Dynamic pricing scheme for IaaS cloud platform based on load balancing: A Q-learning approach

Ren, Jiali; Pang, Lijuan; Cheng, Yan

doi:10.1109/icsess.2017.8343034

Cited by 6 publications

(1 citation statement)

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“…This way, they can indirectly manipulate the system and impact the overall resource allocation and pricing. Therefore, methods such as machine learning based techniques [75], [76] alone cannot be sufficient and new solutions are needed to be devised in order to address the selfish behaviors of the users and providers This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ This article has been accepted for publication in a future issue of this journal, but has not been fully edited.…”

Section: Auctions For Market-oriented Cloud/edge Computingmentioning

confidence: 99%

A Comprehensive Survey on Auction Mechanism Design for Cloud/Edge Resource Management and Pricing

Sharghivand¹,

Derakhshan

Siasi

2021

IEEE Access

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Driven by the vision of cloud and edge computing as the 5th utility, a major challenge is the efficient resources management and pricing taking into account incentives and preferences of cloud/edge providers, users, and the system. In recent years, auction mechanism design has gained wide attention as a tool for addressing this challenge. Here existing surveys lack detailed studies in this area, hence this work presents a comprehensive survey on the state-of-the-art auction-based mechanisms in the field of cloud/edge computing. First, the problem statements and background are presented for cloud/edge computing and auction theory. This is followed by a collaboration model on the benefits of auction mechanism designs to cloud/edge computing. Next, various auction mechanisms in cloud computing are reviewed based upon the following aspects: (1) direction of bids-forward, reverse, and two-sided auctions, (2) the heterogeneity of resources-combinatorial auctions, (3) the number and types of adopted attributes in winner determination-multi-attribute auctions, (4) the setting of auction-offline, online, or sequential auctions, and (5) the interoperability among cloud providers-inter-clouds. For each aspect, existing studies are summarized along with their saliencies and drawbacks. Moreover, existing auction mechanisms in the context of edge computing are also presented, followed by existing challenges and research directions.INDEX TERMS Auction mechanism design, cloud computing, edge computing, resource management, resource pricing.

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Section: Auctions For Market-oriented Cloud/edge Computingmentioning

confidence: 99%