On Distributed Listing of Cliques
Autor: | François Le Gall, Keren Censor-Hillel, Dean Leitersdorf |
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Jazyk: | angličtina |
Rok vydání: | 2020 |
Předmět: |
FOS: Computer and information sciences
Computer science Arboricity 020206 networking & telecommunications Listing (computer) 0102 computer and information sciences 02 engineering and technology Clique (graph theory) 01 natural sciences Combinatorics Computer Science - Distributed Parallel and Cluster Computing 010201 computation theory & mathematics Computer Science - Data Structures and Algorithms 0202 electrical engineering electronic engineering information engineering Cluster (physics) Graph (abstract data type) Data Structures and Algorithms (cs.DS) Distributed Parallel and Cluster Computing (cs.DC) |
Zdroj: | Proceedings of the 39th Symposium on Principles of Distributed Computing PODC |
Popis: | We show an $\tilde{O}(n^{p/(p+2)})$-round algorithm in the \congest model for \emph{listing} of $K_p$ (a clique with $p$ nodes), for all $p =4, p\geq 6$. For $p = 5$, we show an $\tilde{O}(n^{3/4})$-round algorithm. For $p=4$ and $p=5$, our results improve upon the previous state-of-the-art of $O(n^{5/6+o(1)})$ and $O(n^{21/22+o(1)})$, respectively, by Eden et al. [DISC 2019]. For all $p\geq 6$, ours is the first sub-linear round algorithm for $K_p$ listing. We leverage the recent expander decomposition algorithm of Chang et al. [SODA 2019] to create clusters with a good mixing time. Three key novelties in our algorithm are: (1) we carefully iterate our listing process with coupled values of min-degree within the clusters and arboricity outside the clusters, (2) all the listing is done within the cluster, which necessitates new techniques for bringing into the cluster the information about \emph{all} edges that can potentially form $K_p$ instances with the cluster edges, and (3) within each cluster we use a sparsity-aware listing algorithm, which is faster than a general listing algorithm and which we can allow the cluster to use since we make sure to sparsify the graph as the iterations proceed. As a byproduct of our algorithm, we show an \emph{optimal} sparsity-aware algorithm for $K_p$ listing, which runs in $\tilde{\Theta}(1 + m/n^{1 + 2/p})$ rounds in the \clique model. Previously, Pandurangan et al. [SPAA 2018], Chang et al. [SODA 2019], and Censor-Hillel et al. [TCS 2020] showed sparsity-aware algorithms for the case of $p = 3$, yet ours is the first such sparsity aware algorithm for $p \geq 4$. Comment: To appear in PODC 2020 |
Databáze: | OpenAIRE |
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