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Cloud

Instructor Information

Instructor: Weidong Shi (Larry), Ph.D.
Office Location:PGH 567
Telephone: Office – 713-743-3045
E-mail: $_ = "wshi3XXuhYYedu"; s/XX/@/; s/YY/./;
Office Hours:Tuesday, Thursday. 1:30pm – 2:30pm or by appointment

 

Course Information

Course Number: COSC6376
Course Name: Cloud Computing
Course Location: SEC 105
Class Times: TuTh 1:00pm – 2:30pm
Prerequisites: Graduate standing or consent of instructor. Good knowledge of data structures, algorithms, databases, operating systems, and distributed computing. The projects will require good programming skills and sufficient knowledge of Python and script programming. Be prepared to learn new programming frameworks. You should have good experience working in the Linux environment, since our projects will be done in Linux.

 

Teaching Assistant

Name: Olga Datskova
Office Location: PGH 547 (Computer Lab)
Telephone: None
E-mail:
Office Hours: Tue/Thu 12:00-13:00 (or by appointment)

 

Textbook:

There is no textbook for this course. All materials will come from recently published papers and online documents.

Reference:

  • “Cloud Computing, Implementation, Management, and Security” by John W. Rittinghouse and James F. Ransome, ISBN: 978-1-4398-0680-7, CRC Press, 2010
  • “Cloud Application, Architectures”, by George Reese, ISBN: 978-0-1360-0922-1, Addison Wesley, 2009
  • Practical Virtualization Solutions: Virtualization from the Trenches”, by Kenneth Hess, Amy Newman, ISBN: 978-0-1371-42972, Prentice Hall, 2009

 

Description:

This is a graduate level course to cloud computing. In this course, we will explore a few aspects of cloud computing: distributed data crunching with MapReduce, cloud and datacenter filesystems, virtualization, cloud security and privacy, Amazon Web Services, and interactive web-based applications. Students are expected to read extra materials including papers and online resources, finish several mini projects, a large team project, and take the final exam. Participation in the class discussion is strongly encouraged. Guest speakers might be invited for some particular topics.

Learning Objectives:

On completion of this course, students will have a comprehensive knowledge of cloud computing techniques, be able to design and implement applications using Amazon cloud services, have a comprehensive knowledge of best practices in cloud computing, and be able to understand the challenges and issues in cloud computing.

Project Schedule

Project Report Template

Class Schedule and Slides

Date Topic Slide Reading Assignment
8/26 Intro Introduction(pdf), Introduction(ppt) Cloudonomics: A Rigorous Approach to Cloud Benefit Quantification
8/28 Cloudonomics Cloudonomics(pdf), Cloudonomics(ppt)
9/2 Brief Cluster Discussion no slides
9/4 Challenges Challenges(pdf), Challenges(ppt) Brewer’s Conjecture and the Feasibility of Consistent, Available, Partition-Tolerant Web Services
9/9 MapReduce - Part 1 MapReduce(pdf), MapReduce(ppt) MapReduce: Simplified Data Processing on Large Clusters
9/11 MapReduce - Part 2 MapReduce - Part 2(pdf), MapReduce - Part 2(ppt)
9/16 Security - Cloud FPGA
9/18 BigTable
9/23 Amazon AWS Amazon AWS(ppt) Bigtable: A Distributed Storage System for Structured Data
9/25 Dynamo Dynamo(pdf), Dynamo(ppt) Dynamo: Amazon's Highly Available Key-value Store
9/30 NoSql NoSql(pdf), NoSql(ppt)
10/2 PigLatin PigLatin(pdf), PigLatin(ppt) Pig Latin: A Not-So-Foreign Language for Data Processing
10/7 Project presentation
10/9 PigLatin and Virtualization PigLatin and Virtualization(pdf), PigLatin and Virtualization(ppt)
10/14 Virtualization Part 2 Virtualization(pdf), Virtualization(ppt) Xen and the Art of Virtualization
10/16 Virtualization Part 3 and IOV Virtualization(pdf), Virtualization(ppt),Virtualization-IOV(pdf), Virtualization-IOV(ppt) NOX: Towards an Operating System for Networks
10/21 Software Defined Network Software Defined Network(pptx), Software Defined Network(pdf)
10/23 Storage Virtualization Storage Virtualization (pptx), Storage Virtualization (pdf)
10/28 Storage Virtualization Storage Virtualization 2(pptx), Storage Virtualization 2(pdf)
10/30 Scalable Services Scalable Services (pptx), Scalable Services (pdf)
11/04 Scalable Services 2 Scalable Services 2(pptx), Scalable Services 2(pdf)
11/06 Infrastructure as Code Infrastructure as Code(pptx), Infrastructure as Code(pdf)
11/11 Hypothesis Testing HypothesisTesting(pdf)
11/13 Cloud Security Cloud Security(pptx), Cloud Security(pdf)
11/18 Cloud Security All Your Clouds are Belong to us – Security Analysis of Cloud Management Interfaces
11/20 Cloud Security
11/25 Cloud Security : Signature Wrapping Attack Signature Wrapping Attack and Cloud Security(pptx), Signature Wrapping Attack and Cloud Security(pdf) Hey, You, Get Off of My Cloud:(pdf)
11/27 Cloud Security : XSS XSS and Cloud Security(pptx), XSS and Cloud Security(pdf)
12/4 Cloud Cartography, Cyber Insurance Cloud Cartography, Cyber Insurance (pptx), Cloud Cartography, Cyber Insurance (pdf)

 

Homework

 

Grading:

  • Reading summaries 15%
  • Two programming assignments 20%
  • Team Projects 65%

 

Honor Code:

Students are expected to uphold the University of Houston Honor Code and to avoid any instances of academic misconduct in homework assignments and exams. Any violation will be immediately and directly reported to the Dean of Students' Affairs for further action.

Student with Disabilities:

Any student with a documented disability needing accommodations must speak with the instructor.


Created by admin. Last Modification: Tuesday 27 of December, 2016 22:40:42 UTC by admin. (Version 119)

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