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A New Energy Efficient clustering algorithm Based on Routing Spanning Tree for Wireless Sensor Network

IEICE TRANSACTIONS ON COMMUNICATIONS 2017年第12期E100B卷 2110-2120页

作者： Gao, Yating Kang, Guixia Cheng, Jianming Zhang, Ningbo Beijing Univ Posts & Telecommun Minist Educ Key Lab Universal Wireless Commun Beijing 100876 Peoples R China

Wireless sensor networks usually deploy sensor nodes with limited energy resources in unattended environments so that people have difficulty in replacing or recharging the depleted devices. In order to balance the energy dissipation and prolong the network lifetime, this paper proposes a routing spanning tree-based clustering algorithm (RSTCA) which uses routing spanning tree to analyze clustering. In this study, the proposed scheme consists of three phases: setup phase, cluster head (CH) selection phase and steady phase. In the setup phase, several clusters are formed by adopting the K-means algorithm to balance network load on the basis of geographic location, which solves the randomness problem in traditional distributed clustering algorithm. Meanwhile, a conditional inter-cluster data traffic routing strategy is created to simplify the networks into subsystems. For the CH selection phase, a novel CH selection method, where CH is selected by a probability based on the residual energy of each node and its estimated next-time energy consumption as a function of distance, is formulated for optimizing the energy dissipation among the nodes in the same cluster. In the steady phase, an effective modification that counters the boundary node problem by adjusting the data traffic routing is designed. Additionally, by the simulation, the construction procedure of routing spanning tree (RST) and the effect of the three phases are presented. Finally, a comparison is made between the RSTCA and the current distributed clustering protocols such as LEACH and LEACH-DT. The results show that RSTCA outperforms other protocols in terms of network lifetime, energy dissipation and coverage ratio.

关键词： wireless sensor network clustering algorithm routing spanning tree network lifetime energy balance

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Design of a distributed energy-efficient clustering algorithm for heterogeneous wireless sensor networks

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COMPUTER COMMUNICATIONS 2006年第12期29卷 2230-2237页

作者： Qing, Li Zhu, Qingxin Wang, Mingwen Univ Elect Sci & Technol China Sch Comp Sci & Engn Chengdu 610054 Peoples R China

The clustering algorithm is a kind of key technique used to reduce energy consumption. It can increase the scalability and lifetime of the network. Energy-efficient clustering protocols should be designed for the characteristic of heterogeneous wireless sensor networks. We propose and evaluate a new distributed energy-efficient clustering scheme for heterogeneous wireless sensor networks, which is called DEEC. In DEEC, the cluster-heads are elected by a probability based on the ratio between residual energy of each node and the average energy of the network. The epochs of being cluster-heads for nodes are different according to their initial and residual energy. The nodes with high initial and residual energy will have more chances to be the cluster-heads than the nodes with low energy. Finally, the simulation results show that DEEC achieves longer lifetime and more effective messages than current important clustering protocols in heterogeneous environments. (c) 2006 Elsevier B.V. All rights reserved.

关键词： wireless sensor networks clustering algorithm heterogeneous environment energy-efficient

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A linear assignment clustering algorithm based on the least similar cluster representatives

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IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS 1999年第1期29卷 100-104页

作者： Wang, J Chinese Univ Hong Kong Dept Mech & Automat Engn Shatin New Territories Peoples R China

This correspondence presents a linear assignment algorithm for solving the clustering problem. By use of the most dissimilar data as cluster representatives, a linear assignment algorithm is developed based on a linear assignment model for clustering multivariate data. The computational results evaluated using multiple performance criteria show that the clustering algorithm is very effective and efficient, especially for clustering a large number of data with many attributes.

关键词： assignment problem clustering algorithm group technology

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A sequential clustering algorithm with applications to gene expression data

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JOURNAL OF THE KOREAN STATISTICAL SOCIETY 2009年第2期38卷 175-184页

作者： Song, Jongwoo Nicolae, Dan L. Ewha Womans Univ Dept Stat Seoul 120750 South Korea Univ Chicago Dept Stat Chicago IL 60637 USA

clustering algorithms are used in the analysis of gene expression data to identify groups of genes with similar expression patterns. These algorithms group genes with respect to a predefined dissimilarity measure without using any prior classification of the data. Most of the clustering algorithms require the number of clusters as input. and all the objects in the dataset are usually assigned to one of the clusters. We propose a clustering algorithm that finds clusters sequentially, and allows for sporadic objects, so there are objects that are not assigned to any cluster. The proposed sequential clustering algorithm has two steps. First it finds candidates for centers of clusters. Multiple candidates are used to make the search for clusters more efficient. Secondly, it conducts a local search around the candidate centers to find the set of objects that defines a cluster. The candidate clusters are compared using a predefined score, the best cluster is removed from data, and the procedure is repeated. We investigate the performance of this algorithm using simulated data and we apply this method to analyze gene expression profiles in a study on the plasticity of the dendritic cells. (c) 2008 The Korean Statistical Society. Published by Elsevier B.V. All rights reserved.

