Software Architecture for Big Data and the Cloud

Software Architecture for Big Data and the Cloud is designed to be a single resource that brings together research on how software architectures can solve the challenges imposed by building big data software systems. The challenges of big data on the software architecture can relate to scale, security, integrity, performance, concurrency, parallelism, and dependability, amongst others. Big data handling requires rethinking architectural solutions to meet functional and non-functional requirements related to volume, variety and velocity.

The book's editors have varied and complementary backgrounds in requirements and architecture, specifically in software architectures for cloud and big data, as well as expertise in software engineering for cloud and big data. This book brings together work across different disciplines in software engineering, including work expanded from conference tracks and workshops led by the editors.

Discusses systematic and disciplined approaches to building software architectures for cloud and big data with state-of-the-art methods and techniquesPresents case studies involving enterprise, business, and government service deployment of big data applicationsShares guidance on theory, frameworks, methodologies, and architecture for cloud and big data

Fundamentals of Software Architecture for Cloud and Big Data 1. Cloud and Big Data Requirements Engineering 2. Cloud and Big Data Software Architectures and Styles 3. Architecture modelling and description languages for Cloud and Big Data 4. Evaluation, Analysis and Verification for Cloud and Big Data Architectures 5. Architecture-centric evolution for cloud and Big Data 6. Architecting for Data and Cloud Service 7. Self-adaptive and managed architectures for cloud and Big Data 8. Economics-Driven architecting for Cloud in the presence of Big Data 9. Architecture-level testing for Cloud and Big Data Services 10. Ethical and legal issues in architecting for cloud and Big Data

Advanced Applications for Cloud and Big Data applications 11. Data-Driven Applications on the cloud 12. Cloud and Big Data Simulation Tools 13. Architectures for Data Analytic Applications on the Cloud 14. Intelligent Services benefiting from Cloud and Big Data

Future Reflections and Experience Reports