Empirical Gittins: M/G/1 Scheduling from Job Size Samples

Shefali Ramakrishna; Amit Harlev; Ziv Scully

doi:10.1145/3764944.3764974

August 26, 2025ACM SIGMETRICS Performance Evaluation Review

Empirical Gittins: M/G/1 Scheduling from Job Size Samples

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Key Points

Minimizing mean response time is crucial in M/G/1 scheduling situations, which rely on job size information.
The study highlights how different scheduling policies can impact response time in M/G/1 queue systems, revealing important efficiencies.
Each policy's efficiency is directly tied to the job size samples available to the scheduler, emphasizing the need for accurate data.
Understanding job sizes aids in developing optimal scheduling strategies for reduced wait times, applicable across various systems.

Implication

Analysis reveals optimal scheduling affects mean response time in M/G/1 queues, indicating the importance of job size data.

Abstract

We consider the classic problem of minimizing mean response time in the M/G/1 queue. The optimal scheduling policy depends on the amount of information the scheduler has about job sizes (service times).

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Cite This Study

Ramakrishna et al. (2025) studied this question.

synapsesocial.com/papers/68bb3d4e2b87ece8dc955bf7 https://doi.org/10.1145/3764944.3764974

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Empirical Gittins: M/G/1 Scheduling from Job Size Samples

Key Points

Implication

Abstract

Discussion

Cite This Study

Empirical Gittins: M/G/1 Scheduling from Job Size Samples

Key Points

Implication

Abstract

Discussion

Cite This Study

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