• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1873-1893
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• 2023

The development of lightweight, low energy and small-sized sensors incorporated with the wireless networks has brought about a phenomenal growth of Wireless Sensor Networks (WSNs) in its different fields of applications. Moreover, the routing of data is crucial in a wide number of critical applications that includes ecosystem monitoring, military and disaster management. However, the time-delay, energy imbalance and minimized network lifetime are considered as the key problems faced during the process of data transmission. Furthermore, only when the functionality of cluster head selection is available in WSNs, it is possible to improve energy and network lifetime. Besides that, the task of cluster head selection is regarded as an NP-hard optimization problem that can be effectively modelled using hybrid metaheuristic approaches. Due to this reason, an Improved Coyote Optimization Algorithm-based Clustering Technique (ICOACT) is proposed for extending the lifetime for making efficient choices for cluster heads while maintaining a consistent balance between exploitation and exploration. The issue of premature convergence and its tendency of being trapped into the local optima in the Improved Coyote Optimization Algorithm (ICOA) through the selection of center solution is used for replacing the best solution in the search space during the clustering functionality. The simulation results of the proposed ICOACT confirmed its efficiency by increasing the number of alive nodes, the total number of clusters formed with the least amount of end-to-end delay and mean packet loss rate.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.303-303
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• 2022

The purpose of this study was to evaluate agronomic characteristics and identify the useful traits to utilize the wheat genetic resources for breeding programs by understanding the phenotypic variation among germplasm through multivariate analysis. In this study, a total of 394 wheat accessions were characterized for 15 agronomic traits using the National Agrobiodiversity Center (NAC) descriptor list, of which 31 accessions from 6 species and 363 unidentified accession (Triticum spp.) available at the NAC, Rural Development Administration (RDA), Korea. Growth characteristics such as leaf width, culm length, spike length, spikelet length, solid stemmed, days to heading, days to maturity, grain-filing period, and also seed characteristics such as width, height, area, perimeter, circle, solidity, and germination percent were studied. Among the 15 agronomic characteristics, the germination percent showed the smallest variation between resources (CV = 0.4%), and the spikelet length (CV = 66.5%) showed the highest variation. A strong positive correlation was found between seed traits such as seed height and seed area (r = 0.90), seed height and seed perimeter (r = 0.87) and seed length and width (r = 0.80). Principal component analysis (PCA) was conducted and the first five principal components comprised 76.7% of the total variance. Among the first five PCs, PCI accounted for 28.5% and PC2 for 20.0%. Wheat resources (394) were classified into four clusters based on cluster analysis, consisting of 215 resources(I), 117 resources(II), 48 resources(III), and 14 resources(IV). Among the clusters, the resources belonging to Cluster III showed the lowest seed width, height, area, and perimeter characteristics compared to other clusters. The wheat resources belonging to cluster IV had small seed width and low germination percent, but took longer to form heads and mature than resources in other clusters. These results will serve as the basis for further genetic diversity studies, and important agronomic characteristics will be used for improving wheat, including developing high-yielding and resistant varieties to biotic and abiotic stresses via breeding programs.

• Journal of information and communication convergence engineering
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• v.6 no.4
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• pp.466-469
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• 2008

The existing routing protocols in USN environment, PEGASIS is more efficient than LEACH, which is a hierarchical routing protocol, for network configuration based on power consumption. Despite its merit that it can reduce energy consumption per node, however, the PEGASIS protocol also has a weakness that it is less responsive to frequent changes that occur in the configuration of sensor network due to BS nodes that keep changing, which is a typical characteristic of the sensor network. To address this problem, this paper proposes to select sub-cluster heads and have them serve as intermediate nodes. This paper presents and analyses that this method can resolve the aforementioned problem of the PEGASIS algorithm.

• Journal of Industrial Technology
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• v.21 no.A
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• pp.147-153
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• 2001

This paper presents techniques for discovering rules with elastic patterns. Elastic patterns are useful for discovering rules from data sequences with different sampling rates. For fast discovery of rules whose heads and bodies are elastic patterns, we construct a suffix tree from succinct forms of data sequences. The suffix tree is a compact representation of rules, and is also used as an index structure for finding rules matched to a target head sequence. When matched rules cannot be found, the concept of rule relaxation is introduced. Using a cluster hierarchy and a relaxation error, we find the least relaxed rules that provide the most specific information on a target head sequence. Performance evaluation through extensive experiments reseals the effectiveness of the proposed approach.

• Korean Management Science Review
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• v.26 no.3
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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.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2008.10b
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• pp.507-511
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• 2008

Supporting energy efficiency and load balancing in wireless sensor network is the most important issue in devising the hierarchical routing protocols. Recently, the dual layered clustering scheme with GPS was proposed for the supporting of load balancing for cluster heads but there would be many collided messages in the overlapped area between two layers. Thereby, the purpose of this paper is to reduce the collision rate in the overlapped layer by concisely distinguish them with the same number of nodes in them. For the layer partition, this paper uses an equation $x^2+ y^2{\le}(\frac{R}{\sqrt{2\pi}})^2$ to distinguish layers. By using it, the scheme could efficiently distinguish two layers and gets the balanced number of elements in them. Therefore, the proposed routing scheme could prolong the overall network life cycle about 10% compared to the previous two layered clustering scheme.

• International Journal of Internet, Broadcasting and Communication
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• v.7 no.1
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• pp.49-56
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• 2015

As WSN is energy constraint so energy efficiency of nodes is important. Because avoiding long distance communication, clustering operating in rounds is an efficient algorithm for prolonging the lifetime of WSN and its performance depends on duration of a round. A short round time leads to frequent re-clustering while a long round time increases energy consume of cluster heads more. So existing clustering schemes determine proper round time, based on the parameters of initial WSN. But it is not appropriate to apply the round time according to initial value throughout the whole network time because WSN is very dynamic networks nodes can be added or vanished. In this paper we propose a new algorithm which calculates the round time relying on the alive node number to adapt the dynamic WSN. Simulation results validate the proposed algorithm has better performance in terms of energy consumption of nodes and loss rate of data.

• International Journal of Internet, Broadcasting and Communication
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• v.7 no.1
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• pp.23-29
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• 2015

Energy constraints of wireless sensor networks are an important challenge. Data Transmission requires energy. Distance between origin and destination has an important role in energy consumption. In addition, the location of base station has a large impact on energy consumption and a specific method not proposed for it. In addition, a obtain model for location of base station proposed. Also a model for distributed clustering is presented by cluster heads. Eventually, a combination of discussed ideas is proposed to improve the energy consumption. The proposed ideas have been implemented over the LEACH-C protocol. Evaluation results show that the proposed methods have a better performance in energy consumption and lifetime of the network in comparison with similar methods.

• 한국정보통신설비학회:학술대회논문집
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• 2005.08a
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• pp.349-357
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• 2005

In this paper, a new clustering algorithm using the Guaranteed Minimum Coverage (GMC) is proposed. In the new protocol, an appropriate distribution of clusterheads is accomplished by guaranteeing a stochastic coverage at each clusterhead(CH)s. Using this protocol, the communication cost from clusterheads to their member nodes and the load variance in each clusterheads are reduced. Therefore, the network lifetime can be extended and the fair energy consumption for all CHs can be achieved