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.

Table of Contents

Chapter 1: Evaluation Criteria to Run Scientific Applications in the Cloud
Chapter 2: Cloud-Based Infrastructure for Data-Intensive e-Science Applications: Requirements and Architecture
Chapter 3: Securing Cloud Data
Chapter 4: Adaptive Execution of Scientific Workflow Applications on Clouds
Chapter 5: Migrating e-Science Applications to the Cloud: Methodology and Evaluation
Chapter 6: Closing the Gap between Cloud Providers and Scientific Users
Chapter 7: Assembling Cloud-Based Geographic Information Systems: A Pragmatic Approach Using Off-the-Shelf Components
Chapter 8: HCloud, a Healthcare-Oriented Cloud System with Improved Efficiency in Biomedical Data Processing
Chapter 9: RPig: Concise Programming Framework by Integrating R with Pig for Big Data Analytics
Chapter 10: AutoDock Gateway for Molecular Docking Simulations in Cloud Systems
Chapter 11: SaaS Clouds Supporting Biology and Medicine
Chapter 12: Energy-Aware Policies in Ubiquitous Computing Facilities