• 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 Korean Information Science Society Conference
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• 2004.10c
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• pp.10-12
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• 2004

무선 센서네트워크는 센싱 지역에 분산되어 있는 초소형 센서 노드들이 감지/처리한 데이터를 수집노드로 전송하여 원격의 사용자가 센싱 지역의 상황인지를 가능하게 하는 유비쿼터스 컹퓨팅의 기반 네트워크이다. 전력 사용이 극히 제한된 센서 노드를 이용하여 무선 센서 망을 구성, 유지하며 데이터를 수집하기 위해서는 효율적인 망의 형태와 이에 따른 네트워크 배치 전략을 필요로 한다. 클러스터 기반 네트워크의 형태는 밀집도가 높은 센서네트워크에서 데이터병합을 수행하고 노드간 에너지 소비 균형을 이루기 위한 효과적인 구조이다. 본 논문에서는 클러스터 기반의 단일 홉 전송 구조에서 데이터 수집률을 높이고 노드간 에너지 사용의 균형을 이루게 하여 네트워크의 생존시간을 최대화할 수 있는 네트워크 배치 방법을 제안하였다. 클러스터링 기법에 따른 에너지 소비 모델을 분석하고 이를 통해 노드의 적절한 밀집도를 산출하였다. 싱크로부터 멀어질수록, 센서필드의 중앙보다는 외곽에 노드의 배치를 조밀하게 배치하여 네트워크의 생존시간을 늘렸다. 시뮬레이션을 통해 효율적인 네트워크의 배치가 노드간 에너지 소비의 균형을 이루도록 하여 네트워크의 생존시간을 늘일 수 있음을 확인하였다.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.1038-1041
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• 2009

Wireless sensor network with wireless sensor nodes which equipped with temperature, humidity, illumination, or soil sensor etc, get a natural environment information and analyze and utilized variety way.these network consist of a short distance wireless communication and multi-hop techniques with multiple nodes equipped low-power wireless transceivers. so the characteristic of the data collected through the wireless sensor network is obtained from compact nodes within a limited range. However, to get a data from the wireless sensor nodes scattered in a wide range, this network needs a wireless transceiver that consumes many power or a lot of intermediate nodes. then, merit of low cost and low electrical energy decrease. To solve this problem, this paper offers environment monitoring system using autonomous mobile robot that collect data from groups of each sensor networks scattered widely.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.11a
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• pp.866-869
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• 2007

센서 네트워크(Sensor network)는 주변 데이터를 수집하기 위해 널리 퍼뜨려진 작고, 값싼 센서들이 밀집된 무선 네트워크이다. 또한 센서 네트워크는 특수한 활동을 수행하기 위하여 상호 협동하는 센서 노드들의 모임으로 나타낼 수 있으며, 무선 센서 네트워크는 멀리 떨어진 위치에서 물리적인 환경의 감시와 제어를 용이하게 한다. 그러므로, 센서 네트워크는 기후가 혹독한 위치에서 감지한 정보를 모으거나 군사 목적, 주변 환경 감시와 같은 다양한 분야에서 응용되고 있다. 그러나, 일반적으로 저전력 센서들을 이용하는 센서 네트워크는 에너지 효율성을 고려하여 전체 네트워크 성능을 저하시키지 않고 데이터를 수집하는 것이 가장 큰 목적이다. 따라서, 본 논문에서는 위치 측정으로 인한 상대적인 위치 정보에 기반한 클러스터링 기법인 홉 트리(Hop-tree)를 제안한다. 제안된 클러스터링 기법은 위치 측정으로 인해 각 센서 노드들의 상대적인 위치를 알 수 있다는 것과 각 센서 노드들의 에너지를 효율적으로 이용할 수 있다는 장점을 가진다.

