• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.6
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• pp.2815-2822
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• 2011

Clustering method in wireless sensor networks is the technique that forms the cluster to aggregate the data and transmit them at the same time that they can use the energy efficiently. In this paper, I propose the hierarchical unequal clustering method using cluster group model. This divides the entire network into two layers. The data aggregated from layer 2 consisted of cluster group is sent to layer 1, after re-aggregation the total data is sent to base station. This method decreases whole energy consumption by using cluster group model with multi-hop communication architecture. Hot spot problem can be solved by establishing unequal cluster. I also show that proposed hierarchical unequal clustering method is better than previous clustering method at the point of network energy efficiency.

• Journal of Sensor Science and Technology
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• v.10 no.6
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• pp.310-316
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• 2001

We have been designed and constructed an artificial odour recognition system(electronic nose system) using metal oxide type sensor array for recognizing and analyzing various odours. We proposed an unsupervised clustering method based on Euclidean distances in order for human observer to examine easily multi-dimensional data, which has been measured from an array of sensors. This is a combination of Principal Components Analysis(PCA) used as a starting point for Sammom Mapping Method(SMM). No prior assumptions are made of the classes in which odour belong, and the error due to dimensional reduction at the PCA can be minimized without the disadvantages of rotation of clusters when the order of data sets in a data base was changed in the SMM. An artificial odour recognition system with the proposed unsupervised clustering method was applied to assessment of odour differences of Volatile Organic Compounds(VOCs) and Korean whiskies respectively, and demonstrated the best performances throughout the experimental trails.

• Journal of information and communication convergence engineering
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• v.20 no.3
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• pp.143-152
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• 2022

The ongoing adoption of 5G will increase the data traffic, throughput, multimedia services, and power consumption for future wireless applications and services, including sensor and mobile networks. Multipath fading on wireless channels also reduces the system performance and increases energy consumption. To address these issues, device-to-device (D2D) and cooperative communications have been proposed. In this study, we propose two inter-clustering models using the relay selection method to improve system performance and increase energy efficiency in cooperative D2D networks. We develop two inter-clustering models and present their respective algorithms. Subsequently, we run a computer simulation to evaluate each model's outage probability (OP) performance, throughput, and energy efficiency. The simulation results show that inter-clustering model II has the lowest OP, highest throughput, and highest energy efficiency compared with inter-clustering model I and the conventional inter-clustering-based multirelay method. These results demonstrate that inter-clustering model II is well-suited for use in 5G overlay D2D and cellular communications.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.1-9
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• 2017

Recently, the active research into wireless sensor networks has led to the development of sensor nodes with improved performance, including their mobility and location awareness. One of the most important goals of such sensor networks is to transmit the data generated by mobile sensors nodes. Since these sensor nodes move in the mobile wireless sensor networks (MWSNs), the energy consumption required for them to transmit the sensed data to the fixed sink is increased. In order to solve this problem, the use of mobile sinks to collect the data while moving inside the network is studied herein. The important issues are the mobility and energy consumption in MWSNs. Because of the sensor nodes' limited energy, their energy consumption for data transmission affects the lifetime of the network. In this paper, a mobile-sink based energy-efficient clustering scheme is proposed for use in mobile wireless sensor networks (MECMs). The proposed scheme improves the energy efficiency when selecting a new cluster head according to the mobility of the mobile sensor nodes. In order to take into consideration the mobility problem, this method divides the entire network into several cluster groups based on mobile sinks, thereby decreasing the overall energy consumption. Through both analysis and simulation, it was shown that the proposed MECM is better than previous clustering methods in mobile sensor networks from the viewpoint of the network energy efficiency.

