Consumer-and-provider-oriented efficient IaaS resource allocation

Thibaud Ecarot; Djamal Zeghlache; Cedric Brandily

doi:10.1109/IPDPSW.2017.97

Consumer-and-provider-oriented efficient IaaS resource allocation

Thibaud Ecarot, Djamal Zeghlache, Cedric Brandily

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

Abstract

This paper presents a method of cloud resource allocation designed to take into account both consumers and providers' interests. This comes in contrast to today's provider centered models that subject users to more restrictive terms and conditions. Both parties' interests are computed in the form of integer constraints. Costs and availability are embedded as key objectives and performance criteria in the model. We propose a hybrid resolution method based on an evolutionary algorithm augmented with a tabu search and compare performance with other resource allocation algorithms. The comparison results reveal the efficiency of the proposed hybrid evolutionary algorithms.

Original language	English
Title of host publication	Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	77-85
Number of pages	9
ISBN (Electronic)	9781538634080
DOIs	https://doi.org/10.1109/IPDPSW.2017.97
Publication status	Published - 30 Jun 2017
Externally published	Yes
Event	31st IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017 - Orlando, United States Duration: 29 May 2017 → 2 Jun 2017

Publication series

Name	Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017

Conference

Conference	31st IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017
Country/Territory	United States
City	Orlando
Period	29/05/17 → 2/06/17

Keywords

Cloud Computing
Cloud Computing Modeling
Efficient resource allocation
Genetic Algorithm
Optimization
Tabu Search

Access to Document

10.1109/IPDPSW.2017.97

Cite this

Ecarot, T., Zeghlache, D., & Brandily, C. (2017). Consumer-and-provider-oriented efficient IaaS resource allocation. In Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017 (pp. 77-85). Article 7965027 (Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IPDPSW.2017.97

Ecarot, Thibaud ; Zeghlache, Djamal ; Brandily, Cedric. / Consumer-and-provider-oriented efficient IaaS resource allocation. Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 77-85 (Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017).

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title = "Consumer-and-provider-oriented efficient IaaS resource allocation",

abstract = "This paper presents a method of cloud resource allocation designed to take into account both consumers and providers' interests. This comes in contrast to today's provider centered models that subject users to more restrictive terms and conditions. Both parties' interests are computed in the form of integer constraints. Costs and availability are embedded as key objectives and performance criteria in the model. We propose a hybrid resolution method based on an evolutionary algorithm augmented with a tabu search and compare performance with other resource allocation algorithms. The comparison results reveal the efficiency of the proposed hybrid evolutionary algorithms.",

keywords = "Cloud Computing, Cloud Computing Modeling, Efficient resource allocation, Genetic Algorithm, Optimization, Tabu Search",

author = "Thibaud Ecarot and Djamal Zeghlache and Cedric Brandily",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 31st IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017 ; Conference date: 29-05-2017 Through 02-06-2017",

year = "2017",

month = jun,

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doi = "10.1109/IPDPSW.2017.97",

language = "English",

series = "Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "77--85",

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Ecarot, T, Zeghlache, D & Brandily, C 2017, Consumer-and-provider-oriented efficient IaaS resource allocation. in Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017., 7965027, Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017, Institute of Electrical and Electronics Engineers Inc., pp. 77-85, 31st IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017, Orlando, United States, 29/05/17. https://doi.org/10.1109/IPDPSW.2017.97

Consumer-and-provider-oriented efficient IaaS resource allocation. / Ecarot, Thibaud; Zeghlache, Djamal; Brandily, Cedric.
Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 77-85 7965027 (Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017).

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

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AB - This paper presents a method of cloud resource allocation designed to take into account both consumers and providers' interests. This comes in contrast to today's provider centered models that subject users to more restrictive terms and conditions. Both parties' interests are computed in the form of integer constraints. Costs and availability are embedded as key objectives and performance criteria in the model. We propose a hybrid resolution method based on an evolutionary algorithm augmented with a tabu search and compare performance with other resource allocation algorithms. The comparison results reveal the efficiency of the proposed hybrid evolutionary algorithms.

KW - Cloud Computing

KW - Cloud Computing Modeling

KW - Efficient resource allocation

KW - Genetic Algorithm

KW - Optimization

KW - Tabu Search

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DO - 10.1109/IPDPSW.2017.97

M3 - Conference contribution

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Ecarot T, Zeghlache D, Brandily C. Consumer-and-provider-oriented efficient IaaS resource allocation. In Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 77-85. 7965027. (Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017). doi: 10.1109/IPDPSW.2017.97

Consumer-and-provider-oriented efficient IaaS resource allocation

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