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Design of Self-Stabilizing Approximation Algorithms via a Primal-Dual Approach

Authors Yuval Emek, Yuval Gil, Noga Harlev

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Author Details

Yuval Emek
  • Technion - Israel Institute of Technology, Haifa, Israel
Yuval Gil
  • Technion - Israel Institute of Technology, Haifa, Israel
Noga Harlev
  • Technion - Israel Institute of Technology, Haifa, Israel

Funding

This research was supported by VATAT Fund to the Technion Artificial Intelligence Hub (Tech.AI).

Acknowledgements

We thank Laurent Feuilloley for a helpful and insightful discussion.

Cite AsGet BibTex

Yuval Emek, Yuval Gil, and Noga Harlev. Design of Self-Stabilizing Approximation Algorithms via a Primal-Dual Approach. In 26th International Conference on Principles of Distributed Systems (OPODIS 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 253, pp. 27:1-27:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)
https://doi.org/10.4230/LIPIcs.OPODIS.2022.27

Abstract

Self-stabilization is an important concept in the realm of fault-tolerant distributed computing. In this paper, we propose a new approach that relies on the properties of linear programming duality to obtain self-stabilizing approximation algorithms for distributed graph optimization problems. The power of this new approach is demonstrated by the following results: - A self-stabilizing 2(1+ε)-approximation algorithm for minimum weight vertex cover that converges in O(logΔ /(εlog log Δ)) synchronous rounds. - A self-stabilizing Δ-approximation algorithm for maximum weight independent set that converges in O(Δ+log^* n) synchronous rounds. - A self-stabilizing ((2ρ+1)(1+ε))-approximation algorithm for minimum weight dominating set in ρ-arboricity graphs that converges in O((logΔ)/ε) synchronous rounds. In all of the above, Δ denotes the maximum degree. Our technique improves upon previous results in terms of time complexity while incurring only an additive O(log n) overhead to the message size. In addition, to the best of our knowledge, we provide the first self-stabilizing algorithms for the weighted versions of minimum vertex cover and maximum independent set.

Subject Classification

ACM Subject Classification
  • Theory of computation → Approximation algorithms analysis
  • Theory of computation → Distributed algorithms
Keywords
  • self-stabilization
  • approximation algorithms
  • primal-dual

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