• Title/Summary/Keyword: Hierarchical Networks

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Improvement of MAP Load Balancing in Hierarchical Mobile IPv6 (계층적 Mobile IPv6에서의 MAP 부하 분산 개선에 관한 분석)

  • Song, Bok-Sob;Kim, Jeong-Ho
    • The Journal of the Korea Contents Association
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    • v.9 no.2
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    • pp.67-75
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    • 2009
  • The growing need for the mobility supportable networks induces the IP-based mobility management protocols. Though HMIPv6 which manages the micro-mobility of mobile nodes using MAPs suggests an effective method for mobility-support for mobile nodes within the domain that is managed by MAP. There is a problem that traffic may be concentrated on MAPs. In this paper, therefore, we proposed a method that can effectively distribute the traffic which is concentrated on a MAP under phased Mobile IPv6. In our proposed method, two or more MAPs are required and classified as an 'Active MAP' or a 'Passive MAP'. In addition, we defined the state of transition events between Active MAP and Passive MAP and the operations among MAPs for load distribution when an overload condition is occurred at some MAPs by traffic congestion. We compared the performance of our proposed method with its phased Mobile IPv6 to prove the propriety of our proposed method. As a result, we showed that our proposed method can provide an enhanced performance by about 12 percentages in view of packet throughput at the node.

A Top-down based Control Tree Construction Mechanism for Reliable Multicast Transport Protocols (신뢰적인 멀티캐스트 전송 프로토콜을 위한 Top-Down 기반의 제어 트리 구축 방안)

  • Kim, Eun-Sook;Koh, Seok-Joo;Kang, Shin-Gak;Choe, Jong-Won
    • Journal of KIISE:Information Networking
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    • v.28 no.4
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    • pp.611-620
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    • 2001
  • To meet the requirements of reliable service for various applications, a Reliable Multicast Transport Protocol should be implemented over IP Multicast where currently best-effort service is provided. Among the current researches, hierarchical tree-based mechanism has been proposed and actively studied. This mechanism is known to provide high scalability as well as reliability, but needs an additional tree configuring mechanism for building an efficient logical tree in transport layer. Bottom-up approach has been used for creating such a tree. This method has benefits from parallel tree construction for receivers, while it has some drawbacks such that it does not guarantee a loop-free tree and brings heavy message overhead during tree creation process. Therefore, this paper proposes a top-down based mechanism for constructing a control tree, which can guarantee loop-freeness by step-wise mannered tree building. From experimental simulations, it shows that the proposed mechanism has less message overhead. It is recommended that the bottom-up and the proposed top-down will be selectively used in real networks, according to the requirements of the concerned multicast applications.

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Protein Function Finding Systems through Domain Analysis on Protein Hub Network (단백질 허브 네트워크에서 도메인분석을 통한 단백질 기능발견 시스템)

  • Kang, Tae-Ho;Ryu, Jea-Woon;Kim, Hak-Yong;Yoo, Jae-Soo
    • The Journal of the Korea Contents Association
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    • v.8 no.1
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    • pp.259-271
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    • 2008
  • We propose a protein function finding algorithm that is able to predict specific molecular function for unannotated proteins through domain analysis from protein-protein network. To do this, we first construct protein-protein interaction(PPI) network in Saccharomyces cerevisiae from MIPS databases. The PPI network(proteins; 3,637, interactions; 10,391) shows the characteristics of a scale-free network and a hierarchical network that proteins with a number of interactions occur in small and the inherent modularity of protein clusters. Protein-protein interaction databases obtained from a Y2H(Yeast Two Hybrid) screen or a composite data set include random false positives. To filter the database, we reconstruct the PPI networks based on the cellular localization. And then we analyze Hub proteins and the network structure in the reconstructed network and define structural modules from the network. We analyze protein domains from the structural modules and derive functional modules from them. From the derived functional modules with high certainty, we find tentative functions for unannotated proteins.

Real-time Fault Detection and Classification of Reactive Ion Etching Using Neural Networks (Neural Networks을 이용한 Reactive Ion Etching 공정의 실시간 오류 검출에 관한 연구)

  • Ryu Kyung-Han;Lee Song-Jae;Soh Dea-Wha;Hong Sang-Jeen
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.9 no.7
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    • pp.1588-1593
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    • 2005
  • In coagulant control of water treatment plants, rule extraction, one of datamining categories, was performed for coagulant control of a water treatment plant. Clustering methods were applied to extract control rules from data. These control rules can be used for fully automation of water treatment plants instead of operator's knowledge for plant control. To perform fuzzy clustering, there are some coefficients to be determined and these kinds of studies have been performed over decades such as clustering indices. In this study, statistical indices were taken to calculate the number of clusters. Simultaneously, seed points were found out based on hierarchical clustering. These statistical approaches give information about features of clusters, so it can reduce computing cost and increase accuracy of clustering. The proposed algorithm can play an important role in datamining and knowledge discovery.

