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Generalized Exact Scheduling: A Minimal-Variance Distributed Deadline Scheduler

Nakahira, Yorie and Ferragut, Andres and Wierman, Adam (2022) Generalized Exact Scheduling: A Minimal-Variance Distributed Deadline Scheduler. Operations Research . ISSN 0030-364X. doi:10.1287/opre.2021.2232. (In Press)

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Many modern schedulers can dynamically adjust their service capacity to match the incoming workload. At the same time, however, unpredictability and instability in service capacity often incur operational and infrastructural costs. In this paper, we seek to characterize optimal distributed algorithms that maximize the predictability, stability, or both when scheduling jobs with deadlines. Specifically, we show that Exact Scheduling minimizes both the stationary mean and variance of the service capacity subject to strict demand and deadline requirements. For more general settings, we characterize the minimal-variance distributed policies with soft demand requirements, soft deadline requirements, or both. The performance of the optimal distributed policies is compared with that of the optimal centralized policy by deriving closed-form bounds and by testing centralized and distributed algorithms using real data from the Caltech electrical vehicle charging facility and many pieces of synthetic data from different arrival distributions. Moreover, we derive the Pareto-optimality condition for distributed policies that balance the variance and mean square of the service capacity. Finally, we discuss a scalable partially centralized algorithm that uses centralized information to boost performance and a method to deal with missing information on service requirements.

Item Type:Article
Related URLs:
URLURL TypeDescription Paper
Nakahira, Yorie0000-0003-3324-4602
Ferragut, Andres0000-0003-0134-5548
Wierman, Adam0000-0002-5923-0199
Alternate Title:Minimal-Variance Distributed Deadline Scheduling
Additional Information:© 2022 INFORMS. Received: January 01, 2019; Accepted: October 14, 2021; Published Online: February 17, 2022.
Subject Keywords:Stochastic Models; deadline scheduling; service capacity control; exact scheduling; online distributed algorithm; optimal control; optimization
Record Number:CaltechAUTHORS:20201014-143948343
Persistent URL:
Official Citation:Yorie Nakahira, Andres Ferragut, Adam Wierman (2022) Generalized Exact Scheduling: A Minimal-Variance Distributed Deadline Scheduler. Operations Research 0(0).
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:106068
Deposited By: Tony Diaz
Deposited On:14 Oct 2020 21:45
Last Modified:28 Jun 2022 19:45

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