• Title/Summary/Keyword: Nodes Clustering

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CLUSTERING DNA MICROARRAY DATA BY STOCHASTIC ALGORITHM

  • Shon, Ho-Sun;Kim, Sun-Shin;Wang, Ling;Ryu, Keun-Ho
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.438-441
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    • 2007
  • Recently, due to molecular biology and engineering technology, DNA microarray makes people watch thousands of genes and the state of variation from the tissue samples of living body. With DNA Microarray, it is possible to construct a genetic group that has similar expression patterns and grasp the progress and variation of gene. This paper practices Cluster Analysis which purposes the discovery of biological subgroup or class by using gene expression information. Hence, the purpose of this paper is to predict a new class which is unknown, open leukaemia data are used for the experiment, and MCL (Markov CLustering) algorithm is applied as an analysis method. The MCL algorithm is based on probability and graph flow theory. MCL simulates random walks on a graph using Markov matrices to determine the transition probabilities among nodes of the graph. If you look at closely to the method, first, MCL algorithm should be applied after getting the distance by using Euclidean distance, then inflation and diagonal factors which are tuning modulus should be tuned, and finally the threshold using the average of each column should be gotten to distinguish one class from another class. Our method has improved the accuracy through using the threshold, namely the average of each column. Our experimental result shows about 70% of accuracy in average compared to the class that is known before. Also, for the comparison evaluation to other algorithm, the proposed method compared to and analyzed SOM (Self-Organizing Map) clustering algorithm which is divided into neural network and hierarchical clustering. The method shows the better result when compared to hierarchical clustering. In further study, it should be studied whether there will be a similar result when the parameter of inflation gotten from our experiment is applied to other gene expression data. We are also trying to make a systematic method to improve the accuracy by regulating the factors mentioned above.

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A Study on the Efficient TICC(Time Interval Clustering Control) Algorithm using Attribute of Node (노드의 속성을 고려한 효율적인 TICC(Time Interval Clustering Control) 알고리즘에 관한 연구)

  • Kim, Young-Sam;Doo, Kyoung-Min;Lee, Kang-Whan
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.12 no.9
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    • pp.1696-1702
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    • 2008
  • A MANET(Mobile Ad-hoc Network) is a multi-hop routing protocol formed by a collection without the intervention of infrastructure. So the MANET also depended on the property as like variable energy, high degree of mobility, location environments of nodes etc. Generally the various clustering technique and routing algorithm would have proposed for improving the energy efficiency. One of the popular approach methods is a cluster-based routing algorithm using in MANET. In this paper, we propose an algorithm techniques which is TICC (Time Interval Clustering Control) based on energy value in property of each node for solving cluster problem. It provides improving cluster energy efficiency how can being node manage to order each node's energy level. TICC could be able to manage the clustering, re-configuration, maintenance and detection of Node in MANET. Furthermore, the results of modeling shown that Node's energy efficiency and lifetime are improved in MANET.

Lifetime Escalation and Clone Detection in Wireless Sensor Networks using Snowball Endurance Algorithm(SBEA)

  • Sathya, V.;Kannan, Dr. S.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.4
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    • pp.1224-1248
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    • 2022
  • In various sensor network applications, such as climate observation organizations, sensor nodes need to collect information from time to time and pass it on to the recipient of information through multiple bounces. According to field tests, this information corresponds to most of the energy use of the sensor hub. Decreasing the measurement of information transmission in sensor networks becomes an important issue.Compression sensing (CS) can reduce the amount of information delivered to the network and reduce traffic load. However, the total number of classification of information delivered using pure CS is still enormous. The hybrid technique for utilizing CS was proposed to diminish the quantity of transmissions in sensor networks.Further the energy productivity is a test task for the sensor nodes. However, in previous studies, a clustering approach using hybrid CS for a sensor network and an explanatory model was used to investigate the relationship between beam size and number of transmissions of hybrid CS technology. It uses efficient data integration techniques for large networks, but leads to clone attacks or attacks. Here, a new algorithm called SBEA (Snowball Endurance Algorithm) was proposed and tested with a bow. Thus, you can extend the battery life of your WSN by running effective copy detection. Often, multiple nodes, called observers, are selected to verify the reliability of the nodes within the network. Personal data from the source centre (e.g. personality and geographical data) is provided to the observer at the optional witness stage. The trust and reputation system is used to find the reliability of data aggregation across the cluster head and cluster nodes. It is also possible to obtain a mechanism to perform sleep and standby procedures to improve the life of the sensor node. The sniffers have been implemented to monitor the energy of the sensor nodes periodically in the sink. The proposed algorithm SBEA (Snowball Endurance Algorithm) is a combination of ERCD protocol and a combined mobility and routing algorithm that can identify the cluster head and adjacent cluster head nodes.This algorithm is used to yield the network life time and the performance of the sensor nodes can be increased.

