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clustering scheme for cooperative spectrum sensing in cognitive radio networks

IET COMMUNICATIONS 2016年第13期10卷 1590-1595页

作者： Jiao, Yan Yin, Peitong Joe, Inwhee Coll Engn Dept Elect & Comp Engn 17 Haengdang Dong Seoul 133791 South Korea Hanyang Univ 17 Haengdang Dong Seoul 133791 South Korea

For cognitive radio (CR), cooperation in spectrum sensing (SS) using energy detection can increase the detection of primary user signal. However, it also brings extra cooperative sensing overhead due to mutual exchange of large information among CR users. To reduce cooperative sensing overhead and improve sensing performance, the authors propose a novel clustering scheme consists of three stages: pruning, selecting, and clustering. In pruning stage, the CR users without sensing results will not join the following two stages;in the subsequent selecting stage, the CR user who has the most reliable sensing data is selected as the cluster header. For CR network, channel availability is an essence cause of cluster change. Hence, the authors proposed cluster constructing based on SS results correlation in the clustering stage. The simulation results show that the proposed clustering scheme not only has low overhead but also suit to perform in the low signal noise ratio environment.

关键词： cognitive radio cooperative communication signal detection radio spectrum management telecommunication network reliability clustering scheme cooperative spectrum sensing cognitive radio networks energy detection primary user signal detection cooperative sensing overhead CR users pruning stage selecting stage clustering stage sensing data reliability cluster header CR network channel availability signal noise ratio environment

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An Energy Efficient clustering scheme for Data Aggregation in Wireless Sensor Networks

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Journal of Computer Science & Technology 2013年第3期28卷 564-573页

作者：孟金涛苑建蕊冯圣中魏彦杰 Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Institute of Computing Technology Chinese Academy of Sciences Graduate University of Chinese Academy of Sciences CYG SUNRI CO. LTD

In wireless sensor networks, a clustering scheme is helpful in reducing the energy consumption by aggregating data at intermediate sensors. This paper discusses the important issue of energy optimization in hierarchically-clustered wireless sensor networks to minimize the total energy consumption required to collect data. We propose a comprehensive energy consumption model for multi-tier clustered sensor networks, in which all the energy consumptions not only in the phase of data transmissions but also in the phase of cluster head rotations are taken into account. By using this new model, we are able to obtain the solutions of optimal tier number and the resulted optimal clustering scheme on how to group all the sensors into tiers by the suggested numerical method. This then enables us to propose an energy-efficiency optimized distributed multi-tier clustering algorithm for wireless sensor networks. This algorithm is theoretically analyzed in terms of time complexity. Simulation results are provided to show that, the theoretically calculated energy consumption by the new model matches very well with the simulation results, and the energy consumption is indeed minimized at the optimal number of tiers in the multi-tier clustered wireless sensor networks.

关键词： wireless sensor network clustering scheme data aggregating energy efficiency

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CS-CGMP: clustering scheme Using Canada Geese Migration Principle for Routing in Wireless Sensor Networks

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WIRELESS PERSONAL COMMUNICATIONS 2020年第2期115卷 1363-1384页

作者： Kavitha, A. Guravaiah, Koppala Velusamy, R. Leela Natl Inst Technol Dept Comp Sci & Engn Tiruchirapalli 620015 Tamil Nadu India Indian Inst Informat Technol Kottayam Dept Comp Sci & Engn Kottayam 686635 Kerala India

Recently, researchers focus on wireless sensor networks (WSNs) as it plays a vital role in numerous applications. Node energy is one of the resource constraints of WSN. Hence, it is significantly important to design an energy efficient routing. In this paper, a clustering scheme using Canada Geese Migration Principle (CS-CGMP) has been proposed for routing in WSNs. In this approach, the network field is partitioned into zones and number of Cluster Heads (CHs) are selected based on the density of each zone. CGMP is applied for CH rotation. If residual energy of a CH is below threshold value, it has to be rotated to a member node which has high energy. Further, the optimal number of CHs required is assured in every round. CS-CGMP based approach was simulated and the performance parameters with respect to network lifetime, number of alive nodes, number of packets transferred to the BS and CH were analysed by comparing with LEACH-C, (ACH)(2), and DEEC.

