Hardness of Peeling with Stashes

TL;DR

This paper investigates the computational complexity of optimizing stash-based modifications in hypergraph peeling processes, revealing NP-completeness results and polynomial-time solvability in specific cases relevant to hashing applications.

Contribution

It establishes the NP-completeness of minimizing stashed edges or vertices in hypergraph peeling, except for a special case where the problem is polynomial-time solvable.

Findings

NP-complete for all k ≥ 2 on graphs and hypergraphs

Edge stashing is polynomial-time solvable for k=2 on 2-uniform graphs

Provides complexity boundaries for stash optimization in hypergraph peeling

Abstract

The analysis of several algorithms and data structures can be framed as a peeling process on a random hypergraph: vertices with degree less than k and their adjacent edges are removed until no vertices of degree less than k are left. Often the question is whether the remaining hypergraph, the k-core, is empty or not. In some settings, it may be possible to remove either vertices or edges from the hypergraph before peeling, at some cost. For example, in hashing applications where keys correspond to edges and buckets to vertices, one might use an additional side data structure, commonly referred to as a stash, to separately handle some keys in order to avoid collisions. The natural question in such cases is to find the minimum number of edges (or vertices) that need to be stashed in order to realize an empty k-core. We show that both these problems are NP-complete for all $k \geq 2$ on graphs and regular hypergraphs, with the sole exception being that the edge variant of stashing is solvable in polynomial time for $k = 2$ on standard (2-uniform) graphs.