• Journal of the Korean Society for Railway
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• v.11 no.4
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• pp.364-370
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• 2008

In this paper, we proposed new sensor network architecture with autonomous robots based on beacon mode and implemented real time monitoring system in real test-bed environment. The proposed scheme offers beacon based real-time scheduling for reliable association process with parent nodes and dynamically assigns network address by using NAA (Next Address Assignment) mechanism. For the large scale multi-sensor processing, our real-time monitoring system accomplished the intelligent database processing, which can generate not only the alert messages to the civilians but also process various sensing data such as fire, air, temperature and etc. Moreover, we also developed mobile robot which can support network mobility. Though the performance evaluation by using real test-bed system, we illustrate that our proposed system demonstrates promising performance for emergence monitoring systems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.9
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• pp.1704-1709
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• 2016

In this paper, we propose efficient uplink data transmission method in ultra dense wireless networks as in intra-aircraft, where large-scale APs and wireless sensors are deployed. In the ultra dense wireless networks, a performance degradation is inevitable due to the inter-AP interference. However, the performance degradation can be avoided if a scheduling algorithm can estimate the amount of interference caused by each wireless sensor and reflects it. SGIR (Signal-to-Generating Interference Ratio) based scheduling algorithms is a typical example. Unfortunately, the scheduling algorithms based on the interference caused by wireless sensors necessarily yield large scale exchange of information through backhaul which connects APs. Therefore, we, in this paper, propose a novel scheme which can dramatically reduce the amount of information which are exchanged through backhaul connection. Monte-Carlo simulation results show that the proposed scheme can reduce the amount of backhaul traffic by 27% without loss of data transmission rate.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.505-524
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• 2010

Wireless structural monitoring systems consist of networks of wireless sensors installed to record the loading environment and corresponding response of large-scale civil structures. Wireless monitoring systems are desirable because they eliminate the need for costly and labor intensive installation of coaxial wiring in a structure. However, another advantageous characteristic of wireless sensors is their installation modularity. For example, wireless sensors can be easily and rapidly removed and reinstalled in new locations on a structure if the need arises. In this study, the reconfiguration of a rapid-to-deploy wireless structural monitoring system is proposed for monitoring short- and medium-span highway bridges. Narada wireless sensor nodes using power amplified radios are adopted to achieve long communication ranges. A network of twenty Narada wireless sensors is installed on the Yeondae Bridge (Korea) to measure the global response of the bridge to controlled truck loadings. To attain acceleration measurements in a large number of locations on the bridge, the wireless monitoring system is installed three times, with each installation concentrating sensors in one localized area of the bridge. Analysis of measurement data after installation of the three monitoring system configurations leads to reliable estimation of the bridge modal properties, including mode shapes.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.3
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• pp.379-387
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• 2013

In large-scale wireless sensor networks, tremendous amount of dummy packets is usually accompanied by keeping location privacy of the communication source and destination against global eavesdropping. In our earlier work we designed a location privacy routing protocol, ELPR(End-node Location Privacy Routing) in which the generation of dummy packets at each idle time-slot while transferring data packets are restricted to only the nodes within certain areas of encompassing the source and destination, respectively. In this paper, it is given that ELPR provides various degrees of location privacy while PCM(Periodic Collection Method) allows the only fixed level. Simulation results show that as the number of nodes or data packets increases ELPR permits in terms of the number of generated packets more cost-effective location privacy than PCM.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.1070-1088
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• 2017

Recently, the applications of Internet of Things (IoTs) are growing rapidly. Wireless Sensor Network (WSN) becomes an emerging technology to provide the low power wireless connectivity for IoTs. The IPv6 over low-power wireless personal area networks (6LoWPAN) has been proposed by IETF, which gives each WSN device an IPv6 address to connect with the Internet. The transmission congestion in IoTs could be a problem when a large numbers of sensors are deployed in the field. Therefore, it is important to consider whether the WSN devices have be completely integrated into the Internet with proper quality of service (QoS) requirements. The Software Defined Network (SDN) is a new architecture of network decoupling the data and control planes, and using the logical centralized control to manage the forwarding issues in large-scale networks. In this research, the SDN-based 6LoWPAN Border Router (6LBR) is proposed to integrate the transmission from WSNs to Internet. The proposed SDN-based 6LBR communicating between WSNs and the Internet will bring forward the requirements of end-to-end QoS with bandwidth guarantee. Based on our experimental results, we have observed that the selected 6LoWPAN traffic flows achieve lower packet loss rate in the Internet. Therefore, the 6LoWPAN traffic flows classified by SDN-based 6LBR can be reserved for the required bandwidth in the Internet to meet the QoS requirements.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.310-318
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• 2018

