COM 444 Cloud Computing

Home

 

Gediz University, Computer Engineering Department
Fall Semester 2013
Monday
: 14:00 - 16:45, D114

 
  Instructor: Halûk Gümüşkaya  
  Office: D107  
  Office Hours: Mon, Tue, Wed: 13:00 - 13:45  
  Phone: 0232-355 0000 - 2305  
  e-mail: haluk.gumuskaya@gediz.edu.tr  
   
bullet

Course Description

Pages:
bullet

Prerequistes

bullet

Lecture Schedule

bullet

Lecture Schedule

bullet

Regulations and Policies

bullet

Textbooks

bullet

Tools

 

bullet

Grading

 

  Course Description   (3-0-3)

Introduction to what the cloud is and building reliable software systems and components that scale to millions of users and petabytes of data, and are always available. Data Center Networking, Hardware Virtualization, Multi-Core chips and Multi-core Computing, Grid Computing, Service Oriented Architecture, Web Services, New Internet Technologies for Cloud Computing, Cloud Service Classification, Cloud Programming Paradigms, MapReduce Programming Model, Hadoop, Cloud Algorithms (PageRank, adsorption, friend recommendation, TF/IDF), Autonomic Computing.

Objectives: This course provides an introduction to the technologies behind cloud computing. A combination of lectures and hands-on programming assignments and a term project expose the students to the leading cloud computing paradigms and programming interfaces (e.g., Amazon EC2, Hadoop). In addition, lectures provide an overview of the underlying clustering technologies that make cloud computing possible (e.g., cluster networking, software DSM, virtual machines). The students will complete a simple assignment using Amazon EC2 individually and a term project performed in groups of 2-3 students. In the term project, the students will build a private Cloud on a PC cluster from scratch and participate in the design, assembling, configuring, and benchmarking of the private Cloud system. The software stack may include Linux, Hadoop, Xen, OpenNebula, and Ganglia. Each project team is required to prepare a project report, do a live demo and a presentation at the end of the semester.

Term Project: The final term project is done individually for such a small class this year. Sample term project topics include CPU/GPU clusters, virtual clusters, virtual machine architecture, P2P networks, cloud platforms, datacenter architecture, Internet of Things, cloud programming experiments on AWS, innovative applications in the cloud, IoT and social networks, etc. All project topics must be approved by Prof. Dr. Gümüşkaya before starting the effort.

   Prerequisites

bullet

Basic understanding of Linux operating system and some experiences in system level programming (Java, C, or C++) are required. The students are expected to exercise the systems configuration and administration under a Linux cluster.

bullet

COM 440 Distributed Systems (recommended)

bullet

COM 362 Computer Networks I (recommended)

   Lecture Schedule

bullet This is the tentative lecture schedule. Please check this page at least once a week during the semester.

   Textbooks

    Textbook

bullet

Distributed and Cloud Computing: From Parallel Processing to The Internet of Things, K. Hwang, G. Fox and J. Dongarra, Morgan Kaufmann Publishers, 2012.

   Recommended

bullet Mastering Cloud Computing: Foundations and Applications Programming, R. Buyya, C. Vecchiola, S. T. Selvi, Morgan Kaufmann, 2013. (Designed for undergraduate students learning to develop cloud computing applications)
bullet Cloud Computing: Theory and Practice, D. C. Marinescu, Morgan Kaufmann, 2013.
bullet Cloud Computing: Concepts, Technology and Architecture, T. Erl et al., Prentice Hall, 2013.
bullet

Cloud Computing: Principles and Paradigms, R. Buyya, J. Broberg, and A. Goscinski (eds), Wiley, 2011.

bullet

BIG CPU, BIG DATA: Solving the World's Toughest Computational Problems with Parallel Computing, A. Kaminsky, Creative Commons, 2013.

bullet

Hadoop: The Definitive Guide, Tom White, O'Reilly, 2012.

bullet

The Fourth Paradigm: Data-Intensive Scientific Discovery, T. Hey, Tansley and Tolle (Editors), Microsoft Research, 2009. (You can download the book from its web site).

  Tools

bullet

....

  Grading

   
30 % : Project
    20 % : HW Assignments
    20 % : Midterm
    30
% : Final Exam
 

Home