• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.126-148
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• 2015

Different from the existing works on coverage problems in wireless sensor networks (WSNs), this paper considers the exposure-path prevention problem by using the percolation theory in three dimensional (3D) WSNs, which can be implemented in intruder detecting applications. In this paper, to avoid the loose bounds of critical density, a bond percolation-based scheme is proposed to put the exposure-path problem into a 3D uniform lattice. Within this scheme, the tighter bonds of critical density for omnidirectional and directional sensor networks under random sensor deployment-a 3D Poisson process are derived. Extensive simulation results show that our scheme generates tighter bounds of critical density with no exposure path in 3D WSNs.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.12B
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• pp.1670-1679
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• 2011

In the area of wireless sensor networks, sensor coverage and network connectivity problems are caused by a limited detection range and the communication distance of the nodes. To solve the coverage and connectivity problems, many studies are suggested, but most research is restricted to apply into the real environment because they didn't consider various environmental factors on wireless sensor network deployment. So in this paper, we propose a node deployment strategy considering environmental factors and the number of nodes in surveillance and reconnaissance sensor networks(SRSN). The proposed node deployment method divides the installation of the surveillance and reconnaissance sensor networks system into four steps such as identification of influences factors for node placement through IPB process, sensor node deployment based on sensing range, selection of monitoring site, and relay node deployment based on RF communication range. And it deploys the sensor nodes and relay nodes considered the features of the surveillance and reconnaissance sensor network system and environmental factors. The result of simulation indicates that the proposed node deployment method improves sensor coverage and network connectivity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.3
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• pp.901-920
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• 2015

Wireless Sensor Networks (WSNs) are widely used in geographically isolated applications like military border area monitoring, battle field surveillance, forest fire detection systems, etc. Uninterrupted power supply is not possible in isolated locations and hence sensor nodes live on their own battery power. Localization of sensor nodes in isolated locations is important to identify the location of event for further actions. Existing localization algorithms consume more energy at sensor nodes for computation and communication thereby reduce the lifetime of entire WSNs. Existing approaches also suffer with less localization coverage and localization accuracy. The objective of the proposed work is to increase the lifetime of WSNs while increasing the localization coverage and localization accuracy. A novel intelligent unmanned aerial vehicle anchor node (IUAN) is proposed to reduce the communication cost at sensor nodes during localization. Further, the localization computation cost is reduced at each sensor node by the proposed intelligent arc selection (IAS) algorithm. IUANs construct the location-distance messages (LDMs) for sensor nodes deployed in isolated locations and reach the Control Station (CS). Further, the CS aggregates the LDMs from different IUANs and computes the position of sensor nodes using IAS algorithm. The life time of WSN is analyzed in this paper to prove the efficiency of the proposed localization approach. The proposed localization approach considerably extends the lifetime of WSNs, localization coverage and localization accuracy in isolated environments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.4B
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• pp.338-348
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• 2009

The Wireless Sensor Network (WSN) has recently attracted considerable attention due to the low price and ease to deploy it. In particular, in a hostile or harsh regions where sensors cannot be deployed manually, WSNs can be established just by dropping sensors from the air. In this case, however, most likely sensors are not placed at optimal positions, although the location of sensors does have a drastic impact on the WSN performance. Moreover, randomized deployment algorithm can leave holes in terms of coverage in the sensing area. This paper proposes a sensor relocation scheme where mobile sensors move to patch up the holes by appropriate coverage. Simulation results show that the proposed algorithm outperforms prior existing schemes in terms of coverage and lifespan of WSNs.

• 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 Academia-Industrial cooperation Society
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• v.20 no.8
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• pp.15-22
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• 2019

Awireless sensor network utilizes small sensors with a low cost and low power being deployed over a wide area. They monitor the surrounding environment and gather the associated information to transmit it to a base station via multi-hop transmission. Most of the research has mainly focused on static sensors that are located in a fixed position. Unlike a wireless sensor network based on static sensors, we can exploit drone-based technologies for more efficient wireless networks in terms of coverage and energy. In this paper, we introduce a transmission power model and a video encoding power model to design the network environment. We also explain a priority mapping scheme, and deploy drones oriented for network coverage and energy consumption. Through our simulations, this research shows coverage and energy improvements in adrone-based wireless sensor network with fewer sensors, compared to astatic sensor-based wireless sensor network. Concretely, coverage increases by 30% for thedrone-based wireless sensor network with the same number of sensors. Moreover, we save an average of 25% with respect to the total energy consumption of the network while maintaining the coverage required.

• The KIPS Transactions:PartC
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• v.14C no.2
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• pp.139-146
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• 2007

Mobile Sensor Network(MSN) is actively studied due to the advent of mobile sensors such as Robomote and Robotic Sensor Agents(RSAs), However, existing studies on MSN have mainly focused on coverage hole problem which occurs in Stationary Sensor Network(SSN). To address coverage hole problem, these studies make mobile sensors move temporarily so that they do not make the best use of the mobility of mobile sensors, Thus, a mechanism utilizing the continuous movement of mobile sensors is proposed to improve the network coverage performance. However, this mechanism is presently immature and does not explain how to make routing path and send data from mobile sensors to a sink node, Therefore, to efficiently make routing path and send data from mobile sensors to a sink node, we propose a communication protocol for mobile sensor network where mobile sensors continuously move. The proposed protocol deploys not only mobile sensors but also stationary sensors which send sensing data to a sink node instead of mobile sensors. Simulation results show that the proposed protocol improves the performance in terms of network coverage and traffic overhead, compared to conventional SSN protocols.

• Management Science and Financial Engineering
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• v.17 no.2
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• pp.39-62
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• 2011

In wireless sensor network, since each sensor is equipped with a limited power, efficient use of the energy is important. One possible network management scheme is to cluster the sensors into several sets, so that the sensors in each of the sets can completely perform the monitoring task. Then the sensors in one set become active to perform the monitoring task and the rest of the sensors switch to a sleep state to save energy. Therefore, we rotate the roles of the active set among the sensors to maximize the network lifetime. In this paper, we suggest an optimal algorithm for the maximum lifetime coverage problem which maximizes the network lifetime. For comparison, we implemented both the heuristic proposed earlier and our algorithm, and executed computational experiments. Our algorithm outperformed the heuristic concerning the obtained network lifetimes, and it found the solutions in a reasonable amount of time.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10d
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• pp.56-58
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• 2006

Sensing and coverage are the two relevant tasks for a sensor network. Quality of sensor network totally depends upon the sensing ability of sensors. In a certain monitored region success of detecting or sensing an object with the help of sensor network tells that how efficiently the network coverage perform. Here in this paper we have proposed a clustering algorithm for the deployment of sensors and thus calculated the object detection probability. Actually by this work we can easily identify the present network coverage status and accordingly can take action for its improvement.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.334-336
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• 2003

Satellite and airborne hyperspectral sensor images are suitable for investigating the vegetation state in agricultural land. However, image data obtained by an optical sensor inevitably includes mixels caused by high altitude observation. Therefore, mixel analysis method, which estimates both the pure spectra and the coverage of endmembers simultaneously, is required in order to distinguish the qualitative spectral changes due to the chlorophyll quantity or crop variety, from the quantitative coverage change. In this paper, we apply our agricultural independent component analysis (ICA) model to an airborne hyperspectral sensor image, which includes noise and fluctuation of coverage, and estimate pure spectra and the mixture ratio of crop and soil in agricultural land simultaneously.