On the Complexity of Community-aware Network Sparsification

Abstract

Network sparsification is the task of reducing the number of edges of a given graph while preserving some crucial graph property. In community-aware network sparsification, the preserved property concerns the subgraphs that are induced by the communities of the graph which are given as vertex subsets. This is formalized in the -Network Sparsification problem: given an edge-weighted graph G, a collection Z of c subsets of V(G) (communities), and two numbers , b, the question is whether there exists a spanning subgraph G' of G with at most edges of total weight at most b such that G'[C] fulfills for each community C. Here, we consider two graph properties : the connectivity property (Connectivity NWS) and the property of having a spanning star (Stars NWS). Since both problems are NP-hard, we study their parameterized and fine-grained complexity. We provide a tight 2(n2+c) poly(n+|Z|)-time running time lower bound based on the ETH for both problems, where n is the number of vertices in G. The lower bound holds even in the restricted case when all communities have size at most 4, G is a clique, and every edge has unit weight. For the connectivity property, the unit weight case with G being a clique is the well-studied problem of computing a hypergraph support with a minimum number of edges. We then study the complexity of both problems parameterized by the feedback edge number t of the solution graph G'. For Stars NWS, we present an XP-algorithm for t. This answers an open question by Korach and Stern [Disc. Appl. Math. '08] who asked for the existence of polynomial-time algorithms for t=0. In contrast, we show for Connectivity NWS that known polynomial-time algorithms for t=0 [Korach and Stern, Math. Program. '03; Klemz et al., SWAT '14] cannot be extended by showing that Connectivity NWS is NP-hard for t=1.

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