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Efficient resource placement in cloud computing and network applications

Authors:

Yuval Rochman,

Hanoch Levy,

Eli BroshAuthors Info & Claims

ACM SIGMETRICS Performance Evaluation Review, Volume 42, Issue 2

Pages 49 - 51

https://doi.org/10.1145/2667522.2667538

Published: 04 September 2014 Publication History

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Abstract

We address the problem of resource placement in general networking applications, in particular cloud computing. We consider a large-scale service faced by regionally distributed demands for various resources. The service aims at placing the resources across regions to maximize profit, accounting for demand granting revenues minus resource placement costs. Cloud computing and online services, utilizing regional datacenters and facing the problem of where and how much to place various servers, naturally fall under this paradigm.

The main challenge posed by this setting is the need to deal with arbitrary multi-dimensional stochastic demands. We show that, despite the challenging stochastic combinatorial complexity, one can optimize the system operation using fairly efficient algorithms.

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Microsoft Azure home page. http://www.windowsazure.com, 2013.

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R. G. Busacker and P. J. Gowen. A procedure for determining a family of minimal cost network flow patterns. Oro technical report 15, Operational Research Office, Johns Hopkins University, Baltimore, MD, September 1961.

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Liu YZhao DYao W(2025)Stochastic measurement-based multi-cloud consolidation for efficient resource distributionMeasurement10.1016/j.measurement.2024.115973242(115973)Online publication date: Jan-2025
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Wei WLi HZhang Q(2024)HERPExpert Systems with Applications: An International Journal10.1016/j.eswa.2024.125177258:COnline publication date: 15-Dec-2024
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Wei WLi HYang W(2023)Cost-effective stochastic resource placement in edge clouds with horizontal and vertical sharingFuture Generation Computer Systems10.1016/j.future.2022.08.016138(213-225)Online publication date: Jan-2023
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Information & Contributors

Information

Published In

cover image ACM SIGMETRICS Performance Evaluation Review

ACM SIGMETRICS Performance Evaluation Review Volume 42, Issue 2

September 2014

74 pages

ISSN:0163-5999

DOI:10.1145/2667522

Editor:
Giuliano Casale
Imperial College London, London

Issue’s Table of Contents

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 04 September 2014

Published in SIGMETRICS Volume 42, Issue 2

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Liu YZhao DYao W(2025)Stochastic measurement-based multi-cloud consolidation for efficient resource distributionMeasurement10.1016/j.measurement.2024.115973242(115973)Online publication date: Jan-2025
https://doi.org/10.1016/j.measurement.2024.115973
Wei WLi HZhang Q(2024)HERPExpert Systems with Applications: An International Journal10.1016/j.eswa.2024.125177258:COnline publication date: 15-Dec-2024
https://dl.acm.org/doi/10.1016/j.eswa.2024.125177
Wei WLi HYang W(2023)Cost-effective stochastic resource placement in edge clouds with horizontal and vertical sharingFuture Generation Computer Systems10.1016/j.future.2022.08.016138(213-225)Online publication date: Jan-2023
https://doi.org/10.1016/j.future.2022.08.016
Wei WWang QYang WMu Y(2022)Efficient stochastic scheduling for highly complex resource placement in edge cloudsJournal of Network and Computer Applications10.1016/j.jnca.2022.103365202(103365)Online publication date: Jun-2022
https://doi.org/10.1016/j.jnca.2022.103365
Wei WYang WXu H(2022)Burstable resource compatible general resource scheduling for stochastic demands in heterogeneous cloudsU+2605;Ain Shams Engineering Journal10.1016/j.asej.2021.05.01713:1(101503)Online publication date: Jan-2022
https://doi.org/10.1016/j.asej.2021.05.017
Wei WZhang YMu YYang W(2022)Stochastic Demands Oriented General Resource Scheduling With Burstable ResourcesJournal of Grid Computing10.1007/s10723-021-09586-820:1Online publication date: 1-Mar-2022
https://dl.acm.org/doi/10.1007/s10723-021-09586-8
Tavori JLevy H(2021)Tornadoes In The Cloud: Worst-Case Attacks on Distributed Resources SystemsIEEE INFOCOM 2021 - IEEE Conference on Computer Communications10.1109/INFOCOM42981.2021.9488673(1-10)Online publication date: 10-May-2021
https://dl.acm.org/doi/10.1109/INFOCOM42981.2021.9488673
Wei WWang QXu HLiu Y(2021)Highly Complex Resource Scheduling for Stochastic Demands in Heterogeneous CloudsJournal of Grid Computing10.1007/s10723-021-09555-119:1Online publication date: 1-Mar-2021
https://dl.acm.org/doi/10.1007/s10723-021-09555-1
Levy HTavori J(2020)Worst Case Attacks on Distributed Resources SystemsACM SIGMETRICS Performance Evaluation Review10.1145/3439602.343960748:2(9-11)Online publication date: 25-Nov-2020
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Lavi NSherzer ELevy H(2020)Deployment Planning in Vehicular Supported Cellular NetworksProceedings of the 13th EAI International Conference on Performance Evaluation Methodologies and Tools10.1145/3388831.3388855(64-71)Online publication date: 18-May-2020
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