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 issues
• Covers vulnerabilities such as data theft or loss, privacy concerns, infected applications, threats in virtualization, and cross-virtual machine attack
• Describes the implementation of workflows in clouds, proposing an architecture composed of two layers-platform and application
• Details 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 models
• Demonstrates how cloud computing aids in resource control, vertical and horizontal scalability, interoperability, and adaptive scheduling

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.