DMCOJul 4, 2024

Optimal local identifying and local locating-dominating codes

arXiv:2302.13351h-index: 20
Originality Incremental advance
AI Analysis

This work provides foundational results for a new class of covering codes, offering tight bounds and optimal constructions that show negligible cost for localizing identifying codes in hypercubes.

The paper introduces local r-identifying and local r-locating-dominating codes, derives asymptotically tight bounds for optimal local 1-identifying codes in binary hypercubes, and determines optimal densities for these codes in several infinite grids, with seven out of eight constructions proven optimal.

We introduce two new classes of covering codes in graphs for every positive integer $r$. These new codes are called local $r$-identifying and local $r$-locating-dominating codes and they are derived from $r$-identifying and $r$-locating-dominating codes, respectively. We study the sizes of optimal local 1-identifying codes in binary hypercubes. We obtain lower and upper bounds that are asymptotically tight. Together the bounds show that the cost of changing covering codes into local 1-identifying codes is negligible. For some small $n$ optimal constructions are obtained. Moreover, the upper bound is obtained by a linear code construction. Also, we study the densities of optimal local 1-identifying codes and local 1-locating-dominating codes in the infinite square grid, the hexagonal grid, the triangular grid, and the king grid. We prove that seven out of eight of our constructions have optimal densities.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes