• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.4C
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• pp.338-346
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• 2012

Wireless sensor network (WSN) technology provides a variety of medical and healthcare solutions to assist detection and communication of body conditions. However, data reliability inside WSN might be influenced to healthcare routing protocol due to limited hardware resources of computer, storage, and communication bandwidth. For this reason, we have conducted various wireless communication experiments between nodes using parameters such as RF strength, battery status, and deployment status to get a optimal performance of mobile healthcare routing protocol. This experiment may also extend the life time of the nodes. Performance analysis is done to obtain some important parameters in terms of distance and reception rate between the nodes. Our experiment results show optimal distance between nodes according to battery status and RF strength, or deployment status and RF strength. The packet reception rate according to deployment status and RF strength of nodes was also checked. Based on this performance evaluation, the optimized sensor node battery and deployment in the developed our mobile healthcare routing protocol were proposed.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06a
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• pp.265-266
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• 2008

• Proceedings of the Korean Information Science Society Conference
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• 2007.06a
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• pp.282-283
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• 2007

• Journal of KIISE:Information Networking
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• v.33 no.3
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• pp.193-200
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• 2006

The security feature is essential in wireless sensor network such as intrusion detection or obstacle observation. Sensor nodes must have shared secret between nodes to support security such as privacy. Many methods which provide key pre-distribution need too many keys or support poor security. To solve this problem, probabilistic key pre-distribution is proposed. This method needs a few keys and use probabilistic method to share keys. However, this method does not guarantee key sharing between nodes, and neighbor nodes nay not communicate each other. It leads to waste of network resource such as inefficient routing, extra routing protocol. In this paper, we propose new key distribution method using quorum system which needs a few keys and guarantee key sharing between nodes. We also propose extension of the method which needs fewer keys and guarantee key sharing when node deployment knowledge is well known.

• Smart Structures and Systems
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• v.17 no.3
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• pp.523-539
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• 2016

The ambient vibration measurement is an output-data-only dynamic testing where natural excitations are represented, for instance, by winds and typhoons. The modal identification involving output-only measurements requires the use of specific modal identification techniques. This paper presents the application of a reliable method (the Stochastic Subspace Identification - SSI) implemented in a general purpose software. As a criterion toward the robustness of identified modes, a bio-inspired optimization algorithm, with a highly nonlinear objective function, is introduced in order to find the optimal deployment of a reduced number of sensors across a large civil engineering structure for the validation of its modal identification. The Ting Kau Bridge (TKB), one of the longest cable-stayed bridges situated in Hong Kong, is chosen as a case study. The results show that the proposed method catches eigenvalues and eigenvectors even for a reduced number of sensors, without any significant loss of accuracy.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.7
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• pp.9-16
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• 2008

For the efficient routing on a Sensor Network, one may consider a deployment problem to interconnect the sensor nodes optimally. There is an analogous theoretic problem: the Steiner Tree problem of finding the tree that interconnects given points on a plane optimally. One may use the approximation algorithm for the problem to find out the deployment that interconnects the sensor nodes almost optimally. However, the Steiner Tree problem is to interconnect mathematical set of points on a Euclidean plane, and so involves particular cases that do not occur on Sensor Networks. Thus the approach of using the algorithm does not make a proper way of analysis. Differently from the randomly given locations of mathematical points on a Euclidean plane, the locations of sensors on Sensor Networks are assumed to be physically dispersed over some moderate distance with each other. By designing an approximation algorithm for the Sensor Networks in terms of that physical property, one may produce the execution time and the approximation ratio to the optimality that are appropriate for the problem of interconnecting Sensor Networks.

• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.5
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• pp.209-217
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• 2012

In the present, Wireless Sensor Network(WSN) has been used for the purpose of the military operation with surveillance systems and for collecting useful information from the natural environment. Basically, low-power, easy deployment and low cost are the most important factors to be deployed for WSNs. Lots of researches have been studied to meet those requirements, especially on the node capacity and battery lifetime improvements. Recently, the study of wireless mesh networks applied into the surveillance systems has been proceeded as a solution of easy deployment. In this paper, we proposed large-scale intelligent multi-layer surveillance systems based on QoS assuring Wireless Mesh Networks and implemented them in the real testbed environment. The proposed system explains functions and operations for each subsystem as well as S/W and H/W architectures. Experimental results are shown for the implemented subsystems and the performance is satisfactory for the surveillance system. We can identify the possibility of the implemented multi-layer surveillance system to be used in practice.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.9
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• pp.778-786
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• 2012

Sensors that are used on wireless sensor networks can be divided into two types: directional sensors, such as PIR, image, and electromagnetic sensors; and non-directional sensors, such as seismic, acoustic and magnetic sensors. In order to guarantee the line-of-sight of a directional sensor, the installation location of the sensor must be higher than ground level. Among non-directional sensors, seismic sensors should be installed on the ground in order to ensure the maximal performance. As a result, seismic sensors may have network connectivity problems due to communication failure. In this paper, we propose a 3D node deployment method to maximize the coverage and the network connectivity considering the sensor-specific properties. The proposed method is for non-directional sensors to be placed on the ground, while the directional sensor is installed above the ground, using trees or poles, to maximize the coverage. As a result, through the topology that the detection data from non-directional sensors are transmitted to the directional sensor, we can maximize the network connectivity. Simulation results show that our strategy improves sensor coverage and network connectivity.

• ETRI Journal
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• v.33 no.6
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• pp.924-934
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• 2011

Sensor networks play an important role in making the dream of ubiquitous computing a reality. With a variety of applications, sensor networks have the potential to influence everyone's life in the near future. However, there are a number of issues in deployment and exploitation of these networks that must be dealt with for sensor network applications to realize such potential. Localization of the sensor nodes, which is the subject of this paper, is one of the basic problems that must be solved for sensor networks to be effectively used. This paper proposes a probabilistic support vector machine (SVM)-based method to gain a fairly accurate localization of sensor nodes. As opposed to many existing methods, our method assumes almost no extra equipment on the sensor nodes. Our experiments demonstrate that the probabilistic SVM method (PSVM) provides a significant improvement over existing localization methods, particularly in sparse networks and rough environments. In addition, a post processing step for PSVM, called attractive/repulsive potential field localization, is proposed, which provides even more improvement on the accuracy of the sensor node locations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.2889-2909
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• 2017

Wireless sensor networks (WSNs) have attracted lots of attention in recent years due to their potential for various applications. In this paper, we seek how to efficiently deploy relay nodes into traditional static WSNs with constrained locations, aiming to satisfy specific requirements of the industry, such as average energy consumption and average network reliability. This constrained relay node deployment problem (CRNDP) is known as NP-hard optimization problem in the literature. We consider addressing this multi-objective (MO) optimization problem with an improved Artificial Bee Colony (ABC) algorithm with a linear local search (MOABCLLS), which is an extension of an improved ABC and applies two strategies of MO optimization. In order to verify the effectiveness of the MOABCLLS, two versions of MO ABC, two additional standard genetic algorithms, NSGA-II and SPEA2, and two different MO trajectory algorithms are included for comparison. We employ these metaheuristics on a test data set obtained from the literature. For an in-depth analysis of the behavior of the MOABCLLS compared to traditional methodologies, a statistical procedure is utilized to analyze the results. After studying the results, it is concluded that constrained relay node deployment using the MOABCLLS outperforms the performance of the other algorithms, based on two MO quality metrics: hypervolume and coverage of two sets.