Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Indian Institute of Technology Patna

Distributed Systems

Indian Institute of Technology Patna and NPTEL via Swayam

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
A distributed system is a software system in which components located on networked computers communicate and coordinate their actions by passing messages. The components interact with each other in order to achieve a common goal. Distributed applications (distributed apps) are applications or software that runs on multiple computers within a network at the same time and can be stored on servers or with cloud computing. This course provides an in-depth understanding of fundamental principles and models underlying the theory, algorithms, and systems aspects of distributed computing. Few Emerging topics such as Peer-to-Peer computing, Distributed Hash Table, Google File System, HDFS, Spark, Sensor Networks and Security in Distributed Systems will also be covered for significant impact. Upon completing this course, students will have intimate knowledge about how things work in a distributed environment.INTENDED AUDIENCE: Any Interested Learners.PREREQUISITES: Minimum: Data Structures and Algorithms Ideal: Basic networking concepts, Basic OS concepts (e.g., processes, threads, synchronization, file systems, scheduling etc.), Advanced Programming (Good knowledge in C and C++).INDUSTRY SUPPORT: Microsoft Research has conducted this course. Various companies like Google, IBM, Cisco, etc, Distributed systems Group and Distributed systems start-ups are working on this field.

Syllabus

Week 1: Introduction to DS, Message Passing, Leader Election, Distributed Models, Causality and Logical Time Week 2: Logical Time, Global State & Snapshot and Distributed Mutual Exclusion-Non-Token and Quorum based approaches Week 3: Distributed Mutual Exclusion-Token based approaches, Consensus & Agreement, Checkpointing & Rollback Recovery Week 4: Deadlock Detection, DSM and Distributed MST Week 5: Termination Detection, Message Ordering & Group Communication, Fault Tolerance and Self-Stabilization Week 6: Distributed Randomized Algorithms, DHT and P2P Computing Week 7: Case Studies: GFS, HDFS, Map Reduce and Spark Week 8: Case Studies: Sensor Networks, Authentication & Security in DS

Taught by

Prof. Rajiv Misra

Tags

Reviews

Start your review of Distributed Systems

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.