W	Lec	Topics Covered	Supplementary	HW
0 29/9		Registration Week: Course Overview
1 06/10	Lec 1	Distributed System Models and Enabling Technologies Scalable Computing over the Internet, Technologies for Network-Based Systems, System Models for Distributed and Cloud Computing, Software Environments for Distributed Systems and Clouds, Performance, Security
2 13/10	Lec 2	Computer Clusters for Scalable Computing Clustering for Massive Parallelism, Computer Clusters and MPP Architectures, Design Principles of Computer Clusters, Cluster Job and Resource Management, Case Studies of Top Supercomputer Systems	- What is Parallel Computing?
3 20/10	Lec 3	Virtual Machines and Virtualization of Clusters and Datacenters Implementation Levels of Virtualization, Virtualization Structures/Tools and Mechanisms, Virtualization of CPU, Memory, and I/O Devices, Virtual Clusters and Resource Management, Virtualization for Data-Center Automation
4 27/10	Lec 4	Cloud Platform Architecture over Virtualized Data Centers: Data Center Design and Networking What is a Data Center? What does a Data Center Look Like? Warehouse-Scale Data Center Design, Power and Cooling Requirements, Data-Center Interconnection Networks, Design Considerations for WSC	Videos on Data Centers: - Explore a Google Data Center with Street View - Google Container Data Center
5 03/11	Lec 5	Cloud Platform Architecture over Virtualized Data Centers: Cloud Computing Service Models Cloud Computing Services Stack, Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), Today’s Cloud Services Stack, Public, Private & Hybrid Clouds, Market-Oriented Cloud Architecture, Inter-Cloud Resource Management, Cloud Security and Trust Management
6 10/11	Lec 6	Cloud Platform Architecture over Virtualized Data Centers: Major Cloud Service Providers Public Clouds, Amazon Web Services (AWS), Google App Engine, Microsoft Azure	- Amazon Web Services (AWS)    Getting Started with AWS - Introduction to Amazon Web Services (video tutorial) - Good App Engine - Intro. to Google App Engine For Developers (video tutorial) - Microsoft Azure
7 17/11		Midterm Exam I
8 24/11	Lec 7	Service-Oriented Architectures for Distributed Computing Services and Service-Oriented Architecture, Web Services, SOAP Style Web Services, Service Descriptions and IDL for Web Services, REST Style Web Services, Message-Oriented Middleware, Portals and Science Gateways, Discovery, Registries, Metadata, and Databases, Workflow in Service-Oriented Architectures	- SOAP and REST Style Web Service Development Examples in Java - Hadoop installation and configuration on notebooks: 1-, 2- and 4-node clusters using Cloudera Hadoop Distributions - Hadoop installation and configuration on FutureSystems - Indiana University Clusters, our project portal address
9 01/11	Lec 8	Cloud Programming and Software Environments: MapReduce and Hadoop Framework Big Data and Parallel Computing, History of MapReduce, MapReduce Programming Model, Hadoop Framework, Writing Jobs for Hadoop, Hadoop Distributed File System (HDFS), Hadoop Internals, Hadoop 1.0 vs 2.0, MapReduce Cloud Service	- Hadoop home page - Beyond Batch- The Evolution of the Hadoop Ecosystem - Doug Cutting - HDFS-Comics - MapReduce Tutorial (Apache Hadoop Tutorial) - Google MapReduce Tutorial
10 08/12	Lec 9	Cloud Programming and Software Environments: Introduction to YARN and MapReduce 2 Overview of MapReduce 1 and 2, YARN Architecture, MapReduce v2, Managing a YARN Cluster, Cloudera and MR2	- Hadoop Tutorial: Introducing Apache Hadoop (17 minutes)  - Hadoop Tutorial: Intro To Hadoop Developer Training (1 hour)
11 15/12	Lec 10	Cloud Programming and Software Environments: Hadoop Ecosystem Big Data and NoSQL Databases, Hadoop Projects, Hadoop Infrastructures for Big Data Processing, Apache Big Data Stack (ABDS) with HPC Integration	- Hadoop - Just the Basics for Big Data Rookies (1 h 25 min)  - Introduction to Big Data and Hadoop - Edureka.co
12 22/12	Lec 11	Cloud Programming and Software Environments: Hadoop Tutorials MapReduce 1.0, Tuning MapReduce, MapReduce 2.0, Cloudera MapReduce Tutorial, Understanding Hive and Hbase, Understanding Pig, Understanding Workflows and Connectors: Oozie, Sqoop, Flume, Zookeeper, Other Hadoop Libraries: Impala, Mahout, Storm, Understanding Spark, Visualizing Hadoop Output	- Hadoop Fundamentals with Lynn Langit - lynda.com
13 29/12	Lec 12	Internet of Things Internet of Things and the Cloud, Architecture of The Internet of Things and Sensing Layer, Robotics and IoT Expectations, Industrial Internet of Things, Sensor Clouds, Earth/Environment/Polar Science Data Gathered by Sensors, Ubiquitous/Smart Cities, Smart Grid
14 05/12		Midterm Exam I

  Important Notes

	This is the syllabus (Course Information Form) given to students at the beginning of the semester.
	The lecture schedules given in the syllabus are tentative and updated here weekly. Look at this table once a week.
	Almost all the slides used during the semester will be available here.
	You can download the new lecture slides presented in the class after the lecture from this page.
	I may skip several slides during the lecture (The slides given would be generally too much!). They are included in the course material for completeness and to provide a good reference for your future professional engineering life.
	To follow the lecture and understand the materials presented in class better, get the lecture slides and take the print-outs of them, and please bring them to class.
	Purposes for bringing slides to class: 1) To allow better concentration in lecture by reducing note-taking pressure and to provide a study-aid before and after lecture.
	2) You can take your notes on these slides and be active during the lecture. You digest material much better when you actively take notes from step-to-step demonstrations given by your instructor than by just sitting and watching slides.
	Disclaimers: (a) I may not follow these slides exactly in class (b) I may also use the whiteboard and give some extra notes which will not be posted here as needed in class (c) Students are responsible for what I say and teach in class. (d) Reading these slides is not a substitute for attending lecture.