Assessment to support the planning of sustainable data centers with high availability

• Ano de defesa: 2013
• Autor(a) principal: CALLOU, Gustavo Rau de Almeida
• Orientador(a): MACIEL, Paulo Romero Martins
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Universidade Federal de Pernambuco
• Palavras-chave em Português: Redes de Petri; Diagrama de blocos de confiabilidade; Modelo de fluxo de energia; Sustentabilidade; Dependabilidade and arquiteturas de data center; Petri nets; Reliability block diagrams; Energy flow model; Sustainability; Dependability and data center architectures
• Link de acesso: https://repositorio.ufpe.br/handle/123456789/12262

The advent of services such as cloud computing, social networks and e-commerce has led to an increased demand for computer resources from data centers. Prominent issues for data center designers are sustainability, cost, and dependability, which are significantly affected by the redundant architectures required to support these services. Within this context, models are important tools for designers when attempting to quantify these issues before implementing the final architecture. This thesis proposes a set of models for the integrated quantification of the sustainability impact, cost, and dependability of data center power and cooling infrastructures. This is achieved with the support of an evaluation environment which is composed of ASTRO, Mercury and Optimization tools. The approach taken to perform the system dependability evaluation employs a hybrid modeling strategy which recognizes the advantages of both stochastic Petri nets and reliability block diagrams. Besides that, a model is proposed to verify that the energy flow does not exceed the maximum power capacity that each component can provide (considering electrical devices) or extract (assuming cooling equipment). Additionally, an optimization method is proposed for improving the results obtained by Reliability Block Diagrams, Stochastic Petri nets and Energy Flow models through the automatic selection of the appropriate devices from a list of candidate components. This list corresponds to a set of alternative components that may compose the data center architecture. Several case studies are presented that analyze the environmental impact and dependability metrics as well as the operational energy cost of real-world data center power and cooling architectures.