eng
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Leibniz International Proceedings in Informatics
1868-8969
2021-03-11
6:1
6:23
10.4230/LIPIcs.ICDT.2021.6
article
Towards Optimal Dynamic Indexes for Approximate (and Exact) Triangle Counting
Lu, Shangqi
1
Tao, Yufei
1
The Chinese University of Hong Kong, China
In ICDT'19, Kara, Ngo, Nikolic, Olteanu, and Zhang gave a structure which maintains the number T of triangles in an undirected graph G = (V, E) along with the edge insertions/deletions in G. Using O(m) space (m = |E|), their structure supports an update in O(√m log m) amortized time which is optimal (up to polylog factors) subject to the OMv-conjecture (Henzinger, Krinninger, Nanongkai, and Saranurak, STOC'15). Aiming to improve the update efficiency, we study:
- the optimal tradeoff between update time and approximation quality. We require a structure to provide the (ε, Γ)-guarantee: when queried, it should return an estimate t of T that has relative error at most ε if T ≥ Γ, or an absolute error at most ε ⋅ Γ, otherwise. We prove that, under any ε ≤ 0.49 and subject to the OMv-conjecture, no structure can guarantee O(m^{0.5-δ}/Γ) expected amortized update time and O(m^{2/3-δ}) query time simultaneously for any constant δ > 0; this is true for Γ = m^c of any constant c in [0, 1/2). We match the lower bound with a structure that ensures Õ((1/ε)³ ⋅ √m/Γ) amortized update time with high probability, and O(1) query time.
- (for exact counting) how to achieve arboricity-sensitive update time. For any 1 ≤ Γ ≤ √m, we describe a structure of O(min{α m + m log m, (m/Γ)²}) space that maintains T precisely, and supports an update in Õ(min{α + Γ, √m}) amortized time, where α is the largest arboricity of G in history (and does not need to be known). Our structure reconstructs the aforementioned ICDT'19 result up to polylog factors by setting Γ = √m, but achieves Õ(m^{0.5-δ}) update time as long as α = O(m^{0.5-δ}).
https://drops.dagstuhl.de/storage/00lipics/lipics-vol186-icdt2021/LIPIcs.ICDT.2021.6/LIPIcs.ICDT.2021.6.pdf
Triangle Counting
Data Structures
Lower Bounds
Graph Algorithms