• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.711-712
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• 2006

In this paper, we propose algorithm that improves energy efficiency of sensor node. That is, sensor node suggests algorithm that minimizes unnecessary surrounding feeler, and when passes information to neighborhood node, transmit forecasting position of node.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.6
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• pp.1201-1206
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• 2007

In this paper, we propose an algorithm that improve network lifetime by adjusting cluster size according to location information of sensor node in wireless sensor network (WSN) using clustering algorithm. The collected sensing information by sensor nodes in each cluster are transferred to sink node using inter-cluster communications method. Cluster head (CH) that located nearby sink node spend much more energy than those of far from sink node, because nearer CH forwards more data, so network lifetime has a tendency to decrease. Proposed algorithm minimizes energy consumption in adjacent cluster to sink node by decreasing cluster size, and improve CH lifetime by distributing transmission paths. As a result of mathematical analysis, the proposed algorithm shows longer network lifetime in WSN.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.1283-1284
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• 2011

• Smart Structures and Systems
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• v.14 no.4
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• pp.617-641
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• 2014

The energy constraint is still a common issue for the practical application of wireless sensors, since they are usually powered by batteries which limit their lifetime. In this paper, a practical compound energy efficiency strategy is proposed and realized in the implementation of a real time wireless sensor platform. The platform is intended for wireless structural monitoring applications and consists of three parts, wireless sensing unit, base station and data acquisition and configuration software running in a computer within the Matlab environment. The high energy efficiency of the wireless sensor platform is achieved by a proposed adaptive radio transmission power control algorithm, and some straightforward methods, including adopting low power ICs and high efficient power management circuits, low duty cycle radio polling and switching off radio between two adjacent data packets' transmission. The adaptive transmission power control algorithm is based on the statistical average of the path loss estimations using a moving average filter. The algorithm is implemented in the wireless node and relies on the received signal strength feedback piggybacked in the ACK packet from the base station node to estimate the path loss. Therefore, it does not need any control packet overheads. Several experiments are carried out to investigate the link quality of radio channels, validate and evaluate the proposed adaptive transmission power control algorithm, including static and dynamic experiments.

• International journal of advanced smart convergence
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• v.6 no.3
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• pp.59-64
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• 2017

A wireless sensor network is a network in which nodes equipped with sensors capable of collecting data from the real world are configured wirelessly. Because the sensor nodes are configured wirelessly, they have limited power such as batteries. If the battery of the sensor node is exhausted, the node is no longer usable. If more than a certain number of nodes die, the network will not function. There are many wireless sensor network protocols to improve energy efficiency, among which LEACH Protocol is a typical example. The LEACH protocol is a cluster-based protocol that divides sensor space into clusters and transmits and receives data between nodes. Therefore, depending on how the cluster is structured, the shape of the energy cow may decrease or increase. We compare the network lifetimes of the existing LEACH protocols and the three types of protocols that have been improved using fuzzy methods for cluster selection.

• Journal of Korea Multimedia Society
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• v.20 no.11
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• pp.1776-1784
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• 2017

There are two types of WSN(wireless sensor networks) in terms of sensor node's capability, that is, homogeneous or heterogeneous WSN. Even though the latter has better performance than the former, it requires some overhead for deploying nodes or clustering the network. In this paper, we propose a new scheme, called VHS(Virtual Heterogenous Sensor-Network), which uses a homogeneous WSN regarding energy in a heterogeneous way. The proposed scheme's performance has been evaluated and compared with other homogeneous schemes by simulation. The results are shown to be better than the other existing homogeneous schemes used in a sample sensor network application.

• Journal of information and communication convergence engineering
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• v.8 no.2
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• pp.129-135
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• 2010

Wireless sensor networks (WSNs) are an emerging technology and offers economically viable monitoring solution to many challenging applications. However, deploying new technology in hostile environment, without considering security in mind has often proved to be unreasonably unsecured. Apparently, security techniques face many critical challenges in WSNs like data security and secrecy due to its hostile deployment nature. In order to resolve security in WSNs, we propose a novel and efficient secure framework called TriSec: a secure data framework for wireless sensor networks to attain high level of security. TriSec provides data confidentiality, authentication and data integrity to sensor networks. TriSec supports node-to-node encryption using PingPong-128 stream cipher based-privacy. A new PingPong-MAC (PP-MAC) is incorporated with PingPong stream cipher to make TriSec framework more secure. PingPong-128 is fast keystream generation and it is very suitable for sensor network environment. We have implemented the proposed scheme on wireless sensor platform and our result shows their feasibility.

• Journal of IKEEE
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• v.13 no.3
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• pp.39-46
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• 2009

Wireless sensor networks consist of small, autonomous devices with wireless networking capabilities. In order to further increase the applicability in real world applications, minimizing energy consumption is one of the most critical issues. Therefore, accurate energy model is required for the evaluation of wireless sensor networks. In this paper we analyze the power consumption for wireless sensor networks. To develop the power consumption model, we have measured the power characteristics of commercial Kmote node based on TelosB platforms running TinyOS. Based on our model, the estimated lifetime of a battery powered sensor node can use about 6.9 months for application of human detection using PIR sensors. This result indicates that sensor nodes can be used in a monitoring system for elderly living alone.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.6
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• pp.127-134
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• 2016

WBSN (Wireless Body Sensor Network), also called WBAN (Wireless Body Area Networks) generally, is a kind of WSN (Wireless Sensor Network) applications, which is composed of the various sensor nodes residing in human body embodied or in wearable way. The measured data at each sensor node in WBSN requires being synchronized at sink node for exact analysis for status of human body, which is like WSN. Although many time synchronization protocols for WSN has been already developed, they are not appropriate to WBSN. In this paper, a new time synchronization protocol for WBSN considering the characteristics of WBSN is proposed. The proposed scheme is not only simple, but also consumes less power, leading to increasing network life time. We will show that the proposed scheme is appropriate to WBSN by evaluating its performance by simulation.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.2
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• pp.79-86
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• 2016

In wireless sensor networks, increasing the sensing rate of each node to improve the data accuracy usually incurs a decrease of network lifetime. In this study, an energy-adaptive data compression scheme is proposed to efficiently control the sensing rate in an energy-harvesting wireless sensor network (WSN). In the proposed scheme, by utilizing the surplus energy effectively for the data compression, each node can increase the sensing rate without any rise of blackout time. Simulation result verifies that the proposed scheme gathers more amount of sensory data per unit time with lower number of blackout nodes than the other compression schemes for WSN.