Improved distributed approximation for Steiner tree in the CONGEST model

Saikia, Parikshit; Karmakar, Sushanta

doi:10.1016/j.jpdc.2021.08.004

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“…Siebert et al (2020) present a set of integer programmings for the Steiner tree problem with the property that the best solution is obtained by solving all, and provide an optimal Steiner tree. Saikia and Karmakar (2021) present two deterministic distributed algorithms for the Steiner tree problem in the congest model, both of which improve the previous complexity of distributed algorithms for the STP.…”

Section: Related Workmentioning

confidence: 92%

Truthful Mechanisms for Steiner Tree Problems

Zhang

Liu

Deng

et al. 2023

AAAI

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Consider an undirected graph G=(V,E) model for a communication network, where each edge is owned by a selfish agent, who reports the cost for offering the use of her edge. Note that each edge agent may misreport her own cost for the use of the edge for her own benefit. In such a non-cooperative setting, we aim at designing an approximately truthful mechanism for establishing a Steiner tree, a minimum cost tree spanning over all the terminals. We present a truthful-in-expectation mechanism that achieves the approximation ratio ln 4 + ε ≈ 1.39, which matches the current best algorithmic ratio for STP.

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Section: Related Workmentioning

confidence: 92%