research-article

Dynamic Pricing for Maximizing Cloud Revenue: A Column Generation Approach

Authors:

Anjali Agarwal,

Ahmed Saleh BatainehAuthors Info & Claims

ICDCN '17: Proceedings of the 18th International Conference on Distributed Computing and Networking

Article No.: 22, Pages 1 - 9

https://doi.org/10.1145/3007748.3007756

Published: 05 January 2017 Publication History

Abstract

Virtualization underpins the emergence of Infrastructure as a Service (IaaS) to provide service delivery. Even with virtualized resources, the cloud industry suffers from underutilization off the peak load periods. Hence it is essential for a pricing mechanism to satisfy both customers' demands and budgets as well as maximizing the cloud revenue. The limited works on dynamic pricing consider selling the entire population of VMs in the cloud, resulting in increased processing time and risk. Motivated by the aforementioned concerns, this paper proposes a dynamic pricing model that strives to minimize the inevitable stagnant VMs, while working to maximize cloud revenue. In particular, this paper explores the factors that drive price dynamism following the pay-as-you-go pricing scheme that is rapidly adopted in cloud services. We present a new dynamic pricing approach based on a linear programming relaxation of Stochastic Markov Decision processes. To further reduce the high dimensionality, we employ column generation. Numerical evaluations show practical scalability, as well as prominent influences that could be adopted by cloud providers for revenue maximization.

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Cited By

Peng HCheng Y(2023)A Novel Dynamic Pricing Approach for Preemptible Cloud ServicesIEEE Access10.1109/ACCESS.2023.331342511(97807-97825)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3313425
Alzhouri FAgarwal ALiu Y(2021)Maximizing Cloud Revenue using Dynamic Pricing of Multiple Class Virtual MachinesIEEE Transactions on Cloud Computing10.1109/TCC.2018.28780239:2(682-695)Online publication date: 1-Apr-2021
https://doi.org/10.1109/TCC.2018.2878023
Mukherjee ASundarraj RDutta K(2021)Time-preference-based on-spot bundled cloud-service provisioningDecision Support Systems10.1016/j.dss.2021.113607151:COnline publication date: 1-Dec-2021
https://dl.acm.org/doi/10.1016/j.dss.2021.113607
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ICDCN '17: Proceedings of the 18th International Conference on Distributed Computing and Networking

January 2017

367 pages

ISBN:9781450348393

DOI:10.1145/3007748

Copyright © 2017 ACM.

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Published: 05 January 2017

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ICDCN '17: 18th International Conference on Distributed Computing and Networking

January 5 - 7, 2017

Hyderabad, India

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Cited By

Peng HCheng Y(2023)A Novel Dynamic Pricing Approach for Preemptible Cloud ServicesIEEE Access10.1109/ACCESS.2023.331342511(97807-97825)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3313425
Alzhouri FAgarwal ALiu Y(2021)Maximizing Cloud Revenue using Dynamic Pricing of Multiple Class Virtual MachinesIEEE Transactions on Cloud Computing10.1109/TCC.2018.28780239:2(682-695)Online publication date: 1-Apr-2021
https://doi.org/10.1109/TCC.2018.2878023
Mukherjee ASundarraj RDutta K(2021)Time-preference-based on-spot bundled cloud-service provisioningDecision Support Systems10.1016/j.dss.2021.113607151:COnline publication date: 1-Dec-2021
https://dl.acm.org/doi/10.1016/j.dss.2021.113607
Alzhouri FMelhem SAgarwal ADaraghmeh MLiu YYounis S(2020)Dynamic Resource Management for Cloud Spot MarketsIEEE Access10.1109/ACCESS.2020.30074698(122838-122847)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.3007469
Nasiriani NKesidis GWang D(2018)Public Cloud Differential Pricing Design Under Provider and Tenants Joint Demand ResponseProceedings of the Ninth International Conference on Future Energy Systems10.1145/3208903.3208938(21-32)Online publication date: 12-Jun-2018
https://dl.acm.org/doi/10.1145/3208903.3208938
van der Mei Rvan den Berg HGanchev ITutschku KLeitner PLassila PBurakowski WLiberal FArvidsson ÅHoβfeld TWac KMelvin HGrbac THaddad YKey P(2018)State of the Art and Research Challenges in the Area of Autonomous Control for a Reliable Internet of ServicesAutonomous Control for a Reliable Internet of Services10.1007/978-3-319-90415-3_1(1-22)Online publication date: 25-May-2018
https://doi.org/10.1007/978-3-319-90415-3_1

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