Questions
Syllabus
Qns. By Syllabus

Semester

Subject

Bachelors Level/Fourth Year/Seventh Semester/Science bit/seventh semester/cloud computing/syllabus

Bachelors In Information Technology

Institute of Science and Technology, TU

Nature of the course: (Theory+Lab)

F.M: 60+20+20 P.M: 24+8+8

Credit Hrs: 3Hrs

Cloud Computing [BIT408]
Course Objective
i.
The main objective of the course is to introduce fundamental concepts of cloud computing, its technologies, challenges and its applications, to give insight into virtualizations technologies and its architectures, and security in cloud.
Course Description

The course introduces different concepts of cloud computing focusing on architectures, cloud virtualization, programming models, security, platforms and various applications of cloud computing.

S1:Introduction to Cloud Computing[3]
1
Overview and need of cloud computing, History of cloud computing, Cloud stakeholders, Cloud providers, Cloud users, End users, Characteristics and challenges of cloud computing, Benefits and limitations, Cloud computing, Grid Computing, Fog Computing
S2:Cloud Service Models[7]
1
Introduction to cloud service models, SAAS, PAAS, IAAS, XAAS, Server less computing and FAAS model, Cloud deployment model (Private, Public, Hybrid), Cloud Platform (Introduction to Google Cloud Platform, Microsoft Azure, Sales Force, AWS)
S3:Virtualizations[7]
1
Introduction to virtualization, Characteristics of virtualized environments, Types of virtualization (Server, Storage and Network), Machine Image, Virtual Machine, VMware, Hypervisor, Microsoft Hyper-V
S4:SOA and Cloud Management[8]
1
Basic concepts of SOA, Web Services (SOAP, REST), Cloud governance, Cloud Availability and Disaster Recovery, Service Management, Data Management, Resource Management
S5:Cloud Programming Models[10]
1
Thread programming, Task programming, Map-reduce programming, Parallel efficiency of Map Reduce, Comparison between Thread, task and Map reduce
S6:Cloud Security[3]
1
Cloud security fundamentals, Cloud security architecture, Identity management and access control, Cloud computing security challenges, Elimination of intruders in private cloud,
S7:Cloud Based Analytics[7]
1
Data cube, columnar storage, Data Lake, Graph processing, Graph database, Machine learning in the cloud, Fast data processing and streaming in the cloud
References
1.
Raj Kumar Buyya, Christian Vecchiola, S. Thamarai Selvi, Mastering Cloud Computing Cloud Security and Privacy: An Enterprise Perspective on Risks and Compliance, By Tim Mather, Subra Kumaraswamy, Shahed Latif, 2009
2.
David S. Linthicum, Cloud Computing and SOA Convergence in your enterprise
3.
Enterprise Cloud Computing - Technology, Architecture, Applications, Gautam Shroff, Cambridge University Press, 2010
4.
Cloud Computing: Principles and Paradigms, Editors: Rajkumar Buyya, James Broberg, Andrzej M. Goscinski, Wiley,2011
5.
Machine Learning Techniques and Analytics for Cloud Security (Advances in Learning Analytics for Intelligent Cloud-IoT Systems) 1st Edition, Edited by Rajdeep Chakraborty, Anupam Ghosh, Jyotsna Kumar Mandal, 2022
Labrotary Work
The practical work consists of all features of cloud computing