Course: Spring 2012 B534 Distributed systems Graduate Course

Project Details

Project Lead
Judy Qiu 
Project Manager
Tak-Lon Wu 
Project Members
Swati Nagde, Alina Banerjee, Juili Shrotriya, Shweta Patil, Bhumi Patel, Pushkar Newaskar, Ikhyun Park, Robert Templeman, Alina Banerjee, Chintan Desai, Quan Zhou, Yicheng Feng, Yuan Gao, Roberto Hoyle, Qatrunnada Ismail, Viplav Khadke, Ming Lu, Mejbaol Sajib, Harsh Savla, Alhanoof Althnian, Aina Ausaf, shenshen han, Chaitanya Khadilkar, Mayur Masrani, Purshottam Vishwakarma, Ankita Dherange, Ila Jogaikar, Vincy Joy, Nikhil Kulkarni, Pranav Sundriyal, Vivek Kumar Singh, Alina Banerjee, Venu Bangalore Parameshwara Setty, Harish Bharani, Pinank Haria, Bhaskar Jaiswal, Ritesh Kavungal, Ambreen Kazi, Gordon Moon, Dhaval Muchhala, Nupoor Paygude, Gaurav Ranade, Niranjana Ravi, Shravya Saripella, Sahil Shah, Juili Shrotriya, Venkat Kalyan Uppala, Ashish Urankar, Quan Zhang, Mahesh Bhandiwad, Rohit Alekar, Shubham Dubey, bitan saha, Aaron Todd, sandip nandi, Gouri Netravali  
Indiana University, School of Informatics and Computing  
Computer Science (401) 


CSCI-B534 is a course for young computer scientists working in the field of software and systems. It is offered to a class of 52 students (PhD, Masters) and two AIs covering core Computer Science distributed systems curricula ( Distributed systems form a rapidly changing field of computer science. We study the evolutional changes in computing landscape characterized by parallel, distributed, and cloud computing systems. We use FutureGrid testbed to build our prototype systems and have an in-depth study the essential issues in practice such as scalability, performance, availability, security, energy-efficiency, and workload balancing.

Intellectual Merit

Objectives The Internet has greatly expanded the scope and importance of distributed systems to include Web 2.0 sites, Information retrieval (search), Utility (cloud) computing, P2P systems and the Internet of things. Further science is facing an unprecedented data deluge and the emergence of data oriented analysis as a fourth paradigm of scientific methodology after theory, experiment and simulation. This class will use these modern systems to introduce core technologies including communication, concurrency/parallelism, security, fault tolerance and programming models. In particular the course will cover systems and tools to support data intensive science applications. Students will get to know the latest research topics through paper readings and have the opportunity to understand some commercial cloud systems through projects using FutureGrid resources. Scope and topics The content of B534 will cover the design principles, systems architecture, and innovative applications of parallel, distributed, and cloud computing systems. These include massively parallel processors (MPP), supercomputing clusters, service-orient architecture (SOA), computational grids, P2P (peer-to-peer) networks, virtualized datacenters, cloud platforms, Internet of Things (IOT), and Cyber-Physical Systems (CPS). We will cover MapReduce (originated from functional languages) and associated languages but it will focus more on the principles and practice of building distributed systems than on languages.

Broader Impacts

The curricula and tutorials can be re-used in other cloud computing/distributed system educational activities

Scale of Use

Each student will need modest resources