Efficient Contractions of Dynamic Graphs -- with Applications

A non-trivial minimum cut (NMC) sparsifier is a multigraph G that preserves all non-trivial minimum cuts of a given undirected graph G. We introduce a flexible data structure for fully dynamic graphs that can efficiently provide an NMC sparsifier upon request at any point during the sequence of updates. We employ simple dynamic forest data structures to achieve a fast from-scratch construction of the sparsifier at query time. Based on the strength of the adversary and desired type of time bounds, the data structure comes with different guarantees. Specifically, let G be a fully dynamic simple graph with n vertices and minimum degree δ. Then our data structure supports an insertion/deletion of an edge to/from G in n^o (1) worst-case time. Furthermore, upon request, it can return w. h. p. an NMC sparsifier of G that has O (n/δ) vertices and O (n) edges, in O (n) time. The probabilistic guarantees hold against an adaptive adversary. Alternatively, the update and query times can be improved to O (1) and O (n) respectively, if amortized-time guarantees are sufficient, or if the adversary is oblivious. We discuss two applications of our data structure. First, it can be used to efficiently report a cactus representation of all minimum cuts of a fully dynamic simple graph. Using the NMC sparsifier we can w. h. p. build this cactus in worst-case time O (n) against an adaptive adversary. Second, our data structure allows us to efficiently compute the maximal k-edge-connected subgraphs of undirected simple graphs, by repeatedly applying a minimum cut algorithm on the NMC sparsifier. Specifically, we can compute w. h. p. the maximal k-edge-connected subgraphs of a simple graph with n vertices and m edges in O (m+n²/k) time which is an improvement for k = Ω (n^1/8) and works for fully dynamic graphs.