• Smart Structures and Systems
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• v.16 no.4
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• pp.607-621
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• 2015

Wireless sensor technology has been opened up numerous opportunities to advanced health and maintenance monitoring of civil infrastructure. Compare to the traditional tactics, it offers a better way of providing relevant information regarding the condition of building structure health at a lower price. Numerous domestic buildings, especially longer-span buildings have a low frequency response and challenging to measure using deployed numbers of sensors. The way the sensor nodes are connected plays an important role in providing the signals with required strengths. Out of many topologies, the dense and sparse topologies wireless sensor network were extensively used in sensor network applications for collecting health information. However, it is still unclear which topology is better for obtaining health information in terms of greatest components, node's size and degree. Theoretical and computational issues arising in the selection of the optimum topology sensor network for estimating coverage area with sensor placement in building structural monitoring are addressed. This work is an attempt to fill this gap in high-rise building structural health monitoring application. The result shows that, the sparse topology sensor network provides better performance compared with the dense topology network and would be a good choice for monitoring high-rise building structural health damage.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.612-615
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• 2012

Energy efficiency in wireless sensor network is a principal issue because wireless sensor network uses limited energy. In wireless sensor network, because nodes are placed randomly, they may be concentrated in certain area. This dense area causes shortening the life of the concentrated area, and furthermore reducing the life of the entire network. In this paper, we suggest a additional cluster head selection algorithm for reducing the overload of head node in dense area and shows simulation result using our algorithm with LEACH algorithm.

• Smart Structures and Systems
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• v.12 no.3_4
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• pp.399-414
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• 2013

The smart sensor technology has opened new horizons for assessing and monitoring structural health of civil infrastructure. Smart sensor's unique features such as onboard computation, wireless communication, and cost effectiveness can enable a dense network of sensors that is essential for accurate assessment of structural health in large-scale civil structures. While most research efforts to date have been focused on realizing wireless smart sensor networks (WSSN) on bridge structures, relatively less attention is paid to applying this technology to buildings. This paper presents a decentralized damage detection using the WSSN for building structures. An existing flexibility-based damage detection method is extended to be used in the decentralized computing environment offered by the WSSN and implemented on MEMSIC's Imote2 smart sensor platform. Numerical simulation and laboratory experiment are conducted to validate the WSSN for decentralized damage detection of building structures.

• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.101-111
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• 2011

A new MAC protocol, MT-MAC(Multi-Tier Medium Access Control) by name, is proposed for dense sensor networks. Depending on the density of nodes in a virtual cluster, the cluster header performs the splitting to several tiers in nodes of virtual cluster. MT-MAC split the tiers to use modfied-SYNC message after receiving the beacon message from the cluster header. Because only the sensor nodes in the same tier communicate each other, less power is consumed and longer network life time is guaranteed. By a simulation method with NS-2, we evaluated our protocol. In dense nodes environments, MT-MAC protocol shows better results than S-MAC in terms of packet delivery rates throughput and energy consumption.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.433-435
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• 2007

Geographic wireless sensor networks use position information for Greedy routing. Greedy routing works well in dense network where as in sparse network it may fail and require the use of recovery algorithms. Recovery algorithms help the packet to get out of the communication void. However, these algorithms are generally costlier for resource constrained position based wireless sensor type networks. In the present work, we propose a Void Avoidance Algorithm (VAA); a novel idea based on virtual distance upgrading that allows wireless sensor nodes to remove all stuck nodes by transforming the routing graph and forward packet using greedy routing only without recovery algorithm. In VAA, the stuck node upgrades distance unless it finds next hop node which is closer to the destination than itself. VAA guarantees the packet delivery if there is a topologically valid path exists. NS-2 is used to evaluate the performance and correctness of VAA and compared the performance with GPSR. Simulation results show that our proposed algorithm achieves higher delivery ratio, lower energy consumption and efficient path.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.9
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• pp.3034-3055
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• 2014

