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Process and properties of electroless Ni-W-B amorphous electrical resistance film

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中国有色金属学会会刊：英文版 2004年第z1期14卷 144-146页

作者： ZHU Xiao-yun GUO zhong-cheng xu Rui-dong The Centre of New Materials and Surface Engineering Research and Development Kunming University of Science and Technology Kunming 650093 China The Centre of New Materials and Surface Engineering Research and DevelopmentKunming University of Science and Technology Kunming 650093 China The Centre of New Materials and Surface Engineering Research and DevelopmentKunming University of Science and Technology Kunming 650093 China

The process and properties of electroless plating Ni-W-B alloy have been studied. The results show that the deposits containing W and B are obtained, and the deposition rate of the bath is increased with increase of W content when a certain amount of sodium tungstate solution is added in the Ni-B bath. The Ni-W-B alloy is amorphous as deposition and its resistivity increases directly with the increase of W content in the coating, but decreases gradually with increasing the deposit thickness. XRD and SEM show that the distributions of W and B in the Ni-W-B alloy film are very uniform and dispersed without any segregation.

关键词： electroless Ni-W-B alloy electrical resistance film properties

State and parameter identification of linearized water wave equation via adjoint method

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Science China(Information Sciences) 2024年第10期67卷 283-297页

作者： Yang YU cheng-zhong xu Hai-Long PEI Jinpeng YU School of Automation Qingdao University LAGEP Batiment CPE University Claude Bernard-Lyon 1 School of Automation Science and Engineering Key Laboratory of Autonomous Systems and Networked ControlMinistry of Education Guangdong Engineering Technology Research Center of Unmanned Aerial Vehicle SystemSouth China University of Technology

In this paper, we focus on the state and parameter identification problem of a hydrodynamical system. This system is modeled as a linearized water wave equation(LWWE), a hyperbolic state-space model coupled with a Laplace equation. We assume that the wave elevation at two distinct points is the only measurement of water waves. We show that the state and water depth can be reconstructed from this point measurement records. The identification problem is recast as an optimization problem over an infinite-dimensional space. We propose the adjoint method-based identification algorithm to generate an estimated state and water depth. We then performed a numerical simulation to show the effectiveness of our designed algorithm by comparing it with existing studies.

关键词： linearized water wave equation (LWWE) point observation state estimation parameter identification adjoint method numerical simulation

Interference Analysis of Co-Located Container Workloads:A Perspective from Hardware Performance Counters

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Journal of Computer Science & Technology 2020年第2期35卷 412-417页

作者： Wen-Yan Chen Ke-Jiang Ye cheng-Zhi Lu Dong-Dai Zhou cheng-zhong xu Shenzhen Institutes of Advanced Technology Chinese Academy of SciencesShenzhen 518055China School of Information Science and Technology Northeast Normal UniversityChangchun 130117China Faculty of Science and Technology University of MacaoMacao 999078China

Workload characterization is critical for resource management and ***,with the fast development of container technique,more and more cloud service providers like Google and Alibaba adopt containers to provide cloud services,due to the low ***,the characteristics of co-located diverse services(e.g.,interactive on-line services,off-line computing services)running in containers are still not *** this paper,we present a comprehensive analysis of the characteristics of co-located workloads running in containers on the same server from the perspective of hardware *** study quantifies and reveals the system behavior from the micro-architecture level when workloads are running in different co-location *** the analysis of typical hardware events,we provide recommended/unrecommended co-location workload patterns which provide valuable deployment suggestions for datacenter administrators.

关键词： workload characterization container co-location pattern hardware performance counter

Energy-aware application performance management in virtualized data centers

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Frontiers of Computer Science 2012年第4期6卷 373-387页

作者： Hui CHEN Ping LU Pengcheng XIONG cheng-zhong xu Zhiping WANG Shenzhen Institutes of Advanced Technology Chinese Academy of SciencesShenzhen 518055China ZTE Corporation Nanjing 210012China College of Computing Georgia Institute of TechnologyAtlantaGA 30332US Department of Electrical and Computer Engineering Wayne State UniversityDetroitM148202US

