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A Cluster-Based Broadcast Scheduling Scheme for mmWave Vehicular Communication

IEEE COMMUNICATIONS LETTERS 2019年第7期23卷 1202-1206页

作者： Zhang, Xinming Li, Yongzhen Miao, Qingliang Univ Sci & Technol China Sch Comp Sci & Technol Hefei 230027 Anhui Peoples R China Southeast Univ Natl Mobile Commun Res Lab Nanjing 210096 Jiangsu Peoples R China

The development of mmWave vehicular communication helps many use cases of interest requiring higher throughput. However, the high attenuation of mmWave makes it essential to avoid the block of other vehicles and weaken the interference on concurrent mmWave links. In this letter, we first propose a hierarchical multi-hop clustering algorithm considering velocity, relative position, and the proportion of line-of-sight (LOS) neighbors to maintain the stability of the cluster head. Then, we propose a link availability prediction strategy to ensure that the mmWave links among vehicles are LOS as far as possible. Finally, we propose a broadcast scheduling scheme based on the cluster utilizing exclusive region to improve concurrency of mmWave links. The simulation results reflect that our scheme achieves higher throughput and average packets' delivery ratio for a varying number of vehicles and bandwidths of sub-6 GHz.

关键词： Broadcast scheduling clustering algorithm link availability prediction mmWave vehicular communication

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A Survey on Cluster-Based Routing Protocols for Unmanned Aerial Vehicle Networks

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IEEE ACCESS 2019年 7卷 498-516页

作者： Arafat, Muhammad Yeasir Moh, Sangman Chosun Univ Dept Comp Engn Gwangju 61452 South Korea

In recent years, unmanned aerial vehicles (UAVs) have gained popularity for various applications and services in both the military and civilian domains. Multiple UAVs can carry out complex tasks efficiently when they are organized as an ad hoc network, where wireless communication is essential for cooperation and collaboration between UAVs and the ground station. Due to rapid mobility and highly dynamic topology, designing a routing protocol for UAV networks is a challenging task. As the number of UAVs increases, a hierarchical routing called clustering is necessarily required to provide scalability because clustering schemes ensure the basic level of system performance such as throughput, end-to-end delay, and energy efficiency. For approximately a half-decade, several survey articles have been reported on topology-based routing and position-based routing for UAV networks. To the best of the authors' knowledge, however, there is no survey on cluster-based routing in the literature. In this paper, cluster-based routing protocols for UAV networks are extensively surveyed and qualitatively compared in terms of outstanding features, characteristics, competitive advantages, and limitations. Furthermore, open research issues and challenges on cluster-based routing are discussed.

关键词： Unmanned aerial vehicle drone unmanned aerial vehicle network flying ad hoc network routing protocol clustering algorithm scalability

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A clustering algorithm for Heterogeneous Sensor Networks with Multilevel Energies

A Clustering Algorithm for Heterogeneous Sensor Networks wit...

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32nd Chinese Control Conference (CCC)

作者： Zhang Ying Ji Chang-gang Li Jun-fu Shanghai Maritime Univ Coll Informat Engn Shanghai 201306 Peoples R China

ISBN: (纸本)9781479900305

Currently, most clustering algorithms are proposed for homogeneous network, which do not adapt to the heterogeneous network. Energy heterogeneity is ubiquitous in wireless sensor networks, because node initial energy of multi-level energy-heterogeneous wireless sensor network distributes within the scope of certain and randomly, in order to economize heterogeneous nodes energy and extend network stability period, this paper proposed an routing algorithm for multi-level energy-heterogeneous sensor networks which take into account the residual energy of nodes and node-to-base distance multi-stage energy. Resident energy of cluster head and the energy consumption of its base station are considered synthetically between clusters to select the appropriate next-hop route node. Simulation results show that this algorithm can balance network energy consumption efficiently and extend network stability period.

关键词： Heterogeneous Wireless Sensor Network Multi-level Energy clustering algorithm Energy-efficient

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A Bio-Inspired Solution to Cluster-Based Distributed Spectrum Allocation in High-Density Cognitive Internet of Things

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IEEE INTERNET OF THINGS JOURNAL 2019年第6期6卷 9294-9307页

作者： Li, Jiaxun Zhao, Haitao Hafid, Abdelhakim Senhaji Wei, Jibo Yin, Hao Ren, Baoquan Natl Univ Def Technol Coll Elect Sci & Engn Changsha 410073 Hunan Peoples R China Univ Montreal Dept Comp Sci & Operat Res Montreal PQ H3C 3J7 Canada Acad Mil Med Sci Inst Syst Engn Beijing 100091 Peoples R China

