• Journal of Communications and Networks
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• v.17 no.5
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• pp.473-481
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• 2015

In this study, we propose a clustering algorithm to enhance the performance of wireless sensor and actuator networks (WSANs). In each cluster, a multi-level hierarchical structure can be applied to reduce energy consumption. In addition to the cluster head, some nodes can be selected as intermediate nodes (INs). Each IN manages a subcluster that includes its neighbors. INs aggregate data from members in its subcluster, then send them to the cluster head. The selection of intermediate nodes aiming to optimize energy consumption can be considered high computational complexity mixed-integer linear programming. Therefore, a heuristic lowest energy path searching algorithm is proposed to reduce computational time. Moreover, a channel assignment scheme for subclusters is proposed to minimize interference between neighboring subclusters, thereby increasing aggregated throughput. Simulation results confirm that the proposed scheme can prolong network lifetime in WSANs.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1320-1330
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• 2017

Wireless sensor networks for forest monitoring are typically deployed in fields in which manual intervention cannot be easily accessed. An interesting approach to extending the lifetime of sensor nodes is the use of energy harvested from the environment. Design constraints are application-dependent and based on the monitored environment in which the energy harvesting takes place. To reduce energy consumption, we designed a power management scheme that combines dynamic duty cycle scheduling at the network layer to plan node duty time. The dynamic duty cycle scheduling is realized based on a tier structure in which the network is concentrically organized around the sink node. In addition, the multi-paths preserved in the tier structure can be used to deliver residual packets when a path failure occurs. Experimental results show that the proposed method has a better performance.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.9 s.180
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• pp.2361-2370
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• 2000

The introduction of inexpensive cylinder pressure sensors provides new opportunities for precise engine control. This paper presents a control strategy of spark advance based upon cylinder pressure of spark ignition engines. A location of peak pressure(LPP) is the major parameter for controlling the spark timing, and also the UP is estimated, using a multi-layer feedforward neural network, which needs only five pressure sensor output voltage samples at -40˚, -20˚, 0˚, 20˚, 40˚ after top dead center. The neural network plays an important role in mitigating the A/D conversion load of an electronic engine controller by increasing the sampling interval from 10 crank angle(CA) to 20˚ CA. A proposed control algorithm does not need a sensor calibration and pegging(bias calculation) procedure because the neural network estimates the UP from the raw sensor output voltage. The estimated LPP can be regarded as a good index for combustion phasing, and can also be used as an MBT control parameter. The feasibility of this methodology is closely examined through steady and transient engine operations to control individual cylinder spark advance. The experimental results have revealed a favorable agreement of individual cylinder optimal combustion phasing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.5014-5034
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• 2016

This paper discusses how to effectively guarantee the coverage and connectivity quality of wireless sensor networks when joint perception model is used for the nodes whose communication ranges are multi-level adjustable in the absence of position information. A Connect Coverage Algorithm Based on Joint Sensing model (CCAJS) is proposed, with which least working nodes are chosen based on probability model ensuring the coverage quality of the network. The algorithm can balance the position distribution of selected working nodes as far as possible, as well as reduce the overall energy consumption of the whole network. The simulation results show that, less working nodes are needed to ensure the coverage quality of networks using joint perception model than using the binary perception model. CCAJS can not only satisfy expected coverage quality and connectivity, but also decrease the energy consumption, thereby prolonging the network lifetime.

• IEMEK Journal of Embedded Systems and Applications
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• v.2 no.4
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• pp.242-250
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• 2007

Wireless sensor networks are subject to highly heterogeneous system requirements in terms of their functionality and performance due to their broad application areas. Though the heterogeneity hinders the opportunity of developing a single universal platform for sensor networks, efforts to provide uniform, inter-operable and scalable ones for sensor networks are still essential for the growth of the industry as well as their technological advance. As a part of our work to develop such a robust platform, this paper presents the software architecture for sensor nodes with focus on our sensor node operating system and its configuration methodology. Addressing principle issues in its design space which includes programming, execution, task scheduling and software layer models, our architecture is highly reconfigurable with respect to system resources and functional requirements and also highly efficient in supporting multi-threading under small system resources.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.1051-1059
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• 2014

In this paper, we propose an intelligent situation recognition model by collecting and analyzing multiple sensor signals. Multiple sensor signals are collected for fixed time window. A training set of collected sensor data for each situation is provided to K2-learning algorithm to generate Bayesian networks representing causal relationship between sensors for the situation. Statistical characteristics of sensor values and topological characteristics of generated graphs are learned for each situation. A neural network is designed to classify the current situation based on the extracted features from collected multiple sensor values. The proposed method is implemented and tested with UCI machine learning repository data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.7
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• pp.4536-4544
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• 2014

This paper proposes a development tool to efficiently develop node software for various operating system platforms in a sensor network. The proposed tool consisted of several modules, such as writing graphical model diagram, PIM and PSM design, code generation, and deployment file generation. Through the proposed tool, the users can graphically draw a sensor network model and design the PIM and PSM of the node software by setting the values of the predefined attributes. The source code of the node software is generated automatically from the PSM using the code templates of the target platform. The deployment files for installing node software on each node are generated automatically. The proposed tool helps the users to develop node software easily for a range of target platforms, even though they do not have details of the low-level information for a sensor network.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.12
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• pp.3071-3095
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• 2013

Configuring optimization of wireless sensor networks, which can improve the network performance such as utilization efficiency and network lifetime with minimal energy, has received considerable attention in recent years. In this paper, a cross layer optimal approach is proposed for multi-source linear network and grid network under Rayleigh block-fading channels, which not only achieves an optimal utility but also guarantees the end-to-end reliability. Specifically, in this paper, we first strictly present the optimization method for optimal nodal number $N^*$, nodal placement $d^*$ and nodal transmission structure $p^*$ under constraints of minimum total energy consumption and minimum unit data transmitting energy consumption. Then, based on the facts that nodal energy consumption is higher for those nodes near the sink and those nodes far from the sink may have remaining energy, a cross layer optimal design is proposed to achieve balanced network energy consumption. The design adopts lower reliability requirement and shorter transmission distance for nodes near the sink, and adopts higher reliability requirement and farther transmission distance for nodes far from the sink, the solvability conditions is given as well. In the end, both the theoretical analysis and experimental results for performance evaluation show that the optimal design indeed can improve the network lifetime by 20-50%, network utility by 20% and guarantee desire level of reliability.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.1038-1041
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• 2009

Wireless sensor network with wireless sensor nodes which equipped with temperature, humidity, illumination, or soil sensor etc, get a natural environment information and analyze and utilized variety way.these network consist of a short distance wireless communication and multi-hop techniques with multiple nodes equipped low-power wireless transceivers. so the characteristic of the data collected through the wireless sensor network is obtained from compact nodes within a limited range. However, to get a data from the wireless sensor nodes scattered in a wide range, this network needs a wireless transceiver that consumes many power or a lot of intermediate nodes. then, merit of low cost and low electrical energy decrease. To solve this problem, this paper offers environment monitoring system using autonomous mobile robot that collect data from groups of each sensor networks scattered widely.