• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.75-84
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• 2022

The efficiency of the regional fiscal policy implementation is based on the achievement of target criteria in the formation and distribution of own financial resources of local budgets, reducing their deficit and reducing dependence on transfers. It is also relevant to compare the development of financial autonomy of regions in the course of decentralisation of fiscal relations. The study consists in the cluster analysis of the effectiveness of fiscal policy implementation in the context of 24 regions and the capital city of Kyiv (except for temporarily occupied territories) under conditions of fiscal decentralisation. Clustering of the regions of Ukraine by 18 indicators of fiscal policy implementation efficiency was carried out using Ward's minimum variance method and k-means clustering algorithm. As a result, the regions of Ukraine are grouped into 5 homogeneous clusters. For each cluster measures were developed to increase own revenues and minimize dependence on official transfers to increase the level of financial autonomy of the regions. It has been proved that clustering algorithms are an effective tool in assessing the effectiveness of fiscal policy implementation at the regional level and stimulating further expansion of financial decentralisation of regions.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.4
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• pp.79-86
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• 2009

In this paper, we propose a new clustering scheme that provides optimal data aggregation effect and reduces energy consumption of nodes by considering the density of nodes when forming clusters. Since the size of the cluster is determined to ensure optimal data aggregation rate, our scheme reduces transmission range and minimizes interference between clusters. Moreover, by clustering using locally adjacent nodes and aggregating data received from cluster members, we reduce energy consumption of nodes. Through simulation, we confirmed that energy consumption of the whole network is minimized and the sensor network life-time is extended. Moreover, we show that the proposed clustering scheme improves the performance of network compared to previous LEACH clustering scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1535-1554
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• 2016

This paper proposes a novel channel assignment scheme called multi-cluster based dynamic channel assignment (MC-DCA) to improve system performance for the downlink of dense femtocell networks (DFNs) based on orthogonal frequency division multiple access (OFDMA) and frequency division duplexing (FDD). In order to dynamically assign channels for femtocell access points (FAPs), the MC-DCA scheme uses a heuristic method that consists of two steps: one is a multiple cluster assignment step to group FAPs using graph coloring algorithm with some extensions, while the other is a dynamic subchannel assignment step to allocate subchannels for maximizing the system capacity. Through simulations, we first find optimum parameters of the multiple FAP clustering to maximize the system capacity and then evaluate system performance in terms of the mean FAP capacity, unsatisfied femtocell user equipment (FUE) probability, and mean FAP power consumption for data transmission based on a given FUE traffic load. As a result, the MC-DCA scheme outperforms other schemes in two different DFN environments for commercial and office buildings.

• Journal of the Korea Society of Computer and Information
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• v.19 no.11
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• pp.91-96
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• 2014

Since the sensors of Internet of Things (IOT) collect various data, the lifetime of sensor network is very important and the data should be aggregated efficiently. The contiguous collection by the certain sensors occurs an excessive battery consumption and successive transmission of same value of data should be avoided. To solve these things, we propose an weight-based cluster head replacement method that divides whole network into several grids and cluster head is selected by remaining energy, density of alive sensors and location of sensor. The aim of algorithm maximizes the lifetime of network. Our simulation results shows that the proposed method is very simple as well as balances energy consumption.

• Journal of the Korea Society of Computer and Information
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• v.15 no.8
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• pp.149-156
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• 2010

As following the development of the USN technology, sensor node used in sensor network has capability of quick data process and storage to support efficient network configuration is enabled. In addition, tree-based structure was transformed to cluster in the construction of sensor network. However, query processing based on existing tree structure could be inefficient under the cluster-based network. In this paper, we suggest energy efficient query processing mechanism using filtering through data attribute classification in cluster-based sensor network. The suggestion mechanism use advantage of cluster-based network so reduce energy of query processing and designed more intelligent query dissemination. And, we prove excellence of energy efficient side with MATLab.

