2020

The demand on the underwater communications is extremely increasing in searching for underwater resources, marine expedition, or environmental researches, yet there are many problems with the wireless communications because of the characteristics of the underwater environments. Especially, with the underwater wireless networks, there happen inevitable delay time and spacial inequality due to the distances between the nodes. To solve these problems, this paper suggests a new solution based on ALOHA-Q. The suggested method use random NAV value. and Environments take reward through communications success or fail. After then, The environments setting NAV value from reward. This model minimizes usage of energy and computing resources under the underwater wireless networks, and learns and setting NAV values through intense learning. The results of the simulations show that NAV values can be environmentally adopted and select best value to the circumstances, so the problems which are unnecessary delay times and spacial inequality can be solved. Result of simulations, NAV time decreasing 17.5% compared with original NAV.

• Journal of Convergence for Information Technology
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• v.10 no.6
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• pp.41-48
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• 2020

The sensor nodes in underwater IoT networks have practical limitations in power supply. Thus, the reduction of power consumption is one of the most important issues in underwater environments. In this regard, AMC(Adaptive Modulation and Coding) techniques are used by using the relation between SNR and BER. However, according to our hands-on experience, we observed that the relation between SNR and BER is not that tight in underwater environments. Therefore, we propose a deep learning based MLP classification model to reflect multiple underwater channel parameters at the same time. It correctly predicts BER with a high accuracy of 85.2%. The proposed model can choose the best parameters to have the highest throughput. Simulation results show that the throughput can be enhanced by 4.4 times higher than the conventionally measured results.

• Journal of Advanced Navigation Technology
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• v.19 no.1
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• pp.85-90
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• 2015

In this paper, a novel Internet-of-things (IoT) based telecare system is proposed to provide high-quality care services to silver generations. It consists of various sensor nodes including activity sensors, wearable emergency pagers, emergency telephone as a home gateway, and a server as a telecare service platform. Especially, an activity index as a qualification method is presented to analyze the activities of daily living. By using the activity index, the daily/weekly/monthly activity information can be obtained, from which we infer the activity pattern, notice the abrupt change of the activity, and take appropriate actions in abnormal situations.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.40 no.4
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• pp.255-262
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• 2016

There has been intense research on self-diagnosis systems in railway applications, since stability and reliability have become more and more significant issues. Wired sensors have been widely used in the railway vehicles, but because of the difficulty in their maintenance and accessibility, they ar not considered for self-diagnosis systems. To have a self-monitoring system, wireless data transmission and self-powered sensors are required. For this purpose, a thermoelectric energy harvesting module that can generate electricity from temperature gradient between the bogie axle box and ambient environment was introduced in this work. The temperature gradient was measured under actual operation conditions, and the behavior of the thermoelectric module with an external load resistance and booster circuits was studied. The proposed energy harvesting system can be applied for wireless sensor nodes in railroad vehicles with optimization of thermal management.