CCS335: Cloud Computing syllabus for AI&DS 2021 regulation (Professional Elective-II)

Cloud Computing detailed syllabus for Artificial Intelligence & Data Science (AI&DS) for 2021 regulation curriculum has been taken from the Anna Universities official website and presented for the AI&DS students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below.

For Artificial Intelligence & Data Science 5th Sem scheme and its subjects, do visit AI&DS 5th Sem 2021 regulation scheme. For Professional Elective-II scheme and its subjects refer to AI&DS Professional Elective-II syllabus scheme. The detailed syllabus of cloud computing is as follows.

Course Objectives:

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Unit I

CLOUD ARCHITECTURE MODELS AND INFRASTRUCTURE
Cloud Architecture: System Models for Distributed and Cloud Computing – NIST Cloud Computing Reference Architecture – Cloud deployment models – Cloud service models; Cloud Infrastructure: Architectural Design of Compute and Storage Clouds – Design Challenges

Unit II

VIRTUALIZATION BASICS
Virtual Machine Basics – Taxonomy of Virtual Machines – Hypervisor – Key Concepts -Virtualization structure – Implementation levels of virtualization – Virtualization Types: Full Virtualization – Para Virtualization – Hardware Virtualization – Virtualization of CPU, Memory and I/O devices.

Unit III

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Unit IV

CLOUD DEPLOYMENT ENVIRONMENT
Google App Engine – Amazon AWS – Microsoft Azure; Cloud Software Environments -Eucalyptus – OpenStack.

Unit V

CLOUD SECURITY
Virtualization System-Specific Attacks: Guest hopping – VM migration attack – hyperjacking. Data Security and Storage; Identity and Access Management (IAM) – IAM Challenges – IAM Architecture and Practice.

Practical Exercises:

1. Install Virtualbox/VMware/ Equivalent open source cloud Workstation with different flavours of Linux or Windows OS on top of windows 8 and above.
2. Install a C compiler in the virtual machine created using a virtual box and execute Simple Programs
3. Install Google App Engine. Create a hello world app and other simple web applications using python/java.
4. Use the GAE launcher to launch the web applications.
5. Simulate a cloud scenario using CloudSim and run a scheduling algorithm that is not present in CloudSim.
6. Find a procedure to transfer the files from one virtual machine to another virtual machine.
7. Install Hadoop single node cluster and run simple applications like wordcount.
8. Creating and Executing Your First Container Using Docker.
9. Run a Container from Docker Hub

Course Outcomes:

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Text Books:

1. Kai Hwang, Geoffrey C Fox, Jack G Dongarra, “Distributed and Cloud Computing, From Parallel Processing to the Internet of Things”, Morgan Kaufmann Publishers, 2012.
2. James Turnbull, “The Docker Book”, O’Reilly Publishers, 2014.
3. Krutz, R. L., Vines, R. D, “Cloud security. A Comprehensive Guide to Secure Cloud Computing”, Wiley Publishing, 2010.

Reference Books:

1. James E. Smith, Ravi Nair, “Virtual Machines: Versatile Platforms for Systems and Processes”, Elsevier/Morgan Kaufmann, 2005.
2. Tim Mather, Subra Kumaraswamy, and Shahed Latif, “Cloud Security and Privacy: an enterprise perspective on risks and compliance”, O’Reilly Media, Inc., 2009.

For detailed syllabus of all the other subjects of Artificial Intelligence & Data Science 5th Sem, visit AI&DS 5th Sem subject syllabuses for 2021 regulation.

For all Artificial Intelligence & Data Science results, visit Anna University AI&DS all semester results direct link.