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distributed data processing in a telemetric system for monitoring civil engineering constructions

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 1999年第3期48卷 773-777页

作者： Iraqi, A Morawski, RZ Barwicz, A Bock, WJ Univ Quebec Dept Elect Engn Trois Rivieres PQ G9A 5H7 Canada Warsaw Univ Technol Inst Radioelect Fac Elect & Informat Technol PL-00665 Warsaw Poland Univ Quebec Dept Comp Sci Optoelect Lab Hull PQ J8Y 3X7 Canada

The selected aspects of design methodology of a telemetric system for monitoring civil engineering constructions-using fiber-optic strain sensors-are considered. Particular attention is paid to the design decisions concerning the choice of a method for sensor calibration and measurand reconstruction, resulting requirements for computing power and their consequence on the distribution of data processing in the considered telemetric system. The results of this study may be applied for designing a specific telemetric system with fiber-optic sensors of strain.

关键词： Civil engineering distributed data processing Fiber optic sensors Civil engineers data distribution Optical Fibers computational power

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distributed data processing in a United States Naval Shipyard

Distributed data processing in a United States Naval Shipyar...

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作者： Groff, George Thomas United States Naval Postgraduate School

学位级别：硕士

The Shipyard Management Information System is a computer-based system that processes data on virtually e^/ery element of operations within a United States Naval Shipyard. This thesis examines the characteristics and objectives of a general management information system and the philosophies of the Ship- yard Management Information System as envisioned by the Naval Sea Systems Command. The motivations for, and the characteristics of, distributed processing as they apply to management informations systems are presented. It will be shown how an effective distributed data processing system can be created from selective addition of equipment to, and purposeful personnel reorganiza- tion of, the data processing configuration at Mare Island Naval Shipyard.

关键词： distributed data processing Shipyard Management Information System

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A web-based sensor network system with distributed data processing approach via web application

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COMPUTER STANDARDS & INTERFACES 2011年第6期33卷 565-573页

作者： Fukatsu, Tokihiro Kiura, Takuji Hirafuji, Masayuki Natl Agr & Food Res Org Natl Agr Res Ctr Tsukuba Ibaraki 3058666 Japan

We have proposed a Web-based sensor network constructed of Web-based sensor nodes and a remote management system. The Web-based sensor nodes consist of communication units and measurement devices with Web servers. The management system has intelligent processing and rule-based function to manage them flexibly via the Internet and performs various image analyses easily with Web application services. By distributing the image analyses to Web application services, our proposed system provides versatile and scalable data processing. We demonstrated that it can realize the desired image analyses effectively and perform complicated management by changing its operations depending on the results of analysis. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Sensor network Image monitoring Agriculture Web application distributed data processing

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A distributed data processing scheme based on Hadoop for synchrotron radiation experiments

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JOURNAL OF SYNCHROTRON RADIATION 2024年第3期31卷 635-645页

作者： Zhang, Ding Dai, Ze-Yi Sun, Xue-Ping Wu, Xue-Ting Li, Hui Tang, Lin He, Jian-Hua Wuhan Univ Inst Adv Studies Wuhan 430072 Peoples R China

With the development of synchrotron radiation sources and high-frame-rate detectors, the amount of experimental data collected at synchrotron radiation beamlines has increased exponentially. As a result, data processing for synchrotron radiation experiments has entered the era of big data. It is becoming increasingly important for beamlines to have the capability to process large-scale data in parallel to keep up with the rapid growth of data. Currently, there is no set of data processing solutions based on the big data technology framework for beamlines. Apache Hadoop is a widely used distributed system architecture for solving the problem of massive data storage and computation. This paper presents a set of distributed data processing schemes for beamlines with experimental data using Hadoop. The Hadoop distributed File System is utilized as the distributed file storage system, and Hadoop YARN serves as the resource scheduler for the distributed computing cluster. A distributed data processing pipeline that can carry out massively parallel computation is designed and developed using Hadoop Spark. The entire data processing platform adopts a distributed microservice architecture, which makes the system easy to expand, reduces module coupling and improves reliability.

关键词： big data Apache Hadoop distributed data processing microservice architecture

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Image, signal, end distributed data processing for networked eHealth applications

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IEEE ENGINEERING IN MEDICINE AND BIOLOGY MAGAZINE 2007年第5期26卷 14-17页

作者： Maglogiannis, Ilias Wallace, Manolis Karpouzis, Kostas Univ Indianapolis Dept Comp Sci Indianapolis IN 46227 USA

In this era of distributed computing the trend in medical informatics is toward achieving two goals: the availability of software applications and medical information anywhere and anytime and the invisibility of computing. The six papers in this special issue provide an overview of the most promising prospects for the state-of-the-art and emerging field of image, signal, and distributed data processing for networked eHealth applications.

