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Competitive Algorithms for the Online Multiple Knapsack Problem with Application to Electric Vehicle Charging

Sun, Bo and Zeynali, Ali and Li, Tongxin and Hajiesmaili, Mohammad and Wierman, Adam and Tsang, Danny H. K. (2021) Competitive Algorithms for the Online Multiple Knapsack Problem with Application to Electric Vehicle Charging. In: SIGMETRICS '21: Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems. ACM , New York, NY, pp. 67-68. ISBN 9781450380720. https://resolver.caltech.edu/CaltechAUTHORS:20210607-115054262

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Abstract

We introduce and study a general version of the fractional online knapsack problem with multiple knapsacks, heterogeneous constraints on which items can be assigned to which knapsack, and rate-limiting constraints on the assignment of items to knapsacks. This problem generalizes variations of the knapsack problem and of the one-way trading problem that have previously been treated separately, and additionally finds application to the real-time control of electric vehicle (EV) charging. We introduce a new algorithm that achieves a competitive ratio within an additive factor of the best achievable competitive ratios for the general problem and matches or improves upon the best-known competitive ratio for special cases in the knapsack and one-way trading literatures. Moreover, our analysis provides a novel approach to online algorithm design based on an instance-dependent primal-dual analysis that connects the identification of worst-case instances to the design of algorithms. Finally, in the full version of this paper, we illustrate the proposed algorithm via trace-based experiments of EV charging.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1145/3410220.3456271DOIArticle
https://resolver.caltech.edu/CaltechAUTHORS:20201014-142839691Related ItemJournal Article
ORCID:
AuthorORCID
Sun, Bo0000-0003-3172-7811
Li, Tongxin0000-0002-9806-8964
Hajiesmaili, Mohammad0000-0001-9278-2254
Tsang, Danny H. K.0000-0003-0135-7098
Additional Information:© 2021 Copyright held by the owner/author(s). Bo Sun and Danny H.K. Tsang acknowledge the support received from the Hong Kong Research Grant Council (RGC) General Research Fund (Project 16202619 and Project 16211220). Ali Zeynali and Mohammad Hajiesmaili’s research is supported by NSF CNS-1908298 and CAREER 2045641. Tongxin Li’s research is supported by NSF grants (CPS ECCS 1932611 and CPS ECCS 1739355). Adam Wierman acknowledges the support received from NSF grants (AitF-1637598 and NSF CNS-1518941). Bo Sun would also like to thank Dr. Xiaoqi Tan (University of Toronto) for insightful and useful discussions.
Funders:
Funding AgencyGrant Number
Hong Kong Research Grant Council16202619
Hong Kong Research Grant Council16211220
NSFCNS-1908298
NSFCNS-2045641
NSFECCS-1932611
NSFECCS-1739355
NSFCCF-1637598
NSFCNS-1518941
Subject Keywords:online knapsack problems; one-way trading; online algorithms; electric vehicle charging; online primal-dual analysis
Record Number:CaltechAUTHORS:20210607-115054262
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20210607-115054262
Official Citation:Bo Sun, Ali Zeynali, Tongxin Li, Mohammad Hajiesmaili, Adam Wierman, and Danny H.K. Tsang. 2021. Competitive Algorithms for the Online Multiple Knapsack Problem with Application to Electric Vehicle Charging. In Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS ’21 Abstracts), June 14–18, 2021, Virtual Event, China. ACM, New York, NY, USA, 2 pages. https://doi.org/10.1145/3410220.3456271
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:109417
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:07 Jun 2021 22:37
Last Modified:07 Jun 2021 22:37

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