Teacher: Nicola Tonellotto

Question time: Please contact the teacher

Schedule :

Teaching rooms :
Room L1, Polo Fibonacci, first floor.
Room C1, Polo Fibonacci, first floor.
Room C40, ISTI-CNR, Door 19/20, first floor

22/09. Introduction to the course, Logistics. Large-scale problems: status and perspectives.
23/09. Data storage architectures: read-only (search engines), read-write (datastores). Grid computing: elements, definition, architecture, protocols and hourglass model. (slides)
29/09. Grid computing: security, resource management, information management, data management. Architectural models, real-world Grids, Globus Toolkit. (slides)
30/09. Cloud computing: definitions, properties, characteristics. Elasticity, dynamic provisioning and autonomic control. (slides)
03/10. Cloud computing: user benefits, provider benefits, economies of scale. Service models: IAAS, PAAS, SAAS. Deployment models. (slides)
07/10. Cloud computing: comparison with Grids. Cloud programming: fault tolerance, service-oriented architectures, decoupling, autoscaling. (slides)

Grids

Study Notes

1. I. Foster, C. Kesselman, “The Grid 2: Blueprint for a New Computing Infrastructure”, Morgan Kaufmann Publishers Inc., 2003. Chapters 4 and 21.
2. K. Hwang, G. C. Fox, J. Dongarra, “Distributed and Cloud Computing”, Morgan Kaufmann Publishers Inc., 2012. Chapter 7.

Reading Assignments

1. IBM Redbooks, Introduction to Grid Computing, 2003. http://www.redbooks.ibm.com/redbooks/pdfs/sg246778.pdf

Clouds

Study Notes

1. NIST Cloud Computing Reference Architecture
2. Cloud Computing and Grid Computing 360-Degree Compared

Reading Assignments

1. Above the Clouds: A Berkeley View of Cloud Computing
2. Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility

Map Reduce

Study Notes

1. Map-Reduce and the New Software Stack
2. Data-Intensive Text Processing with Map Reduce

Reading Assignments

1. MapReduce: Simplified Data Processing on Large Clusters
2. The Google File System
3. Apapche Hadoop. The scalability update
4. HDFS Scalability: the limits to growth

Virtualization

1. An Overview of Virtual Machine Architectures
2. A Comparison of Software and Hardware Techniques for x86 Virtualization
3. QEMU, a fast and portable dynamic translator

1. The Globus Toolkit Homepage
2. The Hadoop Homepage
3. The Yahoo! Hadoop Tutorial Homepage