• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.6
• /
• pp.1728-1742
• /
• 2023

In this paper, we extended a hierarchical clustering technique, which is the most researched in the sensor network field, and studied a dynamic differential clustering technique to minimize energy consumption and ensure equal lifespan of all sensor nodes while considering the mobility of sinks. In a sensor network environment with mobile sinks, clusters close to the sinks tend to consume more forwarding energy. Therefore, clustering that considers forwarding energy consumption is desired. Since all clusters form a hierarchical tree, the number of levels of the tree must be considered based on the size of the cluster so that the cluster size is not growing abnormally, and the energy consumption is not concentrated within specific clusters. To verify that the proposed DDC protocol satisfies these requirements, a simulation using Matlab was performed. The FND (First Node Dead), LND (Last Node Dead), and residual energy characteristics of the proposed DDC protocol were compared with the popular clustering protocols such as LEACH and EEUC. As a result, it was shown that FND appears the latest and the point at which the dead node count increases is delayed in the DDC protocol. The proposed DDC protocol presents 66.3% improvement in FND and 13.8% improvement in LND compared to LEACH protocol. Furthermore, FND improved 79.9%, but LND declined 33.2% when compared to the EEUC. This verifies that the proposed DDC protocol can last for longer time with more number of surviving nodes.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.4 no.6
• /
• pp.1133-1151
• /
• 2010

Energy balanced consumption routing is based on assumption that the nodes consume energy both in transmitting and receiving. Lopsided energy consumption is an intrinsic problem in low-cost sensor networks characterized by multihop routing and in many traffic overhead pattern networks, and this irregular energy dissipation can significantly reduce network lifetime. In this paper, we study the problem of maximizing network lifetime through balancing energy consumption for uniformly deployed low-cost sensor networks. We formulate the energy consumption balancing problem as an optimal balancing data transmitting problem by combining the ideas of corona cluster based network division and optimized transmitting state routing strategy together with data transmission. We propose a localized cluster based routing scheme that guarantees balanced energy consumption among clusters within each corona. We develop a new energy cluster based routing protocol called "OECR". We design an offline centralized algorithm with time complexity O (log n) (n is the number of clusters) to solve the transmitting data distribution problem aimed at energy balancing consumption among nodes in different cluster. An approach for computing the optimal number of clusters to maximize the network lifetime is also presented. Based on the mathematical model, an optimized energy cluster routing (OECR) is designed and the solution for extending OEDR to low-cost sensor networks is also presented. Simulation results demonstrate that the proposed routing scheme significantly outperforms conventional energy routing schemes in terms of network lifetime.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.8 no.4
• /
• pp.18-22
• /
• 1998

This paper presents a fuzzy c elliptic shells algorithm that detects culusters than can be expressed by hyperellipsoidal shells. The algorithm is computationally efficient since the prototyes of shell clusters are determined by a simple matrix inversion instead of by solving several nonlinear equations. The algorithm also works when the detected shells are partial the optimal number of clusters is unkonown initially. A set of simulation results validates the proposed clustering mehtod.

• Proceedings of the Korean Institute of Communication Sciences Conference
• /
• 1986.10a
• /
• pp.83-86
• /
• 1986

In this paper, we propose the new color image segmentation algorithm using clustering method in the normalized r,g,b coordinates. The number of intrinsic clusters which are included in color image is estimated by the clustering quality measure and the initial centers of clusters are calculated by a hierarchical way. The proposed algorithm was varified by the computer simulation.

• Journal of Information Processing Systems
• /
• v.14 no.4
• /
• pp.989-1009
• /
• 2018

Rapid advances in science and technology with exponential development of smart mobile devices, workstations, supercomputers, smart gadgets and network servers has been witnessed over the past few years. The sudden increase in the Internet population and manifold growth in internet speeds has occasioned the generation of an enormous amount of data, now termed 'big data'. Given this scenario, storage of data on local servers or a personal computer is an issue, which can be resolved by utilizing cloud computing. At present, there are several cloud computing service providers available to resolve the big data issues. This paper establishes a framework that builds Hadoop clusters on the new single-board computer (SBC) Mobile Raspberry Pi. Moreover, these clusters offer facilities for storage as well as computing. Besides the fact that the regular data centers require large amounts of energy for operation, they also need cooling equipment and occupy prime real estate. However, this energy consumption scenario and the physical space constraints can be solved by employing a Mobile Raspberry Pi with Hadoop clusters that provides a cost-effective, low-power, high-speed solution along with micro-data center support for big data. Hadoop provides the required modules for the distributed processing of big data by deploying map-reduce programming approaches. In this work, the performance of SBC clusters and a single computer were compared. It can be observed from the experimental data that the SBC clusters exemplify superior performance to a single computer, by around 20%. Furthermore, the cluster processing speed for large volumes of data can be enhanced by escalating the number of SBC nodes. Data storage is accomplished by using a Hadoop Distributed File System (HDFS), which offers more flexibility and greater scalability than a single computer system.

