Efficient Maintenance of Minimum Spanning Trees in Dynamic Weighted Undirected Graphs

Author:

Luo Mao1,Qin Huigang1,Wu Xinyun1,Xiong Caiquan1,Xia Dahai1,Ke Yuanzhi1ORCID

Affiliation:

1. School of Computer Science, Hubei University of Technology, Wuhan 430068, China

Abstract

This paper presents an algorithm for effectively maintaining the minimum spanning tree in dynamic weighted undirected graphs. The algorithm efficiently updates the minimum spanning tree when the underlying graph structure changes. By identifying the portion of the original tree that can be preserved in the updated tree, our algorithm avoids recalculating the minimum spanning tree from scratch. We provide proof of correctness for the proposed algorithm and analyze its time complexity. In general scenarios, the time complexity of our algorithm is comparable to that of Kruskal’s algorithm. However, the experimental results demonstrate that our algorithm outperforms the approach of recomputing the minimum spanning tree by using Kruskal’s algorithm, especially in medium- and large-scale dynamic graphs where the graph undergoes iterative changes.

Funder

National Natural Science Foundation of China

Science and Technology Research Program of Hubei Province

Publisher

MDPI AG

Reference28 articles.

1. The origins of minimal spanning tree algorithms—Boruvka and Jarník;Nesetril;Doc. Math.,2012

2. CciMST: A clustering algorithm based on minimum spanning tree and cluster centers;Lv;Math. Probl. Eng.,2018

3. Discovering local outliers using dynamic minimum spanning tree with self-detection of best number of clusters;Peter;Int. J. Comput. Appl.,2010

4. OCmst: One-class novelty detection using convolutional neural network and minimum spanning trees;Gallo;Pattern Recognit. Lett.,2022

5. Construction of minimum spanning trees from financial returns using rank correlation;Millington;Phys. A Stat. Mech. Its Appl.,2021

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