CS5224: Cloud Computing – 2016/17 Semester 2

(updated: 29 March 2017)

 

L00: Overview

·       Learning Objectives

·       What we will cover?

·       Course Schedule & Webpage

·       Main Text

·       Module Assessment

Books

1.      Cloud Computing: Concepts, Technology and Architecture, Thomas Erl, Zaigham Mahmood and Ricardo Puttini, Prentice-Hall, 2013. [CTA]

2.      Cloud Computing: Theory and Practice, Dan C. Marinescu, Elvesier, 2013.  [TP]

 

PART A: Principles of Cloud Computing

L01: Introduction [CTA-chapter 3]

·       What and Why

·       Cost Model

·       History

·       Key Business Drivers

·       Basic Concepts & Terminology

·       Goals and Benefits

·       Technical and Non-Technical Challenges

·       Summary

References

1.      Above the Clouds: A Berkeley View of Cloud Computing, 2009.

2.      The NIST Definition of Cloud Computing, NIST Report, 2011.

 

L02: Concepts and Models [CTA – chapter 4]

·       NIST Definition

·       Cloud Characteristics

·       Cloud Service (Delivery) Models

·       Conceptual Reference Architecture

·       Cloud Deployment Models

·       Summary

References

1.       NIST Cloud Computing Reference Architecture, NIST Report, 2011.

 

HO1: IBM Cloud Services (PaaS, SaaS) [hands-on]

·       Objective

·       IBM Cloud Platform – Bluemix

·       Overview

·       Target Consumers

·       Technology

·       Examples

·       PaaS: Setup a HelloWorld Web Server using Boilerplates

·       SaaS: Data Analytics using dashDB, SQL Query and R

·       Summary

References

1.       An Updated Overview and Demonstration of IBM Bluemix, Youtube video, Feb 2016

2.       IBM Bluemix The Cloud Platform for Creating and Delivering Applications, IBM Redbooks, 2015.

3.       Bluemix users: https://www.ibm.com/cloud-computing/bluemix/case-studies

4.       IBM dashDB: http://www-01.ibm.com/support/knowledgecenter/SS6NHC/com.ibm.swg.im.dashdb.kc.doc/welcome.html

5.       SQL Query: http://www.w3schools.com/sql/

6.       R Language: http://cran.r-project.org/doc/manuals/r-release/R-intro.html

7.       Plotting: http://docs.ggplot2.org/current/

 

PART B: Technologies, Programming & Applications

L03: Technologies behind Cloud Computing [CTA – chapter 5 and Appendix D]

·       Resource Hosting

·       Main Components in a Datacenter

·       Server, storage and network

·       Cooling systems and energy

·       Fire protection

·       Security

·       Datacenter Tiers

·       Virtualization

·       Multitenancy

·       Summary

References

1.          Chapters 3 & 4, The Datacenter as a Computer: An Introduction to the Design of Warehouse-Scale Machines, Second Edition, Synthesis Lectures on Computer Architecture, Luiz André Barroso, Jimmy Clidaras, Urs Hölzle, Morgan & Claypool Publishers, 2013.

2.          Data Centres Shine Amid Property Gloom, Straits Times, Jan 12, 2016.

 

H02: Amazon Web Services [hands-on]

·       Objectives

·       Main EC2 Steps

·       Examples

·       Summary

References

1.       http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ec2-launch-instance_linux.html

2.       http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ec2-connect-to-instance-linux.html

3.       http://wiki.apache.org/hadoop/AmazonEC2?action=recall&rev=10

4.       http://wiki.apache.org/hadoop/AmazonEC2

5.       http://docs.aws.amazon.com/ElasticMapReduce/latest/DeveloperGuide/emr-get-started-count-words.html

 

L04: Cloud Architecture [CTA – chapter 11]

·       Purpose

·       How to organize (partition) resources?

·       Workload Distribution

·       Resource Pooling

·       Dynamic Scalability

·       Elastic Resource Capacity

·       Service Load Balancing

·       How to operate/manage resources to meet certain objectives?

·       Cloud Bursting

·       Elastic Disk Provisioning

·       Summary

 

L05: Applications and Paradigms (TP chapter 4)

·       Cloud Applications

·       Types of Applications

·       Elasticity and Workload

·       Challenges in Developing Applications

·       Architectural Styles

·       Coordination of Multiple Activities – Workflow

·       Application Development Models

·       IaaS, PaaS and SaaS

·       MapReduce Programming Model

·       Example: Word Count, GrepTheWeb

·       Summary

References

1.       Cloud Architectures, Jinesh Varia, Amazon, June 2008 (describes Amazon GrepTheWeb production system).

 

L06: Cloud Infrastructure [TP - chapter 3]

·       Cloud Platforms

·       Amazon Web Services

o   Regions & Availability Zones

o   Instances

o   Examples

·       Google Cloud Platform

·       Microsoft Windows Azure

·       Open-source Platforms

·       Cloud Interoperability and Vendor Lock-in

·       Energy use of Data Centers

·       Energy-proportional Systems

·       Summary

References

1.          Architecting for the Cloud: Best Practices, Amazon, 2011.

2.          Overview of Amazon Web Services, January 2014.

 

L07: K-Means Clustering using Elastic MapReduce (IaaS, PaaS)

·       Objective

·       Algorithm

·       K-means in MapReduce

·       K-means using Amazon Elastic MapReduce

·       Summary

·       References

 

L08: Building a Video-Sharing SaaS Cloud Application

·       Objective

·       Design of Application

·       Upload Process

·       Encoding Process

·       Streaming Process

·       Performance and Scaling

·       Pricing

·       Summary

1.       How AWS Pricing Works, July 2014.

 

PART C: Cloud Management

L09: Cost Metrics, Pricing Models, Service Metrics and TCO [CTA chapters 15 & 16]

·       Cost Metrics

·       Business

·       Cloud Usage

·       Cost Management

·       Pricing Models

·       Service Metrics

·       Service Quality

·       Service Availability

·       Service Reliability

·       Service Resiliency

·       Service Level Agreement

·       Total Cost of Ownership

·       Summary

References

1.          How AWS Pricing Works, Amazon, 2012.

2.          The Total Cost of (Non) Ownership of Web Applications in the Cloud, Jinesh Varia, August 2012.

3.          Chapter 6: Modeling Costs in “The Datacenter as a Computer”, 2013.

 

L10: Cloud-enabled Data Analytics

·       Cloud Analytics

·       Analytics Workflow for Big Data

·       Four Key Issues

§  Data Management

§  Model Building and Scoring

§  Visualization and User Interaction

§  Business Models

·       Summary

1.       Big Data Computing and Clouds: Trends and Future Directions, JPDC, 2015.

 

L11: Summary and Open Issues

·       Revisit of Learning Objective

·       Topics Covered

·       Open Issues

·       10 Obstacles and Opportunities

·       Open Issues: 5 Areas

·       Our Research

References

1.          Cloud Computing Synopsis and Recommendations (Open Issues), NIST Report, May 2012.

2.          Challenges and Opportunities with Big Data, Computing Community Consortium, Feb 2012.

 

Books

1.      Cloud Computing: Concepts, Technology and Architecture, Thomas Erl, Zaigham Mahmood and Ricardo Puttini, Prentice-Hall, 2013. [CTA]

2.      Cloud Computing: Theory and Practice, Dan C. Marinescu, Elvesier, 2013.  [TP]