![]() ![]() Teaching Assistants : Shashank Rahul Mishra, Shivam Cholin, Sukanya Sinha. Principles of Distributed Computing, lecture notes by Roger Wattenhofer.Randomized Algorithms, by Rajeev Motwani and Prabhakar Raghavan.Distributed Computing: Fundamentals, Simulations, and Advanced Topics, by Hagit Attiya and Jennifer Welch.Distributed Algorithms, by Nancy Lynch.Distributed Computing: a Locality-Sensitive Approach, by David Peleg.Application Specific Problems: Storage and retrieval of data in peer-to-peer computing, coverage and routing in sensor networks, and rumour spreading in social networking.Fundamental Problems on Distributed Networks: Maximal independent set, minimum spanning tree, vertex colouring, dominating set, routing algorithms, leader election, Byzantine agreement, synchronizers, graph spanners, dynamic networks. ![]() Complexity measures like time, space, and message complexity. Models for Distributed Computer Networks: Message passing and shared memory models, synchronous and asynchronous timing models, failure models.Review of Prerequisite Topics: Graph theory, probability theory covering Markov's inequality, Chebyshev's inequality, Chernoff bounds, Markov chains and random walks.Center for Computational Brain Research (CCBR). ![]()
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