Energy-Aware Self-Stabilizing Distributed Clustering Protocol for Ad Hoc Networks: the case of WSNs

  • Ba, Mandicou;Flauzac, Olivier;Haggar, Bachar Salim;Makhloufi, Rafik;Nolot, Florent;Niang, Ibrahima
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.11
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    • pp.2577-2596
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    • 2013
  • In this paper, we present an Energy-Aware Self-Stabilizing Distributed Clustering protocol based on message-passing model for Ad Hoc networks. The latter does not require any initialization. Starting from an arbitrary configuration, the network converges to a stable state in a finite time. Our contribution is twofold. We firstly give the formal proof that the stabilization is reached after at most n+2 transitions and requires at most $n{\times}log(2n+{\kappa}+3)$ memory space, where n is the number of network nodes and ${\kappa}$ represents the maximum hops number in the clusters. Furthermore, using the OMNeT++ simulator, we perform an evaluation of our approach. Secondly, we propose an adaptation of our solution in the context of Wireless Sensor Networks (WSNs) with energy constraint. We notably show that our protocol can be easily used for constructing clusters according to multiple criteria in the election of cluster-heads, such as nodes' identity, residual energy or degree. We give a comparison under the different election metrics by evaluating their communication cost and energy consumption. Simulation results show that in terms of number of exchanged messages and energy consumption, it is better to use the Highest-ID metric for electing CHs.

An Efficient Load-Sharing Scheme for Internet-Based Clustering Systems (인터넷 기반 클러스터 시스템 환경에서 효율적인 부하공유 기법)

  • 최인복;이재동
    • Journal of Korea Multimedia Society
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    • v.7 no.2
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    • pp.264-271
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    • 2004
  • A load-sharing algorithm must deal with load imbalance caused by characteristics of a network and heterogeneity of nodes in Internet-based clustering systems. This paper has proposed the Efficient Load-Sharing algorithm. Efficient-Load-Sharing algorithm creates a scheduler based on the WF(Weighted Factoring) algorithm and then allocates tasks by an adaptive granularity strategy and the refined fixed granularity algorithm for better performance. In this paper, adaptive granularity strategy is that master node allocates tasks of relatively slower node to faster node and refined fixed granularity algorithm is to overlap between the time spent by slave nodes on computation and the time spent for network communication. For the simulation, the matrix multiplication using PVM is performed on the heterogeneous clustering environment which consists of two different networks. Compared to other algorithms such as Send, GSS and Weighted Factoring, the proposed algorithm results in an improvement of performance by 75%, 79% and 17%, respectively.

