How the Degeneracy Helps for Triangle Counting in Graph Streams

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Abstract

We revisit the well-studied problem of triangle count estimation in graph streams. Given a graph represented as a stream of m edges, our aim is to compute a (1+-ϵ)-approximation to the triangle count T, using a small space algorithm. For arbitrary order and a constant number of passes, the space complexity is known to be essentially (min(m3/2 /T, m/ĝT)) (McGregor et al., PODS 2016, Bera et al., STACS 2017). We give a (constant pass, arbitrary order) streaming algorithm that can circumvent this lower bound for low degeneracy graphs. The degeneracy, K, is a nuanced measure of density, and the class of constant degeneracy graphs is immensely rich (containing planar graphs, minor-closed families, and preferential attachment graphs). We design a streaming algorithm with space complexity ∼O(mK/T). For constant degeneracy graphs, this bound is ∼O(m/T), which is significantly smaller than both m3/2 /T and m/ĝT. We complement our algorithmic result with a nearly matching lower bound of ω(mK/T).

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Bera, S. K., & Seshadhri, C. (2020). How the Degeneracy Helps for Triangle Counting in Graph Streams. In Proceedings of the ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems (pp. 457–467). Association for Computing Machinery. https://doi.org/10.1145/3375395.3387665

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