• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2658-2679
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• 2018

This paper proposes a novel Random Scheduling Algorithm based on Subregion Coverage (RSASC), to solve the SET K-cover problem (an NP-complete problem). SET K-cover problem distributes the set of sensors into the maximum number of mutually exclusive subsets (MESSs) in such a way that each of them can be scheduled for lifetime extension of WSN. Sensor coverage divides the target region into different subregions. RSASC first sorts the subregions in the ascending order concerning their sensor coverage. Then, it forms the subregion groups according to their similar sensor coverage. Lastly, RSASC ensures the K-coverage of each subregion from every group by randomly scheduling the sensors. We consider the target-coverage and area-coverage applications of WSN to analyze the usefulness of our proposed RSASC algorithm. The distinct quality of RSASC is that it utilizes less number of deployed sensors (33% less) to form the optimum number of MESSs with the higher computational speed (saves more than 93% of the time) as compared to the existing three algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4804-4822
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• 2017

Coverage problem is a research hot spot in directional sensor networks (DSNs). However, the major problem affecting the performance of the current coverage-enhancing strategies is that they just optimize the coverage of networks, but ignore the maximum number of sleep sensors to save more energy. Aiming to find an approximate optimal method that can cover maximum area with minimum number of active sensors, in this paper, a new scheduling algorithm based on learning automata is proposed to enhance area coverage, and shut off redundant sensors as many as possible. To evaluate the performance of the proposed algorithm, several experiments are conducted. Simulation results indicate that the proposed algorithm have effective performance in terms of coverage enhancement and sleeping sensors compared to the existing algorithms.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.11
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• pp.463-468
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• 2017

To sense a wide area with mobile nodes, the uniformity of node deployment is a very important issue. In this paper, we consider the coverage problem to sense big data in sparse mobile ad hoc networks. In most existing works on the coverage problem, it has been assumed that the number of nodes is large enough to cover the area in the network. However, the coverage problem in sparse mobile ad hoc networks differs in the sense that a long-distance between nodes should be formed to avoid the overlapping coverage areas. We formulate the sensor coverage problem in sparse mobile ad hoc networks and provide the solution to the problem by a self-organized approach without a central authority. The experimental results show that our approach is more efficient than the existing ones, subject to both of coverage areas and energy consumption.

• Journal of the Korea Institute of Military Science and Technology
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• v.19 no.4
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• pp.443-452
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• 2016

Current low-altitude radar system often fails to detect small unmanned aerial vehicles (UAV) because of their small radar cross section (RCS) compared with larger targets. As a potential alternative, a passive bistatic radar system has been considered. We study an optimal deployment problem for the passive bistatic radar system. We model this problem as a covering problem, and develop an integer programming model. The objective of the model is to maximize coverage of a passive bistatic radar system. Our model takes into account factors specific to a bistatic radar system, including bistatic RCS and transmitter-receiver pair coverage. Considering bistatic RCS instead of constant RCS is important because the slight difference of RCS value for small UAVs could significantly influence the detection probability. The paired radar coverage is defined by using the concept of gradual coverage and cooperative coverage to represent a realistic environment.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.8
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• pp.385-393
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• 2008

The best coverage problem is finding a path whose worst distance to the sensor-set is the best among all paths. Instead, if the user stays close to its nearest two sensors, then the stability of the wireless connection may be guaranteed. So we consider the problem of finding a second best coverage path; given the sensor set U, a starting point s and a target point t, find a path whose worst distance to the second closest sensor is minimized. This paper presents an O(n logn) -time algorithm to find such a path. We also give experimental evidence showing that the connection to the sensor-set along a second best coverage path is more stable than that along the best coverage path.

• The KIPS Transactions:PartA
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• v.16A no.1
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• pp.35-42
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• 2009

This paper proposes a new coverage algorithm for intelligent robot. Many algorithms for improving the performance of coverage have been focused on minimizing the total coverage completion time. However, if one does not have enough time to finish the whole coverage, the optimal path could be different. To tackle this problem, we propose a new coverage algorithm, which we call MaxCoverage algorithm, for covering maximal area within the deadline. The MaxCoverage algorithm decides the navigation flow by greedy algorithm for Set Covering Problem. The experimental results show that the MaxCoverage algorithm performs better than other algorithms for random deadlines.