关键词： .National Technical networked Medical data SEPTEMBER/OCTOBER distributed data processing eHealth Applications telemedicine

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data QUALITY IN A distributed data-processing SYSTEM - THE SHEP PILOT-STUDY

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CONTROLLED CLINICAL TRIALS 1986年第1期7卷 27-37页

作者： BAGNIEWSKA, A BLACK, D MOLVIG, K FOX, C IRELAND, C SMITH, J HULLEY, S UNIV CALIF SAN FRANCISCO SAN FRANCISCO GEN HOSP DEPT EPIDEMIOL & INT HLTH SAN FRANCISCO CA 94110 USA

The Systolic Hypertension in the Elderly Program (SHEP) Pilot was a collaborative clinical trial that distributed to the clinics all data processing tasks except for randomization assignment codes and morbidity and mortality data. The clinics used customized programs to enter and verify data interactively, to maintain their own local master files, and to transmit the data electronically to the Coordinating Center. We measured quality control based on criteria from centralized as well as distributed models: the error rate for baseline forms was 0.5 per 1000 items. Ninety-eight percent of the forms were query-free, and a central reentry of the data in a 5% sample yielded a miskey rate of 2 per 1000 items. The potential problems of distributed data processing are vulnerability of the local master files and the time demands on Coordinating Center programmers for maintaining clinic computer systems. The advantages are the active involvement of clinical staff in their own quality control, the functional accessibility of the clinics to the Coordinating Center in controlling protocol decisions and data monitoring, and the level of accuracy, completeness, and timeliness of the data that can be achieved.

关键词： data systems in collaborative clinical trials distributed data processing data quality control

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A Proposal of a Big Web data Application and Archive for the distributed data processing with Apache Hadoop 7th

A Proposal of a Big Web Data Application and Archive for the...

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7th International Conference on Computational Collective Intelligence (ICCCI)

作者： Lnenicka, Martin Hovad, Jan Komarkova, Jitka Univ Pardubice Fac Econ & Adm Pardubice Czech Republic

ISBN: (纸本)9783319243061;9783319243054

In recent years, research on big data, data storage and other topics that represent innovations in the analytics field has become very popular. This paper describes a proposal of a big web data application and archive for the distributed data processing with Apache Hadoop, including the framework with selected methods, which can be used with this platform. It proposes a workflow to create a web content mining application and a big data archive, which uses modern technologies like Python, PHP, JavaScript, MySQL and cloud services. It also shows the overview about the architecture, methods and data structures used in the context of web mining, distributed processing and big data analytics.

关键词： Big web data Big data analytics Web content mining distributed data processing Python Apache Hadoop

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Development of Digital Platform Architecture of distributed data processing 8

Development of Digital Platform Architecture of Distributed ...

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8th Mediterranean Conference on Embedded Computing (MECO) / Summer School on Cyber-Physical Systems and Internet-of-Things (CPS and IoT)

作者： Perepelkin, Dmitry Gostin, Aleksey Saprykin, Aleksey Ivanchikova, Maria Kosorukov, Sergey RSREU Fac Comp Sci Ryazan Russia

ISBN: (纸本)9781728117393

Current trends, such as the increase in the number of Internet-connected devices, exponential growth of data volumes, development of cloud technologies, change all spheres of economy and business. Global network traffic growth dictates the business need to configure large-scale systems and networks. At the same time, the explosive growth of data transmission forces state and commercial enterprises to look for opportunities to quickly reduce current costs in the continuous implementation of new services and technologies. The paper proposes the development of a web-oriented digital platform of distributed data processing for rendering digital educational services for people with disabilities. In the quality of software implementation of the developed digital platform proposed to use PHP framework Pandora. The architecture of the digital platform is represented as UML class diagrams, plug-ins and widgets. The developed digital platform, thanks to a wide range of software tools and open APIs, implements the ability to quickly connect and deploy new digital services.

关键词： digital platform distributed data processing Pandora framework visual environment

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Accelerating I/O in distributed data processing Systems with Apache Arrow CHFS 25

Accelerating I/O in Distributed Data Processing Systems with...

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25th IEEE International Conference on Cluster Computing (CLUSTER)

作者： Koyama, Sohei Hiraga, Kohei Tatebe, Osamu Univ Tsukuba Tsukuba Ibaraki Japan

ISBN: (纸本)9798350370621

In recent years, distributed data-processing frameworks have become popular for processing big data. However, in an HPC, where the computation and storage nodes are separated, the bandwidth between the computation and storage components is small, causing a reduction in data processing throughput. Therefore, in this paper, data were stored on the computation node to solve the data processing throughput degradation. We propose an I/O acceleration method that integrates Apache Arrow and CHFS. It leverages non-volatile memory, a state-of-the-art storage device, via CHFS and leverages CHFS from a distributed data processing framework via Apache Arrow's abstract file system API. The evaluation results showed that the system achieved up to 11.60 times higher bandwidth than when reading data from the parallel file system Lustre. This study also compared with Apache Arrow with BeeOND and UnifyFS, other ad hoc filesystems. The proposed Apache Arrow CHFS showed up to 1.67x/1.23x better write performance. The implementation is published at https://***/tsukuba-hpcs/arrow-chfs

关键词： parallel file system distributed data processing HPC

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THE MEASURING INSTRUMENT WITH distributed data processing

THE MEASURING INSTRUMENT WITH DISTRIBUTED DATA PROCESSING

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19th IMEKO World Congress

作者： Bach, Jakub Masnicki, Romuald Mindykowski, Janusz Gdynia Tech Univ Gdynia Poland

ISBN: (纸本)9789638841001

In the paper a concept of the measuring instrument with distributed data processing, cooperating with PC is presented. A functional configuration of the instrument performing additional functions connected with measurement result accuracy assessment as well as respective algorithms are shown. The principles of cooperation with PC computer are discussed. The laboratory implementation of the designed instrument and scope of its use for teaching process is proposed.

关键词： distributed data processing calibration uncertainty

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