Contract Scheduling With Predictions
This work addresses the problem of improving contract scheduling efficiency for systems requiring interruptible capabilities, particularly for scenarios where some predictive information about interruptions might be available.
This paper explores contract scheduling when an erroneous prediction about interruption time is available, rather than assuming a worst-case unknown deadline. The authors investigate the trade-offs between robustness (performance with adversarial prediction) and consistency (performance with error-free prediction) for two prediction settings: a direct time prediction and predictions from binary queries.
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.