Fully-dynamic minimum spanning forest with improved worst-case update time

We give a Las Vegas data structure which maintains a minimum spanning forest in an n-vertex edge-weighted undirected dynamic graph undergoing updates consisting of any mixture of edge insertions and deletions. Each update is supported in O(n1/2 - c) worst-case time w.h.p. where c > 0 is some constant, and this bound also holds in expectation. This is the first data structure achieving an improvement over the O(√n) deterministic worst-case update time of Eppstein et al., a bound that has been standing for 25 years. In fact, it was previously not even known how to maintain a spanning forest of an unweighted graph in worst-case time polynomially faster than Θ(√n). Our result is achieved by first giving a reduction from fully-dynamic to decremental minimum spanning forest preserving worst-case update time up to logarithmic factors. Then decremental minimum spanning forest is solved using several novel techniques, one of which involves keeping track of low-conductance cuts in a dynamic graph. An immediate corollary of our result is the first Las Vegas data structure for fully-dynamic connectivity where each update is handled in worst-case time polynomially faster than Θ(√n) w.h.p.; this data structure has O(1) worst-case query time.

[1]  HolmJacob,et al.  Poly-logarithmic deterministic fully-dynamic algorithms for connectivity, minimum spanning tree, 2-edge, and biconnectivity , 2001 .

[2]  Greg N. Frederickson,et al.  Data Structures for On-Line Updating of Minimum Spanning Trees, with Applications , 1985, SIAM J. Comput..

[3]  Bruce M. Kapron,et al.  Dynamic graph connectivity with improved worst case update time and sublinear space , 2015, ArXiv.

[4]  David Eppstein,et al.  Sparsification—a technique for speeding up dynamic graph algorithms , 1997, JACM.

[5]  Thatchaphol Saranurak,et al.  Dynamic spanning forest with worst-case update time: adaptive, Las Vegas, and O(n1/2 - ε)-time , 2017, STOC.

[6]  Bruce M. Kapron,et al.  Dynamic graph connectivity in polylogarithmic worst case time , 2013, SODA.

[7]  Monika Henzinger,et al.  Maintaining Minimum Spanning Trees in Dynamic Graphs , 1997, ICALP.

[8]  Philip N. Klein,et al.  A randomized linear-time algorithm to find minimum spanning trees , 1995, JACM.

[9]  Erik D. Demaine,et al.  Logarithmic Lower Bounds in the Cell-Probe Model , 2005, SIAM J. Comput..

[10]  Christian Wulff-Nilsen,et al.  Faster Fully-Dynamic Minimum Spanning Forest , 2014, ESA.

[11]  Mark H. Overmars,et al.  A balanced search tree with O(1) worst-case update time , 1988, Acta Informatica.

[12]  Shang-Hua Teng,et al.  Nearly-linear time algorithms for graph partitioning, graph sparsification, and solving linear systems , 2003, STOC '04.

[13]  Bernard Chazelle,et al.  A minimum spanning tree algorithm with inverse-Ackermann type complexity , 2000, JACM.

[14]  David R. Karger,et al.  Random sampling in cut, flow, and network design problems , 1994, STOC '94.

[15]  Mikkel Thorup,et al.  Poly-logarithmic deterministic fully-dynamic algorithms for connectivity, minimum spanning tree, 2-edge, and biconnectivity , 2001, JACM.

[16]  Mikkel Thorup,et al.  Faster Worst Case Deterministic Dynamic Connectivity , 2016, ESA.

[17]  Mikkel Thorup,et al.  Maintaining information in fully dynamic trees with top trees , 2003, TALG.

[18]  David Eppstein,et al.  Sparsification-a technique for speeding up dynamic graph algorithms , 1992, Proceedings., 33rd Annual Symposium on Foundations of Computer Science.

[19]  Valerie King,et al.  Fully Dynamic 2-Edge Connectivity Algorithm in Polylogarithmic Time per Operation , 1997 .

[20]  Ken-ichi Kawarabayashi,et al.  Deterministic Global Minimum Cut of a Simple Graph in Near-Linear Time , 2014, STOC.