Polynomial Pass Semi-Streaming Lower Bounds for K-Cores and Degeneracy

May 23, 2024 Β· Declared Dead Β· πŸ› Cybersecurity and Cyberforensics Conference

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Authors Sepehr Assadi, Prantar Ghosh, Bruno Loff, Parth Mittal, Sagnik Mukhopadhyay arXiv ID 2405.14835 Category cs.DS: Data Structures & Algorithms Cross-listed cs.CC Citations 3 Venue Cybersecurity and Cyberforensics Conference Last Checked 4 months ago
Abstract
The following question arises naturally in the study of graph streaming algorithms: "Is there any graph problem which is "not too hard", in that it can be solved efficiently with total communication (nearly) linear in the number $n$ of vertices, and for which, nonetheless, any streaming algorithm with $\tilde{O}(n)$ space (i.e., a semi-streaming algorithm) needs a polynomial $n^{Ξ©(1)}$ number of passes?" Assadi, Chen, and Khanna [STOC 2019] were the first to prove that this is indeed the case. However, the lower bounds that they obtained are for rather non-standard graph problems. Our first main contribution is to present the first polynomial-pass lower bounds for natural "not too hard" graph problems studied previously in the streaming model: $k$-cores and degeneracy. We devise a novel communication protocol for both problems with near-linear communication, thus showing that $k$-cores and degeneracy are natural examples of "not too hard" problems. Indeed, previous work have developed single-pass semi-streaming algorithms for approximating these problems. In contrast, we prove that any semi-streaming algorithm for exactly solving these problems requires (almost) $Ξ©(n^{1/3})$ passes. Our second main contribution is improved round-communication lower bounds for the underlying communication problems at the basis of these reductions: * We improve the previous lower bound of Assadi, Chen, and Khanna for hidden pointer chasing (HPC) to achieve optimal bounds. * We observe that all current reductions from HPC can also work with a generalized version of this problem that we call MultiHPC, and prove an even stronger and optimal lower bound for this generalization. These two results collectively allow us to improve the resulting pass lower bounds for semi-streaming algorithms by a polynomial factor, namely, from $n^{1/5}$ to $n^{1/3}$ passes.
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