Network-Aware Energy-Efficient Virtual Machine Management in Distributed Cloud Infrastructures with On-Site Photovoltaic Production

Camus, Benjamin; Dufossé, Fanny; Blavette, Anne; Quinson, Martin; Orgerie, Anne‐Cécile

doi:10.1109/cahpc.2018.8645901

Cited by 3 publications

(8 citation statements)

References 14 publications

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“…In this work, jobs are allocated at submission time and stay on the same node for all their duration. The benefits of migrating job between nodes to exploit more green power or to improve the consolidation could be investigated [5]. Also, here we consider a fixed Fog architecture that is connected through wired networks.…”

Section: E Discussionmentioning

confidence: 99%

“…In this work, we consider on-site renewable energy production with sources owned by the Fog operator, as it is the case for large-scale Cloud providers [5]. Yet, as we have shown through simulation, exploiting local renewable energy sources in a low-power Fog architecture is complex, even when the geographic distribution allows for variable green production, and even with simple models (e.g.…”

Section: E Discussionmentioning

confidence: 99%

“…During shutting down or booting, a node consumes as much as if all its cores were fully loaded. Each node is considered to take 150 seconds to boot and 10 seconds to shut down [5].…”

Section: A Experimental Setupmentioning

confidence: 99%

“…Many works have been conducted to reduce the environmental impact of the Cloud, either by reducing its overall consumption [3], [8], or by considering the usage of energy coming from renewable sources [12], [18], [23], [2], [5]. These works present noticeable advancements, according to the current architectures of the Cloud.…”

Section: Introductionmentioning

confidence: 99%

“…produced by renewable sources). More and more Cloud providers resort to producing their own renewable energy, like Apple for instance [5]. Yet, the distributed nature of Fog resources makes it harder to exploit locally-produced green energy as more sites are considered.…”

Section: Introductionmentioning

confidence: 99%

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Optimizing Green Energy Consumption of Fog Computing Architectures

Gougeon

Camus

Orgerie

2020

2020 IEEE 32nd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD)

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The Cloud already represents an important part of the global energy consumption, and this consumption keeps increasing. Many solutions have been investigated to increase its energy efficiency and to reduce its environmental impact. However, with the introduction of new requirements, notably in terms of latency, an architecture complementary to the Cloud is emerging: the Fog. The Fog computing paradigm represents a distributed architecture closer to the end-user. Its necessity and feasibility keep being demonstrated in recent works. However, its impact on energy consumption is often neglected and the integration of renewable energy has not been considered yet. The goal of this work is to exhibit an energy-efficient Fog architecture considering the integration of renewable energy. We explore three resource allocation algorithms and three consolidation policies. Our simulation results, based on real traces, show that the intrinsic low computing capability of the nodes in a Fog context makes it harder to exploit renewable energy. In addition, the share of the consumption from the communication network between the computing resources increases in this context, and the communication devices are even harder to power through renewable sources.

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Section: E Discussionmentioning

confidence: 99%

Section: E Discussionmentioning

confidence: 99%

“…During shutting down or booting, a node consumes as much as if all its cores were fully loaded. Each node is considered to take 150 seconds to boot and 10 seconds to shut down [5].…”

Section: A Experimental Setupmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Optimizing Green Energy Consumption of Fog Computing Architectures

Gougeon

Camus

Orgerie

2020

2020 IEEE 32nd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD)

Self Cite

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Amadeus Migration Process a Simulation-Driven Process to Enhance the Migration to a Multi-Cloud Environment

Romdhanne¹,

Boudia²,

Bondoux³

2023

Advanced Computer Science and Information Technology Trends

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With the development of the cloud offers, we observe a prominent trend of applications being migrated from private infrastructure to the cloud. Depending on the application’s complexity, the migration can be complex and needs to consider several dimensions, such as dependency issues, service continuity, and the service level agreement (SLA). Amadeus, the travel industry leader, had partnered with Microsoft to migrate its IT ecosystem to the Azure cloud. This work addresses the specificity of cloud-to-cloud migration and the multi-cloud constraints. In this paper, we summarise the Amadeus Migration process. The process aims to drive the migration from an initial private cloud environment to a target environment that can be a public or hybrid cloud. Further, the process focuses on a prediction phase that guides the migration process. This paper expects to provide an efficient decision-making process that guides managers and architects to optimise and secure their migration process while considering micro-servicesoriented applications targeting an efficient deployment over multi-cloud or hybrid cloud. The prediction relies on the network simulation to predict applications’ behaviour in the cloud and evaluate different scenarios and deployment topologies beforehand. The objective is to predict migrated applications’ behaviour and identify any issue related to the performance, the application’s dependency on other components, or the deployment in the cloud. The migration process proposed in this paper relies on SimGrid, a toolkit developed by INRIA[52] for distributed application modelling. This framework offers a generic process to model IT infrastructure and can assist cloud-to-cloud migration. Specific attention is given to predictive and reactive optimisations. The first results show predictive optimisation's impact on securing KPI and reactive optimisation to optimise the solution cost. Thus, we reach an average cost reduction of 40% in comparaison with the same deployment strategy while keeping the same SLA.

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Levantamento sobre Técnicas de Escalonamento para Computação Verde em Nuvem

Vasconcelos¹,

Cordeiro²

2020

Anais Da XI Escola Regional De Alto Desempenho De São Paulo (ERAD-SP 2020)

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A popularização do uso de plataformas de Computação em Nuvem resultou em um aumento significativo do uso de energia elétrica para a operação de tais plataformas: cerca de 1% da energia produzida no mundo é utilizada em data centers. Este trabalho apresenta uma revisão exploratória sobre as técnicas de gerenciamento de recursos computacionais e de escalonamento para plataformas de Computação em Nuvem que tem como objetivo maximizar o uso de energias renováveis.

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Network-Aware Energy-Efficient Virtual Machine Management in Distributed Cloud Infrastructures with On-Site Photovoltaic Production

Cited by 3 publications

References 14 publications

Optimizing Green Energy Consumption of Fog Computing Architectures

Optimizing Green Energy Consumption of Fog Computing Architectures

Amadeus Migration Process a Simulation-Driven Process to Enhance the Migration to a Multi-Cloud Environment

Levantamento sobre Técnicas de Escalonamento para Computação Verde em Nuvem

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