Fully dynamic $3/2$ approximate maximum cardinality matching in $O(\sqrt{n})$ update time

TL;DR

This paper introduces a randomized fully dynamic algorithm that maintains a 3/2-approximate maximum matching with expected amortized update time of O(√n), improving efficiency for large graphs and ensuring no short augmenting paths.

Contribution

The paper presents the first algorithm achieving a 3/2-approximate maximum matching with all augmenting paths of length at least 5 in sublinear update time.

Findings

Expected amortized update time is O(√n).

Total update time is O(t√n) in expectation.

Algorithm guarantees no short augmenting paths of length less than 5.

Abstract

We present a randomized algorithm to maintain a maximal matching without 3 length augmenting paths in the fully dynamic setting. Consequently, we maintain a $3/2$ approximate maximum cardinality matching. Our algorithm takes expected amortized $O(\sqrt{n})$ time where $n$ is the number of vertices in the graph when the update sequence is generated by an oblivious adversary. Over any sequence of $t$ edge insertions and deletions presented by an oblivious adversary, the total update time of our algorithm is $O(t\sqrt{n})$ in expectation and $O(t\sqrt{n} + n \log n)$ with high probability. To the best of our knowledge, our algorithm is the first one to maintain an approximate matching in which all augmenting paths are of length at least $5$ in $o(\sqrt{m})$ update time.