关键词： Wireless sensor networks Canada Geese Clustered routing Energy aware routing Energy efficient routing clustering scheme

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Flag-Based Vehicular clustering scheme for Vehicular Ad-Hoc Networks

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Computers, Materials & Continua 2023年第12期77卷 2715-2734页

作者： Fady Samann Shavan Askar Department of Energy Engineering Technical College of EngineeringDuhok Polytechnic UniversityDuhok42001Iraq Department of Information System Engineering Technical College of EngineeringErbil Polytechnic UniversityErbil44001Iraq

clustering schemes in vehicular networks organize vehicles into logical *** are vital for improving network performance,accessing the medium,and enabling efficient data *** schemes rely on periodically broadcast hello messages to provide up-to-date information about the ***,the periodic exchange of messages overwhelms the system and reduces *** paper proposes the Flag-based Vehicular clustering(FVC)*** scheme leverages a combination of Fitness Score(FS),Link Expiration Time(LET),and clustering status flags to enable efficient cluster formation in a hybrid *** FVC relies on the periodic broadcast of the basic safety message in the Dedicated Short-Range Communications(DSRC)standard for exchanging the vehicle’s status,FS,and joining *** extra information onto the existing periodic beacon reduces the overhead of exchanging additional control messages,which is the main contribution of this *** scheme is implemented in a hybrid manner by utilizing a Road Side Unit(RSU)to implement a clustering *** work considered the FastPAM algorithm,a fast version of the Partitioning Around Medoids(PAM)clustering algorithm,to generate a list of potential cluster *** FVC scheme uses the LET as the clustering metric with the FastPAM ***,the Lightweight FastPAM Vehicular clustering(LFPVC)algorithm is considered by selecting the initial cluster heads based on the FS instead of the greedy FastPAM’s build *** the absence of the RSU,the vehicles utilize the FS with proper back-off time to self-elect the cluster *** hybrid FVC scheme increased the cluster lifetime by 32%and reduced the control-message overhead by 63%compared to the related ***,the LFPVC algorithm achieved similar results to the FastPAM algorithm.

关键词： clustering scheme VANET FastPAM

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A Performance Evaluation of a Novel clustering scheme Considering Local Node Density over WSN

A Performance Evaluation of a Novel Clustering Scheme Consid...

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International Conference on Future Generation Communication and Networking (FGCN 2011)

作者： Kim, Jeong-Sam Byun, Tae-Young Catholic Univ Daegu Sch Comp & Informat Commun Engn Gyongsan Gyeongbuk South Korea Yeungnam Coll Sci & Technol Div Comp Technol Deagu South Korea

ISBN: (纸本)9783642272004

This paper is an extension of previously proposed a novel clustering scheme. called D-LEACH, that is based on the calculation of local node density to increase the WSN lifetime by efficiently reducing enemy consumption at the sensor node. In this paper. we present both mathematical analysis and performance evaluations of our proposed D-LEACH in view of energy consumption of network. By computer simulation, we showed the ratio of pre-clustering executions, which is an additional stage to existing LEACH, to total rounds over whole network lifetime. Also, we investigate the progress of live nodes according to changes in local node density. and the progress of active nodes considering local node density in D-LEACH.

关键词： clustering scheme D-LEACH WSN Local Node Density

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New Framework of Back Diffusion-based Autonomous Decentralized Control and Its Application to clustering scheme

New Framework of Back Diffusion-based Autonomous Decentraliz...

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Globecom Workshops

作者： Takano, Chisa Aida, Masaki Murata, Masayuki Imase, Makoto Hiroshima City Univ Grad Sch Informat Sci Hiroshima 7313194 Japan Tokyo Metropolitan Univ Grad Sch Syst Design Hino Tokyo 1910065 Japan Osaka Univ Grad Sch Informat Sci & Technol Suita Osaka 5650871 Japan

ISBN: (纸本)9781424488650

We previously proposed a framework for autonomous decentralized control by introducing a partial differential equation based on local-action theory. Although each node in the network acts autonomously on the basis of only the local information directly available to it, our control proposal leads to optimal performance for the whole network. In addition, we have proposed flow control based on a diffusion equation to achieve autonomous load-balancing in the network and have confirmed that realizes congestion avoidance. This paper introduces a new autonomous decentralized control scheme that creates the spatial structures of finite size by using renormalization transformation and back diffusion drift. Moreover, we use the proposed control scheme to realize autonomous decentralized clustering in ad hoc networks.

关键词： autonomous decentralized control autonomous load-balancing back diffusion drift clustering scheme congestion avoidance decentralised control diffusion equation flow control local-action theory mobile ad hoc networks mobile ad hoc networks partial differen

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Neighbor Mobility-based clustering scheme for Vehicular Ad Hoc Networks 2

Neighbor Mobility-based Clustering Scheme for Vehicular Ad H...

