Contract Scheduling With Predictions

TL;DR

This paper explores contract scheduling with predictions, analyzing how to balance robustness against worst-case errors and consistency when predictions about interruptions are available, including scenarios with binary query responses.

Contribution

It introduces a framework for contract scheduling that incorporates predictions about interruptions, analyzing the tradeoffs between robustness and consistency in various prediction settings.

Findings

Identifies tradeoffs between robustness and consistency in contract scheduling with predictions.

Provides positive and negative results for different prediction accuracy scenarios.

Abstract

Contract scheduling is a general technique that allows to design a system with interruptible capabilities, given an algorithm that is not necessarily interruptible. Previous work on this topic has largely assumed that the interruption is a worst-case deadline that is unknown to the scheduler. In this work, we study the setting in which there is a potentially erroneous prediction concerning the interruption. Specifically, we consider the setting in which the prediction describes the time that the interruption occurs, as well as the setting in which the prediction is obtained as a response to a single or multiple binary queries. For both settings, we investigate tradeoffs between the robustness (i.e., the worst-case performance assuming adversarial prediction) and the consistency (i.e, the performance assuming that the prediction is error-free), both from the side of positive and negative results.