• 센서학회지
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• 제19권5호
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• pp.342-348
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• 2010

The wireless sensor networks have been extensively researched. One of the issues in wireless sensor networks is a developing energy-efficient clustering protocol. Clustering algorithm provides an effective way to extend the lifetime of a wireless sensor networks. In this paper, we proposed an energy efficient clustering scheme by adjusting group size. In sensor network, the power consumption in data transmission between sensor nodes is strongly influenced by the distance of two nodes. And cluster size, that is the number of cluster member nodes, is also effected on energy consumption. Therefore we proposed the clustering scheme for high energy efficiency of entire sensor network by controlling cluster size according to the distance between cluster header and sink.

• International Journal of Computer Science & Network Security
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• 제23권7호
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• pp.109-118
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• 2023

Energy awareness is an essential design flaw in wireless sensor network. Clustering is the most highly regarded energy-efficient technique that offers various benefits such as energy efficiency and network lifetime. Clusters create hierarchical WSNs that introduce the efficient use of limited sensor node resources and thus enhance the life of the network. The goal of this paper is to provide an analysis of the various energy efficient clustering algorithms. Analysis is based on the energy efficiency and network lifetime. This review paper provides an analysis of different energy-efficient clustering algorithms for WSNs.

• 디지털산업정보학회논문지
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• 제10권2호
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• pp.47-59
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• 2014

In this paper, I propose a new energy efficient clustering scheme to prolong the network lifetime by reducing energy consumption at the sensor node. It is possible that a node determines whether to participate in clustering with certain probability based on local density. This scheme is useful under the environment that sensor nodes are deployed unevenly within the sensing area. By adjusting the probability of participating in clustering dynamically with local density of nodes, the energy consumption of the network is reduced. So, the lifetime of the network is extended. In the region where nodes are densely deployed, it is possible to reduce the energy consumption of the network by limiting the number of node which is participated in clustering with probability which can be adjusted dynamically based on local density of the node. Through computer simulation, it is verified that the proposed scheme is more energy efficient than LEACH protocol under the environment where node are densely located in a specific area.

• 한국멀티미디어학회논문지
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• 제17권5호
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• pp.590-600
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• 2014

In the wireless sensor network environment, clustering scheme has a problem that a large amount of energy is unnecessarily consumed because of frequently occurred entire re-clustering process. Some of the studies were attempted to improve the network performance by getting rid of the entire network setup process. However, removing the setup process is not worthy. Because entire network setup relieves the burden of some sensor nodes. The primary aim of our scheme is to cut down the energy consumption through minimizing entire setup processes which occurred unnecessarily. Thus, we suggest a re-clustering scheme that considers event detection, transmitting energy, and the load on the nodes. According to the result of performance analysis, our scheme reduces energy consumption of nodes, prolongs the network lifetime, and shows higher data collection rate and higher data accuracy than the existing schemes.

• 한국멀티미디어학회논문지
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• 제17권4호
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• pp.441-457
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• 2014

Observed from the recent performance evaluation of clustering schemes in wireless sensor networks, we found that most of them did not consider various sensor characteristics and its application environment. Without considering these, the performance evaluation results are difficult to be trusted because these networks are application-specific. In this paper, for the fair evaluation, we measured several clustering scheme's performance variations in accordance with sensor data pattern, number of sensors per node, density of points of interest (data density) and sensor coverage. According to the experiment result, we can conclude that clustering methods are easily influenced by POI variation. Network lifetime and data accuracy are also slightly influenced by sensor coverage and number of sensors. Therefore, in the case of the clustering scheme that did not consider various conditions, fair evaluation cannot be expected.

