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CLOUD COMPUTING

(Elective – 2)
OBJECTIVES:
• The student will learn about the cloud environment, building software systems and
components that scale to millions of users in modern internetcloud concepts capabilities
across the various cloud service models including Iaas, Paas, Saas, and developing cloud
based software applications on top of cloud platforms.
UNIT -I: Systems modeling, Clustering and virtualization
Scalable Computing over the Internet, Technologies for Network based systems, System models
for Distributed and Cloud Computing, Software environments for distributed systems and
clouds, 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, Architectural Design of Compute and Storage Clouds,
Public Cloud Platforms, Inter Cloud Resource Management, Cloud Security and Trust
Management. Service Oriented Architecture, Message Oriented Middleware.
UNIT -IV: Cloud Programming and Software Environments
Features of Cloud and Grid Platforms, Parallel & Distributed Programming Paradigms,
Programming Support of Google App Engine, Programming on Amazon AWS and Microsoft
Azure, Emerging Cloud Software Environments.
UNIT- V: 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, Borrowed Virtual Time, Cloud Scheduling Subject to Deadlines,
Scheduling MapReduce Applications Subject to Deadlines.
UNIT- VI: Storage Systems
Evolution of storage technology, storage models, file systems and database, distributed file
systems, general parallel file systems. Google file system. Apache Hadoop, Big Table,
Megastore, Amazon Simple Storage Service (S3)

IV Year – I Semester
L T P C
4 0 0 3
OUTCOMES:
• Understanding the key dimensions of the challenge of Cloud Computing
• Assessment of the economics , financial, and technological implications for selecting
cloud computing for own organization
• Assessing the financial, technological, and organizational capacity of employer’s for
actively initiating and installing cloud-based applications.
• Assessment of own organizations’ needs for capacity building and training in cloud
computing-related IT areas
TEXT BOOKS:

  1. Distributed and Cloud Computing, Kai Hwang, Geoffry C. Fox, Jack J. Dongarra MK
    Elsevier.
  2. Cloud Computing, Theory and Practice, Dan C Marinescu, MK Elsevier.
  3. Cloud Computing, A Hands on approach, ArshadeepBahga, Vijay Madisetti, University
    Press
    REFERNCE BOOKS:
  4. Cloud Computing, A Practical Approach, Anthony T Velte, Toby J Velte, Robert
    Elsenpeter, TMH
  5. Mastering Cloud Computing, Foundations and Application Programming, Raj Kumar
    Buyya, Christen vecctiola, S Tammaraiselvi, TMH

Total 6 Units Download

Last updated on June 4, 2021 4:54 am