Real-time IaaS cost model and estimation results for cloud PC Laboratory Service

Kyung Woon Cho; Hyokyung Bahn

doi:10.1145/3380678.3380686

Real-time IaaS cost model and estimation results for cloud PC Laboratory Service

Kyung Woon Cho, Hyokyung Bahn

Computer Science & Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

IaaS is well known as a very cost effective computing service which enables required infrastructures to be rented on demand without ownership of real hardware. It is very suitable for price sensitive services due to pay-per-use style. Operators of such services would want to adjust utilization policy promptly by estimating costs for cloud infrastructures as soon as possible. However, instantaneous response is not possible due to that cloud service providers offer at least several hours delayed billing information. Our work proposes a real-time IaaS cost estimation model based on resource usages monitored by virtual machine instance. We had operated PC laboratory service on a public cloud during full semester to validate our suggested model. From our experiments, averaged disparity between estimation and actual cost is less than 5.2%.

Original language	English
Title of host publication	CECCC 2019 - 2019 International Communication Engineering and Cloud Computing Conference
Publisher	Association for Computing Machinery
Pages	14-18
Number of pages	5
ISBN (Electronic)	9781450376396
DOIs	https://doi.org/10.1145/3380678.3380686
State	Published - 8 Oct 2019
Event	2019 International Communication Engineering and Cloud Computing Conference, CECCC 2019 - Prague, Czech Republic Duration: 8 Oct 2019 → 10 Oct 2019

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	2019 International Communication Engineering and Cloud Computing Conference, CECCC 2019
Country/Territory	Czech Republic
City	Prague
Period	8/10/19 → 10/10/19

Bibliographical note

Funding Information:
This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. NRF-2016R1A6A3A11930295)

Publisher Copyright:
© 2019 Association for Computing Machinery.

Keywords

CLABO
Cloud PC Laboratory Platform
IaaS Cost Estimation Model
Public Cloud

Access to Document

10.1145/3380678.3380686

Cite this

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title = "Real-time IaaS cost model and estimation results for cloud PC Laboratory Service",

abstract = "IaaS is well known as a very cost effective computing service which enables required infrastructures to be rented on demand without ownership of real hardware. It is very suitable for price sensitive services due to pay-per-use style. Operators of such services would want to adjust utilization policy promptly by estimating costs for cloud infrastructures as soon as possible. However, instantaneous response is not possible due to that cloud service providers offer at least several hours delayed billing information. Our work proposes a real-time IaaS cost estimation model based on resource usages monitored by virtual machine instance. We had operated PC laboratory service on a public cloud during full semester to validate our suggested model. From our experiments, averaged disparity between estimation and actual cost is less than 5.2%.",

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Cho, KW & Bahn, H 2019, Real-time IaaS cost model and estimation results for cloud PC Laboratory Service. in CECCC 2019 - 2019 International Communication Engineering and Cloud Computing Conference. ACM International Conference Proceeding Series, Association for Computing Machinery, pp. 14-18, 2019 International Communication Engineering and Cloud Computing Conference, CECCC 2019, Prague, Czech Republic, 8/10/19. https://doi.org/10.1145/3380678.3380686

Real-time IaaS cost model and estimation results for cloud PC Laboratory Service. / Cho, Kyung Woon; Bahn, Hyokyung.
CECCC 2019 - 2019 International Communication Engineering and Cloud Computing Conference. Association for Computing Machinery, 2019. p. 14-18 (ACM International Conference Proceeding Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Real-time IaaS cost model and estimation results for cloud PC Laboratory Service

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

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Cite this