Business and Environment Performance Evaluation in Supply Chains: A Formal Model-Driven Approach

Alves, Gabriel; Maciel, Paulo; Lima, Ricardo; Magnani, Fábio Santana

doi:10.5772/10621

Cited by 2 publications

(2 citation statements)

References 53 publications

(61 reference statements)

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“…In general, the analysis of exergy in the context of sustainability seeks to maximize the efficiency of energy use or evaluate the degradation of natural resources [19]. This work measures the exergy destroyed in an electrical architecture of cloud computing.…”

Section: B Exergy and Sustainabilitymentioning

confidence: 99%

An Algorithm to Optimize Electrical Flows

Ferreira

Callou

Dantas

et al. 2013

2013 IEEE International Conference on Systems, Man, and Cybernetics

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Cloud computing has expanded in recent years due to many effects, such as accessibility, reliability, and collaboration. To provide those functionalities high availability is in demand, which implies a higher electric energy consumption by the computers that support the cloud infrastructure. Studies that pay attention to this electric energy consumption are important due to its impact on sustainability and operational costs. This paper proposes a power load distribution algorithm (PLDA) to optimize electrical flows of power infrastructures. The PLDA adopts the Energy Flow Model (EFM) as its basis. The EFM is a model that computes sustainability impacts and cost issues, while it respects the energy providing restrictions of each component. In addition, a case study illustrates the applicability of the proposed PLDA through the analysis of six private cloud power architectures. Considerable results were observed, including a reduction on energy consumption of 10.7%, and an improvement (reduction) on the environmental impact of over 140% was obtained.

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Section: B Exergy and Sustainabilitymentioning

confidence: 99%

An Algorithm to Optimize Electrical Flows

Ferreira

Callou

Dantas

et al. 2013

2013 IEEE International Conference on Systems, Man, and Cybernetics

Self Cite

View full text Add to dashboard Cite

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“…Em geral, a análise de exergia, no contexto da sustentabilidade, procura maximizar a eficiência da utilização de energia ou avaliar a degradação dos recursos naturais [16]. Este trabalho mede a exergia destruída.…”

Section: Exergia E Sustentabilidadeunclassified

Stochastic Models for Optimizing Availability, Cost and Sustainability of Data Center Power Architectures through Genetic Algorithm

Austregésilo

Callou

2019

RITA

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In recent years, the growth of information technology has required higher reliability, accessibility, collaboration, availability, and a reduction of costs on data centers due to factors such as social network, cloud computing, and e-commerce. These systems require redundant mechanisms on the data center infrastrucutre to achieve high availability, which may increase the electric energy consumption, impacting in both the sustainability and cost. This work proposes a multi-objective optimization approach, based on Genetic Algorithms, to optimize cost, sustainability and availability of data center power infrastructures. The main goal is to maximize availability and minimize cost and exergy consumed (adopted to estimate the environmental impacts). In order to compute such metrics, this work adopts the energy flow model (EFM), reliability block diagrams (RBD) and stochastic petri nets (SPN). Two case studies are conducted to show the applicability of the proposed strategy: (i) takes into account 5 typical data center architectures that were optimized to conduct the validation process of the proposed strategy; (ii) uses the optimization strategy in two architectures classified by ANSI / TIA-942 (TIER I and II). In both case studies, significant improvements were achieved in the results, which were very close to the optimum one that was obtained by a brute force algorithm that analyzes all the possibilities and returns the optimal solution. It is worth mentioning that the time used to obtain the results using the genetic algorithm approach was significantly lower (6,763,260 times), in comparison with the strategy which combines all the possible combinations to obtain the optimal result. Resumo: Nos últimos anos, o crescimento da tecnologia da informação exigiu maior confiabilidade, acessibilidade, colaboração, disponibilidade e redução de custos nos data centers devido a fatores como redes sociais, computação em nuvem e comércio eletrônico. Esses sistemas exigem mecanismos redundantes na infraestrutura do data center para alcançar uma alta disponibilidade, o que pode aumentar o consumo de energia elétrica, impactando tanto na sustentabilidade quanto no custo. Este trabalho propõe uma abordagem de otimização multi-objetivo, baseada em Algoritmos Genéticos, para otimizar custos, sustentabilidade e disponibilidade de infraestruturas de energia em data centers. O principal objetivo é maximizar a disponibilidade e minimizar o custo e a exergia consumida (adotada para estimar os impactos ambientais). Para computar tais métricas, este trabalho adota o modelo de fluxo de energia (EFM), diagramas de blocos de confiabilidade (RBD) e redes de petri estocásticas (SPN). Dois estudos de caso são conduzidos: (i) leva em consideração 5 arquiteturas típicas de data centers para mostrar a aplicabilidade e validação da estratégia proposta; (ii) utiliza a estratégia de otimização em duas arquiteturas classificadas pela norma ANSI/TIA-942 (TIER I e II). Em ambos estudos de caso, observou-se uma melhora significativa nos resultados que fic...

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Business and Environment Performance Evaluation in Supply Chains: A Formal Model-Driven Approach

Cited by 2 publications

References 53 publications

An Algorithm to Optimize Electrical Flows

An Algorithm to Optimize Electrical Flows

Stochastic Models for Optimizing Availability, Cost and Sustainability of Data Center Power Architectures through Genetic Algorithm

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