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The Space Complexity of Sum Labelling
H. Fernau,
Published in Springer Science and Business Media Deutschland GmbH
2021
Volume: 12867 LNCS
   
Pages: 230 - 244
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. Note that every n-vertex sum graph can be represented by a sorted list of n positive integers where edge queries can be answered in O(log n) time. Thus, limiting the size of the vertex labels upper-bounds the space complexity of storing the graph. We show that every n-vertex, m-edge, d-degenerate graph can be made a sum graph by adding at most m isolated vertices to it such that the size of each vertex label is at most O(n2d). This enables us to store the graph using O(mlog n) bits of memory. For sparse graphs (graphs with O(n) edges), this matches the trivial lower bound of Ω(nlog n). Since planar graphs and forests have constant degeneracy, our result implies an upper bound of O(n2) on their label size. The previously best known upper bound on the label size of general graphs with the minimum number of isolated vertices was O(4n), due to Kratochvíl, Miller & Nguyen [23]. Furthermore, their proof was existential whereas our labelling can be constructed in polynomial time. © 2021, Springer Nature Switzerland AG.
About the journal
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Science and Business Media Deutschland GmbH
ISSN03029743