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Computational Science, Engineering & Technology Series
ISSN 1759-3158
CSETS: 27
TRENDS IN PARALLEL, DISTRIBUTED, GRID AND CLOUD COMPUTING FOR ENGINEERING
Edited by:
Chapter 14

Grid Technology for Collaborative Computing in Engineering

H.M. Chen and Y.C. Lin

Department of Construction Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan

Full Bibliographic Reference for this chapter
H.M. Chen, Y.C. Lin, "Grid Technology for Collaborative Computing in Engineering", in , (Editors), "Trends in Parallel, Distributed, Grid and Cloud Computing for Engineering", Saxe-Coburg Publications, Stirlingshire, UK, Chapter 14, pp 321-334, 2011. doi:10.4203/csets.27.14
Keywords: grid computing, grid middleware, grid technology, distributed computing, engineering, collaborative computing.

Summary
This chapter introduces grid services based on state-of-the-art grid technology and describes relevant architecture, standards, middleware, and several application programming interfaces (APIs). Grid computing provides scientists and engineers with a powerful problem-solving platform that integrates and uses resources (e.g. computers, storage, network communications, sensors, and scientific instruments) distributed throughout a computational grid. With these grid users may coordinate remote resources to achieve computational goals that would otherwise require prohibitively high investments in onsite resources. Various middleware has been developed to handle specific grid functions and implement grid standards. Such functions generally may be categorized by software component type, e.g. common runtime, security, execution management, data management, and information services, which are available to develop a wide range of grid infrastructures and distributed applications.

The Java Community Grid (CoG) Kit [1] is a Java-based wrapper for grid fundamental libraries. This kit defines and implements a set of general components that map grid functions into a commodity environment and provides application developers with programming interfaces that are more advanced and flexible. CoG Kits have also been developed for the Perl, CORBA, Python, Javascript and Matlab communities. Furthermore, running a grid portal implemented with the Java CoG Kit allows grid users to access grid services via a web browser, perform computing processes cooperatively, and expose data and applications.

Grid applications for engineering generally may be classified into one of the following groups: system integration, optimization, distributed experimental simulation, structural analysis, building design, geosciences, fluid dynamic computation and infrastructure observation. Several relevant studies grid applications in these groups will be introduced and summarized.

References
[1]
G. Von Laszewski, I. Foster, J. Gawor, P. Lane, "A Java commodity Grid kit", Concurrency Computation Practice and Experience, 12(8-9), 645-662, 2001. doi:10.1002/cpe.572.abs

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