The Complexity of Symmetry Breaking in Massive Graphs
Christian Konrad, Sriram V. Pemmaraju, Talal Riaz, Peter Robinson

TL;DR
This paper investigates the complexity of symmetry breaking problems like MIS and $eta$-ruling sets in large-scale graph models, providing new algorithms, bounds, and demonstrating separations in space complexity.
Contribution
It introduces improved algorithms and lower bounds for MIS and $eta$-ruling sets in the $k$-machine and streaming models, revealing new complexity insights.
Findings
Improved $ ilde{O}(m/k^2)$-round algorithm for MIS in the $k$-machine model.
First $ ilde{ ext{Omega}}(n/k^2)$ lower bound for MIS in the $k$-machine model.
Efficient algorithms for $eta$-ruling sets with hierarchical sampling, showing separation from MIS in space complexity.
Abstract
The goal of this paper is to understand the complexity of symmetry breaking problems, specifically maximal independent set (MIS) and the closely related -ruling set problem, in two computational models suited for large-scale graph processing, namely the -machine model and the graph streaming model. We present a number of results. For MIS in the -machine model, we improve the -round upper bound of Klauck et al. (SODA 2015) by presenting an -round algorithm. We also present an round lower bound for MIS, the first lower bound for a symmetry breaking problem in the -machine model. For -ruling sets, we use hierarchical sampling to obtain more efficient algorithms in the -machine model and also in the graph streaming model. More specifically, we obtain a -machine algorithm that runs in…
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