A Simpler Analysis for $\varepsilon$-Clairvoyant Flow Time Scheduling

TL;DR

This paper simplifies the proof of optimality for the SLF algorithm in minimizing total flow time within the $\varepsilon$-clairvoyant scheduling setting, enhancing understanding of its theoretical foundations.

Contribution

The paper provides a simplified proof of the optimality of the SLF algorithm for $\varepsilon$-clairvoyant flow time scheduling, clarifying its theoretical basis.

Findings

Simplified proof of SLF algorithm's optimality

Enhanced understanding of $\varepsilon$-clairvoyant scheduling

Theoretical validation of flow time minimization

Abstract

We simplify the proof of the optimality of the Shortest Lower-Bound First (SLF) algorithm, introduced by Gupta, Kaplan, Lindermayr, Schl\"oter, and Yingchareonthawornchai [FOCS'25], for minimizing the total flow time in the $\varepsilon$-clairvoyant setting.