Cloud Computing

Course Title: Cloud Computing

Course No: BIT408

Nature of the Course: Theory + Lab

Semester: 7

Full Marks: 60 + 20 + 20

Pass Marks: 24 + 8 + 8

Credit Hours: 3

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.

Course Objectives

The main objective of the course is to:

Introduce fundamental concepts of cloud computing, its technologies, challenges and its applications
Give insight into virtualization technologies and its architectures
Understand security in cloud

Course Contents

1. Introduction to Cloud Computing

3 hrs

1.1. Overview and need of cloud computing

1.2. History of cloud computing

1.3. Cloud stakeholders

Cloud providers

Cloud users

End users

1.4. Characteristics and challenges of cloud computing

1.5. Benefits and limitations

1.6. Cloud computing, Grid Computing, Fog Computing

2. Cloud Service Models

7 hrs

2.1. Introduction to cloud service models

2.2. SAAS, PAAS, IAAS, XAAS

2.3. Server less computing and FAAS model

2.4. Cloud deployment model

Private

Public

Hybrid

2.5. Cloud Platform

Introduction to Google Cloud Platform

Microsoft Azure

Sales Force

3. Virtualizations

7 hrs

3.1. Introduction to virtualization

3.2. Characteristics of virtualized environments

3.3. Types of virtualization

Server

Storage

Network

3.8. Microsoft Hyper-V

4. SOA and Cloud Management

8 hrs

4.1. Basic concepts of SOA

4.2. Web Services

SOAP

REST

4.3. Cloud governance

4.4. Cloud Availability and Disaster Recovery

4.5. Service Management

4.6. Data Management

4.7. Resource Management

5. Cloud Programming Models

10 hrs

5.1. Thread programming

5.2. Task programming

5.3. Map-reduce programming

5.4. Parallel efficiency of Map Reduce

5.5. Comparison between Thread, task and Map reduce

6. Cloud Security

3 hrs

6.1. Cloud security fundamentals

6.2. Cloud security architecture

6.3. Identity management and access control

6.4. Cloud computing security challenges

6.5. Elimination of intruders in private cloud

7. Cloud Based Analytics

7 hrs

7.1. Data cube

7.2. Columnar storage

7.3. Data Lake

7.4. Graph processing

7.5. Graph database

7.6. Machine learning in the cloud

7.7. Fast data processing and streaming in the cloud

Laboratory Works

The practical work consists of all features of cloud computing.

1.Cloud Computing Features

Reference Books

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

Notes:

This syllabus follows the official BIT curriculum of Tribhuvan University. In case of any doubt or revision, the university's published syllabus shall be considered authoritative.

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Cloud Computing

Course Description

Course Objectives

Course Contents

Laboratory Works

Reference Books

Notes: