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abstract

Batch spot market for data analytics cloud providers

Published: 24 September 2017 Publication History

Abstract

Hosting data analytics services is challenging as their workload is often composed of on-line (e.g., interactive or streaming), requiring fast on-demand provisioning, and batch jobs. As workload demand fluctuations lead to varying idle capacity, efficient resource management is difficult, in particular given different provider objectives, e.g., utilization, revenue.

References

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AmazonEC2. [n. d.]. Amazon Spot Instances, ([n. d.]).
[2]
Kubernetes. [n. d.]. Kubernetes. ([n. d.]).
[3]
Youngseok Yang, Geon-Woo Kim, Won Wook Song, Yunseong Lee, Andrew Chung, Zhengping Qian, Brian Cho, and Byung-Gon Chun. 2017. Pado: A Data Processing Engine for Harnessing Transient Resources in Datacenters. In Proceedings of Eurosys'17 (EuroSys '17). ACM, New York, NY, USA.
[4]
Matei Zaharia, Mosharaf Chowdhury, Michael J. Franklin, Scott Shenker, and Ion Stoica. 2010. Spark: Cluster Computing with Working Sets. In Proceedings of the 2Nd USENIX Conference on Hot Topics in Cloud Computing (HotCloud'10). USENIX Association, Berkeley, CA, USA.
[5]
X. Zhang, Z. Huang, C. Wu, Z. Li, and F. C. M. Lau. 2017. Online Auctions in IaaS Clouds: Welfare and Profit Maximization With Server Costs. IEEE/ACM Transactions on Networking 25, 2 (April 2017), 1034--1047.

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Published In

cover image ACM Conferences
SoCC '17: Proceedings of the 2017 Symposium on Cloud Computing
September 2017
672 pages
ISBN:9781450350280
DOI:10.1145/3127479
Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 September 2017

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  1. cloud computing
  2. performance

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SoCC '17
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SoCC '17: ACM Symposium on Cloud Computing
September 24 - 27, 2017
California, Santa Clara

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Overall Acceptance Rate 169 of 722 submissions, 23%

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