Online algorithms are a hallmark of worst case optimization under uncertainty. On the other
hand, in practice, the input is often far from worst case, and has some predictable …

We present a simple polylogarithmic-time deterministic distributed algorithm for network
decomposition. This improves on a celebrated 2 O (√ log n)-time algorithm of Panconesi …

Symmetry-breaking problems are among the most well studied in the field of distributed
computing and yet the most fundamental questions about their complexity remain open. In …

Network decomposition is a central tool in distributed graph algorithms. We present two
improvements on the state of the art for network decomposition, which thus lead to …

Over the past 30 years numerous algorithms have been designed for symmetry breaking
problems in the LOCAL model, such as maximal matching, MIS, vertex coloring, and edge …

We present O (loglog n)-round algorithms in the Massively Parallel Computation (MPC)
model, with Õ (n) memory per machine, that compute a maximal independent set, a 1+ ε …

There are distributed graph algorithms for finding maximal matchings and maximal
independent sets in O (Δ+ log* n) communication rounds; here, n is the number of nodes …

The gap between the known randomized and deterministic local distributed algorithms
underlies arguably the most fundamental and central open question in distributed graph …

This paper is centered on the complexity of graph problems in the well-studied LOCAL
model of distributed computing, introduced by Linial [FOCS'87]. It is widely known that for …

We show that any randomised Monte Carlo distributed algorithm for the Lovász local lemma
requires Omega (log log n) communication rounds, assuming that it finds a correct …