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Audric Lhoas

dblp:155/7277 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2015
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Cloud and datacenter computing · 77% Energy-efficient computing · 12% Performance modeling and evaluation · 12%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Cloud and datacenter computing
green cloud
0.212015
Modeling and Evaluation of Energy Policies in Green Clouds · IEEE Trans. Parallel Distributed Syst. 2015
Cloud and datacenter computing › resource allocation
resource allocation policy
0.212015
Modeling and Evaluation of Energy Policies in Green Clouds · IEEE Trans. Parallel Distributed Syst. 2015
Performance modeling and evaluation › stochastic petri nets
stochastic reward nets
0.112015
Modeling and Evaluation of Energy Policies in Green Clouds · IEEE Trans. Parallel Distributed Syst. 2015

Methods — techniques the papers use, named apart from their topics

stochastic reward nets · 0.2analytical modeling · 0.2
YearPublicationVenuePosition
2015 Modeling and Evaluation of Energy Policies in Green Clouds
abstract
Following the as-a-service philosophy, a cloud service provider offers computing utilities in the form of virtual resources instantiated on top of a physical infrastructure. In order to meet business requirements still providing high-quality services, performance evaluation needs to be carefully carried out with the aim of optimizing data center utilization and increasing user satisfaction. In this context, power efficiency plays a critical role pushing service providers towards the application of innovative green strategies. In this paper, we present an analytical framework, based on stochastic reward nets, that allows to evaluate different resource allocation policies in a green cloud. A use case is shown in order to illustrate the approach, modeling scattering and saturation allocation policies and comparing them to a purely physical data center scenario. A validation of the proposed model against the CloudSim framework is presented and several numerical results are provided, demonstrating the effectiveness of the approach as a powerful tool for a cloud service provider to perform well-informed decisions about the resource allocation policies to be enforced.
Dario Bruneo, Audric Lhoas, Francesco Longo 0001, Antonio Puliafito
IEEE Trans. Parallel Distributed Syst.2