关键词： clustering algorithm Microarrays Sequential clustering clustering score

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Linguistic neutrosophic partitioned Maclaurin symmetric mean operators based on clustering algorithm and their application to multi-criteria group decision-making

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ARTIFICIAL INTELLIGENCE REVIEW 2020年第3期53卷 2131-2170页

作者： Liu, Peide You, Xinli Shandong Univ Finance & Econ Sch Management Sci & Engn Jinan 250014 Shandong Peoples R China

Linguistic neutrosophic number (LNN) can describe evaluation information by three linguistic variables indicating truth-membership, indeterminacy-membership and falsity-membership respectively, which is an effective tool to represent uncertainty, the partitioned Maclaurin symmetric mean (PMSM) operator can reflect the interrelationships among criteria where there are interrelationships among criteria in the same partition, but the criteria in different partitions are irrelevant, so, in this paper, we extend the PMSM operator to LNNs, define linguistic neutrosophic partitioned Maclaurin symmetric mean operator and linguistic neutrosophic weighted partitioned Maclaurin symmetric mean (LNWPMSM) operator, and discuss the properties and theorems of the proposed operators. Then we propose a clustering algorithm for linguistic neutrosophic sets based on the similarity measure to give some objective and reasonable partitions among criteria, and based on the LNWPMSM operator and the objective partition structure of the criteria, a novel multi-criteria group decision-making method is developed for linguistic neutrosophic environment. Finally, one practical example is presented to illustrate the applicability of the proposed method, and a comparison analysis is to show the advantages of the proposed method compared with the existing methods.

关键词： LNNs LNWPMSM operator Similarity measures clustering algorithm MCGDM

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Security clustering algorithm Based on Integrated Trust Value for Unmanned Aerial Vehicles Network

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KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS 2020年第4期14卷 1773-1795页

作者： Zhou, Jingxian Wang, Zengqi Civil Aviat Univ China Informat Secur Evaluat Ctr Tianjin 300300 Peoples R China Civil Aviat Univ China Sch Comp Sci & Technol Tianjin 300300 Peoples R China

Unmanned aerial vehicles (UAVs) network are a very vibrant research area nowadays. They have many military and civil applications. Limited bandwidth, the high mobility and secure communication of micro UAVs represent their three main problems. In this paper, we try to address these problems by means of secure clustering, and a security clustering algorithm based on integrated trust value for UAVs network is proposed. First, an improved the k-means++ algorithm is presented to determine the optimal number of clusters by the network bandwidth parameter, which ensures the optimal use of network bandwidth. Second, we considered variables representing the link expiration time to improve node clustering, and used the integrated trust value to rapidly detect malicious nodes and establish a head list. Node clustering reduce impact of high mobility and head list enhance the security of clustering algorithm. Finally, combined the remaining energy ratio, relative mobility, and the relative degrees of the nodes to select the best cluster head. The results of a simulation showed that the proposed clustering algorithm incurred a smaller computational load and higher network security.

关键词： UAVs network clustering algorithm cluster head selection Bayesian trust model network security

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A configuration-based clustering algorithm for family formation

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COMPUTERS & INDUSTRIAL ENGINEERING 1996年第1-2期31卷 147-150页

作者： Suer, GA Cedeno, AA POLYTECH UNIV DEPT IND ENGNSAN JUANPR 00919

In Cellular Manufacturing literature, early work focused on the use of routers as a way of forming product families and manufacturing cells. Later, several measures of similarity among machines and parts have been proposed by different authors. In this paper, a new clustering algorithm is proposed that considers the number of machines of each type and the most recent configuration of cells in revising the values of similarity coefficient. The potential benefits of the procedure is demonstrated with a simple example.

