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Open problems in queueing theory inspired by datacenter computing

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  • Mor Harchol-Balter

    (Carnegie Mellon University)

Abstract

Datacenter operations today provide a plethora of new queueing and scheduling problems. The notion of a “job” has become more general and multi-dimensional. The ways in which jobs and servers can interact have grown in complexity, involving parallelism, speedup functions, precedence constraints, and task graphs. The workloads are vastly more variable and more heavy-tailed. Even the performance metrics of interest are broader than in the past, with multi-dimensional service-level objectives in terms of tail probabilities. The purpose of this article is to expose queueing theorists to new models, while providing suggestions for many specific open problems of interest, as well as some insights into their potential solution.

Suggested Citation

  • Mor Harchol-Balter, 2021. "Open problems in queueing theory inspired by datacenter computing," Queueing Systems: Theory and Applications, Springer, vol. 97(1), pages 3-37, February.
    • Handle: RePEc:spr:queues:v:97:y:2021:i:1:d:10.1007_s11134-020-09684-6
    DOI: 10.1007/s11134-020-09684-6
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    References listed on IDEAS

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    Cited by:

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    2. Samuli Aalto & Ziv Scully, 2023. "Minimizing the mean slowdown in the M/G/1 queue," Queueing Systems: Theory and Applications, Springer, vol. 104(3), pages 187-210, August.
    3. Alexander Dudin & Sergei Dudin & Olga Dudina, 2023. "Analysis of a Queueing System with Mixed Service Discipline," Methodology and Computing in Applied Probability, Springer, vol. 25(2), pages 1-19, June.
    4. Neil Walton, 2022. "Queueing: a perennial theory," Queueing Systems: Theory and Applications, Springer, vol. 100(3), pages 557-559, April.

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