Improved Distributed Expander Decomposition and Nearly Optimal Triangle Enumeration

April 17, 2019 · Declared Dead · 🏛 ACM SIGACT-SIGOPS Symposium on Principles of Distributed Computing

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Authors Yi-Jun Chang, Thatchaphol Saranurak arXiv ID 1904.08037 Category cs.DS: Data Structures & Algorithms Cross-listed cs.DC Citations 54 Venue ACM SIGACT-SIGOPS Symposium on Principles of Distributed Computing Last Checked 3 months ago
Abstract
An $(ε,φ)$-expander decomposition of a graph $G=(V,E)$ is a clustering of the vertices $V=V_{1}\cup\cdots\cup V_{x}$ such that (1) each cluster $V_{i}$ induces subgraph with conductance at least $φ$, and (2) the number of inter-cluster edges is at most $ε|E|$. In this paper, we give an improved distributed expander decomposition. Specifically, we construct an $(ε,φ)$-expander decomposition with $φ=(ε/\log n)^{2^{O(k)}}$ in $O(n^{2/k}\cdot\text{poly}(1/φ,\log n))$ rounds for any $ε\in(0,1)$ and positive integer $k$. For example, a $(0.01,1/\text{poly}\log n)$-expander decomposition can be computed in $O(n^γ)$ rounds, for any arbitrarily small constant $γ>0$. Previously, the algorithm by Chang, Pettie, and Zhang can construct a $(1/6,1/\text{poly}\log n)$-expander decomposition using $\tilde{O}(n^{1-δ})$ rounds for any $δ>0$, with a caveat that the algorithm is allowed to throw away a set of edges into an extra part which forms a subgraph with arboricity at most $n^δ$. Our algorithm does not have this caveat. By slightly modifying the distributed algorithm for routing on expanders by Ghaffari, Kuhn and Su [PODC'17], we obtain a triangle enumeration algorithm using $\tilde{O}(n^{1/3})$ rounds. This matches the lower bound by Izumi and Le Gall [PODC'17] and Pandurangan, Robinson and Scquizzato [SPAA'18] of $\tildeΩ(n^{1/3})$ which holds even in the CONGESTED CLIQUE model. This provides the first non-trivial example for a distributed problem that has essentially the same complexity (up to a polylogarithmic factor) in both CONGEST and CONGESTED CLIQUE. The key technique in our proof is the first distributed approximation algorithm for finding a low conductance cut that is as balanced as possible. Previous distributed sparse cut algorithms do not have this nearly most balanced guarantee.
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