Breaching the 2-approximation barrier for connectivity augmentation: a reduction to Steiner tree

The basic goal of survivable network design is to build a cheap network that maintains the connectivity between given sets of nodes despite the failure of a few edges/nodes. The Connectivity Augmentation Problem (CAP) is arguably one of the most basic problems in this area: given a k(-edge)-connected graph G and a set of extra edges (links), select a minimum cardinality subset A of links such that adding A to G increases its edge connectivity to k+1. Intuitively, one wants to make an existing network more reliable by augmenting it with extra edges. The best known approximation factor for this NP-hard problem is 2, and this can be achieved with multiple approaches (the first such result is in [Frederickson and Jájá’81]). It is known [Dinitz et al.’76] that CAP can be reduced to the case k=1, a.k.a. the Tree Augmentation Problem (TAP), for odd k, and to the case k=2, a.k.a. the Cactus Augmentation Problem (CacAP), for even k. Several better than 2 approximation algorithms are known for TAP, culminating with a recent 1.458 approximation [Grandoni et al.’18]. However, for CacAP the best known approximation is 2. In this paper we breach the 2 approximation barrier for CacAP, hence for CAP, by presenting a polynomial-time 2ln(4)−967/1120+є<1.91 approximation. From a technical point of view, our approach deviates quite substantially from the current related literature. In particular, the better-than-2 approximation algorithms for TAP either exploit greedy-style algorithms or are based on rounding carefully-designed LPs. These approaches exploit properties of TAP that do not seem to generalize to CacAP. We instead use a reduction to the Steiner tree problem which was previously used in parameterized algorithms [Basavaraju et al.’14]. This reduction is not approximation preserving, and using the current best approximation factor for Steiner tree [Byrka et al.’13] as a black-box would not be good enough to improve on 2. To achieve the latter goal, we “open the box” and exploit the specific properties of the instances of Steiner tree arising from CacAP. In our opinion this connection between approximation algorithms for survivable network design and Steiner-type problems is interesting, and it might lead to other results in the area.

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