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2015 International Conference on Platform Technology and Service (PlatCon)

作者： Kwon, Jung-Hyok Kwon, Cheolhee Kim, Eui-Jik LIG Nex1 Co Ltd Software R&D Lab Songnam South Korea Hallym Univ Dept Convergence Software Chunchon South Korea

ISBN: (纸本)9781479918881

This paper focuses on a stable clustering scheme for vehicular ad-hoc network. In the vehicular environment, vehicles self-configure the cluster based network for communication between vehicles. Because of the unique characteristics of the vehicle environment such as high mobility and changeable topology, applying the appropriate clustering scheme is very important for maintaining consistent network topology. Therefore, in this paper, we propose a novel clustering scheme considering neighbor vehicles' mobility. The proposed scheme elects a cluster head which has the lowest "neighbor vehicles mobility" value to provide reliable network topology. In the future work, we evaluate the performance of the proposed scheme in terms of rate of topology change, the number of cluster head change and overall network throughput, comparing to existing clustering scheme.

关键词： clustering scheme Topology formation Mobility Vehicular ad hoc network VANET

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Matrix Factorization and Deep Autoencoder based clustering scheme for Large-scale UAV Networks 97

Matrix Factorization and Deep Autoencoder based Clustering S...

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97th IEEE Vehicular Technology Conference (VTC-Spring)

作者： Fang, Jiaolan Wang, Chan Li, Rongpeng Wei, Hanyu Zhao, Minjian Zhejiang Univ Coll Informat Sci & Elect Engn Hangzhou 310027 Peoples R China

ISBN: (纸本)9798350311143

In recent years, unmanned aerial vehicle (UAV) ad-hoc networks have achieved rapid development due to their autonomy and high reliability. Typically, clustering is widely adopted to reduce the degradation of network performance in large-scale UAV networks. However, due to the limited channel resources and complex communication environment, it becomes challenging to obtain complete information needed for clustering from remote nodes. In addition, the high dimension and nonlinear relationships of data also make large-scale clustering diffcult. Therefore, in this paper, we propose a noval distributed clustering scheme. First, a matrix factorization (MF) based time series algorithm is proposed to predict and complement the incomplete information. Second, we adopt deep autoencoder to wisely incorporate the non-linear relationship of information needed for clustering. Finally we extract features as input to k-means to obtain clustering results. Simulation results demonstrate the effectiveness of the proposed clustering scheme.

关键词： UAV ad-hoc networks clustering scheme matrix factorization deep autoencoder

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An Efficient clustering scheme in Vehicular Ad-Hoc Networks 8

An Efficient Clustering Scheme in Vehicular Ad-Hoc Networks

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8th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON)

作者： Kannekanti, Sudev Yaswanth Nunna, Gowri S. P. Bobba, Viswanath Koranjan Reddy Yadama, Anirudh Kumar Elleithy, Abdelrahman Texas A&M Univ Kingsville Dept Elect Engn & Comp Sci Kingsville TX 78363 USA William Paterson Univ Dept Comp Sci Wayne NJ 07470 USA

ISBN: (纸本)9781538611043

Vehicular Ad-hoc network (VANET) is comprised of a group of vehicles which forms a network and can interact between themselves even moving with high velocity. We are creating the VANET by using the methods of MANET (Mobile Ad-Hoc Network) and applying them onto the vehicular domain. The sensors which are attached to the vehicles help in sharing the information among the vehicles or with the roadside infrastructure. As the topology in vehicular network is more dynamic, creation of a stable cluster is a major issue. In this paper we are selecting the best clustering technique and solving the major issues in forming the cluster from the available clustering methods like velocity-based, Connectivity-based and the Neighbor-Vehicles mobility based clustering.

关键词： clustering scheme VANET Topology Cluster Head

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Multi-objective topology optimization incorporating an adaptive weighed-sum method and a configuration-based clustering scheme

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COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING 2021年 385卷 114015-114015页

作者： Ryu, Namhee Seo, Minsik Min, Seungjae Hanyang Univ Dept Automot Engn Seoul 04763 South Korea

A novel multi-objective topology optimization method is developed by simultaneously considering the diversity and uniformity of the optimum solutions in the objective and design variable spaces. To guarantee the diversity of the solutions, a configuration-based clustering scheme is developed and applied to avoid similar designs. By clustering Pareto optimal designs during the optimization process, the searching region in the objective space is gradually reduced, and the time cost required for optimization can be decreased. Additionally, the uniformity of the solutions in the objective space is considered using an adaptive weight determination scheme. The results of the benchmark problems confirm that using the proposed method could reduce the time cost. Furthermore, the overall Pareto front and configuration of different designs are also explored. (C) 2021 Elsevier B.V. All rights reserved.

关键词： Adaptive weight clustering scheme Compromise programming method Multi-objective optimization Pareto front Topology optimization

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