Random Rank-Based, Hierarchical or Trivial: Which Dynamic Graph Algorithm Performs Best in Practice?

Abstract

Fully dynamic graph algorithms that achieve polylogarithmic or better time per operation use either a hierarchical graph decomposition or random-rank based approach. There are so far two graph properties for which efficient algorithms for both types of data structures exist, namely fully dynamic (Delta + 1) coloring and fully dynamic maximal matching. In this paper we present an extensive experimental study of these two types of algorithms for these two problems together with very simple baseline algorithms to determine which of these algorithms are the fastest. Our results indicate that the data structures used by the different algorithms dominate their performance.

References in corpus (5)

• Hyperbolic Geometry of Complex Networks
• Unifying and Strengthening Hardness for Dynamic Problems via the Online Matrix-Vector Multiplication Conjecture
• Fully Dynamic $(\Delta +1)$-Coloring in Constant Update Time
• Recent Advances in Fully Dynamic Graph Algorithms
• Constant-Time Dynamic Weight Approximation for Minimum Spanning Forest