• Journal of KIISE
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• v.44 no.9
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• pp.976-985
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• 2017

Wireless mesh network (WMN) is a promising technology for building a cost-effective and easily-deployed wireless networking infrastructure. To efficiently utilize limited radio resources in WMNs, packet transmissions (particularly, redundant packet transmissions) should be carefully managed. We therefore propose a lightweight traffic redundancy elimination (LTRE) scheme to reduce redundant packet transmissions in software-defined wireless mesh networks (SD-WMNs). In LTRE, the controller determines the optimal path of each packet to maximize the amount of traffic reduction. In addition, LTRE employs three novel techniques: 1) machine learning (ML)-based information request, 2) ID-based source routing, and 3) popularity-aware cache update. Simulation results show that LTRE can significantly reduce the traffic overhead by 18.34% to 48.89%.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.6
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• pp.85-96
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• 2003

Wireless LAM in itself is vulnerable to eavesdropping and modification attack, and thus, IEEE 802.11i and IEEE 802. 1x/1aa have been defined to secure the wireless channel. These protocols accompanied by RADIUS and EAP-TLS provide users of wireless LAM with integrity and confidentiality services, and also they perform authentication and access control of wireless ports. In this paper, we suggest a method to implement accounting session using authentication session of IEEE 802. 1x and accounting state machine is designed with the accounting session. Also, we propose a key exchange mechanism to establish secure channel between stations and an access point. The mechanism is designed to be inter-operable with IEEE 802. 1aa.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.5
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• pp.434-441
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• 2004

In this paper, an exoskeleton-type motion capturing system is designed and implemented. The device is designed to have 12 degree-of-freedom entirely to represent human arm motions. Forward and inverse kinematics of the device are analyzed to make sure of its singular positions. With the designed model parameters, simulation studies are conducted to verify that the designed motion capturing system is effective to represent human motions within the workspace. As a counterpart of the exoskeleton system, a mobile robot is built to follow human motion restrictively. Experimental studies of teleoperation from the exoskeleton device to control the mobile robot are carried out to show feasible application of wireless man-machine interface.

• Journal of Information Processing Systems
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• v.16 no.3
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• pp.523-529
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• 2020

Future information and communication technology (ICT) is constantly evolving and converging in diverse fields depending on the wireless environment, and the trend is being further developed to increase the speed of wireless networks. Future ICT is needed in many areas such as active senior & solo-economy, hyper-connected society, intelligent machine, industrial boundary collapse, secured self, and the sharing economy. However, a lot of research is needed to solve problems such as machine learning, security, prediction, unmanned technology, etc. Therefore, this paper describes some technologies developed in the areas of blockchain, fault diagnosis, security, agricultural ICT, cloud, life safety and care, and climate monitoring in order to provide insights into the future paradigm.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.2
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• pp.85-97
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• 2011

Wireless sensor networks have emerged as one of the key enabling technologies for ubiquitous computing since wireless intelligent sensor nodes connected by short range communication media serve as a smart intermediary between physical objects and people in ubiquitous computing environment. We recognize the wireless sensor network as a massively distributed and deeply embedded system. Such systems require concurrent and asynchronous event handling as a distributed system and resource-consciousness as an embedded system. Since the operating environment and architecture of wireless sensor networks, with the seemingly conflicting requirements, poses unique design challenges and constraints to developers, we propose a very new operating system for sensor nodes based on finite state machine. In this paper, we clarify the design goals reflected from the characteristics of sensor networks, and then present the heart of the design and implementation of a compact and efficient state-driven operating system, SenOS. We describe how SenOS can operate in an extremely resource constrained sensor node while providing the required reactivity and dynamic reconfigurability with low update cost. We also compare our experimental results after executing some benchmark programs on SenOS with those on TinyOS.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.1
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• pp.83-97
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• 2021

