research-article

Online Auctions in IaaS Clouds: Welfare and Profit Maximization with Server Costs

Authors:

Francis C.M. LauAuthors Info & Claims

ACM SIGMETRICS Performance Evaluation Review, Volume 43, Issue 1

Pages 3 - 15

https://doi.org/10.1145/2796314.2745855

Published: 15 June 2015 Publication History

Abstract

Auction design has recently been studied for dynamic resource bundling and VM provisioning in IaaS clouds, but is mostly restricted to the one-shot or offline setting. This work targets a more realistic case of online VM auction design, where: (i) cloud users bid for resources into the future to assemble customized VMs with desired occupation durations; (ii) the cloud provider dynamically packs multiple types of resources on heterogeneous physical machines (servers) into the requested VMs; (iii) the operational costs of servers are considered in resource allocation; (iv) both social welfare and the cloud provider's net profit are to be maximized over the system running span. We design truthful, polynomial time auctions to achieve social welfare maximization and/or the provider's profit maximization with good competitive ratios. Our mechanisms consist of two main modules: (1) an online primal-dual optimization framework for VM allocation to maximize the social welfare with server costs, and for revealing the payments through the dual variables to guarantee truthfulness; and (2) a randomized reduction algorithm to convert the social welfare maximizing auctions to ones that provide a maximal expected profit for the provider, with competitive ratios comparable to those for social welfare. We adopt a new application of Fenchel duality in our primal-dual framework, which provides richer structures for convex programs than the commonly used Lagrangian duality, and our optimization framework is general and expressive enough to handle various convex server cost functions. The efficacy of the online auctions is validated through careful theoretical analysis and trace-driven simulation studies.

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Online Auctions in IaaS Clouds: Welfare and Profit Maximization with Server Costs

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Online Auctions in IaaS Clouds: Welfare and Profit Maximization with Server Costs
SIGMETRICS '15: Proceedings of the 2015 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems

Auction design has recently been studied for dynamic resource bundling and VM provisioning in IaaS clouds, but is mostly restricted to the one-shot or offline setting. This work targets a more realistic case of online VM auction design, where: (i) cloud ...
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Auction mechanisms have recently attracted substantial attention as an efficient approach to pricing and resource allocation in cloud computing. This work, to the authors' knowledge, represents the first online combinatorial auction designed in the ...

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Published In

cover image ACM SIGMETRICS Performance Evaluation Review

ACM SIGMETRICS Performance Evaluation Review Volume 43, Issue 1

Performance evaluation review

June 2015

468 pages

ISSN:0163-5999

DOI:10.1145/2796314

Editors:
Derek Eager
University of Saskatchewan
,
Carey Williamson
University of Calgary

Issue’s Table of Contents

SIGMETRICS '15: Proceedings of the 2015 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems
June 2015
488 pages
ISBN:9781450334860
DOI:10.1145/2745844
General Chairs:
Bill Lin
University of California, San Diego
,
Jun (Jim) Xu
Georgia Tech
,
Program Chairs:
Sudipta Sengupta
Microsoft Research
,
Devavrat Shah
Massachusetts Institute of Technology

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Published: 15 June 2015

Published in SIGMETRICS Volume 43, Issue 1

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https://doi.org/10.1109/TMC.2020.3034499
Liu GXiao ZChronopoulos ALiu CTang Z(2022)A Many-to-Many Demand and Response Hybrid Game Method for Cloud EnvironmentsIEEE Transactions on Cloud Computing10.1109/TCC.2019.295613410:1(158-171)Online publication date: 1-Jan-2022
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Pang JHan ZZhou RTan HCao Y(2022)Online scheduling algorithms for unbiased distributed learning over wireless edge networksJournal of Systems Architecture10.1016/j.sysarc.2022.102673131(102673)Online publication date: Oct-2022
https://doi.org/10.1016/j.sysarc.2022.102673
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Han ZTan HWang RChen GLi YLau F(2019)Energy-Efficient Dynamic Virtual Machine Management in Data CentersIEEE/ACM Transactions on Networking10.1109/TNET.2019.289178727:1(344-360)Online publication date: 1-Feb-2019
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Li JZhu YYu JLong CXue GQian S(2018)Online Auction for IaaS Clouds: Towards Elastic User Demands and Weighted Heterogeneous VMsIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2018.281456629:9(2075-2089)Online publication date: 1-Sep-2018
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