Cloud federation offers new business models to enforce more flexible energy management strategies. Independent Cloud providers are exclusively bounded to the specific energy supplier powering its Data Centers. The situation radically change if we consider a federation of cooperating Cloud providers. In such a context a proper migration of virtual machines among providers can lead to global energy sustainability and cost-saving strategy. In this paper, we discuss a decision system for Cloud federation brokerage able to combine these two strategies. More specifically, we present Multi-Criteria Decision Making (MCDM) algorithm able to discover the most convenient Cloud providers candidate to join a particular energy-aware federation. In the end, modelling different possible real Cloud providers, we demonstrate how the algorithm can accommodate different Cloud federation scenarios characterized by particular energy-aware parameters.

Re-Powering Service Provisioning in Federated Cloud Ecosystems: An Algorithm Combining Energy Sustainability and Cost-Saving Strategies

Giacobbe, Maurizio;Celesti, Antonio
Conceptualization
;
Fazio, Maria;Villari, Massimo;Puliafito, Antonio
2018-01-01

Abstract

Cloud federation offers new business models to enforce more flexible energy management strategies. Independent Cloud providers are exclusively bounded to the specific energy supplier powering its Data Centers. The situation radically change if we consider a federation of cooperating Cloud providers. In such a context a proper migration of virtual machines among providers can lead to global energy sustainability and cost-saving strategy. In this paper, we discuss a decision system for Cloud federation brokerage able to combine these two strategies. More specifically, we present Multi-Criteria Decision Making (MCDM) algorithm able to discover the most convenient Cloud providers candidate to join a particular energy-aware federation. In the end, modelling different possible real Cloud providers, we demonstrate how the algorithm can accommodate different Cloud federation scenarios characterized by particular energy-aware parameters.
2018
978-3-319-72124-8
978-3-319-72125-5
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11570/3087809
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