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Energy/Distance Estimation-based and Distributed Selection/Migration of Cluster Heads in Wireless Sensor Networks (센서 네트워크의 에너지 및 거리 추정 기반 분산 클러스터 헤드 선정과 이주 방법)

  • Kim, Dong-Woo;Park, Jong-Ho;Lee, Tae-Jin
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.44 no.3 s.357
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    • pp.18-25
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    • 2007
  • In sensor networks, sensor nodes have limited computational capacity, power and memory. Thus energy efficiency is one of the most important requirements. How to extend the lifetime of wireless sensor networks has been widely discussed in recent years. However, one of the most effective approaches to cope with power conservation, network scalability, and load balancing is clustering technique. The function of a cluster head is to collect and route messages of all the nodes within its cluster. Cluster heads must be changed periodically for low energy consumption and load distribution. In this paper, we propose an energy-aware cluster head selection algorithm and Distance Estimation-based distributed Clustering Algorithm (DECA) in wireless sensor networks, which exchanges cluster heads for less energy consumption by distance estimation. Our simulation result shows that DECA can improve the system lifetime of sensor networks up to three times compared to the conventional scheme.

A Sequential Indexing Method for Multidimensional Range Queries (다차원 범위 질의를 위한 순차 색인 기법)

  • Cha Guang-Ho
    • Journal of KIISE:Databases
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    • v.32 no.3
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    • pp.254-262
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    • 2005
  • This paper presents a new sequential indexing method called segment-page indexing (SP-indexing) for multidimensional range queries. The design objectives of SP-indexing are twofold:(1) improving the range query performance of multidimensional indexing methods (MIMs) and (2) providing a compromise between optimal index clustering and the full index reorganization overhead. Although more than ten years of database research has resulted in a great variety of MIMs, most efforts have focused on data-level clustering and there has been less attempt to cluster indexes. As a result, most relevant index nodes are widely scattered on a disk and many random disk accesses are required during the search. SP-indexing avoids such scattering by storing the relevant nodes contiguously in a segment that contains a sequence of contiguous disk pages and improves performance by offering sequential access within a segment. Experimental results demonstrate that SP-indexing improves query performance up to several times compared with traditional MIMs using small disk pages with respect to total elapsed time and it reduces waste of disk bandwidth due to the use of simple large pages.

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.

Role-based Self-Organization Protocol of Clustering Hierarchy for Wireless Sensor Networks (무선 센서 네트워크를 위한 계층형 클러스터링의 역할 기반 자가 구성 프로토콜)

  • Go, Sung-Hyun;Kim, Hyoung-Jin
    • Journal of the Korea Society of Computer and Information
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    • v.13 no.6
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    • pp.137-145
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    • 2008
  • In general, a large-scale wireless sensor network(WSNs) is composed of hundreds of or thousands of sensor nodes. In this large-scale wireless sensor networks, it is required to maintain and manage the networks to lower management cost and obtain high energy efficiency. Users should be provided with sensing service at the level of quality for users through an efficient system. In evaluating the result data quality provided from this network to users, the number of sensors related to event detection has an important role. Accordingly, the network protocol which can provide proper QoS at the level of users demanding quality should be designed in a way such that the overall system function has not to be influenced even if some sensor nodes are in error. The energy consumption is minimized at the same time. The protocol suggested in this article is based on the LEACH protocol and is a role-based self-Organization one that is appropriate for large-scale networks which need constant monitoring.

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A Stable Clustering Scheme Based on Node Mobility for Mobile Ad Hoc Networks (모바일 애드 혹 네트워크에서 이동성을 고려한 안정적인 클러스터링 기법)

  • Kim, Hyek-Su;Hwang, Jun-Ho;Yoo, Myung-Sik
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.5B
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    • pp.480-488
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    • 2009
  • A mobile ad-hoc network is an autonomous collection of wireless mobile nodes that organizes a temporary network without any network infrastructure. Due to node mobility, it is a challenging task to maintain the network topology. In this paper, we propose a stable clustering algorithm that uses node mobility for cluster formation. In the proposed algorithm, the node mobility is measured by counting the number of nodes entering into/leaving from its transmission range. The node having the lowest mobility is selected as a cluster head. For topology maintenance with reduced control overhead, the cluster head adaptively controls the broadcasting period of hello message to the measured node mobility. Through computer simulations, it is verified that the proposed algorithm outperforms previous clustering algorithms in terms of control overhead, the rate of node mobility changes and the number of cluster head changes.