Wireless sensors that make up the Wireless Sensor Network generally have extremely limited power and resources. The wireless sensor enters the sleep state at a certain interval to conserve power. The Sleep deflation attack is a deadly attack that consumes power by preventing wireless sensors from entering the sleep state, but there is no clear countermeasure. Thus, in this paper, using clustering-based binary search tree structure, the Sleep deprivation attack detection model is proposed. The model proposed in this paper utilizes one of the characteristics of both attack sensor nodes and normal sensor nodes which were classified using machine learning. The characteristics used for detection were determined using Long Short-Term Memory, Decision Tree, Support Vector Machine, and K-Nearest Neighbor. Thresholds for judging attack sensor nodes were then learned by applying the SVM. The determined features were used in the proposed algorithm to calculate the values for attack detection, and the threshold for determining the calculated values was derived by applying SVM.Through experiments, the detection model proposed showed a detection rate of 94% when 35% of the total sensor nodes were attack sensor nodes and improvement of up to 26% in power retention.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.2
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• pp.354-359
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• 2016

Power plants maintenance data is to be sent to management server system via a communication network. In this case, reliable communication network is required. Transmission of the power plants maintenance data is used in the wired communication network or wireless communication network. PLC communication network is a kind of wired communication network. However PLC communication network is easily affected by noise. On the vulnerable areas in power line system, such as a mountain or rural areas, it is difficult to form a power line communication network. For a wireless communication, environment are also influenced factors in wireless communication. Harsh environmental factors are bring the communication characteristic degradation. In such areas it can be used a combination of two networks and in this way the complementary function can be achieved. Power plants are distributed in various regions across the country. The appropriate communication network is needed to maintain the power plant.This study investigated the effect of environment on the wired communication and wireless communication. It would examine a variable factor which is affect to the communication characteristic. We used PLC communication for wired communication network and ZigBee communication for wireless communication network. We investigated the characteristics of a single communication network and it raised the need for a complex communication technology to complement a single communication network.

• Journal of Biosystems Engineering
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• v.32 no.3
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• pp.197-205
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• 2007

The objective of this study was to design and implement a gateway for remote monitoring a combine. Many researchers have designed and implemented trouble-shooting system of agricultural machine. but the system didn't have network system or used wired network system. But monitoring machine have been operated in the out of door. In such an environment, each machine have to be operated under on a guarantee of mobility and stability. Thus, we have developed a gateway with an embedded system including the XScale PXA255 processor and wireless network device. We have also built an embedded Linux kernel and several devices. We developed an embedded application for monitoring a combine and this application is also capable of receiving signals from other clients and sending them to a server via Wireless LAN. Finally, results of performance evaluation which measured CPU share and memory sizes have shown that it is possible to provide monitoring service stably.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.571-573
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• 2018

The loss of data collected from the sensor node in the wireless sensor network environment is caused by the hidden node of the sensor node and power shortage. In order to solve these problems, researches have been actively carried out to maintain the network effectively, but there is no study on the situation where the maintenance of the network is impossible. Therefore, research is needed to infer lost data in situations where network maintenance is impossible. In this paper, use particulate matter data of specific cities to deduce lost data. Analyze the accumulated data through machine learning and identify the possibility of inferring lost data.

• ETRI Journal
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• v.44 no.5
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• pp.733-745
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• 2022

In software-defined wireless networking (SDWN), the optimal routing technique is one of the effective solutions to improve its performance. This routing technique is done by many different methods, with the most common using integer linear programming problem (ILP), building optimal routing metrics. These methods often only focus on one routing objective, such as minimizing the packet blocking probability, minimizing end-to-end delay (EED), and maximizing network throughput. It is difficult to consider multiple objectives concurrently in a routing algorithm. In this paper, we investigate the application of machine learning to control routing in the SDWN. An intelligent routing algorithm is then proposed based on the machine learning to improve the network performance. The proposed algorithm can optimize multiple routing objectives. Our idea is to combine supervised learning (SL) and reinforcement learning (RL) methods to discover new routes. The SL is used to predict the performance metrics of the links, including EED quality of transmission (QoT), and packet blocking probability (PBP). The routing is done by the RL method. We use the Q-value in the fundamental equation of the RL to store the PBP, which is used for the aim of route selection. Concurrently, the learning rate coefficient is flexibly changed to determine the constraints of routing during learning. These constraints include QoT and EED. Our performance evaluations based on OMNeT++ have shown that the proposed algorithm has significantly improved the network performance in terms of the QoT, EED, packet delivery ratio, and network throughput compared with other well-known routing algorithms.