• Proceedings of the Korean Information Science Society Conference
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• 2005.11a
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• pp.325-327
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• 2005

이동 애드혹 네트워크에서 트리와 메쉬 기반의 멀티캐스트 메커니즘들은 트리의 빈번한 재구성 및 자원 사용의 비효율적인 문제점을 가지고 있다. 이를 해결하기 위하여 제안된 오버레이 멀티캐스트 메커니즘들 역시 오버레이 트리의 재구성으로 인한 과부하와 밀접한 멤버간의 비효율적인 전송, 그리고 네트워크 확장성에 대한 문제점들을 갖는다. 본 논문에서는 이를 개선하기 위해 위치정보를 기반으로 밀접한 멤버노드들을 클러스터로 관리하여 클러스터 내에서는 브로드캐스팅을 적용하고, 멀티캐스트 소스와 클러스터 대표노드들간에는 유니캐스팅을 적용하는 오버레이 멀티캐스트 메커니즘을 제안한다.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.10a
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• pp.279-282
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• 2000

물류시스템설계 및 개선의 일환으로 차량운송계획 문제는 매우 중요시되는 분야이다. 본 연구는 유전자 알고리즘을 이용한 통합물류 운송계획문제(Integrated Vehicle Routing Problem : IVRP)를 위한 전산화 모델의 개발로서 운송 중인 차량의 자동위치 조회시스템(Automatic Vehicle Location System : AVL)을 이용하여 차량운송의 통제기능을 높이며, 차량운송 효율을 높이는 목적으로 VRP문제와 AVL문제를 연계하는 통합운송시스템의 개념 연구이다. 본 연구에서는 다-물류센터를 고려한 운송 영역할당(Sector Clustering), 경로계획 문제(VRP) 및 유전자 알고리즘을 이용한 운송순서 계획(GA-TSP)을 고려한 통합운송계획모델의 개발을 목적으로 차량의 운송간의 통신 및 통제 등의 기능을 위하여 위치 추적을 가진 GPS와 통신시스템을 위한 TRS 및 위치설정을 위한 GIS를 고려하였다. 본 연구에서의 AVL시스템 개발을 위한 GPS, GIS 및TRS 등 AVL시스템의 구성요소에 대하여 그 개요를 조사 연구하였다. 또한 GPS, GIS을 기반으로한 물류시스템의 구성과 시스템에 필요한 기능 및 구성요소를 파악하고 서브 시스템을 구성하여 각 서브 시스템의 기본설계를 실시하기 위한 연구이다.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 1998.04a
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• pp.31-38
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• 1998

In this study, statistical analyses implemented in the EPRI EQHAZARD programs were employed to estimate the sismicity parameters in the Korean peninsula based upon an combined Korean earthquake catalog. The combined earthquake catalog was prepared by performing earthquake clustering analysis on the collected earthquake catalogs provided by experts of the seismic panel during the PSA for Yonggwang Units 1 & 2. The duplicate earthquake events and secondary events in earthquake clusters have been successfully screened. The resultant earthquake catalog was analyzed to quantitatively assess the incompleteness of the earthquake catalog for specified earthquake magnitudes and time periods. The result shows that the earthquake catalog of the Korean peninsula is complete for the times periods of 1392 ~ 1750 and 1905 ~ 1989 (AD) and earthquake magnitude above 4.5. The PSHA methodology of EQHAZARD features the estimation of inhomogeneous a-and b-values within a seismic source. This study shows various results of a-and b-value is well constrained lying between o.6 and 1.0. Also the confidence of estimated a-and b-value for a specifed location was assessed by quantifing the uncertainty of these parameters using bootstrap simulation.

• Communications for Statistical Applications and Methods
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• v.12 no.2
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• pp.305-312
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• 2005

In the cluster analysis, Hotelling's $T^2$ can be used to estimate the unknown number of clusters based on the idea of multiple comparison procedure. Especially, its threshold is obtained according to the probability of committing the type one error. Examples are used to compare Hotelling's $T^2$ with other classical location test statistics such as Sum-of-Squared Error and Wilks' $\Lambda$ The hierarchical clustering is used to reveal the underlying structure of the data. Also related criteria are reviewed in view of both the between variance and the within variance.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.1142-1145
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• 2008

This paper proposes a novel cluster-based lookup service in mobile ad hoc networks. By applying a self-adaptive multi-hop clustering, we avoid the empty region problem of grid system and omit the need of GPS device. The novelty of the proposed scheme is in its exploitation of hashing function for location querying to achieve low communication overhead. By varying different simulation parameters, we show that the proposed scheme is scalable and adaptive to many networks scenarios. Experiment results demonstrate that our scheme reduces the communication overhead significantly.

