Multi-objective optimization framework for VMI distribution in federated cloud repositories

Dragi Kimovski; Nishant Saurabh; Sandi Gec; Vlado Stankovski; Radu Prodan

doi:10.1007/978-3-319-58943-5_19

Multi-objective optimization framework for VMI distribution in federated cloud repositories

Dragi Kimovski^*, Nishant Saurabh, Sandi Gec, Vlado Stankovski, Radu Prodan

^*Corresponding author for this work

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

Abstract

Cloud Federation facilitates the concept of aggregation of multiple services administered by different providers, thus opening the possibility for the customers to profit from lower cost and better performance, while allowing for the cloud providers to offer more sophisticated services. Unfortunately, current state-of-the-art does not provide any substantial means for streamlined adaptation of federated Cloud environments. One of the essential barriers that prevents Cloud federation is the inefficient management of distributed storage repositories for Virtual Machine Images (VMI). In such environments, the VMIs are currently stored by Cloud providers in proprietary centralised repositories without considering application characteristics and their runtime requirements, causing high deployment and instantiation overheads. In this paper, a novel multi-objective optimization framework for VMI placement across distributed repositories in federated Cloud environment has been proposed. Based on the communication performance requirements, VMI use patterns, and structure of images or input data, the framework provides efficient means for transparent optimization of the distribution and placement of VMIs across distributed repositories to significantly lower their provisioning time for complex resource requests and for executing the user applications.

Original language	English
Title of host publication	Euro-Par 2016: Parallel Processing Workshops
Subtitle of host publication	Euro-Par 2016 International Workshops, Grenoble, France, August 24-26, 2016, Revised Selected Papers
Editors	Frederic Desprez, Pierre-Francois Dutot
Publisher	Springer
Pages	236-247
Number of pages	12
Edition	1
ISBN (Electronic)	978-3-319-58943-5
ISBN (Print)	978-3-319-58942-8
DOIs	https://doi.org/10.1007/978-3-319-58943-5_19
Publication status	Published - 28 May 2017
Event	22nd International Conference on Parallel and Distributed Computing, Euro-Par 2016 - Grenoble, France Duration: 24 Aug 2016 → 26 Aug 2016

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	10104
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	22nd International Conference on Parallel and Distributed Computing, Euro-Par 2016
Country/Territory	France
City	Grenoble
Period	24/08/16 → 26/08/16

Bibliographical note

Funding Information:
This work is being accomplished as a part of project ENTICE:“dEcentralised repositories for traNsparent and efficienT vIrtual maChine opErations”, funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 644179.

Publisher Copyright:
© Springer International Publishing AG 2017.

Funding

This work is being accomplished as a part of project ENTICE:“dEcentralised repositories for traNsparent and efficienT vIrtual maChine opErations”, funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 644179.

Keywords

Distributed storage repositories
Federated cloud environment
Multi-objective optimization

Access to Document

10.1007/978-3-319-58943-5_19

Cite this

Kimovski, D., Saurabh, N., Gec, S., Stankovski, V., & Prodan, R. (2017). Multi-objective optimization framework for VMI distribution in federated cloud repositories. In F. Desprez, & P.-F. Dutot (Eds.), Euro-Par 2016: Parallel Processing Workshops: Euro-Par 2016 International Workshops, Grenoble, France, August 24-26, 2016, Revised Selected Papers (1 ed., pp. 236-247). (Lecture Notes in Computer Science; Vol. 10104 ). Springer. https://doi.org/10.1007/978-3-319-58943-5_19

Kimovski, Dragi ; Saurabh, Nishant ; Gec, Sandi et al. / Multi-objective optimization framework for VMI distribution in federated cloud repositories. Euro-Par 2016: Parallel Processing Workshops: Euro-Par 2016 International Workshops, Grenoble, France, August 24-26, 2016, Revised Selected Papers. editor / Frederic Desprez ; Pierre-Francois Dutot. 1. ed. Springer, 2017. pp. 236-247 (Lecture Notes in Computer Science).

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title = "Multi-objective optimization framework for VMI distribution in federated cloud repositories",

abstract = "Cloud Federation facilitates the concept of aggregation of multiple services administered by different providers, thus opening the possibility for the customers to profit from lower cost and better performance, while allowing for the cloud providers to offer more sophisticated services. Unfortunately, current state-of-the-art does not provide any substantial means for streamlined adaptation of federated Cloud environments. One of the essential barriers that prevents Cloud federation is the inefficient management of distributed storage repositories for Virtual Machine Images (VMI). In such environments, the VMIs are currently stored by Cloud providers in proprietary centralised repositories without considering application characteristics and their runtime requirements, causing high deployment and instantiation overheads. In this paper, a novel multi-objective optimization framework for VMI placement across distributed repositories in federated Cloud environment has been proposed. Based on the communication performance requirements, VMI use patterns, and structure of images or input data, the framework provides efficient means for transparent optimization of the distribution and placement of VMIs across distributed repositories to significantly lower their provisioning time for complex resource requests and for executing the user applications.",

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Kimovski, D, Saurabh, N, Gec, S, Stankovski, V & Prodan, R 2017, Multi-objective optimization framework for VMI distribution in federated cloud repositories. in F Desprez & P-F Dutot (eds), Euro-Par 2016: Parallel Processing Workshops: Euro-Par 2016 International Workshops, Grenoble, France, August 24-26, 2016, Revised Selected Papers. 1 edn, Lecture Notes in Computer Science, vol. 10104 , Springer, pp. 236-247, 22nd International Conference on Parallel and Distributed Computing, Euro-Par 2016, Grenoble, France, 24/08/16. https://doi.org/10.1007/978-3-319-58943-5_19

Multi-objective optimization framework for VMI distribution in federated cloud repositories. / Kimovski, Dragi; Saurabh, Nishant; Gec, Sandi et al.
Euro-Par 2016: Parallel Processing Workshops: Euro-Par 2016 International Workshops, Grenoble, France, August 24-26, 2016, Revised Selected Papers. ed. / Frederic Desprez; Pierre-Francois Dutot. 1. ed. Springer, 2017. p. 236-247 (Lecture Notes in Computer Science; Vol. 10104 ).

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

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N1 - Funding Information: This work is being accomplished as a part of project ENTICE:“dEcentralised repositories for traNsparent and efficienT vIrtual maChine opErations”, funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 644179. Publisher Copyright: © Springer International Publishing AG 2017.

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Kimovski D, Saurabh N, Gec S, Stankovski V, Prodan R. Multi-objective optimization framework for VMI distribution in federated cloud repositories. In Desprez F, Dutot PF, editors, Euro-Par 2016: Parallel Processing Workshops: Euro-Par 2016 International Workshops, Grenoble, France, August 24-26, 2016, Revised Selected Papers. 1 ed. Springer. 2017. p. 236-247. (Lecture Notes in Computer Science). doi: 10.1007/978-3-319-58943-5_19

Multi-objective optimization framework for VMI distribution in federated cloud repositories

Abstract

Publication series

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Bibliographical note

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Keywords

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