• Journal of Information Processing Systems
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• 제7권1호
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• pp.29-42
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• 2011

Wireless sensor networks are composed of a large number of sensor nodes with limited energy resources. One critical issue in wireless sensor networks is how to gather sensed information in an energy efficient way, since their energy is limited. The clustering algorithm is a technique used to reduce energy consumption. It can improve the scalability and lifetime of wireless sensor networks. In this paper, we introduce a clustering protocol with mode selection (CPMS) for wireless sensor networks. Our scheme improves the performance of BCDCP (Base Station Controlled Dynamic Clustering Protocol) and BIDRP (Base Station Initiated Dynamic Routing Protocol) routing protocol. In CPMS, the base station constructs clusters and makes the head node with the highest residual energy send data to the base station. Furthermore, we can save the energy of head nodes by using the modes selection method. The simulation results show that CPMS achieves longer lifetime and more data message transmissions than current important clustering protocols in wireless sensor networks.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2019년도 춘계학술대회
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• pp.260-263
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• 2019

접근이 어렵거나 지속적인 모니터링이 필요한 서비스에 적용 가능한 WSN(Wireless Sensor Network) 기술은 최근 그 응용 분야의 확대 및 효율성으로 연구 개발의 필요성이 점증하고 있는 분야이다. 본 논문은 WSN의 패킷 전송률을 증가시키고 센서 노드들의 수명을 연장하기 위해 제시된 기존 연구들을 분석한 후, 센서 노드들에 Clustering 및 위치 기반 기법 적용 시 기존 연구 대비 성능 향상 요인들을 분석하였으며 이를 기반으로 패킷 손실률과 네트워크 수명 측면에서 향후 WSN의 성능 향상을 위한 새로운 기법에 대한 연구를 수행 할 예정이다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제3권3호
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• pp.331-343
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• 2009

Many types of sensor data exhibit strong correlation in both space and time. Both temporal and spatial suppressions provide opportunities for reducing the energy cost of sensor data collection. Unfortunately, existing clustering algorithms are difficult to utilize the spatial or temporal opportunities, because they just organize clusters based on the distribution of sensor nodes or the network topology but not on the correlation of sensor data. In this paper, we propose a novel clustering algorithm based on the correlation of sensor data. We modify the advertisement sub-phase and TDMA schedule scheme to organize clusters by adjacent sensor nodes which have similar readings. Also, we propose a spatio-temporal suppression scheme for our clustering algorithm. In order to show the superiority of our clustering algorithm, we compare it with the existing suppression algorithms in terms of the lifetime of the sensor network and the size of data which have been collected in the base station. As a result, our experimental results show that the size of data is reduced and the whole network lifetime is prolonged.

• 한국산학기술학회논문지
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• 제11권10호
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• pp.3950-3957
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• 2010

무선 센서 네트워크는 한정된 자원의 센서 노드들로 구성되어 있고, 한번 구성된 후에는 유지 보수가 어렵다는 단점을 갖고 있다. 따라서 무선 센서 네트워크에서는 에너지 소비를 최소화하고, 한정된 자원을 효율적으로 사용하여 네트워크 수명을 최대화하는 것이 중요한 문제이다. 본 논문에서는 클러스터링 방식에서 클러스터 수를 효율적으로 지정하여 에너지 소모량을 최적화하는 기법을 제안한다. 이 기법은 무선 전송에 소비되는 에너지양은 거리(임계값)에 따라 많은 차이가 있으므로 이러한 임계값을 고려하여 클러스터 수를 지정함으로써 에너지 소비를 줄이는 방식이다. 실험을 통하여 제안된 클러스터링 기법은 LEACH(Low-Energy Adaptive Clustering Hierarchy)에 비해 전체 에너지 소모량 측면에서 높은 성능을 나타냄을 확인하였다.

• 경영과학
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• 제26권3호
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• pp.55-65
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• 2009

The objective of this paper is to propose an ant colony optimization (ACO) for clustering design in wireless sensor network problem. This proposed ACO approach is designed to deal with the dynamics of the sensor nodes which can be adaptable to topological changes to any network graph in a time. Long communication distances between sensors and a sink in a sensor network can greatly consume the energy of sensors and reduce the lifetime of a network. We can greatly minimize the total communication distance while minimizing the number of cluster heads using proposed ACO. Simulation results show that our proposed method is very efficient to find the best solutions comparing to the optimal solution using CPLEX in 100, 200, and 400 node sensor networks.