Distortion-Oblivious Algorithms for Minimizing Flow Time

Yossi Azar, Stefano Leonardi, Noam Touitou

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


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 ~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).

Original languageEnglish
Title of host publicationACM-SIAM Symposium on Discrete Algorithms, SODA 2022
PublisherAssociation for Computing Machinery
Number of pages23
ISBN (Electronic)9781611977073
StatePublished - 2022
Event33rd Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2022 - Alexander, United States
Duration: 9 Jan 202212 Jan 2022

Publication series

NameProceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms


Conference33rd Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2022
Country/TerritoryUnited States


Dive into the research topics of 'Distortion-Oblivious Algorithms for Minimizing Flow Time'. Together they form a unique fingerprint.

Cite this