Both performance and energy cost are impor- tant concerns for current data center operators. Traditionally, however, IT and mechanical engineers have separately op- timized the cyber and physical aspects of data center operations. This paper considers both of these aspects with the eventual goal of developing performance and power management techniques that operate holistically to control the entire cyber-physical complex of data center installations. Toward this end, we propose a balance of payments model for holis- tic power and performance management. As an example of coordinated cyber-physical system management, the energy- aware cyber-physical system （EaCPS） uses an application controller on the cyber side to guarantee application perfor- mance, and on the physical side, it utilizes electric current- aware capacity management （CACM） to smartly place exe- cutables to reduce the energy consumption of each chassis present in a data center rack. A web application, representa- tive of a multi-tier web site, is used to evaluate the perfor- mance of the controller on the cyber side, the CACM control on the physical side, and the holistic EaCPS methods in a mid-size instrumented data center. Results indicate that coor- dinated EaCPS outperforms separate cyber and physical con- trol modules.

关键词： cyber physical system energy management re-source management virtualization data centers

CloudRank-D： benchmarking and ranking cloud computing systems for data processing applications

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Frontiers of Computer Science 2012年第4期6卷 347-362页

作者： Chunjie LUO Jianfeng ZHAN Zhen JIA Lei WANG Gang LU Lixin ZHANG cheng-zhong xu Ninghui SUN State Key Laboratory of Computer Architecture Institute of Computing TechnologyChinese Academy of SciencesBeijing 100019China Department of Electrical and Computer Engineering Wayne State UniversityDetroitM148202USA Shenzhenlnstitute of Advanced Technology Chinese Academy of SciencesShenzhen 518055China

With the explosive growth of information, more and more organizations are deploying private cloud systems or renting public cloud systems to process big data. However, there is no existing benchmark suite for evaluating cloud performance on the whole system level. To the best of our knowledge, this paper proposes the first benchmark suite CloudRank-D to benchmark and rank cloud computing sys- tems that are shared for running big data applications. We an- alyze the limitations of previous metrics, e.g., floating point operations, for evaluating a cloud computing system, and propose two simple metrics： data processed per second and data processed per Joule as two complementary metrics for evaluating cloud computing systems. We detail the design of CloudRank-D that considers representative applications, di- versity of data characteristics, and dynamic behaviors of both applications and system software platforms. Through experi- ments, we demonstrate the advantages of our proposed met- tics. In several case studies, we evaluate two small-scale de- ployments of cloud computing systems using CloudRank-D.

关键词： data center systems clouds big data applica- tions benchmarks evaluation metrics

Towards adaptable and tunable cloud-based map-matching strategy for GPS trajectories

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Frontiers of Information Technology & Electronic Engineering 2016年第12期17卷 1305-1319页

作者： Aftab Ahmed CHANDIO Nikos TZIRITAS Fan ZHANG Ling YIN cheng-zhong xu Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China Institute of Mathematics and Computer Science University of Sindh Jamshoro 70680 Pakistan Department of Electrical and Computer Engineering Wayne State University Detroit 48202 USA

Smart cities have given a significant impetus to manage traffic and use transport networks in an intelligent way. For the above reason, intelligent transportation systems （ITSs） and location-based services （LBSs） have become an interesting research area over the last years. Due to the rapid increase of data volume within the transportation domain, cloud environment is of paramount importance for storing, accessing, handling, and processing such huge amounts of data. A large part of data within the transportation domain is produced in the form of Global Positioning System （GPS） data. Such a kind of data is usually infrequent and noisy and achieving the quality of real-time transport applications based on GPS is a difficult task. The map-matching process, which is responsible for the accurate alignment of observed GPS positions onto a road network, plays a pivotal role in many ITS applications. Regarding accuracy, the performance of a map-matching strategy is based on the shortest path between two consecutive observed GPS positions. On the other extreme, processing shortest path queries （SPQs） incurs high computational cost. Current map-matching techniques are approached with a fixed number of parameters, i.e., the number of candidate points （NCP） and error circle radius （ECR）, which may lead to uncertainty when identifying road segments and either low-accurate results or a large number of SPQs. Moreover, due to the sampling error, GPS data with a high-sampling period （i.e., less than 10 s） typically contains extraneous datum, which also incurs an extra number of SPQs. Due to the high computation cost incurred by SPQs, current map-matching strategies are not suitable for real-time processing. In this paper, we propose real-time map-matching （called RT-MM）, which is a fully adaptive map-matching strategy based on cloud to address the key challenge of SPQs in a map-matching process for real-time GPS trajectories. The evaluation of our approach against state-of-the-art a