• Journal of Electrical Engineering and Technology
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• v.7 no.6
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• pp.1023-1033
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• 2012

An underwater planar covering problem is studied where the coverage region consists of polygonal cells, and line sweep motion is used for coverage. In many subsea applications, sidescan sonar has become a common tool, and the sidescan sonar data is meaningful only when the sonar is moving in a straight line. This work studies the optimal line sweep coverage where the sweep paths of the cells consist of straight lines and no turn is allowed inside the cell. An optimal line sweep coverage solution is presented when the line sweep path is parallel to an edge of the cell boundary. The total time to complete the coverage task is minimized. A unique contribution of this work is that the optimal sequence of cell visits is computed in addition to the optimal line sweep paths and the optimal cell decomposition.

• Journal of Communications and Networks
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• v.11 no.1
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• pp.57-71
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• 2009

Networking together hundreds or thousands of cheap sensor nodes allows users to accurately monitor a remote environment by intelligently combining the data from the individual nodes. As sensor nodes are typically battery operated, it is important to efficiently use the limited energy of the nodes to extend the lifetime of the wireless sensor network (WSN). One of the fundamental issues in WSNs is the coverage problem. In this paper, the border coverage problem in WSNs is rigorously analyzed. Most existing results related to the coverage problem in wireless sensor networks focused on planar networks; however, three dimensional (3D) modeling of the sensor network would reflect more accurately real-life situations. Unlike previous works in this area, we provide distributed algorithms that allow the selection and activation of an optimal border cover for both 2D and 3D regions of interest. We also provide self-healing algorithms as an optimization to our border coverage algorithms which allow the sensor network to adaptively reconfigure and repair itself in order to improve its own performance. Border coverage is crucial for optimizing sensor placement for intrusion detection and a number of other practical applications.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.3B
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• pp.453-461
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• 2010

A critical issue in wireless sensor networks is an energy-efficiency since the sensor batteries have limited energy power and, in most cases, are not rechargeable. The most practical manner relate to this issue is to use a node wake-up scheduling protocol that some sensor nodes stay active to provide sensing service, while the others are inactive for conserving their energy. Especially, CTC (Connected Target Coverage) problem has been considered as a representative energy-efficiency problem considering connectivity as well as target coverage. In this paper, we propose a new energy consumption model considering multiple-targets and create a new problem, CMTC (Connected Multiple-Target Coverage) problem, of which objective is to maximize the network lifetime based on the energy consumption model. Also, we present SPT (Shortest Path based on Targets)-Greedy algorithm to solve the problem. Our simulation results show that SPT-Greedy algorithm performs much better than previous algorithm in terms of the network lifetime.

• Health Policy and Management
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• v.19 no.3
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• pp.142-165
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• 2009

Although providing universal coverage for health care through the National Health Insurance(NHI) is a remarkable achievement, the issue of limited benefit coverage of the NHI has been at the core of national debate over how to improve its coverage. This study aims to evaluate benefit extension strategies and implemented policies with regard to the NHI since 1989 using 'policy window theory' proposed by John W. Kingdon. Understanding problem stream, policy stream, political stream, and coupling streams regarding the NHI, in particular benefit extension, would contribute to broaden policy debates and to develop more effective strategies for the future. Historically, political stream had opened policy window in the past two decades and policy streams can be characterized by three waves. Three streams have been coupled since 2003 and the government had a strong will to fulfill better performance of NHI coverage. Study findings indicate that identification of problem structure regarding NHI benefit was not connected with policy stream tightly. In addition, there has been limited discussion on policy goal and principles for extension coverage of the NHI. Policy strategies to improve coverage of the NHI should be linked to characteristics of problem and sought solutions under the principle which is expected to be sustainable through consensus in the society.