Syllabus

The course covers many topics:

  • Advanced models for large distributed & cloud systems
  • Replication, group and many-to-many communication, and systems for QoS
  • Middleware for development and management of large distributed & cloud systems
  • Infrastructures for global data storage and processing

and it assumes a strong participation through:

  • Individual experience
  • Reading articles on selected topics
  • Deepening through an individual project
  • Development of an individual project
  • Presentation and argument on the subject

Advanced models for large distributed & cloud systems

  • Class Starting: general information and presentation
  • Goals, Basics, and Models: classifications, service and cloud models, parallelization models
  • Middleware & Cloud Models: definitions, categories, basic organization, and patterns for large distributed and cloud systems
  • Overlay Networks and Global File Systems: definitions, basics and distributed solutions for distributed data indexing and storage
  • Client Server and Muticast Middleware: one-to-one remote procedure call support, and infrastructure support for many-to-many communications

Replication, group and many-to-many communication, and systems for QoS

  • Replication: models, strategies and protocols
  • Systems and protocols for QoS
  • Communication and groups

Middleware for large distributed & cloud systems

  • CORBA: middleware, operating environment and exercises
  • OpenStack: an example of a widely-diffused cloud IaaS

Infrastructures for global data storage and processing

  • Ebay principles for viable Data Center
  • Global data storage: solutions for long-term and short-term data memorization
  • Global data processing in batch: batching-based big data processing in the cloud
  • Global stream processing: streaming-based big data processing in the cloud