• Title/Summary/Keyword: Hierarchical Network

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i-LEACH : Head-node Constrained Clustering Algorithm for Randomly-Deployed WSN (i-LEACH : 랜덤배치 고정형 WSN에서 헤더수 고정 클러스터링 알고리즘)

  • Kim, Chang-Joon;Lee, Doo-Wan;Jang, Kyung-Sik
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.16 no.1
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    • pp.198-204
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    • 2012
  • Generally, the clustering of sensor nodes in WSN is a useful mechanism that helps to cope with scalability problem and, if combined with network data aggregation, may increase the energy efficiency of the network. The Hierarchical clustering routing algorithm is a typical algorithm for enhancing overall energy efficiency of network, which selects cluster-head in order to send the aggregated data arriving from the node in cluster to a base station. In this paper, we propose the improved-LEACH that uses comparably simple and light-weighted policy to select cluster-head nodes, which results in reduction of the clustering overhead and overall power consumption of network. By using fine-grained power model, the simulation results show that i-LEACH can reduce clustering overhead compared with the well-known previous works such as LEACH. As result, i-LEACH algorithm and LEACH algorithm was compared, network power-consumption of i-LEACH algorithm was improved than LEACH algorithm with 25%, and network-traffic was improved 16%.

Implementation of the Classification using Neural Network in Diagnosis of Liver Cirrhosis (간 경변 진단시 신경망을 이용한 분류기 구현)

  • Park, Byung-Rae
    • Journal of Intelligence and Information Systems
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    • v.11 no.1
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    • pp.17-33
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    • 2005
  • This paper presents the proposed a classifier of liver cirrhotic step using MR(magnetic resonance) imaging and hierarchical neural network. The data sets for classification of each stage, which were normal, 1type, 2type and 3type, were analysis in the number of data was 231. We extracted liver region and nodule region from T1-weight MR liver image. Then objective interpretation classifier of liver cirrhotic steps. Liver cirrhosis classifier implemented using hierarchical neural network which gray-level analysis and texture feature descriptors to distinguish normal liver and 3 types of liver cirrhosis. Then proposed Neural network classifier learned through error back-propagation algorithm. A classifying result shows that recognition rate of normal is $100\%$, 1type is $82.8\%$, 2type is $87.1\%$, 3type is $84.2\%$. The recognition ratio very high, when compared between the result of obtained quantified data to that of doctors decision data and neural network classifier value. If enough data is offered and other parameter is considered this paper according to we expected that neural network as well as human experts and could be useful as clinical decision support tool for liver cirrhosis patients.

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Clustering Scheme using Memory Restriction for Wireless Sensor Network (무선센서네트워크에서 메모리 속성을 이용한 클러스터링 기법)

  • Choi, Hae-Won;Yoo, Kee-Young
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.1B
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    • pp.10-15
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    • 2009
  • Recently, there are tendency that wireless sensor network is one of the important techniques for the future IT industry and thereby application areas in it are getting growing. Researches based on the hierarchical network topology are evaluated in good at energy efficiency in related protocols for wireless sensor network. LEACH is the best well known routing protocol for the hierarchical topology. However, there are problems in the range of message broadcasting, which should be expand into the overall network coverage, in LEACH related protocols. Thereby, this paper proposes a new clustering scheme to solve the co-shared problems in them. The basic idea of our scheme is using the inherent memory restrictions in sensor nodes. The results show that the proposed scheme could support the load balancing by distributing the clusters with a reasonable number of member nodes and thereby the network life time would be extended in about 1.8 times longer than LEACH.

ZigBee Network Formation based on Trust Model and Trustworthiness Measurement (신뢰모델기반의 ZigBee 네트워크 구성 및 신뢰성 측정)

  • Hwang, Jae-Woo;Park, Ho-Hyun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.5
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    • pp.1284-1294
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    • 2010
  • The ZigBee is one of the most important technologies for composing USN. It is one of the IEEE 802.15.4 standards to support personal area networks. It uses a hierarchical routing or an on-demand route discovery strategy as an address allocation method. A hierarchical routing doesn't use a routing table but only uses a child node or a parent node as an intermediate node for data delivery. Therefore, the ZigBee network's topology greatly affects the overall network performance. In this paper, we propose a more trustworthy algorithm than only using the depth and widely variable LQI during network formation, and moreover we propose an algorithm to measure network's trustworthiness. We simulate our algorithm using the NS-2 and implement our network using the MG2400 ZigBee module for verifying performance.

