Review of Prerequisite Topics: Graph theory, probability theory covering Markov's inequality, Chebyshev's inequality, Chernoff bounds, Markov chains and random walks.
Models for Distributed Computer Networks: Message passing and shared memory models, synchronous and asynchronous timing models, failure models. Complexity measures like time, space, and message complexity.
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.
References
Distributed Computing: a Locality-Sensitive Approach, by David Peleg.
Distributed Algorithms, by Nancy Lynch.
Distributed Computing: Fundamentals, Simulations, and Advanced Topics, by Hagit Attiya and Jennifer Welch.
Randomized Algorithms, by Rajeev Motwani and Prabhakar Raghavan.
Principles of Distributed Computing, lecture notes by Roger Wattenhofer.
