Price Fluctuation in Online Leasing

Feldkord, Björn; Markarian, Christine; Heide, Friedhelm Meyer auf der

doi:10.1007/978-3-319-71147-8_2

Cited by 9 publications

(7 citation statements)

References 13 publications

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“…(Khanafer, Kodialam, and Puttaswamy 2013) allowed constraints (first or second moment) on the stochastic adversary. (Feldkord, Markarian, and Der Heide 2017) generalized the problem by considering fluctuations in rental prices. (Meyerson 2005) considered that the choices of purchase are limited in time.…”

Section: Ski-rental and Applicationsmentioning

confidence: 99%

Online Hedge Reservation for Diverse Plans and Competitive Analysis

Bao

Yuan

et al. 2021

ICAPS

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In this paper, we investigate the plan reservation problem with diverse plans in mobile networks. The pricing scheme includes: 1) Pay-as-you-go (PAYG) payment; 2) All-in-one plan: an upfront fee is charged to cover data volume of a period of time; and 3) Directional plan: an upfront fee is charged to cover data volume of a specific app for a period of time. We investigate online plan reservation with competitive analysis, as the data volume is not known until an app is used. The problem is challenging as there are multiple directional plans and one all-in-one plan, creating a large decision space and complicated correlations among the decisions. We propose the Online Hedge Reservation (OHR) Algorithm to solve the problem and prove that it achieves e^beta/(e^beta-1) competitive ratio when each plan is valid till the end of each calendar month and 2e^beta/(e^beta-1) competitive ratio when each plan is valid for a full month, where beta is the ratio of prices of the directional plans and the all-in-one plan. This is an exciting neat extension of the competitive ratio e/(e-1) of the classic ski-rental problem. Finally, trace-driven simulation is conducted to further verify the advantages of the OHR Algorithm.

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Section: Ski-rental and Applicationsmentioning

confidence: 99%

Online Hedge Reservation for Diverse Plans and Competitive Analysis

Bao

Yuan

et al. 2021

ICAPS

View full text Add to dashboard Cite

show abstract

“…Li et al [28] study the case when a demand does not need to be served immediately when it arrives, but instead has a deadline which must be respected. Feldkord, Markarian and auf der Heide [12] discuss what happens when leasing costs are allowed to fluctuate over time. Markarian [31] extends the leasing model for the case in which a demand can be refused by paying a penalty, and for the case in which a demand may be delayed by incurring a penalty per unit of delayed time.…”

Section: Related Workmentioning

confidence: 99%

“…This idea can be formalized as follows. 12 Theorem 34 ([6, 11]). Given a minimization problem on a finite metric (V, d) whose objective function is a non-negative linear combination of distances in d, if there is an α-competitive algorithm for the special case of tree metrics, then there is a randomized O(α • lg |V |)-competitive algorithm for the general case.…”

Section: Consequences For Network Leasing Problemsmentioning

confidence: 99%

“…Some literature has been devoted to leasing variants of classical optimization problems [1,3,7,9,10,33]. Also, variants of PP and related problems were studied [12,20,24,28,31]. A traditional problem whose leasing variant was studied by Meyerson [32] is the Steiner forest problem.…”

Section: Introductionmentioning

confidence: 99%

“…Further Research Directions. Another future research direction is to study generalizations such as GPP and 2DPP to other leasing models, such as those defined in [28,12].…”

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confidence: 99%

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