COM 444 Cloud Computing

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Gediz University, Computer Engineering Department
Fall Semester 2015
Tuesday
: 09:00 - 11:45, A-Z04

 
  Instructor: Halûk Gümüşkaya  
  Office: D107  
  Office Hours:  
  Phone: 0232-355 0000 - 2305  
  e-mail: haluk.gumuskaya@gediz.edu.tr  
   
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Course Description

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Prerequistes

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Lecture Schedule

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Lecture Schedule

 

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Textbooks

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Tool and Platforms

 

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Grading

 

  Course Description   (3-0-3)

Distributed System Models and Enabling Technologies, Computer Clusters for Scalable Computing, Virtual Machines and Virtualization of Clusters and Datacenters, Cloud Platform Architecture over Virtualized Data Centers: Data Center Design and Networking, Cloud Computing Service Models, Major Cloud Service Providers. Service Oriented Architectures. Cloud Programming and Software Environments: MapReduce and Hadoop Framework, Grid Computing, Internet of Things.

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, OpenStack, and OpenNebula. 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 or performed in groups of 2-3 students for such a small class this year. Sample term project topics include CPU/GPU clusters, virtual clusters, virtual machine architecture, 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

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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.

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COM 440 Distributed Systems (recommended)

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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

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

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

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

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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 and Platforms

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Public cloud platforms: Amazon Web Services, Google App Engine, Microsoft Azure, Heroku, .... 

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FutureSystems - Indiana University Clusters, our project portal address, and all projects.

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Virtualization software (Oracle VM Box, VMware, KVM, Xen, ...)

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Hadoop Ecosystem - Cloud software tools to develop and run data-intensive applications that run on local powerful notebooks and on a cloud service platform such as Amazon Elastic MapReduce, Google Hadoop Platform, Microsoft Hadoop or IBM Hadoop )

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Cloud computing platforms (OpenStackOpenNebula, ...)

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CloudSim - A framework for modeling and simulation of cloud computing infrastructures and services

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Java development environments

  Grading

    25 % : Midterm Exam I
    25 % : Midterm Exam II
    20 % : Homework
    30
% : Final Exam
 

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