R-20 Syllabus for CSE-AI&ML, JNTUK w. e. f. 2020 – 21
JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY: KAKINADA
KAKINADA – 533 003, Andhra Pradesh, India
DEPARTMENT OF CSE - ARTIFICIAL INTELLIGENCE & MACHINE LEARNING
IV B Tech I Sem
L
T
P
C
3
0
0
3
CLOUD COMPUTING
(Professional Elective-IV)
Course Objectives:
To explain the evolving computer model caned cloud computing.
To introduce the various levels of services that can be achieved by cloud.
To describe the security aspects in cloud.
To motivate students to do programming and experiment with the various cloud computing
environments.
Course Outcomes: At the end of the course, student will be able to
Illustrate the key dimensions of the challenge of Cloud Computing
Classify the Levels of Virtualization and mechanism of tools.
Analyze Cloud infrastructure including Google Cloud and Amazon Cloud.
Create Combinatorial Auctions for cloud resource and design scheduling algorithms for computing
cloud
Assess control storage systems and cloud security, the risks involved its impact and develop cloud
application
UNIT I:
Systems Modeling, Clustering and Virtualization: Scalable Computing over the Internet-The Age of
Internet Computing, Scalable computing over the internet, Technologies for Network Based Systems,
System models for Distributed and Cloud Computing, , Performance, Security and Energy Efficiency
UNIT II:
Virtual Machines and Virtualization of Clusters and Data Centers: Implementation Levels of
Virtualization, Virtualization Structures/ Tools and Mechanisms, Virtualization of CPU, Memory and I/O
Devices, Virtual Clusters and Resource Management, Virtualization for Data-Center Automation.
UNIT III:
Cloud Platform Architecture: Cloud Computing and Service Models, Public Cloud Platforms, Service
Oriented Architecture, Programming on Amazon AWS and Microsoft Azure
UNIT IV:
Cloud Resource Management and Scheduling: Policies and Mechanisms for Resource Management,
Applications of Control Theory to Task Scheduling on a Cloud, Stability of a Two Level Resource
Allocation Architecture, Feedback Control Based on Dynamic Thresholds. Coordination of Specialized
Autonomic Performance Managers, Resource Bundling, Scheduling Algorithms for Computing Clouds-Fair
Queuing, Start Time Fair Queuing.
UNIT V:
Storage Systems: Evolution of storage technology, storage models, file systems and database, distributed
file systems, general parallel file systems. Google file system.
