The Study of Distance-Labelings for Cycle Graphs

Authors

  • Alissa Shen St. Stephen’s Episcopal School, Austin, Texas, USA.
  • Jian Shen Department of Mathematics, Texas State University, San Marcos, Texas, USA.

DOI:

https://doi.org/10.9734/bpi/rhmcs/v9/4690C

Keywords:

Graph, graph theory, channel assignment, distance labeling, cycle graph, neuroscience, neuronal pathway

Abstract

Let G = (V, E) be a graph and Cm be the cycle graph with m vertices. In this chapter, we continued Yeh’s work [1] on the distance labeling of the cycle graph Cm . An n-set distance labeling of a graph G is the labeling of the vertices (with n labels per vertex) of G under certain constraints determined by the distance between each pair of vertices in G. Following Yeh’s notation [1], the smallest value for the largest label in an n-set distance labeling of G is denoted by \(\lambda\)1(n) (G) The basic findings were given in [1] for \(\lambda\)1(2) (Cm) for all m and \(\lambda\)1(n) (Cm) for some m where n \(\ge\) 3. However, due to case-by-case difficulties, there were still gaps that remained unstudied.  For these uncovered cases, we proved a lower bound for \(\lambda\)1(n) (Cm). Then we developed an algorithm for finding an n-set distance labeling for n \(\ge\) 3 based on our proof of the lower bound. We verified every single case for n = 3 up to n = 500 by this same algorithm, which revealed that the upper bound is the same as the lower bound for n \(\le\) 500. Potential future research application is briefly discussed at the end of this paper.

Published

2023-04-22

How to Cite

Alissa Shen, & Jian Shen. (2023). The Study of Distance-Labelings for Cycle Graphs. Research Highlights in Mathematics and Computer Science Vol. 9, 172–188. https://doi.org/10.9734/bpi/rhmcs/v9/4690C