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The Online Knapsack Problem with Departures

Authors:

Mohammad Hajiesmaili,

John C. S. Lui,

Danny H.K. TsangAuthors Info & Claims

Proceedings of the ACM on Measurement and Analysis of Computing Systems, Volume 6, Issue 3

Article No.: 57, Pages 1 - 32

https://doi.org/10.1145/3570618

Published: 08 December 2022 Publication History

Abstract

The online knapsack problem is a classic online resource allocation problem in networking and operations research. Its basic version studies how to pack online arriving items of different sizes and values into a capacity-limited knapsack. In this paper, we study a general version that includes item departures, while also considering multiple knapsacks and multi-dimensional item sizes. We design a threshold-based online algorithm and prove that the algorithm can achieve order-optimal competitive ratios. Beyond worst-case performance guarantees, we also aim to achieve near-optimal average performance under typical instances. Towards this goal, we propose a data-driven online algorithm that learns within a policy-class that guarantees a worst-case performance bound. In trace-driven experiments, we show that our data-driven algorithm outperforms other benchmark algorithms in an application of online knapsack to job scheduling for cloud computing.

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Cited By

Bostandoost RLechowicz AHanafy WBashir NShenoy PHajiesmaili M(2024)LACS: Learning-Augmented Algorithms for Carbon-Aware Resource Scaling with Uncertain DemandProceedings of the 15th ACM International Conference on Future and Sustainable Energy Systems10.1145/3632775.3661942(27-45)Online publication date: 4-Jun-2024
https://dl.acm.org/doi/10.1145/3632775.3661942
Tabatabaie MHe S(2024)Driver Maneuver Interaction Identification with Anomaly-Aware Federated Learning on Heterogeneous Feature RepresentationsProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36314217:4(1-28)Online publication date: 12-Jan-2024
https://dl.acm.org/doi/10.1145/3631421
Leng SGuo YZhang LHao FCao XLi FKou W(2024)Online and Collaboratively Mitigating Multi-Vector DDoS Attacks for Cloud-Edge ComputingICC 2024 - IEEE International Conference on Communications10.1109/ICC51166.2024.10623052(1394-1399)Online publication date: 9-Jun-2024
https://doi.org/10.1109/ICC51166.2024.10623052
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The Online Knapsack Problem with Departures

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The online knapsack problem is a classic online resource allocation problem in networking and operations research. Its basic version studies how to pack online arriving items of different sizes and values into a capacity-limited knapsack. In this paper, ...
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The online knapsack problem is a classic online resource allocation problem in networking and operations research. Its basic version studies how to pack online arriving items of different sizes and values into a capacity-limited knapsack. In this paper, ...

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cover image Proceedings of the ACM on Measurement and Analysis of Computing Systems

Proceedings of the ACM on Measurement and Analysis of Computing Systems Volume 6, Issue 3

POMACS

December 2022

534 pages

EISSN:2476-1249

DOI:10.1145/3576048

Editors:
Augustin Chaintreau
Columbia University
,
Leana Golubchik
University of Southern California, United States
,
Zhi-Li Zhang
University of Minnesota, United States

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Copyright © 2022 ACM.

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Publication History

Published: 08 December 2022

Published in POMACS Volume 6, Issue 3

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Hong Kong Research Grant Council (RGC) General Research Fund
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Cited By

Bostandoost RLechowicz AHanafy WBashir NShenoy PHajiesmaili M(2024)LACS: Learning-Augmented Algorithms for Carbon-Aware Resource Scaling with Uncertain DemandProceedings of the 15th ACM International Conference on Future and Sustainable Energy Systems10.1145/3632775.3661942(27-45)Online publication date: 4-Jun-2024
https://dl.acm.org/doi/10.1145/3632775.3661942
Tabatabaie MHe S(2024)Driver Maneuver Interaction Identification with Anomaly-Aware Federated Learning on Heterogeneous Feature RepresentationsProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36314217:4(1-28)Online publication date: 12-Jan-2024
https://dl.acm.org/doi/10.1145/3631421
Leng SGuo YZhang LHao FCao XLi FKou W(2024)Online and Collaboratively Mitigating Multi-Vector DDoS Attacks for Cloud-Edge ComputingICC 2024 - IEEE International Conference on Communications10.1109/ICC51166.2024.10623052(1394-1399)Online publication date: 9-Jun-2024
https://doi.org/10.1109/ICC51166.2024.10623052
Lechowicz AChristianson NZuo JBashir NHajiesmaili MWierman AShenoy P(2023)The Online Pause and Resume Problem: Optimal Algorithms and An Application to Carbon-Aware Load ShiftingProceedings of the ACM on Measurement and Analysis of Computing Systems10.1145/36267767:3(1-32)Online publication date: 12-Dec-2023
https://dl.acm.org/doi/10.1145/3626776
Hajiesmaili M(2023)Trade-off Analysis in Learning-augmented Algorithms with Societal Design CriteriaACM SIGMETRICS Performance Evaluation Review10.1145/3626570.362659051:2(53-58)Online publication date: 2-Oct-2023
https://dl.acm.org/doi/10.1145/3626570.3626590
Sun BYang LHajiesmaili MWierman ALui JTowsley DTsang D(2023)The Online Knapsack Problem with DeparturesACM SIGMETRICS Performance Evaluation Review10.1145/3606376.359357651:1(59-60)Online publication date: 27-Jun-2023
https://dl.acm.org/doi/10.1145/3606376.3593576
Sun BYang LHajiesmaili MWierman ALui JTowsley DTsang DSmirni EAvrachenkov KGill PUrgaonkar B(2023)The Online Knapsack Problem with DeparturesAbstract Proceedings of the 2023 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems10.1145/3578338.3593576(59-60)Online publication date: 19-Jun-2023
https://doi.org/10.1145/3578338.3593576
Bostandoost RSun BJoe-Wong CHajiesmaili M(2023)Near-optimal Online Algorithms for Joint Pricing and Scheduling in EV Charging NetworksProceedings of the 14th ACM International Conference on Future Energy Systems10.1145/3575813.3576878(72-83)Online publication date: 16-Jun-2023
https://doi.org/10.1145/3575813.3576878
Ma WSimchi-Levi DZhao J(undefined)A Competitive Analysis of Online Knapsack Problems with Unit DensitySSRN Electronic Journal10.2139/ssrn.3423199
https://doi.org/10.2139/ssrn.3423199

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