Recently, the importance of big data analysis is increasing as a large amount of data is generated by various devices connected to the Internet with the advent of Internet of Things (IoT). Especially, it is necessary to analyze various large-scale IoT streaming sensor data generated in real time and provide various services through new meaningful prediction. This paper proposes a real-time indoor PM10 concentration prediction LSTM model based on streaming data generated from IoT sensor using AWS. We also construct a real-time indoor PM10 concentration prediction service based on the proposed model. Data used in the paper is streaming data collected from the PM10 IoT sensor for 24 hours. This time series data is converted into sequence data consisting of 30 consecutive values from time series data for use as input data of LSTM. The LSTM model is learned through a sliding window process of moving to the immediately adjacent dataset. In order to improve the performance of the model, incremental learning method is applied to the streaming data collected every 24 hours. The linear regression and recurrent neural networks (RNN) models are compared to evaluate the performance of LSTM model. Experimental results show that the proposed LSTM prediction model has 700% improvement over linear regression and 140% improvement over RNN model for its performance level.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.8
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• pp.1926-1933
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• 2013

Many localization algorithms have been proposed for Wireless Sensor Networks (WSNs). The IEEE 802.15.4a-based location-aware-system can provide precise ranging distance between two mobile nodes. The mobile nodes can obtain their exact locations by using accurate ranging distances. However, the indoor environments contain various obstacles which cause non-line-of-sight (NLOS) conditions. In NLOS condition, the IEEE 802.15.4a-based location-aware system has a large scale location error. To solve the problem, we propose location error compensation in indoor environment by using MST-based topology control. Experimental and simulation results show that the proposed algorithm improves location accuracy in NLOS conditions.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.4
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• pp.28-38
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• 2009

In this study, a remote air quality monitoring system for underground spaces was developed by using NDIR-based CO$_2$ sensor. And the remote monitoring system based on wireless sensor networks was installed practically on the subway station platform. More than 6.5 million citizens commutate everyday by the Seoul subway transportation that is the most typical public transportation. They concern about air quality with increasing interest on public health or many workers in subway stations or underground shopping centers. Recently, the Korean Ministry of Environment has operated the air quality monitoring system in some subway stations for testing phase. However, it showed many defects which are large-scale, high-cost and maintenance of precision sensors imported from abroad. Therefore this research includes the reliability test and a theoretical study about the inexpensive commercialized CO$_2$ sensor for reliable measurement of air quality which changes rapidly by the surrounding environments. And then we develop the wireless sensor nodes and the gateway applied for remote air quality monitoring. In addition, web server program was realized to manage air quality in the subway platform. This result will be valuable for a basic research for air quality management in underground spaces for future study.

• Journal of Internet Computing and Services
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• v.11 no.4
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• pp.11-22
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• 2010

In case that group communication protocols assume every process is interested in all events occurring in a large scale group, the events multicasting to a subset of a large process group, such as a sensor network, potentially varying for every event based on their interests might lead to very high communication overhead on each individual process. Moreover, despite the importance of both guaranteeing message delivery order and supporting overlapped group using gossip based group communication for multicasting in sensor or P2P networks, there exist little research works on development of gossip-based protocols to satisfy all these requirements. In this paper, we present a new gossip-based causal message order guaranteeing multicast protocol based on local views and delegates representing subgroups and fully utilizing multi-group features to improve scalability. In the proposed protocol, the message delivery order in overlapped groups has been guaranteed consistently by all corresponding members of the groups including delegates. Therefore, these features of the proposed protocol might be significantly scalable rather than those of the protocols guaranteeing atomic order dependencies between multicast messages by hierarchical membership list of dedicated groups like traditional committee protocols and much stronger rather than fully decentralized protocols guaranteeing dependencies between multicast messages based on only local views. And the proposed protocol is a hybrid approach improving the inherent scalability of multicast nature by gossip-based technique in all communications.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.11
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• pp.1589-1597
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• 2016

In this paper, we propose a system in a large-scale environment, such as desert and ocean, that can reduce the overall transmission power consumption in mobile sensor network. It is known that the transmission power consumption in wireless sensor network is proportional to the square of transmission distance. Therefore, if the locations of mobile sensors are far from the sink node, the power consumption required for data transmission increases, leading to shortened operating time of the sensors. Hence, in this paper, we propose a system that can reduce the power consumption by allowing to transmit data only if the transmission range of the sensors is within a predetermined distance. Moreover, the energy efficiency of the overall sensor network can even be improved by reducing the number of data transmissions at the sink node to gateway based on compressed sensing. The proposed system is actually implemented using Arduino and Raspberry Pi and it is confirmed that source data can be approximately decoded even when the gateway received encoded data fewer than the required number of data from the sink node. The performance of the proposed system is analyzed in theory.