A Minimum Data-Rate Guaranteed Resource Allocation With Low Signaling Overhead in Multi-Cell OFDMA Systems

  • Kwon, Ho-Joong;Lee, Won-Ick;Lee, Byeong-Gi
    • Journal of Communications and Networks
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    • v.11 no.1
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    • pp.26-35
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    • 2009
  • In this paper, we investigate how to do resource allocation to guarantee a minimum user data rate at low signaling overhead in multi-cell orthogonal frequency division multiple access (OFDMA) wireless systems. We devise dynamic resource allocation (DRA) algorithms that can minimize the QoS violation ratio (i.e., the ratio of the number of users who fail to get the requested data rate to the total number of users in the overall network). We assume an OFDMA system that allows dynamic control of frequency reuse factor (FRF) of each sub-carrier. The proposed DRA algorithms determine the FRFs of the sub-carriers and allocate them to the users adaptively based on inter-cell interference and load distribution. In order to reduce the signaling overhead, we adopt a hierarchical resource allocation architecture which divides the resource allocation decision into the inter-cell coordinator (ICC) and the base station (BS) levels. We limit the information available at the ICC only to the load of each cell, that is, the total number of sub-carriers required for supporting the data rate requirement of all the users. We then present the DRA with limited coordination (DRA-LC) algorithm where the ICC performs load-adaptive inter-cell resource allocation with the limited information while the BS performs intra-cell resource allocation with full information about its own cell. For performance comparison, we design a centralized algorithm called DRA with full coordination (DRA-FC). Simulation results reveal that the DRA-LC algorithm can perform close to the DRA-FC algorithm at very low signaling overhead. In addition, it turns out to improve the QoS performance of the cell-boundary users, and achieve a better fairness among neighboring cells under non-uniform load distribution.

Hybrid Word-Character Neural Network Model for the Improvement of Document Classification (문서 분류의 개선을 위한 단어-문자 혼합 신경망 모델)

  • Hong, Daeyoung;Shim, Kyuseok
    • Journal of KIISE
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    • v.44 no.12
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    • pp.1290-1295
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    • 2017
  • Document classification, a task of classifying the category of each document based on text, is one of the fundamental areas for natural language processing. Document classification may be used in various fields such as topic classification and sentiment classification. Neural network models for document classification can be divided into two categories: word-level models and character-level models that treat words and characters as basic units respectively. In this study, we propose a neural network model that combines character-level and word-level models to improve performance of document classification. The proposed model extracts the feature vector of each word by combining information obtained from a word embedding matrix and information encoded by a character-level neural network. Based on feature vectors of words, the model classifies documents with a hierarchical structure wherein recurrent neural networks with attention mechanisms are used for both the word and the sentence levels. Experiments on real life datasets demonstrate effectiveness of our proposed model.

A Domain-based Reactive Routing Protocol for the Hybrid WMN (하이브리드 WMN을 위한 가상 도메인 기반의 반응형 라우팅 프로토콜)

  • Kim, Ho-Cheal
    • Journal of the Korea Society of Computer and Information
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    • v.19 no.7
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    • pp.59-70
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    • 2014
  • This paper propose a new wireless multi-hop routing protocol that takes the hierarchical mesh of the hybrid WMN into account. WMN that is possible to provide various applications of wireless networks still has many open issues that should be solved despite the studies carried out over a decade. Especially, in routing protocol area, a problem degrading the routing efficiency by applying one of the routing protocols, which are designed for the MANET, to the hybrid WMN be solved above all. For the improvement of the routing performance, both good routing protocol and metric are essential. However, the recent studies are only concentrated in routing metric by use of the cross-layer design. Therefore, this paper is dedicated to the routing protocol that is essential for the performance of the routing but needed more studies. The proposed protocol in this paper is reactive, and designed to reorganize the hybrid WMN with several pseudo domains, and carry out domain-based route decision. By the simulation result for the performance analysis of the proposed protocol, the average delay for the route decision was decreased by 43% compared to AODV that is the typical reactive protocol.

An Hierarchical Key Management Scheme for Assure Data Integrity in Wireless Sensor Network (WSN에서 데이터 무결성을 보장하는 계층적인 키 관리 기법)

  • Jeong, Yoon-Su;Hwang, Yoon-Cheol;Lee, Sang-Ho
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.3C
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    • pp.281-292
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    • 2008
  • A main application of sensor networks are to monitor and to send information about a possibly hostile environment to a powerful base station connected to a wired network. To conserve power from each sensor, intermediate network nodes should aggregate results from individual sensors. However, it can make it that a single compromised sensor can render the network useless, or worse, mislead the operator into trusting a false reading. In this paper, we propose a protocol to give us a key aggregation mechanism that intermediate network nodes could aggregate data more safely. The proposed protocol is more helpful at multi-tier network architecture in secure sessions established between sensor nodes and gateways. From simulation study, we compare the amount of the energy consumption overhead, the time of key transmission and the ratio of of key process between the proposed method and LHA-SP. The simulation result of proposed protocol is low 3.5% a lord of energy consumption than LHA-SP, the time of key transmission and the ration of key process is get improved result of each 0.3% and 0.6% than LHA-SP.

