The Space Complexity of Sum Labelling
Henning Fernau, Kshitij Gajjar

TL;DR
This paper explores the computational complexity of sum graphs, providing bounds on label sizes for various graph classes and demonstrating polynomial-time label construction, significantly improving previous exponential bounds.
Contribution
It establishes polynomial-time methods for constructing sum graph labels with size bounds, improving upon prior exponential bounds and linking label size to graph properties.
Findings
Bound of O(n^2d) on label size for d-degenerate graphs
Sum graph label construction is polynomial-time
For sparse graphs, label size matches lower bounds
Abstract
A graph is called a sum graph if its vertices can be labelled by distinct positive integers such that there is an edge between two vertices if and only if the sum of their labels is the label of another vertex of the graph. Most papers on sum graphs consider combinatorial questions like the minimum number of isolated vertices that need to be added to a given graph to make it a sum graph. In this paper, we initiate the study of sum graphs from the viewpoint of computational complexity. Notice that every -vertex sum graph can be represented by a sorted list of positive integers where edge queries can be answered in time. Therefore, limiting the size of the vertex labels also upper-bounds the space complexity of storing the graph in the database. We show that every -vertex, -edge, -degenerate graph can be made a sum graph by adding at most isolated…
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Taxonomy
TopicsGraph Labeling and Dimension Problems · Digital Image Processing Techniques · Data Management and Algorithms
