Distortion-Oblivious Algorithms for Minimizing Flow Time
Yossi Azar, Stefano Leonardi, Noam Touitou
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 𝜇, an 𝑂 (𝜇 2 )-competitive algorithm ALG 𝜇 which handles distortions up to 𝜇 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 Õ (𝜇), which is a quadratic improvement over the algorithm from STOC 2021, and is nearly optimal (we show a randomized lower bound of Ω(𝜇) on competitiveness).
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 558b0918-78d6-448a-8331-5ccb3c6a78a7Cited by top-tier papers13
- Algorithms with Prediction PortfoliosMichael Dinitz, Sungjin Im, Thomas Lavastida, Benjamin Moseley et al.NeurIPS 2022 · 33 citations
- Sorting with PredictionsXingjian Bai, Christian CoesterNeurIPS 2023 · 29 citations
- Minimalistic Predictions to Schedule Jobs with Online Precedence ConstraintsAlexandra Anna Lassota, Alexander Lindermayr, Nicole Megow, Jens SchlöterICML 2023 · 17 citations
- Algorithms for Caching and MTS with reduced number of predictionsKarim Abdel Sadek, Marek EliásICLR 2024 · 10 citations
- Speed-Oblivious Online Scheduling: Knowing (Precise) Speeds is not NecessaryAlexander Lindermayr, Nicole Megow, Martin RappICML 2023 · 9 citations
Builds on3
- Learning Augmented Energy Minimization via Speed ScalingÉtienne Bamas, Andreas Maggiori, Lars Rohwedder, Ola SvenssonNeurIPS 2020 · 84 citations
- Online Scheduling via Learned WeightsSilvio Lattanzi, Thomas Lavastida, Benjamin Moseley, Sergei VassilvitskiiSODA 2020 · 83 citations
- Flow time scheduling with uncertain processing timeYossi Azar, Stefano Leonardi, Noam TouitouSTOC 2021
Related papers
- An Optimal Online Algorithm for Robust Flow Time SchedulingAnupam Gupta, Amit Kumar, Debmalya Panigrahi, Zhaozi WangSODA 2026 · 5 citations
- On Smoothness Bounds for Non-Clairvoyant Scheduling with PredictionsTianming Zhao, Albert ZomayaICLR 2026
- A Little Clairvoyance Is All You NeedAnupam Gupta, Haim Kaplan, Alexander Lindermayr, Jens Schlöter et al.FOCS 2025 · 5 citations
- Minimizing Completion Times for Stochastic Jobs via Batched Free TimesAnupam Gupta, Benjamin Moseley, Rudy ZhouSODA 2023 · 1 citation
- Online Duet between Metric Embeddings and Minimum-Weight Perfect MatchingsSujoy Bhore, Arnold Filtser, Csaba D. TóthSODA 2024 · 4 citations
