research-article

SpotOn: a batch computing service for the spot market

Authors:

Supreeth Subramanya,

Prateek Sharma,

Prashant ShenoyAuthors Info & Claims

SoCC '15: Proceedings of the Sixth ACM Symposium on Cloud Computing

Pages 329 - 341

https://doi.org/10.1145/2806777.2806851

Published: 27 August 2015 Publication History

Abstract

Cloud spot markets enable users to bid for compute resources, such that the cloud platform may revoke them if the market price rises too high. Due to their increased risk, revocable resources in the spot market are often significantly cheaper (by as much as 10×) than the equivalent non-revocable on-demand resources. One way to mitigate spot market risk is to use various fault-tolerance mechanisms, such as checkpointing or replication, to limit the work lost on revocation. However, the additional performance overhead and cost for a particular fault-tolerance mechanism is a complex function of both an application's resource usage and the magnitude and volatility of spot market prices.

We present the design of a batch computing service for the spot market, called SpotOn, that automatically selects a spot market and fault-tolerance mechanism to mitigate the impact of spot revocations without requiring application modification. SpotOn's goal is to execute jobs with the performance of on-demand resources, but at a cost near that of the spot market. We implement and evaluate SpotOn in simulation and using a prototype on Amazon's EC2 that packages jobs in Linux Containers. Our simulation results using a job trace from a Google cluster indicate that SpotOn lowers costs by 91.9% compared to using on-demand resources with little impact on performance.

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Cited By

M. Prasanthi G.Chishma P. Padmavathi K. Reethika A. Chandra Sekhar (2024)Improving Amazon EC2 Spot Instances Price Prediction using Machine Learning AlgorithmInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology10.32628/CSEIT2410210210:2(713-720)Online publication date: 22-Apr-2024
https://doi.org/10.32628/CSEIT24102102
Kim KLee KChua TNgo CKa-Wei Lee RKumar RLauw H(2024)Making Cloud Spot Instance Interruption Events VisibleProceedings of the ACM Web Conference 202410.1145/3589334.3645548(2998-3009)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3589334.3645548
Lim JKim KLee K(2024)Workload-Aware Live Migratable Cloud Instance Detector2024 IEEE 24th International Symposium on Cluster, Cloud and Internet Computing (CCGrid)10.1109/CCGrid59990.2024.00029(178-188)Online publication date: 6-May-2024
https://doi.org/10.1109/CCGrid59990.2024.00029
Show More Cited By

Index Terms

SpotOn: a batch computing service for the spot market
1. Software and its engineering
  1. Software creation and management
    1. Designing software
  2. Software organization and properties
    1. Contextual software domains
      1. Operating systems

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Information & Contributors

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Published In

cover image ACM Conferences

SoCC '15: Proceedings of the Sixth ACM Symposium on Cloud Computing

August 2015

446 pages

ISBN:9781450336512

DOI:10.1145/2806777

General Chair:
Shahram Ghandeharizadeh
University of Southern California
,
Program Chairs:
Magdalena Balazinska
University of Washington
,
Michael J. Freedman
Princeton University
,
Publications Chair:
Sumita Barahmand
Microsoft

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 the author(s) 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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Publication History

Published: 27 August 2015

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National Science Foundation

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SoCC '15

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SoCC '15: ACM Symposium on Cloud Computing

August 27 - 29, 2015

Hawaii, Kohala Coast

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SoCC '15 Paper Acceptance Rate 34 of 157 submissions, 22%;

Overall Acceptance Rate 169 of 722 submissions, 23%

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Cited By

M. Prasanthi G.Chishma P. Padmavathi K. Reethika A. Chandra Sekhar (2024)Improving Amazon EC2 Spot Instances Price Prediction using Machine Learning AlgorithmInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology10.32628/CSEIT2410210210:2(713-720)Online publication date: 22-Apr-2024
https://doi.org/10.32628/CSEIT24102102
Kim KLee KChua TNgo CKa-Wei Lee RKumar RLauw H(2024)Making Cloud Spot Instance Interruption Events VisibleProceedings of the ACM Web Conference 202410.1145/3589334.3645548(2998-3009)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3589334.3645548
Lim JKim KLee K(2024)Workload-Aware Live Migratable Cloud Instance Detector2024 IEEE 24th International Symposium on Cluster, Cloud and Internet Computing (CCGrid)10.1109/CCGrid59990.2024.00029(178-188)Online publication date: 6-May-2024
https://doi.org/10.1109/CCGrid59990.2024.00029
Xu ZPan LLiu S(2024)An Online Algorithm Based on Replication for Using Spot Instances in IaaS CloudsJournal of Computer Science and Technology10.1007/s11390-023-1535-439:1(103-115)Online publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1007/s11390-023-1535-4
Mandal SLal SSensarma SSaha SMaji GKhatua SDas R(2024)An Online Algorithm for Cost Minimization of Amazon EC2 Burstable ResourcesDistributed Computing and Intelligent Technology10.1007/978-3-031-50583-6_8(117-132)Online publication date: 4-Jan-2024
https://doi.org/10.1007/978-3-031-50583-6_8
Wang ZTu YWang NGao LNie JWei ZGu YYu G(2023)FSP: Towards Flexible Synchronous Parallel Frameworks for Distributed Machine LearningIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2022.322873334:2(687-703)Online publication date: 1-Feb-2023
https://doi.org/10.1109/TPDS.2022.3228733
Teylo LArantes LSens PDrummond L(2023)Scheduling Bag-of-Tasks in Clouds Using Spot and Burstable Virtual MachinesIEEE Transactions on Cloud Computing10.1109/TCC.2021.312542611:1(984-996)Online publication date: 1-Jan-2023
https://doi.org/10.1109/TCC.2021.3125426
Alourani AKshemkalyani A(2022)Cost-Effective Spot Instances Provisioning Using Features of Cloud MarketsInternational Journal of Cloud Applications and Computing10.4018/IJCAC.30827612:1(1-27)Online publication date: 30-Nov-2022
https://doi.org/10.4018/IJCAC.308276
Iqbal SLi HBergsma SBeschastnikh IHu AGavrilovska AAltınbüken DBinnig C(2022)CoSpotProceedings of the 13th Symposium on Cloud Computing10.1145/3542929.3563499(540-556)Online publication date: 7-Nov-2022
https://dl.acm.org/doi/10.1145/3542929.3563499
Kadupitiya JJadhao VSharma P(2022)SciSpot: Scientific Computing On Temporally Constrained Cloud Preemptible VMsIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2022.315727233:12(3575-3588)Online publication date: 1-Dec-2022
https://doi.org/10.1109/TPDS.2022.3157272
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