Nonstandard Machine Learning Algorithms for Microarray Data Mining

  • Zhang, Byoung-Tak
    • Proceedings of the Korean Society for Bioinformatics Conference
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    • 2001.10a
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    • pp.165-196
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    • 2001
  • DNA chip 또는 microarray는 다수의 유전자 또는 유전자 조각을 (보통 수천내지 수만 개)칩상에 고정시켜 놓고 DNA hybridization 반응을 이용하여 유전자들의 발현 양상을 분석할 수 있는 기술이다. 이러한 high-throughput기술은 예전에는 생각하지 못했던 여러가지 분자생물학의 문제에 대한 해답을 제시해 줄 수 있을 뿐 만 아니라, 분자수준에서의 질병 진단, 신약 개발, 환경 오염 문제의 해결 등 그 응용 가능성이 무한하다. 이 기술의 실용적인 적용을 위해서는 DNA chip을 제작하기 위한 하드웨어/웻웨어 기술 외에도 이러한 데이터로부터 최대한 유용하고 새로운 지식을 창출하기 위한 bioinformatics 기술이 핵심이라고 할 수 있다. 유전자 발현 패턴을 데이터마이닝하는 문제는 크게 clustering, classification, dependency analysis로 구분할 수 있으며 이러한 기술은 통계학과인공지능 기계학습에 기반을 두고 있다. 주로 사용된 기법으로는 principal component analysis, hierarchical clustering, k-means, self-organizing maps, decision trees, multilayer perceptron neural networks, association rules 등이다. 본 세미나에서는 이러한 기본적인 기계학습 기술 외에 최근에 연구되고 있는 새로운 학습 기술로서 probabilistic graphical model (PGM)을 소개하고 이를 DNA chip 데이터 분석에 응용하는 연구를 살펴본다. PGM은 인공신경망, 그래프 이론, 확률 이론이 결합되어 형성된 기계학습 모델로서 인간 두뇌의 기억과 학습 기작에 기반을 두고 있으며 다른 기계학습 모델과의 큰 차이점 중의 하나는 generative model이라는 것이다. 즉 일단 모델이 만들어지면 이것으로부터 새로운 데이터를 생성할 수 있는 능력이 있어서, 만들어진 모델을 검증하고 이로부터 새로운 사실을 추론해 낼 수 있어 biological data mining 문제에서와 같이 새로운 지식을 발견하는 exploratory analysis에 적합하다. 또한probabilistic graphical model은 기존의 신경망 모델과는 달리 deterministic한의사결정이 아니라 확률에 기반한 soft inference를 하고 학습된 모델로부터 관련된 요인들간의 인과관계(causal relationship) 또는 상호의존관계(dependency)를 분석하기에 적합한 장점이 있다. 군체적인 PGM 모델의 예로서, Bayesian network, nonnegative matrix factorization (NMF), generative topographic mapping (GTM)의 구조와 학습 및 추론알고리즘을소개하고 이를 DNA칩 데이터 분석 평가 대회인 CAMDA-2000과 CAMDA-2001에서 사용된cancer diagnosis 문제와 gene-drug dependency analysis 문제에 적용한 결과를 살펴본다.

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Design and Analysis of Digital Circuit System Considering Power Distribution Networks (파워 분배망을 고려한 디지털 회로 시스템의 설계와 분석)

  • Lee, Sang-Min;Moon, Gyu;Wee, Jae-Kyung
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.41 no.4
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    • pp.15-22
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    • 2004
  • This paper presents the channel analysis considering power distribution network(PDN) system of PCB. For achieve the target PDN system we proposed the useful design approach for acquiring the characteristic target of power distribution network in overall frequency ranges. The proposed method is based on the hierarchical approach related to frequency ranges and the path-based equivalent circuit model to consider the interference of the current paths between the decoupling capacitors and the board through it is a lumped model for fast and easy calculation, experimental results show that the proposed model is almost as precise as the numerical analysis. The analysis of PDN system shows that although the effective inductance of package dominatly affects the power noise and the signal transfer through data channel, the board PDNs also can not be neglected for achieving the accurate channel signaling. Therefore, we must design concurrently the chip, package, and board from the initial spec design of high speed digital system.