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Asymptotic Analysis of Probabilistic Scheduling for Erasure-Coded Heterogeneous Systems

Jinan, R and Gautam, G and Parag, P and Aggarwal, V (2023) Asymptotic Analysis of Probabilistic Scheduling for Erasure-Coded Heterogeneous Systems. In: Performance Evaluation Review, 50 (4). pp. 8-10.

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Official URL: https://doi.org/10.1145/3595244.3595248


We consider (k, k) fork-join scheduling on a large number (say, N) of parallel servers with two sets of heterogeneous rates. An incoming task is split into k sub-tasks and dispatched to k servers according to a probabilistic selection policy, with parameter ps being the selection probability of slower servers. Mean task completion time admits an integral form, and thus it is analytically intractable to compute ps that minimizes it. In this work, we provide an upper bound on the mean task completion time, and determine ps that minimizes this upper bound. Numerically, this choice has been shown to be near-optimal.

Item Type: Journal Article
Publication: Performance Evaluation Review
Publisher: Association for Computing Machinery
Additional Information: The copyright for this article belongs to Association for Computing Machinery.
Keywords: Heterogeneous systems; K-server; Parallel servers; Probabilistic scheduling; Probabilistics; Selection policies; Selection probabilities; Subtask; Task completion time; Upper Bound, Asymptotic analysis
Department/Centre: Division of Interdisciplinary Sciences > Robert Bosch Centre for Cyber Physical Systems
Date Deposited: 15 Jun 2023 07:51
Last Modified: 15 Jun 2023 07:51
URI: https://eprints.iisc.ac.in/id/eprint/81952

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