The Common Instrument Middleware Architecture: Overview of Goals and Implementation

Devadithya, Tharaka; Chiu, Ken; Huffman, Kianosh; McMullen, Donald F.

doi:10.1109/e-science.2005.77

Cited by 28 publications

(19 citation statements)

References 2 publications

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“…Many Grid Systems such as CIMA [1][2][3][4], GridCC [5,6] and RINGrid [7][8][9][10] have already done lots of research and implementation in data acquisition. Focusing mainly on device resource collaboration and virtualization, these systems usually use dedicated computation nodes and are designed according the peak workloads.…”

Section: Introductionmentioning

confidence: 99%

A Scalable Data Acquisition Architecture in Web-Based IOT

Guo

et al. 2012

Information and Business Intelligence

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Abstract. The data acquisition system in Web-based IOT needs to consider not only the requirements of the daily routine analysis of the data, but also the requirements from the real-time reaction of an emergency, which presents a dilemma for system design. This paper presents scalable distributed data acquisition system architecture SCADA, which can extend the system capability temporally using extra resources to meet the demands. Based on the traditional Master-Worker model, the system makes uses of the executors for task execution and resource allocation and can execute the tasks efficiently. The experiment proves the scalability of SCADA.

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Section: Introductionmentioning

confidence: 99%

A Scalable Data Acquisition Architecture in Web-Based IOT

Guo

et al. 2012

Information and Business Intelligence

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“…In related work we have shown how portals can be used to organize access to instruments through the Common Instrument Middleware Architecture (CIMA) [2] and how individual portlets can provide specialized, role and task specific functionality as users, technicians and system administrators interact in the generation, analysis and management of data from shared instrument resources. In this paper we will focus on the approach taken to develop portlets for managing crystallographic data in a group of cooperating laboratories.…”

Section: Introductionmentioning

confidence: 99%

Providing Portlet-Based Client Access to CIMA-Enabled Crystallographic Instruments, Sensors, and Data

Yin

McMullen

Nacar

et al. 2006

2006 7th IEEE/ACM International Conference on Grid Computing

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Abstract-The Common Instrument Middleware Architecture (CIMA) project, supported by the NSF Middleware Initiative, aims at making scientific instruments and sensors remotely accessible by providing a general solution for services and user interfaces to remotely access data from instruments and to remotely monitor experiments. X-ray crystallography is one of several motivating applications for the development of CIMA. Data such as CCD frames and sensor readings may be accessed by portals through middleware services as they are being acquired or through persistent archives. CIMA software may be used to federate online instruments in multiple labs, so this project must also address problems in data management and data sharing. This paper describes a collaboration between the CIMA and the Open Grid Computing Environments (OGCE) project to enable remote users to monitor instruments and interact with data gathered from CIMA-enabled crystallography laboratories through various Web portal components (portlets) running within a standards-compliant portal container. We also discuss an approach taken to develop portlets that use Web Services for data management and solutions for managing distributed identity and access control.

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“…We are developing the Common Instrument Middleware Architecture (CIMA) [22], a broad, middleware-based approach that can be used to solve remote access and control problems in many areas and on many scales. Use of a common middleware specification enables instrument users to build, test and deploy software to implement their experiments as needed, and to continue to use existing software with minimal modification when instruments are redesigned or upgraded.…”

Section: Scientific Instruments and Web 20mentioning

confidence: 99%

Self-Repairing Computers

Fox

Patterson²

2003

Sci Am

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Abstract:Web 2.0-style services and capabilities collectively define a comprehensive distributed computing environment that may be considered an alternative or supplement to existing Grid computing approaches for e-Science. Web 2.0 is briefly summarized as building upon network-enabled, stateless services with simple message formats and message exchange patterns to build rich client interfaces, mash-ups (custom, composite, Web applications), and online communities. In this article, we review several of our activities in these areas: service architectures for Chemical Informatics; Web 2.0 approaches for managing real-time data from online experiments; management and federation of digital entities and their metadata obtained from multiple services; and the use of tagging and social bookmarking to foster scientific networking at minority serving institutions. We conclude with a discussion of further research opportunities in the application of Web 2.0 to e-Science.

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The Common Instrument Middleware Architecture: Overview of Goals and Implementation

Cited by 28 publications

References 2 publications

A Scalable Data Acquisition Architecture in Web-Based IOT

A Scalable Data Acquisition Architecture in Web-Based IOT

Providing Portlet-Based Client Access to CIMA-Enabled Crystallographic Instruments, Sensors, and Data

Self-Repairing Computers

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