A Design of Hierarchical Gaussian ARTMAP using Different Metric Generation for Each Level (계층별 메트릭 생성을 이용한 계층적 Gaussian ARTMAP의 설계)

  • Choi, Tea-Hun;Lim, Sung-Kil;Lee, Hyon-Soo
    • Journal of KIISE:Software and Applications
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    • v.36 no.8
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    • pp.633-641
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    • 2009
  • In this paper, we proposed a new pattern classifier which can be incrementally learned, be added new class in learning time, and handle with analog data. Proposed pattern classifier has hierarchical structure and the classification rate is improved by using different metric for each levels. Proposed model is based on the Gaussian ARTMAP which is an artificial neural network model for the pattern classification. We hierarchically constructed the Gaussian ARTMAP and proposed the Principal Component Emphasis(P.C.E) method to be learned different features in each levels. And we defined new metric based on the P.C.E. P.C.E is a method that discards dimensions whose variation are small, that represents common attributes in the class. And remains dimensions whose variation are large. In the learning process, if input pattern is misclassified, P.C.E are performed and the modified pattern is learned in sub network. Experimental results indicate that Hierarchical Gaussian ARTMAP yield better classification result than the other pattern recognition algorithms on variable data set including real applicable problem.

An Energy Consumption Model using Hierarchical Unequal Clustering Method (계층적 불균형 클러스터링 기법을 이용한 에너지 소비 모델)

  • Kim, Jin-Su;Shin, Seung-Soo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.12 no.6
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    • pp.2815-2822
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    • 2011
  • Clustering method in wireless sensor networks is the technique that forms the cluster to aggregate the data and transmit them at the same time that they can use the energy efficiently. In this paper, I propose the hierarchical unequal clustering method using cluster group model. This divides the entire network into two layers. The data aggregated from layer 2 consisted of cluster group is sent to layer 1, after re-aggregation the total data is sent to base station. This method decreases whole energy consumption by using cluster group model with multi-hop communication architecture. Hot spot problem can be solved by establishing unequal cluster. I also show that proposed hierarchical unequal clustering method is better than previous clustering method at the point of network energy efficiency.

HFIFO(Hierarchical First-In First-Out) : A Delay Reduction Method for Frame-based Packet Transmit Scheduling Algorithm (계층적 FIFO : 프레임 기반 패킷 전송 스케쥴링 기법을 위한 지연 감축 방안)

  • 김휘용;유상조;김성대
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.27 no.5C
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    • pp.486-495
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    • 2002
  • In this paper, we propose a delay reduction method for frame-based packet transmit scheduling algorithm. A high-speed network such as ATM network has to provide some performance guarantees such as bandwidth and delay bound. Framing strategy naturally guarantees bandwidth and enables simple rate-control while having the inherently bad delay characteristics. The proposed delay reduction method uses the same hierarchical frame structure as HRR (Hierarchical Round-Robin) but does not use the static priority scheme such as round-robin. Instead, we use a dynamic priority change scheme so that the delay unfairness between wide bandwidth connection and narrow bandwidth connection can be eliminated. That is, we use FIFO (First-In First-Out) concept to effectively reduce the occurrence of worst-case delay and to enhance delay distribution. We compare the performance for the proposed algorithm with that of HRR. The analytic and simulation results show that HFIFO inherits almost all merits of HRR with fairly better delay characteristics.

A Hierarchical Cluster Tree Based Address Assignment Method for Large and Scalable Wireless Sensor Networks (대규모 무선 센서 네트워크를 위한 계층적 클러스터 트리 기반 분산 주소 할당 기법)

  • Park, Jong-Jun;Jeong, Hoon;Hwang, So-Young;Joo, Seong-Soon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.12B
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    • pp.1514-1523
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    • 2009
  • It is well known that the current wireless sensor networks addressing methods do not work efficiently in networks more than a few hundred nodes. A standard protocol in ZigBee-Standard feature in ZigBee 2007 gives balanced tree based address assignment method with distributed manner. However, it was limited to cover less than hundreds of sensor nodes due to the wasteful use of available address space, because composed sensor networks usually make an unbalanced tree topology in the real deployment. In this paper, we proposed the hierarchical cluster tree based address assignment method to support large and scalable networks. This method provides unique address for each node with distributed manner and supports hierarchical cluster tree on-demand. Simulation results show that the proposed method reduces orphan nodes due to the address exhaustion and supports larger network with limited address space compared with the ZigBee distributed address assignment method defined in ZigBee-Standard feature in ZigBee 2007.