• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1259-1276
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• 2017

As technologies related to sensor network are currently emerging and the use of GeoSensor is increasing along with the development of Internet of Things (IoT) technology, spatial query processing systems to efficiently process spatial sensor data are being actively studied. However, existing spatial query processing systems do not support a spatial-temporal data type and a spatial-temporal operator for processing spatialtemporal sensor data. Therefore, they are inadequate for processing spatial-temporal sensor data like GeoSensor. Accordingly, this paper developed a spatial-temporal query processing system, for efficient spatial-temporal query processing of spatial-temporal sensor data in a sensor network. Lastly, this paper verified the utility of System through a scenario, and proved that this system's performance is better than existing systems through performance assessment of performance time and memory usage.

• Smart Structures and Systems
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• v.33 no.6
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• pp.465-482
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• 2024

In this paper, a robust wireless sensor network configuration design method is proposed to develop the optimal configuration under the consideration of sensor failure and energy consumption. A malfunctioned sensor in a wireless sensor network may lead to data transmission failure of the entire sensing cluster, inducing severe deterioration in system identification performance. The proposed method determines a wireless sensor network configuration that is robust against sensor failure. By utilizing Bayesian inference, we introduce a robust indicator to evaluate the impact on estimation accuracy of sensor configurations with various malfunctioned sensors. Moreover, a network formation strategy is proposed to optimize the energy efficiency of the wireless sensor network configuration. Therefore, the resultant robust wireless sensor network configuration can operate with the minimum energy consumption while the measurement information of the sensor network with malfunctioned sensors can be guaranteed. The proposed method is illustrated by designing the robust wireless sensor network configurations of a truss model and a bridge model.

• The KIPS Transactions:PartC
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• v.14C no.6
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• pp.519-524
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• 2007

One of the most important issues on the sensor network with resource limited sensor nodes is prolonging the network lifetime by effectively utilizing the limited node energy. The most representative mechanism to achieve a long lived sensor network is the clustering mechanism which can be further classified into the single hop mode and the multi hop mode. The single hop mode requires that all sensor nodes in a cluster communicate directly with the cluster head(CH) via single hop md, in the multi hop mode, sensor nodes communicate with the CH with the help of other Intermediate nodes. One of the most critical factors that impact on the performance of the existing multi hop clustering mechanism is the cluster size and, without the assumption on the uniform node distribution, finding out the best cluster size is intractable. Since sensor nodes in a real sensor network are distributed non uniformly, the fixed size mechanism may not work best for real sensor networks. Therefore, in this paper, we propose a new dynamic size multi hop clustering mechanism in which the cluster size is determined according to the distance from the sink to relieve the traffic passing through the CHs near the sink. We show that our proposed scheme outperforms the existing fixed size clustering mechanisms by carrying out numerical analysis and simulations.

• Journal of Communications and Networks
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• v.16 no.4
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• pp.465-474
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• 2014

Wireless sensor network (WSN) is considered to be one of the most important research fields for ubiquitous healthcare (u-healthcare) applications. Healthcare systems combined with WSNs have only been introduced by several pioneering researchers. However, most researchers collect physiological data from medical nodes located at static locations and transmit them within a limited communication range between a base station and the medical nodes. In these healthcare systems, the network link can be easily broken owing to the movement of the object nodes. To overcome this issue, in this study, the fast link exchange minimum cost forwarding (FLE-MCF) routing protocol is proposed. This protocol allows real-time multi-hop communication in a healthcare system based on WSN. The protocol is designed for a multi-hop sensor network to rapidly restore the network link when it is broken. The performance of the proposed FLE-MCF protocol is compared with that of a modified minimum cost forwarding (MMCF) protocol. The FLE-MCF protocol shows a good packet delivery rate from/to a fast moving object in a WSN. The designed wearable platform utilizes an adaptive linear prediction filter to reduce the motion artifacts in the original electrocardiogram (ECG) signal. Two filter algorithms used for baseline drift removal are evaluated to check whether real-time execution is possible on our wearable platform. The experiment results shows that the ECG signal filtered by adaptive linear prediction filter recovers from the distorted ECG signal efficiently.

