This Article 
 Bibliographic References 
 Add to: 
The Cloud Agnostic e-Science Analysis Platform
Nov.-Dec. 2011 (vol. 15 no. 6)
pp. 85-89
Ajith Ranabahu, Kno.e.sis, Wright State University
Paul Anderson, College of Charleston
Amit Sheth, Kno.e.sis, Wright State University

The amount of data being generated for e-Science domains has grown exponentially in the past decade, yet the adoption of new computational techniques in these fields hasn't seen similar improvements. The presented platform can exploit the power of cloud computing while providing abstractions for scientists to create highly scalable data processing workflows.

1. A. Manjunatha et al., "Identifying and Implementing the Underlying Operators for Nuclear Magnetic Resonance-Based Metabolomics Data Analysis," Proc. 3rd Int'l Conf. Bioinformatics and Computational Biology, Int'l Soc. Computers and Their Applications, 2011; .
2. M. Fowler and R. Parsons, Domain-Specific Languages, Addison-Wesley Professional, 2010.
3. D. Mahle et al., "A Generalized Model for Metabolomic Analyses: Application to Dose and Time-Dependent Toxicity," Metabolomics, vol. 7, no. 2, 2011, pp. 206–216; .
4. T. Hey and A. Trefethen, "The Data Deluge: An e-Science Perspective," Grid Computing: Making the Global Infrastructure a Reality, F. Berman, G. Fox, and T. Hey eds., John Wiley & Sons, 2003; doi:10.1002/0470867167.ch36.

Index Terms:
cloud computing, scientific workflows, domain specific languages
Ajith Ranabahu, Paul Anderson, Amit Sheth, "The Cloud Agnostic e-Science Analysis Platform," IEEE Internet Computing, vol. 15, no. 6, pp. 85-89, Nov.-Dec. 2011, doi:10.1109/MIC.2011.159
Usage of this product signifies your acceptance of the Terms of Use.