• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.7A
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• pp.697-705
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• 2010

In Wireless Sensor Networks (WSNs), blanket (area) coverage analysis is generally carried to find the minimum number of active sensor nodes required to cover a monitoring interest area with the desired fractional coverage-threshold. Normally, the coverage analysis is performed using the stochastic geometry as a tool. The major component of such coverage analysis is the assumed sensing model. Hence, the accuracy of such analysis depends on the underlying assumption of the sensing model: how well the assumed sensing model characterizes the real sensing phenomenon. In this paper, we review the coverage analysis for different deterministic and probabilistic sensing models like Boolean and Shadow-fading model; and extend the analysis for Exponential and hybrid Boolean-Exponential model. From the analytical performance comparison, we demonstrate the redundancy (in terms of number of sensors) that could be resulted due to the coverage analysis based on the detection capability mal-characterizing sensing models.

• Journal of Environmental Impact Assessment
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• v.13 no.5
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• pp.263-276
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• 2004

This research is primarily intended to propose a new concept for aggregate control of impervious coverage using remote sensing and GIS. An empirical study for a case study site was conducted to demonstrate how a standard remote sensing and GIS technology can be used to assist in implementing the aggregate control for impervious coverage as intermediary between decision makers and scientists. Guidelines for a replicable methodology are presented to provide a strong theoretical basis for the standardization of factors involved in the aggregate control; the meaningful definition of land mosaic in terms of pervious areas, classification of pervious intensity, change detection for pervious areas. Detailed visual maps (e.g. estimation of impervious surface allowable) can be generated over large areas quickly and easily to increase the scientific and objective decision-making for the aggregate control. It is anticipated that this research output could be used as a valuable reference to confirm the potential of remote sensing and GIS in the aggregate control for impervious coverage.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1105-1107
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• 2003

Remote sensing data processing and analysis system can be developed based on the Grid Coverage Specification and this kind of system is also can be easily interoperate with GIS systems conforming OpenGIS specification. This paper proposes a method to implement easily and quickly the new grid coverages that provide new operations, or services, by reusing the existing grid coverage components, which is based on the fact that the pipeline constructed by grid coverages can be represented in one grid coverage. This method complements easily the deficiency of the existing grid coverage components and enables quick implementation of the new grid coverage that provides complex processing operations.

• Journal of Sensor Science and Technology
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• v.22 no.4
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• pp.268-275
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• 2013

Efficient energy management becomes a critical design issue for complex WSN (Wireless Sensor Network). Most of complex WSN employ the sleep mode to reduce the energy dissipation. However, it should cause the reduction of sensing coverage. This paper presents new wake-up algorithm for reducing energy consumption in complex WSN. The proposed wake-up algorithm is devised using geometric probability. It determined which node will be waked-up among the nodes having overlapped sensing coverage. The only one sensor node will be waked-up and it is ready to sense the event occurred uniformly. The simulation results show that the lifetime is increased by 15% and the sensing coverage is increased by 20% compared to the other scheduling methods. Consequently, the proposed wake-up algorithm can eliminate the power dissipation in the overlapped sensing coverage. Thus, it can be applicable for the various WSN suffering from the limited power supply.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.564-564
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• 2004

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.116-119
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• 2015

In this paper we propose an algorithm for environment monitoring using multiple mobile sensor (MS) nodes. Our focus is on maximizing sensing coverage of a group of MS nodes for monitoring a phenomenon in an unknown and open area over time. In the proposed algorithm, MS nodes are iteratively relocated to new positions at which a higher sensing coverage can be obtained. We formulated an integer linear programming (ILP) optimization problem to find the optimal positions for MS nodes with the objective of coverage maximization. The performance evaluation was performed to confirm that the proposed algorithm can enable MS nodes to relocate to high interest positions, and obtain a maximum sensing coverage.

• Journal of the Korea Society of Computer and Information
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• v.21 no.1
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• pp.73-78
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• 2016

In wireless sensor networks, sensors have capabilities of sensing and wireless communication, computing power and collect data such as sound, movement, vibration. Sensors need to communicate wirelessly to send their sensing data to other sensors or the base station and so they are vulnerable to many attacks like garbage packet injection that cannot be prevented by using traditional cryptographic mechanisms. To defend against such attacks, a behavior-based attack detection is used in which some specialized monitoring nodes overhear the communications of their neighbors(normal nodes) to detect illegitimate behaviors. It is desirable that the total sensing area of normal nodes covered by monitoring nodes is as large as possible. The previous researches have focused on selecting the monitoring nodes so as to maximize the number of normal nodes(node coverage), which does not guarantee that the area sensed by the selected normal nodes is maximized. In this study, we have developed an algorithm for selecting the monitoring nodes needed to cover the maximum sensing area. We also have compared experimentally the covered sensing areas computed by our algorithm and the node coverage algorithm.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1310-1311
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• 2003

Oil Field Geographical Information System (OFGIS) manages multiple spatial data, attribute data, and topographic data, which include almost every kind of ground info rmation and underground information. Subsystems managed by OFGIS include petroleum exploration subsystem (PESS), petroleum development and engineering subsystem (PDESS), petrochemical subsystem (PCSS), petroleum storage and transportation subsystem (PSTSS), petroleum sale subsystem (PSSS), etc. A basic OFGIS framework consists of oil field infrastructure coverage (OFIC), oil field specialized information coverage (OFSIC) and oil field synthesis and decision service coverage (OFSDSC). Basic function of OFGIS includes database management, geographic information management, spatial information processing and application.

• Proceedings of KOSOMES biannual meeting
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• 2018.06a
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• pp.5-5
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• 2018

• 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.