• The Journal of the Korea Contents Association
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• v.13 no.2
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• pp.52-61
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• 2013

In wireless sensor networks, the geographical positioning scheme is one of core technologies for sensor applications such as disaster monitoring and environment monitoring. For this reason, studies on range-free positioning schemes have been actively progressing. The density probability scheme based on central limit theorem and normal distribution was proposed to improve the location accuracy in non-uniform sensor network environments. The density probability scheme measures the final positions of unknown nodes by estimating distance through the sensor node communication. However, it has a problem that all of the neighboring nodes have the same 1-hop distance. In this paper, we propose an efficient sensor positioning scheme that overcomes this problem. The proposed scheme performs the second positioning step through the sensing range control after estimating the 1-hop distance of each node in order to minimize the estimation error. Our experimental results show that our proposed scheme improves the accuracy of sensor positioning by about 9% over the density probability scheme and by about 48% over the DV-HOP scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.8B
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• pp.777-785
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• 2009

In recent wireless sensor networks, stationary nodes and mobile nodes co-exist to provide a diverse service. However, because there are multiple mobile nodes located in the wireless sensor network, there is a potential for the instability due to the frequent network reconfiguration and the traffic caused by densely concentration of mobile nodes while mobile nodes are switching locations. In order to solve this problem, we propose the pumping node architecture to solve this traffic congestion problem due to the crowds of mobile nodes. The pumping node can be reduced heavy traffic by pumping through the backbone network caused by the densely concentration of the mobile nodes. As a result, the architecture reduces the traffic in the sensor network with high reliability.

• The Journal of the Korea Contents Association
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• v.12 no.3
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• pp.55-66
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• 2012

In wireless sensor networks, a positioning scheme is one of core technologies for sensor applications such as disaster monitoring and environment monitoring. The One of the most positioning scheme, called DV-HOP does not consider non-uniform sensor networks that are actual distributed environments. Therefore, the accuracy of the existing positioning scheme is low in non-uniform network environments. Moreover, because it requires many anchor nodes for high accuracy in non-uniform network environments, it is expensive to construct the network. To overcome this problem, we propose a novel sensor positioning scheme using density probability models in non-uniform wireless sensor networks. The proposed scheme consists of the density probability model using the deployment characteristics of sensor nodes and the distance refinement algorithm for high accuracy. By doing so, the proposed scheme ensures the high accuracy of sensor positioning in non-uniform networks. To show the superiority of our proposed scheme, we compare it with the existing scheme. Our experimental results show that our proposed scheme improves about 44% accuracy of sensor positioning over the existing scheme on average even in non-uniform sensor networks.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1B
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• pp.68-77
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• 2010

Wireless sensor networks are installed in various environments and collect sensing data through wireless links. The quality of a wireless link may be unstable due to environment causes and hardware performance in wireless sensor networks. Since the change of the link quality may cause data loss, sensor nodes need to adaptively estimate the change of the link quality. Also, the routing protocol should deal with this situation. In this paper, the adaptive link quality estimation and routing scheme in the large-scale wireless sensor networks are proposed. When the quality of a link is unstable, sensor nodes agilely estimate the quality of links, and the new route is selected. When quality of a link is stable, the link quality is occasionally estimated so that the energy consumption is reduced. Moreover, sensor nodes exchange less beacons in order to reduce an overhead in dense networks. In the case of sparse network, the sensor nodes exchange more beacons for finding a better route. We prove that the proposed scheme can improve the energy efficiency and reliability.

• Proceedings of the Korea Contents Association Conference
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• 2012.05a
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• pp.33-34
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• 2012

무선 센서 네트워크의 다양한 응용에 있어 센서 노드의 지리학적 위치 측정은 매우 중요하다. 이를 위해 비-거리(Range-Free) 기반 위치 측정 기법에 대한 연구가 활발하게 진행 중이며, 비 균일 네트워크 환경에서 위치 정확도를 향상하기 위한 밀집 확률 기반의 위치 측정 기법이 제안되었다. 밀집 확률 기반의 위치 측정 기법에서 추정 거리 산출 시 노드 통신 반경 내 1-홉 거리는 모두 동일한 값을 갖는데 이는 반경 내 가까운 이웃 노드와 먼 이웃 노드가 있어도 모두 같은 거리로 추정하기 때문에 위치 측정 시 오차가 발생 할 수 있다. 따라서 본 논문에서는 이러한 오차를 줄이기 위해 각 노드마다 거리 추정 후 센싱 반경을 조절하여 2차 지역 거리 평가를 통해 센서의 위치를 측정하는 기법을 제안한다. 성능평가 결과, 제안하는 기법이 기존 기법에 비해 측위 정확도가 크게 향상되었다.