Distributed Detection of Cycles

Author:

Fraigniaud Pierre1,Olivetti Dennis2

Affiliation:

1. CNRS and University Paris Diderot, Paris, France

2. Aalto University, Konemiehentie, Espoo, Finland

Abstract

Distributed property testing in networks has been introduced by Brakerski and Patt-Shamir [6], with the objective of detecting the presence of large dense sub-networks in a distributed manner. Recently, Censor-Hillel et al. [7] have revisited this notion and formalized it in a broader context. In particular, they have shown how to detect 3-cycles in a constant number of rounds by a distributed algorithm. In a follow-up work, Fraigniaud et al. [21] have shown how to detect 4-cycles in a constant number of rounds as well. However, the techniques in these latter works were shown not to generalize to larger cycles C k with k ≥ 5. In this article, we completely settle the problem of cycle detection by establishing the following result: For every k ≥ 3, there exists a distributed property testing algorithm for C k -freeness, performing in a constant number of rounds. All these results hold in the classical congest model for distributed network computing. Our algorithm is 1-sided error. Its round-complexity is O (1ϵ) where ϵ ∈ (0,1) is the property-testing parameter measuring the gap between legal and illegal instances.

Funder

Academy of Finland

Agence Nationale de la Recherche

Publisher

Association for Computing Machinery (ACM)

Subject

Computational Theory and Mathematics,Computer Science Applications,Hardware and Architecture,Modelling and Simulation,Software

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1. Local certification of graph decompositions and applications to minor-free classes;Journal of Parallel and Distributed Computing;2024-11

2. Deterministic near-optimal distributed listing of cliques;Distributed Computing;2024-06-20

3. Computing Minimum Weight Cycle in the CONGEST Model;Proceedings of the 43rd ACM Symposium on Principles of Distributed Computing;2024-06-17

4. Even-Cycle Detection in the Randomized and Quantum CONGEST Model;Proceedings of the 43rd ACM Symposium on Principles of Distributed Computing;2024-06-17

5. On the power of threshold-based algorithms for detecting cycles in the CONGEST model;Theoretical Computer Science;2024-05

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