Course: Fall 2012 B534 Distributed Systems Graduate Course

Project Details

Project Lead
Judy Qiu 
Project Manager
Tak-Lon Wu 
Project Members
Siddhardh Changavalli, Lokesh Chaudhari, Muthu Chidambaram, harish chidire, Ninad Faterpekar, Jesun Firoz, Shantanu Govindjiwala, Srikanth Iyer, Prithvi Raj Jampana, Abhimanyu Jha, Chen Jiang, Sachin Joshi, Supun Kamburugamuve, Munir Khabibullaev, Pranoy Khara, Kartik Mathur, Patrick McChesney, Lakshmi Nookala, Abhyodaya Padiyar, Pallavi Pudakalakatti, Shiva Ray, Sneha Shekatkar, Puneet Singh, Kai Song, Monisha Thakur, Ajay Chaitanya Veluvolu, Kang Zhao, Karthik Mallekav Nagaraj, Jayesh Kawli, Viknes Balasubramanee, Shubhada Karavinkoppa, Viknes Balasubramanee, Kailash Nagarkoti, Ramesh Prasad, Priyanka Jaganathan, Ramesh Prasad, Kailash Nagarkoti, Ila Jogaikar  
Institution
Indiana University, School of Informatics and Computing  
Discipline
Computer Science (401) 

Abstract

Fall 2012 CSCI-B534 is a course for young computer scientists working in the field of software and systems. It is offered to a class of 34 students (PhD, Masters) and two AIs covering core Computer Science distributed systems curricula (http://salsahpc.indiana.edu/csci-b534-fall-2012/). 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