• Korean Management Science Review
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• v.18 no.2
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• pp.125-134
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• 2001

This paper is concerned with the development of a GIS-based distribution system with service consideration. The proposed model could be used for a wide range of logistics applications in planning, engineering and operational purpose for logistics system. This research addresses the formulation of those complex prob1ems of two-echelon logistics system to plan the incorporating supply center locations and distribution problems based on GIS. We propose an integrated logistics model for determining the optimal patterns of supply centers and inventory allocations (customers) with a three-step sequential approach. 1) First step, Developing GIS-distance model and stochastic set-covering program to determine Optimel pattern of supply center location. 2) Second step, Optimal sector-clustering to support customers. 3) Third step, Optimal vehicle rouse scheduling based on GIS, GIS-VRP In this research we developed GUI-tree program, the GIS-VRP provide the vehicle to users and freight information in real time. We applied a set of sample examples to this model and demonstrated samp1e results. It has been found that the proposed model is potentially efficient and useful in solving multi-depot problem through examples. However the proposed model can provide logistics decision makers to get the best supply schedule.

• Journal of Information Processing Systems
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• v.1 no.1 s.1
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• pp.49-54
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• 2005

With the recent advances in Micro Electro Mechanical System (MEMS) technology, low cost and low power consumption wireless micro sensor nodes have become available. However, energy-efficient routing is one of the most important key technologies in wireless sensor networks as sensor nodes are highly energy-constrained. Therefore, many researchers have proposed routing protocols for sensor networks, especially cluster-based routing protocols, which have many advantages such as reduced control messages, bandwidth re-usability, and improved power control. Some protocols use information on the locations of sensor nodes to construct clusters efficiently. However, it is rare that all sensor nodes know their positions. In this article, we propose another cluster-based routing protocol for sensor networks. This protocol does not use information concerning the locations of sensor nodes, but uses the remaining energy of sensor networks and the desirable number of cluster heads according to the circumstances of the sensor networks. From performance simulation, we found that the proposed protocol shows better performance than the low-energy adaptive clustering hierarchy (LEACH).

• Journal of KIISE
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• v.44 no.9
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• pp.966-975
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• 2017

In Internet of Things (IoT), the aim of the nodes (called 'Things') is to exchange information with each other, whereby they gather and share information with each other through self decision-making. Therefore, we cannot apply existing aggregation algorithms of Wireless sensor networks that aim to transmit information to only a sink node or a central server, directly to the IoT environment. In addition, since existing algorithms aggregate information from all sensor nodes, problems can arise including an increasing number of transmissions and increasing transmission delay and energy consumption. In this paper, we propose the clustering and property based data exchange method for energy efficient information sharing. First, the proposed method assigns the properties of each node, including the sensing data and unique resource. The property determines whether the node can respond to the query requested from the other node. Second, a cluster network is constructed considering the location and energy consumption. Finally, the nodes communicate with each other efficiently using the properties. For the performance evaluation, TOSSIM was used to measure the network lifetime and average energy consumption.

• Journal of Computing Science and Engineering
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• v.6 no.3
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• pp.227-242
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• 2012

Vehicular Ad Hoc Networks (VANETs) are highly dynamic and unstable due to the heterogeneous nature of the communications, intermittent links, high mobility and constant changes in network topology. Currently, some of the most important challenges of VANETs are the scalability problem, congestion, unnecessary duplication of data, low delivery rate, communication delay and temporary fragmentation. Many recent studies have focused on a hybrid mechanism to disseminate information implementing the store and forward technique in sparse vehicular networks, as well as clustering techniques to avoid the scalability problem in dense vehicular networks. However, the selection of intermediate nodes in the store and forward technique, the stability of the clusters and the unnecessary duplication of data remain as central challenges. Therefore, we propose an adaptable destination-based dissemination algorithm (DBDA) using the publish/subscribe model. DBDA considers the destination of the vehicles as an important parameter to form the clusters and select the intermediate nodes, contrary to other proposed solutions. Additionally, DBDA implements a publish/subscribe model. This model provides a context-aware service to select the intermediate nodes according to the importance of the message, destination, current location and speed of the vehicles; as a result, it avoids delay, congestion, unnecessary duplications and low delivery rate.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.135-140
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• 2017

The demand for aquatic products in the domestic and overseas is increased, so that the aquaculture industry can achieve high performance by controlling and standardizing the production even with a relatively small amount of resources compared with existing fisheries. However, traditional method has problems of low productivity such as natural disasters and ecosystem pollution, and it is necessary to develop a new culture system that can move to the optimal culture site. In order to find the optimal location, you need to collect and analyze the necessary data such as temperature and DO in real time. Data analysis was performed by using K-means clustering method based on machine learning, so that it was possible to decision when and where to move the farm by repeated unsupervised learning. The proposed research could solve the problems of low productivity such as natural disasters and ecosystem pollution if applied to regressive fish farmers.