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. 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:Discusses the challenges imposed by big data on scientific data infrastructures, including security and trust issuesCovers vulnerabilities such as data theft or loss, privacy concerns, infected applications, threats in virtualization, and cross-virtual machine attackDescribes the implementation of workflows in clouds, proposing an architecture composed of two layers—platform and applicationDetails infrastructure-as-a-service (IaaS), platform-as-a-service (PaaS), and software-as-a-service (SaaS) solutions based on public, private, and hybrid cloud computing modelsDemonstrates how cloud computing aids in resource control, vertical and horizontal scalability, interoperability, and adaptive schedulingFeaturing 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.

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

Olivier Terzo holds a bachelor’s degree from the University Institute of Nancy, France, and an M.Sc and Ph.D from the Polytechnic of Turin, Italy. Dr. Terzo is senior researcher and head of the Research Area: Advanced Computing and Electromagnetics (ACE) at the Istituto Superiore Mario Boella (ISMB), Turin, Italy. Previously at ISMB, he served as researcher in the e-security laboratory and as head of the Research Unit Infrastructures and Systems for Advanced Computing (IS4AC). His current research focuses on application integration in cloud environments. He has published more than 60 papers in conference proceedings and journals, and as book chapters. Lorenzo Mossucca studied computer engineering at the Polytechnic of Turin. Since 2007, Dr. Mossucca has worked as a researcher at the ISMB in IS4AC. His current research interests include studies of distributed databases, distributed infrastructures, and grid and cloud computing. For the past few years, he has focused his research on the migration of scientific applications to the cloud, particularly in bioinformatics and earth sciences. He has published more than 30 papers in conference proceedings, journals, and posters, and as book chapters. He is part of the IEEE Technical Program Committee and is a reviewer for many international conferences.