@inproceedings{1c4e459b6e564e0f8af66b818bed1fef,
title = "Distortion-Oblivious Algorithms for Minimizing Flow Time",
abstract = "We consider the classic online problem of scheduling on a single machine to minimize total flow time. In STOC 2021, the concept of robustness to distortion in processing times was introduced: for every distortion factor, an 12o-competitive algorithm ALG which handles distortions up to was presented. However, using that result requires one to know the distortion of the input in advance, which is impractical. We present the first distortion-oblivious algorithms: algorithms which are competitive for every input of every distortion, and thus do not require knowledge of the distortion in advance. Moreover, the competitive ratios of our algorithms are \textasciitilde{}1o, which is a quadratic improvement over the algorithm from STOC 2021, and is nearly optimal (we show a randomized lower bound of O1o on competitiveness).",
author = "Yossi Azar and Stefano Leonardi and Noam Touitou",
note = "Publisher Copyright: Copyright {\textcopyright} 2022 by SIAM Unauthorized reproduction of this article is prohibited.; 33rd Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2022 ; Conference date: 09-01-2022 Through 12-01-2022",
year = "2022",
language = "الإنجليزيّة",
series = "Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms",
publisher = "Association for Computing Machinery",
pages = "252--274",
booktitle = "ACM-SIAM Symposium on Discrete Algorithms, SODA 2022",
address = "الولايات المتّحدة",
}