Multi-tenant virtualized infrastructures allow cloud providers to minimize costs through workload consolidation. One of the largest costs is power consumption, which is challenging to understand in heterogeneous environments. We propose a power modeling methodology that tackles this complexity using a divide-andconquer approach. Our results outperform previous research work, achieving a relative error of 2% on average and under 4% in almost all cases. Models are portable across similar architectures, enabling predictions of power consumption before migrating a tenant to a different hardware platform. Moreover, we show the models allow us to evaluate colocations of tenants to reduce overall consumption.

Power consumption models for multi-tenant server infrastructures

Ferroni, Matteo;CORNA, ANDREA;DAMIANI, ANDREA;Brondolin, Rolando;Santambrogio, Marco D.
2017-01-01

Abstract

Multi-tenant virtualized infrastructures allow cloud providers to minimize costs through workload consolidation. One of the largest costs is power consumption, which is challenging to understand in heterogeneous environments. We propose a power modeling methodology that tackles this complexity using a divide-andconquer approach. Our results outperform previous research work, achieving a relative error of 2% on average and under 4% in almost all cases. Models are portable across similar architectures, enabling predictions of power consumption before migrating a tenant to a different hardware platform. Moreover, we show the models allow us to evaluate colocations of tenants to reduce overall consumption.
2017
Multi-tenant cloud infrastructures; Power consumption models; Virtualization; Software; Information Systems; Hardware and Architecture
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1046990
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