• Journal of Internet Computing and Services
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• v.9 no.4
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• pp.43-50
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• 2008

Various studies are being conducted to achieve efficient routing and reduce energy consumption in wireless sensor networks where energy replacement is difficult. Among routing mechanisms, the clustering technique has been known to be most efficient. The clustering technique consists of the elements of cluster construction and data transmission. The elements that construct a cluster are repeated in regular intervals in order to equalize energy consumption among sensor nodes in the cluster. The algorithms for selecting a cluster head node and arranging cluster member nodes optimized for the cluster head node are complex and requires high energy consumption. Furthermore, energy consumption for the data transmission elements is proportional to $d^2$ and $d^4$ around the crossover region. This paper proposes a means of reducing energy consumption by increasing the efficiency of the cluster construction elements that are regularly repeated in the cluster technique. The proposed approach maintains the number of sensor nodes in a cluster at a constant level by equally partitioning the region where nodes with density considerations will be allocated in cluster construction, and reduces energy consumption by selecting head nodes near the center of the cluster. It was confirmed through simulation experiments that the proposed approach consumes less energy than the LEACH algorithm.

• Journal of KIISE
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• v.42 no.11
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• pp.1430-1440
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• 2015

In contrast with battery-based wireless sensor networks (WSNs), solar-powered WSNs can operate for a longtime assuming that there is no hardware fault. Meanwhile, a mobile sink can save the energy consumption of WSN, but its ineffective movement may incur so much energy waste of not only itself but also an entire network. To solve this problem, many approaches, in which a mobile sink visits only on clustering-head nodes, have been proposed. But, the clustering scheme also has its own problems such as energy imbalance and data instability. In this study, therefore, a cluster-based energy-aware data-sharing scheme (CE-DSS) is proposed to effectively support a mobile sink in a solar-powered WSN. By utilizing the redundant energy efficiently, CE-DSS shares the gathered data among cluster-heads, while minimizing the unexpected black-out time. The simulation results show that CE-DSS increases the data reliability as well as conserves the energy of the mobile sink.

• Journal of Digital Convergence
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• v.14 no.1
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• pp.171-179
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• 2016

The energy consumption problem in wireless sensor networks is investigated. The problem is to expend as little energy as possible receiving and transmitting data, because of constrained battery. In this paper, in order to extend the lifetime of the network, we proposed a location-based clustering algorithm for wireless sensor network with skewed-topology. The proposed algorithm is to deploy multiple child nodes at the sink to avoid bottleneck near the sink and to save energy. Proposed algorithm can reduce control traffic overhead by creating a dynamic cluster. We have evaluated the performance of our clustering algorithm through an analysis and a simulation. We compare our algorithm's performance to the best known centralized algorithm, and demonstrate that it achieves a good performance in terms of the life time.

• 전자공학회논문지 IE
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• v.47 no.1
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• pp.41-47
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• 2010

It is very important to prolong the lifetime of wireless sensor networks by using their limited energy efficiently, since it is not possible to change or recharge the battery of sensor nodes after deployment. LEACH protocol is a typical routing protocol based on the clustering scheme for the efficient use of limited energy. It is composed of a few clusters, which consist of head nodes and member nodes. Though LEACH starts from the supposition that all nodes have data transferred to a head, there must be some nodes having useless data in actual state. In this paper we propose a power saving scheme by making a member node dormant if previous sensed data and current data is same. We evaluate the performance of the proposed scheme in comparison with original clustering algorithms. Simulation results validate our scheme has better performance in terms of the number of alive nodes as time evolves.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.1984-2002
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• 2020

With the appearance of wireless spectrum crisis in traditional cellular network, device-to-device (D2D) communication has been regarded as a promising solution to ease heavy traffic burden by enabling precise content delivery among mobile users. However, due to the channel sharing, the interference between D2D and cellular users can affect the transmission rate and narrow the throughput in the network. In this paper, we firstly present a weighted interference minimization cluster formation model involving both social attribute and physical closeness. The weighted-interference, which is evaluated under the susceptible-infected(SI) model, is utilized to gather user in social and physical proximity. Then, we address the cluster formation problem via spectrum clustering with iterative operation. Finally, we propose the stable matching theory algorithm in order to maximize rate oriented to accomplish the one-to-one resource allocation. Numerical results show that our proposed scheme acquires quite well clustering effect and increases the accumulative transmission rate compared with the other two advanced schemes.