With the emergence of Internet of Things (IoT), where any device is able to connect to the Internet and monitor/control physical elements, several applications were made possible, such as smart cities, smart health care, and smart transportation. The wide range of the requirements of these applications drives traditional IoT to cognitive IoT (CIoT) that supports smart resource allocation, automatic network operation and intelligent service provisioning. To enable CIoT, there is a need for flexible and reliable wireless communication. In this paper, we propose to combine cognitive radio (CR) with a biological mechanism called reaction-diffusion to provide efficient spectrum allocation for CIoT. We first formulate the quantization of qualitative connectivity-flexibility tradeoff problem to determine the optimal cluster size (i.e., number of cluster members) that maximizes clustered throughput but minimizes communication delay. Then, we propose a bio-inspired algorithm which is used by CIoT devices to form cluster distributedly. We compute the optimal values of the algorithm's parameters (e.g., contention window) of the proposed algorithm to increase the network's adaption to different scenarios (e.g., spectrum homogeneity and heterogeneity) and to decrease convergence time, communication overhead, and computation complexity. We conduct a theoretical analysis to validate the correctness and effectiveness of proposed bio-inspired algorithm. Simulation results show that the proposed algorithm can achieve excellent clustering performance in different scenarios.

关键词： Bio-inspired solution clustering algorithm cognitive Internet of Things (CIoT) cognitive radio (CR) spectrum allocation

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A methodology to develop a geospatial transportation typology

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JOURNAL OF TRANSPORT GEOGRAPHY 2021年 93卷 103061-103061页

作者： Popovich, Natalie Spurlock, C. Anna Needell, Zachary Jin, Ling Wenzel, Tom Sheppard, Colin Asudegi, Mona Lawrence Berkeley Natl Lab 1 Cyclotron Rd Berkeley CA 94720 USA Fed Highway Adm 1200 New Jersey Ave SE Washington DC 20590 USA

We introduce a methodology to develop a geo-typology (geotype) that categorizes each location in the United States in terms of their main drivers of transportation demand and supply. We develop the first comprehensive set of geotypes for both urban and rural areas across the entire United States. This typology is designed to facilitate national level modeling of multi-modal transportation system's response to alternative investment strategies differentiated across different types of locations. We develop a two-stage clustering procedure to systematically and quantitatively characterize the ways in which locations across the nation are similar or different with respect to their potential response to investment strategies of interest. First, we cluster all 73,057 census tracts, using factor analysis and the CLARA clustering algorithm into "microtypes" based on their street network and economic characteristics. Then we cluster regions (core-basic statistical areas and counties) into "geotypes" using PAM clustering according to their commute configurations, polycentricity and density. The resulting set captures both local and regional variation. These microtypes and geotypes are comparable across all locations, enabling a national level perspective, while maintaining sufficient heterogeneity to support a variety of transportation analyses capturing critical geographic variation.

关键词： Geo-spatial Neighborhood Typology Geotype Transportation investment Machine learning clustering algorithm

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Multiplexing Gains Through clustering In Cloud Radio Access Network

Multiplexing Gains Through Clustering In Cloud Radio Access ...

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Mathematics, Computer Engineering and Computer Science (ICMCECS), International Conference in

作者： Umasabor Nelson Bala Salihu Nathaniel Salawu Suleiman Zubair Department Of Telecommunication Engineering Federal University Of Technology Minna Nigeria

ISBN: (数字)9781728131269

ISBN: (纸本)9781728131276

There is an increase in the energy consumption and cost of base station deployment due to increase in the number of devices which require a dense deployment of base stations to handle the resultant data traffic. C-RAN (Cloud Radio Access Network) was proposed to remedy the problem of increasing data traffic volume and reduce the capital expenditure and operating expenditure of Mobile Network operators. Cloud Radio Access Network (C-RAN) allows for network resources to be shared amongst several base stations thereby reducing cost. By using different clustering algorithms such as K-means, Hierarchical and Gaussian Mixture Models to cluster these base stations there is a reduction in the needed network resources and this reduces cost. Capacity Utility and cost of deployment are the metrics used in making a comparative analysis of the different clustering algorithms used in this work. From evaluation of the methodology, it showed that the Hierarchical clustering algorithm had a Capacity Utility of 0.0012, Gaussian Mixture Models had 0.0035 and K-means with 0.0044 and when you compare this with the Capacity Utility before clustering of 0.63 it can be seen that the Hierarchical clustering algorithm had reduced the needed network resources better than Gaussian Mixture Models and K-means. The 3 clustering algorithms were also able to reduce the number of needed base stations from 182 to 80, thereby reducing Cost of deployment.

关键词： clustering algorithm Statistical Multiplexing Gain Mobile Network. clustering algorithms BASE STATION mobile communication mobile networking Web resources Wireless networks energy consumption deployment Cluster Analysis Capital Expenditures Clouds Mixture models Evaluation Methodology

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Research on Application of Data Mining Technology in Risk Assessment Process of Audit

Research on Application of Data Mining Technology in Risk As...