关键词： Map-matching GPS trajectories Tuning-based Cloud computing Bulk synchronous parallel

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Prepartition: Load Balancing Approach for Virtual Machine Reservations in a Cloud Data Center

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Journal of Computer Science & Technology 2023年第4期38卷 773-792页

作者：田文洪徐敏贤周光耀吴逵须成忠 Rajkumar Buyya School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu 610054China Yangtze Delta Region Institute(Huzhou) University of Electronic Science and Technology of ChinaHuzhou 313001China Institute of Advanced Computing and Digital Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China Department of Computer Science University of VictoriaVictoriaBCV8W 3P6Canada State Key Laboratory of Internet of Things for Smart City University of MacaoMacao 999078China School of Computing and Information Systems University of MelbourneMelbourne 3010Australia

Load balancing is vital for the efficient and long-term operation of cloud data *** virtualization,post(reactive)migration of virtual machines(VMs)after allocation is the traditional way for load balancing and consoli***,it is not easy for reactive migration to obtain predefined load balance objectives and it may interrupt services and bring ***,we provide a new approach,called Prepartition,for load *** partitions a VM request into a few sub-requests sequentially with start time,end time and capacity demands,and treats each sub-request as a regular VM *** this way,it can proactively set a bound for each VM request on each physical machine and makes the scheduler get ready before VM migration to obtain the predefined load balancing goal,which supports the resource allocation in a fine-grained *** with real-world trace and synthetic data show that our proposed approach with offline version(PrepartitionOff)scheduling has 10%–20%better performance than the existing load balancing baselines under several metrics,including average utilization,imbalance degree,makespan and Capacity_*** also extend Prepartition to online load *** results show that our proposed approach also outperforms state-of-the-art online algorithms.

关键词： cloud computing physical machine(PM) virtual machine(VM) reservation load balancing Prepartition

An Infinite-Dimensional Luenberger-like Observer for Water Waves

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An Infinite-Dimensional Luenberger-like Observer for Water W...

Big-Data Processing Techniques and Their Challenges in Transport Domain

第37届中国控制会议

作者： Yang YU Hai-Long PEI cheng-zhong xu Key Laboratory of Autonomous Systems and Networked Control Ministry of EducationUnmanned Aerial Vehicle Systems Engineering Technology Research Center of GuangdongCollege of Automation Science and EngineeringSouth China University of Technology LAGEP Batiment CPEUniversity Claude Bernard-Lyon 1

The paper deals with the observation problem by using an infinite dimensional observer for the water wave system governed by linearized water wave partial differential *** consider that the water wave system evolves in some infinitedimensional Hilbert *** output measurement of dynamical system is supposed to be the water wave surface *** infinite-dimensional exponentially convergent Luenberger-like observer is proposed to estimate the states of water water system:water velocity potential and surface *** simulations by the finite difference scheme are carried out to validate the proposed observer.

关键词： infinite dimension system observer convergence finite difference method

来源： cnki会议评论

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ZTE Communications 2015年第1期13卷 50-59页

作者： Aftab Ahmed Chandio Nikos Tziritas cheng-zhong xu Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Institute of Mathematics and Computer Science University of Sindh Department of Electrical and Computer Engineering Wayne State University

This paper describes the fundamentals of cloud computing and current big-data key technologies. We categorize big-da- ta processing as batch-based, stream-based, graph-based, DAG-based, interactive-based, or visual-based according to the processing technique. We highlight the strengths and weaknesses of various big-data cloud processing techniques in order to help the big-data community select the appropri- ate processing technique. We also provide big data research challenges and future directions in aspect to transportation management systems.

关键词： big-data cloud computing transportation management sys-tems MapReduce bulk synchronous parallel

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