• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.147-151
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• 2005

CAN(Controller Area Network) is a simple and efficient network system for real time control and measurement. As it is not only good at error detection but also strong in electromagnetic interference, CAN has been widely used all over the industries. Basically, CAN needs a master node in charge of sensor data collection, node scheduling for data transmission to a monitoring system and error detection. According to the number of mater nodes, the CAN system is classified into two type of master system. One is a single master system that has only one master node and the other is a multi-master system where any sensor node can become a master node depending on the system's conditions. While it has the advantage of its fault tolerance, the multi-master system will suffer form the overall performance degradation when a defect is found in the master node. It is because all sensor nodes pertaining to a defective master node lose their position. Moreover, it is difficult and expensive to implement. For a single master system, the whole system will be broken down when a problem happens to a single master. In this paper, a dynamic master system is presented that there are several sub-master nodes of which basic functions are those of other sensor nodes at ordinary times but dynamically changed to replace the failing master node. An effective scheduling algorithm is also proposed to choose an appropriate node among sub-master nodes, where each sub-master node has its precedence value. The performance of the dynamic master system is experimented and analyzed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.3B
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• pp.493-502
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• 2010

In this paper we propose a scalable sensor network system that makes mesh network among the sink nodes to solve the scalability problem of existing sensor network which is caused by multi-hop networking between the sensor nodes. In the proposed system, the sink nodes have the wireless networking ability to communicate with another sink nodes in mesh fashion, and with the monitoring nodes which is located in the local area or internet area. Especially, the system includes L4(Application Layer) routing mechanism that provides subscribe/publish service to serve selective transmission of sensor data to the specific monitoring nodes. The collected sensor data is transmitted to the monitoring nodes when the sensor data is matched with the monitoring node's interesting value.

• Journal of Information Processing Systems
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• v.2 no.1
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• pp.39-43
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• 2006

In this paper, we proposed TASL-MAC, a medium-access control (MAC) protocol for wireless sensor networks. In wireless sensor networks, sensor nodes are usually deployed in a special environment, are assigned with long-term work, and are supported by a limited battery. As such, reducing the energy consumption becomes the primary concern with regard to wireless sensor networks. At the same time, reducing the latency in multi-hop data transmission is also very important. In the existing research, sensor nodes are expected to be switched to the sleep mode in order to reduce energy consumption. However, the existing proposals tended to assign the sensors with a fixed Sleep/Listening schedule, which causes unnecessary idle listening problems and conspicuous transmission latency due to the diversity of the traffic-load in the network. TASL-MAC is designed to dynamically adjust the duty listening time based on traffic load. This protocol enables the node with a proper data transfer rate to satisfy the application's requirements. Meanwhile, it can lead to much greater power efficiency by prolonging the nodes' sleeping time when the traffic. We evaluate our implementation of TASL-MAC in NS-2. The evaluation result indicates that our proposal could explicitly reduce packet delivery latency, and that it could also significantly prolong the lifetime of the entire network when traffic is low.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.5B
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• pp.557-565
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• 2011

In this paper, we assume that sensor nodes organize the multi-hop networks, are fixed, and operate as full function devices(FFD). The wireless sensor network(WSN) only consists of mobile nodes without the assistance from the fixed infrastructure, which increases the flexibility of the network. However, it is difficult to perform routing in the WSN, since sensor nodes freely join in and drop out of the network, and some sensor nodes have very low power. We propose the algorithm combining routing schemes based on the bitmap and cluster methods in this paper. Through computer simulations, we show the validity of the proposed algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.4
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• pp.793-797
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• 2004

Wireless sensor networks use battery-operated computing and sensing devices. And It can be expected to be deployed in an ad hoc networs. MAC is different from traditional wireless MACs such as IEEE 802.11 in almost every way. so self-configuration and power saving in sensor network are very important goals, while per-node fairness and latency are less important. In this paper, so we use a given prototype for efficient energy conservation to reduce power consumtion that is one of the important character in sensor network and compare energy consumption and collision with IEEE 802.11 MAC. finally we conclude the paper and analyze it.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.182-185
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• 2004

Wireless sensor networks use battery-operated computing and sensing devices. And It can be expected to be deployed in an ad hoc networs. MAC is different from traditional wireless MACs such as IEEE 802.11 in almost every way. so self-configuration and power saving in sensor network are very important goals, while per-node fairness and latency are less important. In this paper, so we use a given prototype for efficient energy conservation to reduce power consumtion that is one of the important character in sensor network and compare energy consumption and collision with IEEE 802.11 MAC. Finally we conclude the paper and analyze it.