关键词： clustering algorithm cellular manufacturing cell configuration

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Digital signal processing based on a clustering algorithm for Ir/Au TES microcalorimeter

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IEEE TRANSACTIONS ON NUCLEAR SCIENCE 2006年第1期53卷 259-264页

作者： Zen, N Kunieda, Y Takahashi, H Hiramoto, K Nakazawa, M Fukuda, D Ukibe, M Ohkubo, M Univ Tokyo Dept Quantum Engn Tokyo 1138656 Japan Univ Tokyo Ctr Engn Tokyo 1538904 Japan Natl Inst Adv Ind Sci & Technol Tsukuba Ibaraki 3058561 Japan

In recent years, cryogenic microcalorimeters using their superconductirig transition edge have been under development for possible application to the research for astronomical X-ray observations. To improve the energy resolution of superconducting transition edge sensors (TES), several correction methods have been developed. Among them, a clustering method based on digital signal processing has recently been proposed. In this paper, we applied the clustering method to Ir/Au bilayer TES. This method resulted in almost a 10% improvement in the energy resolution. Conversely, from the point of view of imaging X-ray spectroscopy, we applied the clustering method to pixellated Ir/Au-TES devices. We will thus show how a clustering method which sorts signals by their shapes is also useful for position identification.

关键词： X-ray apparatus calorimeters particle calorimetry position sensitive particle detectors signal processing superconducting particle detectors Ir/Au bilayer TES microcalorimeter astronomical X-ray observations clustering algorithm correction methods cryoge X-RAY EQUIPMENT particle calorimetry Energy resolution signal processing superconducting particle detectors clustering algorithms TES gene Calorimeters clustering methods Microcalorimeters

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EMASS: A Novel Energy, Safety and Mobility Aware-Based clustering algorithm for FANETs

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IEEE ACCESS 2021年 9卷 105506-105520页

作者： Aissa, Mohamed Abdelhafidh, Maroua Ben Mnaouer, Adel Univ Nizwa Nizwa 616 Oman Univ Sfax Digital Res Ctr Sfax SM RTS Lab Signals SystMs Sfax 3029 Tunisia Canadian Univ Dubai Dept Comp Engn & Computat Sci Dubai U Arab Emirates

The Unmanned Aerial Vehicles (UAVs), organized as a Flying Ad-hoc NETwork (FANET), are used to make effective remote monitoring in diverse applications. Due to their high mobility, their energy consumption is increasingly affected leading to reduced network stability and communication efficiency. The design of node clustering of a FANET needs to consider the number of UAVs in the vicinity (transmission range) in order to ensure an adaptive reliable routing. Novel clustering schemes have been employed to deal with the highly dynamic flying behavior of UAVs and to maintain network stability. In this context, a new clustering algorithm is proposed to address the fast mobility of UAVs and provide safe inter-UAV distance, stable communication and extended network lifetime. The main contributions of this paper are first to extend and improve important metrics used in two well-known algorithms in the literature namely: The Bio-Inspired clustering Scheme for FANETs (BICSF) and the Energy Aware Link-based clustering (EALC). Then, exploiting the improved metrics, an Energy and Mobility-aware Stable and Safe clustering (EMASS) algorithm, built upon new schemes useful for ensuring stability and safety in FANETs, is proposed. The simulation results showed that the EMASS algorithm outperformed the BICSF and the EALC algorithms in terms of better cluster stability, guaranteed safety, higher packet deliverability, improved energy saving and lower delays.

关键词： clustering algorithms Ad hoc networks Routing Reliability Routing protocols Stability criteria Network topology Unmanned aerial vehicle (UAV) clustering algorithm energy consumption stability mobility safe-inter-UAV distance Flying Ad-hoc NETwork (FANET)

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A geographical division clustering algorithm for multiple flying base stations

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INTERNET TECHNOLOGY LETTERS 2021年第4期4卷

作者： Lee, Jongyul Lyu, Xiao Friderikos, Vasilis Kings Coll London Dept Engn Ctr Telecommun Res CTR London WC2R 2LS England

Unmanned Aerial Vehicles (UAVs) can play a significant role as flying base station (FBSs) in assisting terrestrial base stations (BSs) to increase overall network capacity by providing localized transmission to a set of users. In that respect, FBSs can be deployed from a terrestrial macro BS which can act as the depot. In this letter, we propose two flavors of a Geographical Division (GD) clustering algorithm to assign FBSs located at the same terrestrial BS to a set of end users. Numerical investigations demonstrate that the proposed algorithm outperforms the two most widely used and best known clustering algorithms for this specific problem, namelyK-means and Hierarchical clustering algorithms.

关键词： 5G clustering algorithm flying base stations UAV unmanned aerial vehicles wireless networks

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