← 研踪 PaperTrailarXiv:2608.19096 · v2
Approximating Minimum Dominating Set with Few Awake Rounds
首次提交 2026-08-20 00:45
版本更新 2026-11-10 04:16
雷达观测 2026-11-11 11:04
摘要
We study the Minimum Dominating Set (MDS) problem in the sleeping CONGEST model (Chatterjee, Gmyr, and Pandurangan, PODC 2020), a generalization of the standard CONGEST model, in which a node may sleep in some rounds and can only compute, send messages, or receive messages when it is awake. The awake complexity of an algorithm in this model is the worst case number (over all inputs and all nodes) of rounds a node is awake for during the execution of the algorithm. While there are several -approximation algorithms (in expectation) for MDS that run in rounds, all of these have awake complexity. Whether this awake complexity can be improved is the question that drives our work. We present the first -approximation algorithm for MDS with awake complexity. The approximation guarantee holds in expectation, and the algorithm runs in rounds. We can reduce the awake complexity further, but at the cost of approximation: we present, for any , an algorithm in the sleeping CONGEST model that computes an -approximate dominating set in expectation in rounds with awake complexity. Our results depend on a generalization of the CONGEST model Set Cover algorithm of Grunau, Mitrović, Rubinfeld, and Vakilian (SODA 2020) that we develop. This generalization computes an -approximate dominating set in rounds for parameters . Our sleeping CONGEST algorithms apply a variety of techniques including sampling-based estimation and scheduling using virtual binary trees to the aforementioned 2-parameter Set Cover algorithm.
作者备注:Full version of the conference paper published in the proceedings of the 40th International Symposium on Distributed Computing (DISC 2026)
期刊信息:DISC 2026, LIPIcs 397, 53:1-53:21 (2026)
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v2 · 2026-11-10 04:16 · 最新观测版本
Approximating Minimum Dominating Set with Few Awake Rounds
We study the Minimum Dominating Set (MDS) problem in the sleeping CONGEST model (Chatterjee, Gmyr, and Pandurangan, PODC 2020), a generalization of the standard CONGEST model, in which a node may sleep in some rounds and can only compute, send messages, or receive messages when it is awake. The awake complexity of an algorithm in this model is the worst case number (over all inputs and all nodes) of rounds a node is awake for during the execution of the algorithm. While there are several -approximation algorithms (in expectation) for MDS that run in rounds, all of these have awake complexity. Whether this awake complexity can be improved is the question that drives our work. We present the first -approximation algorithm for MDS with awake complexity. The approximation guarantee holds in expectation, and the algorithm runs in rounds. We can reduce the awake complexity further, but at the cost of approximation: we present, for any , an algorithm in the sleeping CONGEST model that computes an -approximate dominating set in expectation in rounds with awake complexity. Our results depend on a generalization of the CONGEST model Set Cover algorithm of Grunau, Mitrović, Rubinfeld, and Vakilian (SODA 2020) that we develop. This generalization computes an -approximate dominating set in rounds for parameters . Our sleeping CONGEST algorithms apply a variety of techniques including sampling-based estimation and scheduling using virtual binary trees to the aforementioned 2-parameter Set Cover algorithm.
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