• Journal of the Korean Ceramic Society
• /
• v.34 no.9
• /
• pp.979-985
• /
• 1997

The three-dimensional particle packing process is simulated using Lahey FORTRAN 90 as a programming language running on a personal computer. Particle clusters constructed with rearrangement which occurs during packing have higher average coordination number and packing density than particle clusters rearranged after packing. Rearranging particles can not completely block other particles from entering pore volume in 3-dimensional packing unlike in 2-dimensional packing. It is found that there is a region of instability where lower packing density results from the destruction of the ordered packing.

• The Journal of the Korea Contents Association
• /
• v.7 no.6
• /
• pp.22-30
• /
• 2007

Most real word systems such as world economy, stock market, and medical applications, contain a series of dynamic and complex phenomena. One of common methods to understand these systems is to build a model and analyze the behavior of the system. In this paper, we investigated methods for best clustering over time series data. As a first step for clustering, BIC (Bayesian Information Criterion) approximation is used to determine the number of clusters. A search technique to improve clustering efficiency is also suggested by analyzing the relationship between data size and BIC values. For clustering, two methods, model-based and similarity based methods, are analyzed and compared. A number of experiments have been performed to check its validity using real data(stock price). BIC approximation measure has been confirmed that it suggests best number of clusters through experiments provided that the number of data is relatively large. It is also confirmed that the model-based clustering produces more reliable clustering than similarity based ones.

• The Journal of the Korea Contents Association
• /
• v.6 no.1
• /
• pp.80-84
• /
• 2006

Motivated by the fact that cluster reduction strategies such as inserting a vowel or deleting a consonant in resolving English complex clusters differ depending on studies, this paper investigates the repair strategies employed by Korean EFL students. A total of 60 college students participated in the present study and the participants' production of English voiceless word-initial and word-final clusters was measured using the materials designed for this study. It has been shown that prosodic positions such as onset and coda and the number of cluster sequences influenced cluster reduction strategies. The error rates of both insertion and deletion were noticeably higher in the coda position than in the onset position and both insertion and deletion error rates were higher in triconsonatal cluster than in biconsonantal cluster sequences. Overall, the insertion rate was higher than the deletion rate. However, the deletion rate was significantly higher than the insertion rate in triconsonantal coda cluster sequences. Because of this, the deletion rate was higher than the insertion rate for triconsonantal cluster sequences across onset and coda. Also, the high deletion rate of triconsonantal coda clusters contributed to the high deletion rate for the coda clusters in general.

• Development and Reproduction
• /
• v.26 no.2
• /
• pp.91-98
• /
• 2022

Genomic DNA (gDNA) set apart from two populations of Korean Charybdis crab (Charybdis japonica) was augmented by PCR experiments. The five oligonucleotides primers (ONT-primers) were spent to yield the number of unique loci shared to each crab population (ULSECP) and number of loci shared by the two crab populations (LSTCP). 305 fragments (FRAGs) were identified in the Charybdis crab population A (CCPA), and 344 in the Charybdis crab population B (CCPB): 44 number of ULSECP (14.43%) in the CCPA and 110 (31.98%) in the CCPB. 44 number of LSTCP, with an average of 8.8 per primer, were detected in the two crab populations. The bandsharing (BS) value between entity's no. 01 and no. 10 was the lowest (0.371) between the two CCPs. The average bandsharing (ABS) values of individuals in the CCPA (0.575±0.014) were lesser than in those originated from the CCPB (0.705±0.011) (p < 0.05). The polar hierarchical dendrogram (PHD) achieved by the five ONT-primers denotes three genetic clusters (GCs): cluster I (CHARYBCRAB 01, 04, 05, 06, and 08), cluster II (CHARYBCRAB 02, 03, 07, 09, 10, and 11) and cluster III (CHARYBCRAB 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, and 22). The shortest genetic distance (GD) displaying significant molecular difference (MD) was between individuals CHARYBCRAB no. 18 and CHARYBCRAB no. 17 (0.055).

• Journal of Advanced Marine Engineering and Technology
• /
• v.20 no.3
• /
• pp.11-18
• /
• 1996

Liquid droplets of water and argon surrounded by their vapor have been simulated by the milecular dynamics method. To explore the surface phenomena of clusters, each molecule is classified into 'liquid', 'surface', or 'vapor' with respect to the number of neighbor molecules. The contribution of a 'surface' molecule of the water cluster to the far infrared spectrum is almist the same as that of the 'liquid' molecule. Hence, the liquid-vapor interface is viewed as geometrically and temporally varying boundary of 'liquid' molecules with only a single layer of 'surface' molecules that might have different characteristics from the 'liquid' molecules. The time scale of the 'phase change' of each molecule is estimated for the argon cluster by observing the instantancous kinetic and potential energies of each molecule. To compare the feature of clusters with macroscopic droplets, the temperature dependence of the surface tension of the argon cluster is estimated.