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Engineering Edge Orientation Algorithms

Authors Henrik Reinstädtler , Christian Schulz , Bora Uçar

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Author Details

Henrik Reinstädtler
  • Heidelberg University, Germany
Christian Schulz
  • Heidelberg University, Germany
Bora Uçar
  • CNRS and LIP, ENS de Lyon, France
  • UMR5668 (CNRS, ENS de Lyon, Inria, UCBL1), France

Funding

We acknowledge support by DFG grant SCHU 2567/3-1. The authors acknowledge support by the state of Baden-Württemberg through bwHPC.

Cite AsGet BibTex

Henrik Reinstädtler, Christian Schulz, and Bora Uçar. Engineering Edge Orientation Algorithms. In 32nd Annual European Symposium on Algorithms (ESA 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 308, pp. 97:1-97:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)
https://doi.org/10.4230/LIPIcs.ESA.2024.97

Abstract

Given an undirected graph G, the edge orientation problem asks for assigning a direction to each edge to convert G into a directed graph. The aim is to minimize the maximum out-degree of a vertex in the resulting directed graph. This problem, which is solvable in polynomial time, arises in many applications. An ongoing challenge in edge orientation algorithms is their scalability, particularly in handling large-scale networks with millions or billions of edges efficiently. We propose a novel algorithmic framework based on finding and manipulating simple paths to face this challenge. Our framework is based on an existing algorithm and allows many algorithmic choices. By carefully exploring these choices and engineering the underlying algorithms, we obtain an implementation which is more efficient and scalable than the current state-of-the-art. Our experiments demonstrate significant performance improvements compared to state-of-the-art solvers. On average our algorithm is 6.59 times faster when compared to the state-of-the-art.

Subject Classification

ACM Subject Classification
  • Theory of computation → Design and analysis of algorithms
Keywords
  • edge orientation
  • pseudoarboricity
  • graph algorithms

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