On the Optimization of Self-Organization and Self-Management Hardware Resource Allocation for Heterogeneous Clouds

There is a tendency, during the last years, to migrate from the traditional homogeneous clouds and centralized provisioning of resources to heterogeneous clouds with specialized hardware governed in a distributed and autonomous manner. The CloudLightning architecture proposed recently introduced a d...

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Autores principales:	Konstantinos M. Giannoutakis, Christos K. Filelis-Papadopoulos, George A. Gravvanis, Dimitrios Tzovaras
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	simulation optimization high performance computing heterogeneity cloud computing Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/916ad612c2bf498ba75fbe50388b760b
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spelling	oai:doaj.org-article:916ad612c2bf498ba75fbe50388b760b2021-11-25T17:17:27ZOn the Optimization of Self-Organization and Self-Management Hardware Resource Allocation for Heterogeneous Clouds10.3390/computers101101472073-431Xhttps://doaj.org/article/916ad612c2bf498ba75fbe50388b760b2021-11-01T00:00:00Zhttps://www.mdpi.com/2073-431X/10/11/147https://doaj.org/toc/2073-431XThere is a tendency, during the last years, to migrate from the traditional homogeneous clouds and centralized provisioning of resources to heterogeneous clouds with specialized hardware governed in a distributed and autonomous manner. The CloudLightning architecture proposed recently introduced a dynamic way to provision heterogeneous cloud resources, by shifting the selection of underlying resources from the end-user to the system in an efficient way. In this work, an optimized Suitability Index and assessment function are proposed, along with their theoretical analysis, for improving the computational efficiency, energy consumption, service delivery and scalability of the distributed orchestration. The effectiveness of the proposed scheme is being evaluated with the use of simulation, by comparing the optimized methods with the original approach and the traditional centralized resource management, on real and synthetic High Performance Computing applications. Finally, numerical results are presented and discussed regarding the improvements over the defined evaluation criteria.Konstantinos M. GiannoutakisChristos K. Filelis-PapadopoulosGeorge A. GravvanisDimitrios TzovarasMDPI AGarticlesimulationoptimizationhigh performance computingheterogeneitycloud computingElectronic computers. Computer scienceQA75.5-76.95ENComputers, Vol 10, Iss 147, p 147 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	simulation optimization high performance computing heterogeneity cloud computing Electronic computers. Computer science QA75.5-76.95
spellingShingle	simulation optimization high performance computing heterogeneity cloud computing Electronic computers. Computer science QA75.5-76.95 Konstantinos M. Giannoutakis Christos K. Filelis-Papadopoulos George A. Gravvanis Dimitrios Tzovaras On the Optimization of Self-Organization and Self-Management Hardware Resource Allocation for Heterogeneous Clouds
description	There is a tendency, during the last years, to migrate from the traditional homogeneous clouds and centralized provisioning of resources to heterogeneous clouds with specialized hardware governed in a distributed and autonomous manner. The CloudLightning architecture proposed recently introduced a dynamic way to provision heterogeneous cloud resources, by shifting the selection of underlying resources from the end-user to the system in an efficient way. In this work, an optimized Suitability Index and assessment function are proposed, along with their theoretical analysis, for improving the computational efficiency, energy consumption, service delivery and scalability of the distributed orchestration. The effectiveness of the proposed scheme is being evaluated with the use of simulation, by comparing the optimized methods with the original approach and the traditional centralized resource management, on real and synthetic High Performance Computing applications. Finally, numerical results are presented and discussed regarding the improvements over the defined evaluation criteria.
format	article
author	Konstantinos M. Giannoutakis Christos K. Filelis-Papadopoulos George A. Gravvanis Dimitrios Tzovaras
author_facet	Konstantinos M. Giannoutakis Christos K. Filelis-Papadopoulos George A. Gravvanis Dimitrios Tzovaras
author_sort	Konstantinos M. Giannoutakis
title	On the Optimization of Self-Organization and Self-Management Hardware Resource Allocation for Heterogeneous Clouds
title_short	On the Optimization of Self-Organization and Self-Management Hardware Resource Allocation for Heterogeneous Clouds
title_full	On the Optimization of Self-Organization and Self-Management Hardware Resource Allocation for Heterogeneous Clouds
title_fullStr	On the Optimization of Self-Organization and Self-Management Hardware Resource Allocation for Heterogeneous Clouds
title_full_unstemmed	On the Optimization of Self-Organization and Self-Management Hardware Resource Allocation for Heterogeneous Clouds
title_sort	on the optimization of self-organization and self-management hardware resource allocation for heterogeneous clouds
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/916ad612c2bf498ba75fbe50388b760b
work_keys_str_mv	AT konstantinosmgiannoutakis ontheoptimizationofselforganizationandselfmanagementhardwareresourceallocationforheterogeneousclouds AT christoskfilelispapadopoulos ontheoptimizationofselforganizationandselfmanagementhardwareresourceallocationforheterogeneousclouds AT georgeagravvanis ontheoptimizationofselforganizationandselfmanagementhardwareresourceallocationforheterogeneousclouds AT dimitriostzovaras ontheoptimizationofselforganizationandselfmanagementhardwareresourceallocationforheterogeneousclouds
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On the Optimization of Self-Organization and Self-Management Hardware Resource Allocation for Heterogeneous Clouds

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