• The Journal of the Korea Contents Association
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• v.14 no.10
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• pp.20-31
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• 2014

Recently, cache sharing methods have been studied in order to effectively reply to user requests in mobile P2P networks. In this paper, we propose a cache sharing scheme based on a cluster considering the peer connectivity in mobile P2P networks. The proposed scheme shares caches by making a cluster that consists of peers preserving the connectivity among them for a long time. The proposed scheme reduces data duplication to efficiently use the cache space in a cluster. The cache space is divided into two parts with a data cache and a temporary cache for a cache space. It is possible to reduce the delay time when the cluster topology is changed or the cache data is replaced utilizing a temporary cache. The proposed scheme checks the caches of peers in a route to a cluster header and the caches of one-hop peers in order to reduce the communication cost. It is shown through performance evaluation that the proposed scheme outperforms the existing schemes.

• Proceedings of the Conference
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• 2005.06a
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• pp.28-32
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• 2005

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.2
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• pp.89-96
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• 2015

Location-based social media data have high potential to be used in various area such as big data, location based services and so on. In this study, we applied a series of analysis methodology to figure out how the important keywords in location-based social media are spatially distributed by analyzing text information. For this purpose, we collected tweet data with geo-tag in Gangnam district and its environs in Seoul for a month of August 2013. From this tweet data, principle keywords are extracted. Among these, keywords of three categories such as food, entertainment and work and study are selected and classified by category. The spatial clustering is conducted to the tweet data which contains keywords in each category. Clusters of each category are compared with buildings and benchmark POIs in the same position. As a result of comparison, clusters of food category showed high consistency with commercial areas of large scale. Clusters of entertainment category corresponded with theaters and sports complex. Clusters of work and study showed high consistency with areas where private institutes and office buildings are concentrated.

• Journal of the Korean Geographical Society
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• v.43 no.3
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• pp.392-411
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• 2008

The purpose of this paper is to develop a method for exploring hotspot patterns of house price volatility where there is a high fluctuation in price and homogeneity of direction of price volatility. These patterns are formed when the majority of householders in an area show an adaptive tendency in their decision making. This paper suggests a method that consists of two analytical parts. The first part uses spatial scan statistics to detect spatial clusters of houses with a positive range of price volatility. The second part utilizes local Moran's I to evaluate the homogeneity of direction of price volatility within each cluster. The method is applied to the areas of Gangnam-Gu, Seocho-Gu, and Songpa-Gu in Seoul from August to November of 2003; the Participatory Government of Korea designated these areas and this period as the most speculative. The results of the analysis show that the area around Gaepo-Dong was as a hotspot before the Government's anti-speculative 10.29 policy in 2003; the house prices in the same area stabilized in October, 2003 and the area was identified as a coldspot in December, 2003. This case study shows that the suggested method enables exploration of hotspot of house price volatility at micro spatial scales which had not been detected by visual analysis.

• Journal of the Economic Geographical Society of Korea
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• v.20 no.2
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• pp.189-213
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• 2017

This study seeks to critically examine the significance and limits of the cluster adaptive cycle model for analysis of cluster evolution and to propose research issues for future analysis of cluster evolution based on this critical examination. Until the 1980s, research on industrial complexes including clusters was based on a 'static perspective' that focuses on the aspect of economic space at a specific point in time, but the research paradigm has recently shifted to a 'dynamic perspective' focusing on 'evolution' of 'complex adaptive systems'. As a result, the adaptive cycle model has attracted attention as an analysis tool of dynamically evolving clusters. However, the cluster adaptive cycle model has emerged by being appropriately modified and expanded according to the properties of the cluster and its evolution. The cluster adaptive cycle model is a comprehensive analysis framework that identifies the characteristics of cluster evolution in terms of resource accumulation, interdependence, and resilience and classifies cluster evolution paths into six different categories. Nevertheless, there is still a need for further discussion and supplementation in terms of theoretical and empirical research to expand and deepen the model. Therefore, research issues for future analysis of cluster evolution are to specify and elaborate the cluster evolution model, to emphasize the concept of resilience, and to verify the applicability and usefulness of the model through empirical research.

• Journal of Internet Computing and Services
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• v.13 no.5
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• pp.1-8
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• 2012

In this paper, we propose a new clustering combination based on numerical data driven for rule generation mechanism. In large and complicated space, a clustering method can obtain limited performance results. To overcome the single clustering method problem, hybrid combined methods can solve problem to divided simple cluster estimation. Fundamental structure of the proposed method is combined by mountain clustering and modified Chen clustering to extract detail cluster information in complicated data distribution of non-parametric space. It has automatic rule generation ability with advanced density based operation when intelligent systems including neural networks and fuzzy inference systems can be generated by clustering results. Also, results of the mechanism will be served to information of decision support system to infer the useful knowledge. It can extend to healthcare and medical decision support system to help experts or specialists. We show and explain the usefulness of the proposed method using simulation and results.

• Journal of Korea Spatial Information System Society
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• v.10 no.4
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• pp.21-26
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• 2008

A method for processing huge airborne laser scanned data using parallel computing and virtual grid is proposed and the method is tested by generating raster DSM(Digital Surface Model) with IDW(Inverse Distance Weighting). Parallelism is involved for fast interpolation of huge point data and virtual grid is adopted for enhancing searching efficiency of irregularly distributed point data. Processing time was checked for the method using cluster constituted of one master node and six slave nodes, resulting in efficiency near to 1 and load scalability property. Also large data which cannot be processed with a sole system was processed with cluster system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.4
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• pp.1001-1008
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• 2015

Mobile Ad hoc Network(MANET) consists of a node that has mobility. In MANET, the node has routing, the node builds a network of their own, no dependent infrastructure. Topology are exchanged due to node mobility in MANET. For reducing the change of topology, hierarchical network algorithm has been investigated. In hierarchical network, cluster member node communicates through cluster head node. When the load-balancing of cluster head node is exceed, assigned cluster member node can't communicate with base station. To solve this problem, we proposed Load Tolerance algorithm. The proposed algorithm, when cluster member node can't send a message by cluster head node that exceed load-balancing, then the cluster member node sends a message by selected load tolerance node. Through a simulation, the proposed algorithm improves packet delivery ratio in cluster routing.

• Journal of the Economic Geographical Society of Korea
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• v.19 no.4
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• pp.764-781
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• 2016

During the last two decades, industrial cluster policies for promoting regional economic growth and industrial development have been flourishing all over the world. Even though cluster policies have partly contributed to regional industrial growth and innovation capabilities, they have long been blamed for regional industrial lock-ins and declining regional industrial resilience because of applying homeogenous cluster policies and regional specialized strategic industrial promotion policies for various localities, which are based on so-called 'selection and concentration' principle. This paper suggests postcluster policy focused on placed-based smart specialization and regional business platform strategies.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.5
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• pp.117-121
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• 2018

A Wireless Sensor Network is a network that is composed of wireless sensor nodes. There is no restriction on the place where it can be installed because it is composed wirelessly. Instead, sensor nodes have limited energy, such as batteries. Therefore, to use the network for a long time, energy consumption should be minimized. Several protocols have been proposed to minimize energy consumption, and the typical protocol is the LEACH protocol. The LEACH protocol is a cluster-based protocol that minimizes energy consumption by dividing the sensor field into clusters. Depending on how you organize the clusters of sensor field, network lifetimes may increase or decrease. In this paper, we will improve the network lifetime by improving the cluster head selection method in LEACH Protocol.