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International Conference on Economic Management and Model Engineering (ICEMME)

作者： Yan, Jun Wang, Xiaoxin Wang, Binrong Zhang, Yuan Univ Sci & Technol Beijing Tianjin Coll Sch Management Tianjin Peoples R China Univ Sci & Technol Beijing Donlinks Sch Econ & Management Beijing Peoples R China

ISBN: (纸本)9781728155883

In the information age, great changes have taken place in the internal and external environment of enterprises. In the face of huge data from all sides, it has become a difficult point in the current audit work to find out the doubtful points in the audit. However, the development of information technology brings an opportunity to audit. The application of data mining technology and applicable data mining algorithm can help the smooth progress of risk assessment process in audit. This paper first expounds the advantages of data mining technology in risk assessment, then lists its implementation procedures in risk assessment, and finally gives an example to illustrate the application process of clustering algorithm in risk assessment.

关键词： risk assessment data mining clustering algorithm

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Exploring the development trend of internet finance in China: Perspective from club convergence

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NORTH AMERICAN JOURNAL OF ECONOMICS AND FINANCE 2021年 58卷 101505-101505页

作者： Bai, Caiquan Yan, Hong Yin, Shanggang Feng, Chen Wei, Qian Shandong Univ Ctr Econ Res Jinan 250100 Shandong Peoples R China Fudan Univ Sch Int Relat & Publ Affairs Shanghai 200433 Peoples R China Nanjing Normal Univ Sch Geog Nanjing 210023 Jiangsu Peoples R China Shanghai Univ Finance & Econ Sch Publ Econ & Adm Shanghai 200433 Peoples R China

We first employ beta-conditional convergence and log t regression tests based on nonlinear timevarying factor model and club clustering algorithm to analyze the convergence characteristics of the development level of Internet finance in 335 prefecture-level cities in China. The result of log t regression test illustrates that there is no convergence as a whole in the development level of China's Internet finance. However, seven convergence clubs and a divergent group have been formed, and the development level and growth rate of Internet finance among these convergence clubs have shown obvious differences. Moreover, we also employ the Ordered Probit to explore the formation mechanism of the convergence clubs. The results reveal that the regions with a higher level of economic development, traditional financial development, economic openness and Internet development are more inclined to converge in a club with a higher Internet finance development level. Alternatively, the regions that are interfered with more by the government or that have a lower degree of marketization, tend to converge in a club with a lower level. Finally, according to the conclusions, we propose corresponding policy recommendations for promoting the regional coordinated development of China's Internet finance.

关键词： Internet finance Club convergence clustering algorithm Log t test Ordered Probit Model

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A Distributed Energy-efficient clustering algorithm based on Weighted Probability for Wireless Sensor Networks

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INTERNATIONAL JOURNAL OF FUTURE GENERATION COMMUNICATION AND NETWORKING 2013年第4期6卷 83-97页

作者： Xie, Dongfeng Sun, Qi Zhou, Qianwei Qiu, Yunzhou Yuan, Xiaobing Shanghai Inst Microsyst & Informat Technol Wireless Sensor Network Lab 865 Chang Ning Rd Shanghai 200050 Peoples R China

clustering problem is one of the significant issues for wireless sensor networks concerned with energy consumption and large-scale deployment. Several energy-efficient clustering algorithms have been proposed to improve the energy utilization efficiency and prolong the network lifetime. In this paper, we propose a new clustering scheme after a comprehensive analysis on existing protocols. In our algorithm, named WPCA (Weighted Probabilistic clustering algorithm), every node independently decides whether to be a cluster head according to a weighted probability, which is related to the ratio between node's residual energy and average remaining energy. The nodes with more residual energy are assigned larger weight value to further increase the chances to be elected as cluster heads. In addition, the rotation procedure of cluster heads in previous algorithms is totally abandoned. Simulation results show that WPCA achieves longer lifetime than previous probabilisticbased clustering algorithms and gets a very close approximation compared with a deterministic clustering method.

关键词： EWireless sensor networks clustering algorithm Energy-efficient Probabilistic Distributed

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Stochastic Economic Dispatching Strategy of the Active Distribution Network Based on Comprehensive Typical Scenario Set

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IEEE ACCESS 2020年 8卷 201147-201157页

作者： Zhu, Huimin Yuan, Shun Li, Chunlai Shenyang Univ Technol Sch Elect Engn Shenyang 110870 Peoples R China

The increasing penetration of renewable energy resources in the distribution network has posed great uncertainties and challenges for the system security operation. To model various uncertain factors like the wholesale market price and renewable energy generation in the active distribution network (ADN), a similarity measurement method considering the amplitude, volatility and variation trend is proposed. The Latin hypercube sampling method and Graph Pyramid clustering algorithm are adopted to obtain the comprehensive typical scenario set. Furthermore, this study proposes a scenario-based stochastic day-ahead optimal economic dispatch approach based on typical scenario set. The energy trading between the distribution system and the wholesale energy market, various distributed generators, network topology and power flow model are jointly formulated in the proposed operation model. The effectiveness and scalability of the proposed approach are verified using the IEEE 33-bus system. Numerical simulation results under different implementation scenarios indicate that the proposed approach offers a high computational efficiency and promotes the security and economy of the distribution system operation, which has a promising industrial application value.

关键词： Active distribution network renewable energy resources stochastic optimization clustering algorithm typical scenario set

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