The amount of data in everyday life has been exploding. This data increase has been especially significant in scientific fields, where substantial amounts of data must be captured, communicated, aggregated, stored, and analyzed. Cloud Computing with e-Science Applications explains how cloud computing can improve data management in data-heavy fields such as bioinformatics, earth science, and computer science.
The book begins with an overview of cloud models supplied by the National Institute of Standards and Technology (NIST), and then:
Featuring significant contributions from research centers, universities, and industries worldwide, Cloud Computing with e-Science Applications presents innovative cloud migration methodologies applicable to a variety of fields where large data sets are produced. The book provides the scientific community with an essential reference for moving applications to the cloud.
"I found the material presented in Chapter 11 (titled SaaS Clouds Supporting Biology and Medicine) to be highly enlightening and informative. The discussion on high performance computing in the context of cloud computing with applications in computational biology and medicine is very educational. There are a number of research problems in biology and medicine that demand access to large and federated data sets. The discussion in this chapter provides a means for understanding the cases and situations in which the cloud can be utilized for such important purposes."
—Hamid R. Arabnia, University of Georgia, Athens, USA
" … the book shows many advantages and the power of cloud computing in solving e-science applications, as compared to other types of high performance computing infrastructures. The selection of e-science applications included in the book comprise representative problems from bio-science, health, data processing, workflows arising in bussinesses, etc. … well-written and easy to read not only for specialist but also people with basic knowledge on cloud computing."
—Fatos Xhafa, Technical University of Catalonia
About the Authors
List of Contributors
Evaluation Criteria to Run Scientific Applications in the Cloud; Eduardo Roloff, Alexandre da Silva Carissimi, and Philippe Olivier Alexandre Navaux
Cloud-Based Infrastructure for Data-Intensive e-Science Applications: Requirements and Architecture; Yuri Demchenko, Canh Ngo, Paola Grosso, Cees de Laat, and Peter Membrey
Securing Cloud Data; Sushmita Ruj and Rajat Saxena
Adaptive Execution of Scientific Workflow Applications on Clouds; Rodrigo N. Calheiros, Henry Kasim, Terence Hung, Xiaorong Li, Sifei Lu, Long Wang, Henry Palit, Gary Lee, Tuan Ngo, and Rajkumar Buyya
Migrating e-Science Applications to the Cloud: Methodology and Evaluation; Steve Strauch, Vasilios Andrikopoulos, Dimka Karastoyanova, and Karolina Vukojevic-Haupt
Closing the Gap between Cloud Providers and Scientific Users; David Susa, Harold Castro, and Mario Villamizar
Assembling Cloud-Based Geographic Information Systems: A Pragmatic Approach Using Off-the-Shelf Components; Muhammad Akmal, Ian Allison, and Horacio González–Vélez
HCloud, a Healthcare-Oriented Cloud System with Improved Efficiency in Biomedical Data Processing; Ye Li, Chenguang He, Xiaomao Fan, Xucan Huang, and Yunpeng Cai
RPig: Concise Programming Framework by Integrating R with Pig for Big Data Analytics; MingXue Wang and Sidath B. Handurukande
AutoDock Gateway for Molecular Docking Simulations in Cloud Systems; Zoltán Farkas, Péter Kacsuk, Tamás Kiss, Péter Borsody, Ákos Hajnal, Ákos Balaskó, and Krisztián Karóczkai
SaaS Clouds Supporting Biology and Medicine; Philip Church, Andrzej Goscinski, Adam Wong, and Zahir Tari
Energy-Aware Policies in Ubiquitous Computing Facilities; Marina Zapater, Patricia Arroba, José Luis Ayala Rodrigo, Katzalin Olcoz Herrero, and José Manuel Moya Fernandez