Cloud computing with e-science applications

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. This book describes how cloud computing can significantly improve data management in different scientific fields, such as bioinformatics, earth science, and computer science. This book focuses on how cloud computing helps in the areas of resource control, vertical and horizontal scalability, and adaptive scheduling"

Preface Acknowledgments 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, Xia…