• The Journal of Korean Association of Computer Education
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• v.23 no.1
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• pp.77-90
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• 2020

The purpose of the study is to provide educational implications for more effective Problem-based learning(PBL) by investigating students' learning types based on their online learning behaviors. A total of 1,341 students participated in the study, and they engaged in a six-week-long PBL program run by K University. For the study, participants' online activity data were collected. From the data, a total of 48 variables that represent their various online learning behaviors were extracted. Based on the variables, hierarchical cluster analysis was conducted to analyze learning types. Also, the differences in learning characteristics and achievements were investigated by considering types of learning. As a result, the learning types in online PBL were classified as 'high-level participation (cluster 1)', 'medium-level participation (cluster 2)', and 'low-level participation (cluster 3)'. In addition, the achievement level was found to be highest in 'high-level participation (cluster 1)' and lowest in 'low-level participation (cluster 3)'. Based on the results, the implications for improving online PBL were suggested.

• Journal of the Korea Society of Computer and Information
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• v.14 no.2
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• pp.139-147
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• 2009

BLAST (Basic Local Alignment Search Tool) is a best well-known tool in a bioinformatics area. BLAST quickly compares input sequences with annotated huge sequence databases and predicts their functions. It helps biologists to make it easy to annotate newly found sequences with reduced experimental time, scope, and cost. However, as the amount of sequences is increasing remarkably with the advance of sequencing machines, performance of BLAST has been a critical issue and tried to solve it with several alternatives. In this paper, we propose a new PC-Based Cluster system (E-Cluster), a new physical data design methodology (logical partitioning technique) and a query routing technique (intra-query routing). To verify our system, we measure response time, speedup, and efficiency for various sizes of sequences in NR (Non-Redundancy) database. Experimental result shows that proposed system has better speedup and efficiency (maximum 600%) than those o( conventional approaches such as SMF machines, clusters, and grids.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.176-179
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• 2002

In recent years, an increasing amount of computer network research has focused on the problem of cluster system in order to achieve higher performance and lower cost. The load unbalance is the major defect that reduces performance of a cluster system that uses parallel program in a form of SPMD (Single Program Multiple Data). Also, the load unbalance is a problem of MPP (Massive Parallel Processors), and distributed system. The cluster system is a loosely-coupled distributed system, therefore, it has higher communication overhead than MPP. Dynamic load balancing can solve the load unbalance problem of cluster system and reduce its communication cost. The cluster systems considered in this paper consist of P heterogeneous nodes connected by a switch-based network. The master node can predict the average execution time of tasks for each slave node based on the information from the corresponding slave node. Then, the master node redistributes remaining tasks to each node considering the predicted execution time and the communication overhead for task migration. The proposed dynamic load balancing uses execution time prediction to optimize the task redistribution. The various performance factors such as node number, task number, and communication cost are considered to improve the performance of cluster system. From the simulation results, we verified the effectiveness of the proposed dynamic load balancing algorithm.

• Journal of Korea Multimedia Society
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• v.21 no.6
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• pp.667-677
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• 2018

Since sensor networks consist of sensor nodes with limited energy resources, so efficient energy use of sensor nodes is very important in the design of sensor networks. Sensor nodes consume a lot of energy for data transmission. Clustering technique is used to efficiently use energy in data transmission. Recently, mobile sink techniques have been proposed to reduce the energy load concentrated on the cluster header near a sink node. The CMS(Cluster-based Mobile sink) technique minimizes the generation of control messages by creating a data transmission path while creating clusters, and supports the inter-cluster one-hop transmission. But, there is a case where there is no connectivity between neighbor clusters, it causes a problem of having a long hop data transmission path regardless of local distance. In this paper, we propose a SCBC(Strong connection balancing cluster) to support the path of the minimum number of hops. The proposed scheme minimizes the number of hops in the data transmission path and supports efficient use of energy in the cluster header. This also minimizes a number of hops in data transmission paths even when the sink moves and establishes a new path, and it supports the effect of extending the life cycle of the entire sensor network.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06a
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• pp.143-144
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• 2007