Hybrid approach for energy aware management of multi-cloud architecture integrating user machines

D Borgetto; Rodrigue Chakode; Benjamin Depardon; Cédric Eichler; Jean-Marie Garcia; H Hbaieb; Thierry Monteil; E Pelorce; A Rachdi; Ahmad Al Sheikh; P Stolf

Hybrid approach for energy aware management of multi-cloud architecture integrating user machines

D Borgetto ¹ Rodrigue Chakode ^{2, 3} Benjamin Depardon ⁴ Cédric Eichler ⁵ Jean-Marie Garcia ⁵ H Hbaieb ⁶ Thierry Monteil ⁵ E Pelorce ⁶ A Rachdi ⁷ Ahmad Al Sheikh ⁵ P Stolf ¹

1 IRIT - Institut de recherche en informatique de Toulouse

2 LIG - Laboratoire d'Informatique de Grenoble

3 MESCAL - Middleware efficiently scalable

Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble

4 SysFera [Villeurbanne]

5 LAAS-SARA - Équipe Services et Architectures pour Réseaux Avancés

LAAS - Laboratoire d'analyse et d'architecture des systèmes [Toulouse]

6 Degetel

7 QoS Design

Abstract : The arrival and development of remotely accessible services via the cloud has transfigured computer technology. However, its impact on personal computing remains limited to cloud-based applications. Meanwhile, acceptance and usage of telephony and smartphones have exploded. Their sparse administration needs and general user friendliness allows all people, regardless of technology literacy, to access, install and use a large variety of applications. We propose in this paper a model and a platform to offer personal computing a simple and transparent usage similar to modern telephony. In this model, user machines are integrated within the classical cloud model, consequently expanding available resources and management targets. In particular, we defined and implemented a modular architecture including resource managers at different levels that take into account energy and QoS concerns. We also propose simulation tools to design and size the underlying infrastructure to cope with the explosion of usage. Functionalities of the resulting platform are validated and demonstrated through various utilization scenarios. The internal scheduler managing resource usage is experimentally evaluated and compared with classical method-ologies, showing a significant reduction of energy consumption with almost no QoS degradation.

Keywords : autonomic computing sharing users resources hybrid cloud energy aware schedulers

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Journal articles

Domain :

Computer Science [cs]

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https://hal.archives-ouvertes.fr/hal-01228290
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