Wireless Sensor Networks have extensively been utilized for ambient data collection from simple linear structures to dense tiered deployments. Issues related to optimal resource allocation still persist for simplistic deployments including linear and hierarchical networks. In this work, we investigate the case of dimensioning parameters for linear and tiered wireless sensor network deployments with notion of providing extended lifetime and reliable data delivery over extensive infrastructures. We provide a single consolidated reference for selection of intrinsic sensor network parameters like number of required nodes for deployment over specified area, network operational lifetime, data aggregation requirements, energy dissipation concerns and communication channel related signal reliability. The dimensioning parameters have been analyzed in a pipeline monitoring scenario using ZigBee communication platform and subsequently referred with analytical models to ensure the dimensioning process is reflected in real world deployment with minimum resource consumption and best network connectivity. Concerns over data aggregation and routing delay minimization have been discussed with possible solutions. Finally, we propose a node placement strategy based on a dynamic programming model for achieving reliable received signals and consistent application in structural health monitoring with multi hop and long distance connectivity.

• Journal of the Korea Society of Computer and Information
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• v.13 no.2
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• pp.177-183
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• 2008

In this paper we suggest a hybrid MAC protocol for wireless sensor networks (WSN) to enhance network performance. The proposed MAC scheme is specifically designed for wireless sensor networks which consist of lots nodes. The contributions of this paper are: First, the proposed scheduling algorithm is independent of network topology. Even though the BS node has lots of one hop node in dense mode network, all the time slots can be assigned fully without increasing frequencies. Second, BS one hop nodes can use more than one time slots if necessary, so total network performance is increased. We compare the network performance of the proposed scheme with previous one, HyMAC [1].

• Proceedings of the Korean Information Science Society Conference
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• 2005.07a
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• pp.427-429
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• 2005

Energy efficiency is the most challenging issue in wireless sensor network to prolong the life time of the network, as the sensors has to be unattended. Cluster based communication can reduce the traffic on the network and gives the opportunity to other sensors for periodic sleep and thus save energy. Passive clustering (PC) can perform a significant role to minimize the network load as it is less computational and light weight. First declaration wins method of PC without any priority generates severe collision in the network and forms the clusters very dense with large amount of overlapping region. We have proposed several modifications for the existing passive clustering algorithm to prolong the life time of the network with better cluster formation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5425-5448
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• 2018

Wireless sensor network has been widely used in Internet of Things (IoT) applications to support large and dense networks. As sensor nodes are usually tiny and provided with limited hardware resources, the existing multiple access methods, which involve high computational complexity to preserve the protocol performance, is not available under such a scenario. In this paper, we propose an intelligent Medium Access Control (MAC) protocol selection scheme based on machine learning in wireless sensor networks. We jointly consider the impact of inherent behavior and external environments to deal with the application limitation problem of the single type MAC protocol. This scheme can benefit from the combination of the competitive protocols and non-competitive protocols, and help the network nodes to select the MAC protocol that best suits the current network condition. Extensive simulation results validate our work, and it also proven that the accuracy of the proposed MAC protocol selection strategy is higher than the existing work.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.2
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• pp.247-268
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• 2011

Due to the application-specific nature of wireless sensor networks, the sensitivity to such a requirement as data reporting interval varies according to the type of application. Such considerations require an application-specific, parameter tuning paradigm allowing us to maximize energy conservation prolonging the operational network lifetime. In this paper, we propose a reporting interval adaptive, sensor control platform for energy-saving data gathering in wireless sensor networks. The ultimate goal is to extend the network lifetime by providing sensors with high adaptability to application-dependent or time-varying, reporting interval requirements. The proposed sensor control platform is based upon a two phase clustering (TPC) scheme which constructs two types of links within each cluster - namely, direct link and relay link. The direct links are used for control and time-critical, sensed data forwarding while the relay links are used only for multi-hop data reporting. Sensors opportunistically use the energy-saving relay link depending on the user reporting, interval constraint. We present factors that should be considered in deciding the total number of relay links and how sensors are scheduled for sensed data forwarding within a cluster for a given reporting interval and link quality. Simulation and implementation studies demonstrate that the proposed sensor control platform can help individual sensors save a significant amount of energy in reporting data, particularly in dense sensor networks. Such saving can be realized by the adaptability of the sensor to the reporting interval requirements.