• Journal of Sensor Science and Technology
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• v.8 no.6
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• pp.461-468
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• 1999

In this paper, we have implemented a gas recognition system for classification and identification of explosive gases such as methane, propane, and butane using a sensor array and an artificial neural network. Such explosive gases which can be usually detected in the oil factory and LPG pipeline are very dangerous for a human being. We analyzed the characteristics of a multi-dimensional sensor signals obtained from the nine sensors using the principal component analysis(PCA) technique. Also, we implemented a gas pattern recognizer using a multi-layer neural network with error back propagation learning algorithm, which can classify and identify the sorts of gases and concentrations for each gas. The simulation and experimental results show that the proposed gas recognition system is effective to identify the explosive gases. And also, we used DSP board(TMS320C31) to implement the proposed gas recognition system using the neural network for real time processing.

• Journal of Digital Contents Society
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• v.15 no.6
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• pp.663-673
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• 2014

The WBAN technology means a short distance wireless network which provides each device interactive communication by connecting devices inside and outside of body. Standardization on the physical layer, data link layer, network layer and application layer is in progress by IEEE 802.15.6 TG BAN. Wireless body area network is usually configured in energy efficient using sensor and zigbee device due to the power limitation and the characteristics of human body. Wireless sensor network consist of sensor field and sink node. Sensor field are composed a lot of sensor node and sink node collect sensing data. Wireless sensor network has capacity of the self constitution by protocol where placed in large area without fixed position. In this paper, we proposed the efficient addressing scheme for improving the performance of routing algorithm by using ZigBee in WBAN environment. A distributed address allocation scheme used an existing algorithm that has wasted in address space. Therefore proposing x, y and z coordinate axes from divided address space of 16 bit to solve this problems. Each node was reduced not only bitwise but also multi hop using the coordinate axes while routing than Cskip algorithm. I compared the performance between the standard and the proposed mechanism through the numerical analysis. Simulation verified performance about decrease averaging multi hop count that compare proposing algorithm and another. The numerical analysis results show that proposed algorithm reduced the multi hop better than ZigBee distributed address assignment

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.6
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• pp.1142-1147
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• 2015

As a method to increase the scalability and efficiency of wireless sensor networks, a scheme to construct networks hierarchically has received considerable attention among researchers. Researches on the methods to construct wireless networks hierarchically have been conducted focusing on how to select nodes such that they constitute a backbone network of wireless network. Nodes comprising the backbone network should be connected themselves and can cover other remaining nodes. A problem to find the minimum number of nodes which satisfy these conditions is known as the minimum connected dominating set (MCDS) problem. The MCDS problem is NP-hard, therefore there is no efficient algorithm which guarantee the optimal solutions for this problem at present. In this paper, we propose a novel multi-start local search algorithm to solve the MCDS problem efficiently. For the performance evaluation of the proposed method, we conduct extensive experiments and report the results.

• Journal of IKEEE
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• v.26 no.3
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• pp.364-372
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• 2022

This paper proposes the design and implementation results for human and object classification systems utilizing frequency modulated continuous wave (FMCW) radar sensor. Such a system requires the process of radar sensor signal processing for multi-target detection and the process of deep learning for the classification of human and object. Since deep learning requires such a great amount of computation and data processing, the lightweight process is utmost essential. Therefore, binary neural network (BNN) structure was adopted, operating convolution neural network (CNN) computation in a binary condition. In addition, for the real-time operation, a hardware accelerator was implemented and verified via FPGA platform. Based on performance evaluation and verified results, it is confirmed that the accuracy for multi-target classification of 90.5%, reduced memory usage by 96.87% compared to CNN and the run time of 5ms are achieved.