• Convergence Security Journal
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• v.5 no.4
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• pp.49-58
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• 2005

We propose a specific ubiquitous sensor network (USN) architecture as a promising candidate of the future telemedicine model which offers the patient's mobility and more cost-efficient medical care system. This new USN architecture is a kind of cell-based secure sensor network supporting encrypted multi-casting communications and it has a hybrid routing protocol by adapting flat routing to hierarchical routing. For the patient's privacy and the protection of patient's vital information from eavesdropping, we adopt a lightweight PKI-based secure communication protocol with some formal presentation on its core procedure.

• Journal of the Korea Society of Computer and Information
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• v.10 no.4 s.36
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• pp.239-248
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• 2005

The reliability and efficiency of network must be considered in the large scale wireless sensor networks. Broadcast method must be used rather than unicast method to enhance the reliability of networks. In recently proposed GRAB (GRAdient Broadcast) can certainly enhance reliability of networks fy using broadcast but its efficiency regarding using energy of network is low due to using only one sink. Hence, the lifetime of networks is reduced. In the paper we propose the scheme of SMSGB (Selective Multi Sink Gradient Broadcast) which uses single sink of multi-sink networks. The broadcast based SMSGB can secure reliability of large scale wireless sensor networks. The SMSGB can also use the network's energy evenly via multi sink distribution. Our experiments show that using SMSGB was reliable as GRAB and it increased the network's lifetime by 18% than using GRAB.

• Journal of Advanced Navigation Technology
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• v.11 no.4
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• pp.408-414
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• 2007

Research advances in the areas of micro-sensor device and wireless network technology, has made it possible to develop energy efficient and low cost wireless sensor nodes. In this paper, the forward error control (FEC) scheme for lower power consumption and excellent BER(Bit Error Rate) performance during transmission propose in multi-hop wireless sensor network based on FSK modem. The FEC technique uses extra processing power related to encoding and decoding, it is need complex functions to be built into the sensor node. The probability of receiving a correct bit and codeword for relaying a frame over h nodes to the sink node is calculated as a function of channel parameter, number of hops, number of bits transmitted and the distance between the different nodes.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.6
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• pp.1238-1240
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• 2009

In the wireless sensor network, cooperative transmission is an effective technique to combat multi-path fading and reduce transmitted power. Relay selection and power allocation are important technical issues to determine the performance of cooperative transmission. In this paper, we proposed a new multi-relay selection and power allocation algorithm to increase network lifetime. The proposed relay selection scheme minimizes the transmitted power and increase the network lifetime by considering residual power as well as channel conditions. Simulation results show that proposed algorithm obtains much longer network lifetime than the conventional algorithm.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.5
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• pp.913-919
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• 2011

In this paper, we present a new efficient event detection algorithm for sensor networks with faults. We focus on multi-attributed events, which are sets of data points that correspond to interesting or unusual patterns in the underlying phenomenon that the network monitors. Conventional algorithms cannot detect some events because they treat only their own sensor readings which can be affected easily by environmental or physical problem. Our approach exploits spatio-temporal correlation of sensor readings. Sensor nodes exchange a fault-tolerant code encoded their own readings with neighbors, organize virtual sensor readings which have spatio-temporal correlation, and determine a result for multi-attributed events from them. In the result, our proposed algorithm provides improvement of detecting multi-attributed events and reduces the number of false-negatives due to negative environmental effects.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.6
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• pp.736-741
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• 2005

The highly popular algorithm to determine routing path for the multi-hopping wireless sensor network is DSR(Dynamic Source Routing), which is one of the Demand-Driven way to makes the route only when there is a request for sending data. However, because DSR attaches the route's record on the sending packet, the bigger number of sensor node is, the heavier packet in DSR becomes. In this paper, we try to propose the new optimal routing path selecting algorithm which does not make the size of packet bigger by using proper routing table even though the number of sensor node increases, and we try to show our algorithm is more stable and reliable because it is based on the cost function considering some network resources of each sensor node such as power consumption, mobility, traffic in network, distance(hop) between source and destination.