Double Coverage with Machine-Learned Advice

Alexander, Lindermayr,; Megow, Nicole; Simon, Bertrand

doi:10.48550/arxiv.2103.01640

Cited by 2 publications

(2 citation statements)

References 19 publications

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“…This dataset could also be used for related problems such as k-server on the line for which few relevant datasets are available (Lindermayr, Megow, and Simon 2021). The remaining question on the theoretical side of LTSP resides in the dependency in n of an optimal algorithm.…”

Section: Discussionmentioning

confidence: 99%

An Exact Algorithm for the Linear Tape Scheduling Problem

Honoré

Simon

Suter³

2022

ICAPS

Self Cite

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Magnetic tapes are often considered as an outdated storage technology, yet they are still used to store huge amounts of data. Their main interests are a large capacity and a low price per gigabyte, which come at the cost of a much larger file access time than on disks. With tapes, finding the right ordering of multiple file accesses is thus key to performance. Moving the reading head back and forth along a kilometer long tape has a non-negligible cost and unnecessary movements thus have to be avoided. However, the optimization of tape request ordering has rarely been studied in the scheduling literature, much less than I/O scheduling on disks. For instance, minimizing the average service time for several read requests on a linear tape remains an open question. Therefore, in this paper, we aim at improving the quality of service experienced by users of tape storage systems, and not only the peak performance of such systems. To this end, we propose a reasonable polynomial-time exact algorithm while this problem and simpler variants have been conjectured NP-hard. We also refine the proposed model by considering U-turn penalty costs accounting for inherent mechanical accelerations. Then, we propose a low-cost variant of our optimal algorithm by restricting the solution space, yet still yielding an accurate suboptimal solution. Finally, we compare our algorithms to existing solutions from the literature on logs of the mass storage management system of a major datacenter. This allows us to assess the quality of previous solutions and the improvement achieved by our low-cost algorithm. Aiming for reproducibility, we make available the complete implementation of the algorithms used in our evaluation, alongside the dataset of tape requests that is, to the best of our knowledge, the first of its kind to be publicly released.

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Section: Discussionmentioning

confidence: 99%

An Exact Algorithm for the Linear Tape Scheduling Problem

Honoré

Simon

Suter³

2022

ICAPS

Self Cite

View full text Add to dashboard Cite

show abstract

“…This dataset could also be used for related problems such as k-server on the line for which few relevant datasets are available [17]. The remaining question on the theoretical side of LTSP resides in the possible improvements in the running time of an exact algorithm.…”

Section: Discussionmentioning

confidence: 99%

An Exact Algorithm for the Linear Tape Scheduling Problem

Honoré¹,

Simon²,

Suter³

2021

Preprint

Self Cite

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Magnetic tapes are often considered as an outdated storage technology, yet they are still used to store huge amounts of data. Their main interests are a large capacity and a low price per gigabyte, which come at the cost of a much larger file access time than on disks. With tapes, finding the right ordering of multiple file accesses is thus key to performance. Moving the reading head back and forth along a kilometer long tape has a non-negligible cost and unnecessary movements thus have to be avoided. However, the optimization of tape request ordering has then rarely been studied in the scheduling literature, much less than I/O scheduling on disks. For instance, minimizing the average service time for several read requests on a linear tape remains an open question.Therefore, in this paper, we aim at improving the quality of service experienced by users of tape storage systems, and not only the peak performance of such systems. To this end, we propose a reasonable polynomial-time exact algorithm while this problem and simpler variants have been conjectured NP-hard. We also refine the proposed model by considering U-turn penalty costs accounting for inherent mechanical accelerations. Then, we propose a low-cost variant of our optimal algorithm by restricting the solution space, yet still yielding an accurate suboptimal solution. Finally, we compare our algorithms to existing solutions from the literature on logs of the mass storage management system of a major datacenter. This allows us to assess the quality of previous solutions and the improvement achieved by our low-cost algorithm. Aiming for reproducibility, we make available the complete implementation of the algorithms used in our evaluation, alongside the dataset of tape requests that is, to the best of our knowledge, the first of its kind to be publicly released.

show abstract

Double Coverage with Machine-Learned Advice

Cited by 2 publications

References 19 publications

An Exact Algorithm for the Linear Tape Scheduling Problem

An Exact Algorithm for the Linear Tape Scheduling Problem

An Exact Algorithm for the Linear Tape Scheduling Problem

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