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Fast deterministic algorithms for computing all eccentricities in (hyperbolic) Helly graphs
- Source :
- Algorithms and Data Structures 17th International Symposium, WADS 2021, Virtual Event, August 9–11, 2021, Proceedings, Algorithms and Data Structures 17th International Symposium (WADS 2021), Algorithms and Data Structures 17th International Symposium (WADS 2021), Aug 2021, Halifax, Nova Scotia (Virtual Event), Canada. pp.300-314, ⟨10.1007/978-3-030-83508-8_22⟩, Lecture Notes in Computer Science ISBN: 9783030835071, WADS
- Publication Year :
- 2021
- Publisher :
- HAL CCSD, 2021.
-
Abstract
- A graph is Helly if every family of pairwise intersecting balls has a nonempty common intersection. The class of Helly graphs is the discrete analogue of the class of hyperconvex metric spaces. It is also known that every graph isometrically embeds into a Helly graph, making the latter an important class of graphs in Metric Graph Theory. We study diameter, radius and all eccentricity computations within the Helly graphs. Under plausible complexity assumptions, neither the diameter nor the radius can be computed in truly subquadratic time on general graphs. In contrast to these negative results, it was recently shown that the radius and the diameter of an n-vertex m-edge Helly graph G can be computed with high probability in \(\tilde{\mathcal O}(m\sqrt{n})\) time (i.e., subquadratic in \(n+m\)). In this paper, we improve that result by presenting a deterministic \({\mathcal O}(m\sqrt{n})\) time algorithm which computes not only the radius and the diameter but also all vertex eccentricities in a Helly graph. Furthermore, we give a parameterized linear-time algorithm for this problem on Helly graphs, with the parameter being the Gromov hyperbolicity \(\delta \). More specifically, we show that the radius and a central vertex of an m-edge \(\delta \)-hyperbolic Helly graph G can be computed in \(\mathcal O(\delta m)\) time and that all vertex eccentricities in G can be computed in \(\mathcal O(\delta ^2 m)\) time. To show this more general result, we heavily use our new structural properties obtained for Helly graphs.
- Subjects :
- Vertex (graph theory)
FOS: Computer and information sciences
[INFO.INFO-CC]Computer Science [cs]/Computational Complexity [cs.CC]
Discrete Mathematics (cs.DM)
[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]
Parameterized complexity
[INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS]
0102 computer and information sciences
Computer Science::Computational Geometry
01 natural sciences
Intersection
Computer Science::Discrete Mathematics
Computer Science - Data Structures and Algorithms
Mathematics::Metric Geometry
Data Structures and Algorithms (cs.DS)
0101 mathematics
Mathematics
010102 general mathematics
Graph theory
Radius
Metric space
010201 computation theory & mathematics
Metric (mathematics)
Eccentricity (mathematics)
Algorithm
Computer Science - Discrete Mathematics
Subjects
Details
- Language :
- English
- ISBN :
- 978-3-030-83507-1
- ISBNs :
- 9783030835071
- Database :
- OpenAIRE
- Journal :
- Algorithms and Data Structures 17th International Symposium, WADS 2021, Virtual Event, August 9–11, 2021, Proceedings, Algorithms and Data Structures 17th International Symposium (WADS 2021), Algorithms and Data Structures 17th International Symposium (WADS 2021), Aug 2021, Halifax, Nova Scotia (Virtual Event), Canada. pp.300-314, ⟨10.1007/978-3-030-83508-8_22⟩, Lecture Notes in Computer Science ISBN: 9783030835071, WADS
- Accession number :
- edsair.doi.dedup.....0ff2b106242632dc8d7412040f59fbeb
- Full Text :
- https://doi.org/10.1007/978-3-030-83508-8_22⟩