Congratulations to my student Olumuyiwa (“M”) Oluwasanmi who successfully defended his dissertation on “Practical, Scalable Algorithms for Byzantine agreement” last week!
Usually on this blog, I allow only a 1 slide dissertation summary, but today I’m making an exception for 2 slides (at least they have the same x-axis :). The slides below summarize the performance of 4 Byzantine agreement algorithms. The CKS algorithm is from the paper “Random oracles in Constantinople: Practical asynchronous Byzantine agreement using cryptography“. The remaining 3 algorithms are from M’s dissertation, and the algorithms with the RB prefix assume the existence of a random beacon.
Filed under: Uncategorized | Tags: Byzantine agreement, distributed computing, grants, theory
The process of grant writing was completely opaque to me when I was a grad student. As a faculty member, I now take the position that grant writing is intrinsically important, and that all grad students should learn something about it in order to get insight into the long-term planning process for doing research. For this reason, it’d be nice to see more examples of funded grants publicly available.
Last January, I posted a one page project summary for one of my funded NSF proposals. This year again I was lucky enough to have a proposal funded and I’m posting the one page summary below. I hope that some readers find it useful.
Roger Wattenhoffer shares with me slides from his talk on “local looking” distributed algorithms that I think will be interesting to the distributed computing community. This talk was given at another workshop at Bertinoro this summer – a workshop on sublinear algorithms (blogged by Piotr Indyk here). Roger’s talk particularly focuses on lowerbounds and upperbounds for many “local looking” distributed problems like Maximal Independent Set, Minimal Vertex Cover, Minimum Dominating Set and Maximal Matching. The talk discusses the known lowerbounds for these problems: they are all known to require a number of rounds that is Omega(sqrt(log n)) and Omega(log Delta).
The talk also discusses upperbounds – in particular it also discusses a beautiful randomized algorithm for Maximal Independent Set that takes O(log n) rounds in expectation (I’ve recently posted slides from one of my own recent talks on this nice randomized MIS algorithm here. )
Finally, the talk illuminates many interesting open problems in distributed algorithms for these types of problems:
- Is there a deterministic algorithm for Maximal Independent Set (MIS) that takes polylog n rounds?
- Can we close the gap for randomized algorithms for MIS between the best lowerbound O(sqrt(log n)), and the best upperbound, O(log n)?
- What are the problem boundaries between O(1), O(log*n), O(log n) and O(diameter)? A nice picture illustrating what is open on these boundaries is given in the last couple slides of the talk.