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Advisor(s)
Abstract(s)
A computação em nuvem teve um avanço considerável nos últimos anos, trazendo grandes
benefícios incluindo escalabilidade, flexibilidade, acessibilidade global, melhor utilização
de recursos e redução de custos, entre outros. Apesar de todos os benefícios,
esta adesão e crescimento trás consigo grandes desafios como otimização do uso de
recursos computacionais, redução de custos, garantia da qualidade de serviço (Quality
of Service (QoS)), segurança, etc. As garantias da qualidade de serviço são estabelecidas
através de Service Level Agreements (SLAs), que são contratos estabelecidos entre
o cliente e o fornecedor do serviço de computação em nuvem, visando especificar de
forma mensurável as metas de nível de serviço a serem cumpridas, além dos papéis
e responsabilidades das partes envolvidas. Este trabalho apresenta um estudo sobre
cumprimento de SLAs por algoritmos de alocação de máquinas virtuais em ambientes
de computação em nuvem. O trabalho tem em consideração métricas como disponibilidade,
custo, tempo de conclusão de uma aplicação (task completion time) e nível de
tolerância a faltas, avaliando o cumprimento de tais métricas em diferentes cenários.
O estudo é realizado utilizando o framework CloudSim Plus para modelação e execução
de simulações de computação em nuvem. São introduzidos dois módulos no framework
visando: (i) especificação de SLAs e templates de máquinas virtuais em formato
JavaScript Object Notation (JSON), seguindo padrões do Amazon Elastic Compute
Cloud (Amazon EC2); (ii) injeção de faltas aleatórias, permitindo avaliar como os SLAs
são afetados perante o surgimento de faltas nos servidores.
Por fim, o trabalho apresenta uma proposta para automação da criação e alocação de
máquinas virtuais, visando cumprir os SLAs e libertar o cliente da necessidade de especificar
a quantidade mínima de máquinas virtuais para atendimento dos níveis de serviço
exigidos. Mesmo com todo o nível de automação que os fornecedores de computação
em nuvem possam oferecer, os resultados obtidos mostram que é possível melhorar a
automação destes serviços, reduzindo a necessidade de intervenção do cliente e as violações
de SLA devido a uma inadequada configuração de máquinas virtuais realizada
pelo cliente.
Cloud computing has made considerable progress in recent years, bringing great benefits including scalability, flexibility, global accessibility, improved resource utilization and cost savings, among others. Despite all the benefits, this adhesion and growth carries with it great challenges such as optimization of the use of computational resources, reduction of costs, Quality of Service (QoS) assurance, security, etc. Guarantees are provided through Service Level Agreements (SLAs), which are agreements between the customer and the cloud computing service provider to measurably specify the service level goals to be fulfilled, as well as the roles and responsibilities of the parties involved. This work presents a study on compliance with service level agreements by algorithms for allocating virtual machines in cloud computing environments. The work takes into account metrics such as availability, cost, task completion time and level of fault tolerance, evaluating the compliance of such metrics in different scenarios. The study is conducted using the CloudSim Plus framework for modeling and running cloud computing simulations. Two modules are introduced in the framework about: (i) specification of SLAs and virtual machine templates in JSON format, following Amazon Elastic Compute Cloud (Amazon EC2) standards; (ii) injection of random faults, allowing to evaluate how the SLAs are affected by the occurrence of faults in servers. Finally, this work presents a proposal for automation of the creation and allocation of virtual machines, aiming to comply with the SLAs and free the client from the need to specify the minimum number of virtual machines to meet the required service levels. Even with all the automation level provided by cloud service providers, the obtained results show it is possible to further improve the automation of these services by reducing the need for customer intervention and SLA violations due to an inadequate configuration of virtual machines performed by the client.
Cloud computing has made considerable progress in recent years, bringing great benefits including scalability, flexibility, global accessibility, improved resource utilization and cost savings, among others. Despite all the benefits, this adhesion and growth carries with it great challenges such as optimization of the use of computational resources, reduction of costs, Quality of Service (QoS) assurance, security, etc. Guarantees are provided through Service Level Agreements (SLAs), which are agreements between the customer and the cloud computing service provider to measurably specify the service level goals to be fulfilled, as well as the roles and responsibilities of the parties involved. This work presents a study on compliance with service level agreements by algorithms for allocating virtual machines in cloud computing environments. The work takes into account metrics such as availability, cost, task completion time and level of fault tolerance, evaluating the compliance of such metrics in different scenarios. The study is conducted using the CloudSim Plus framework for modeling and running cloud computing simulations. Two modules are introduced in the framework about: (i) specification of SLAs and virtual machine templates in JSON format, following Amazon Elastic Compute Cloud (Amazon EC2) standards; (ii) injection of random faults, allowing to evaluate how the SLAs are affected by the occurrence of faults in servers. Finally, this work presents a proposal for automation of the creation and allocation of virtual machines, aiming to comply with the SLAs and free the client from the need to specify the minimum number of virtual machines to meet the required service levels. Even with all the automation level provided by cloud service providers, the obtained results show it is possible to further improve the automation of these services by reducing the need for customer intervention and SLA violations due to an inadequate configuration of virtual machines performed by the client.
Description
Keywords
Alocação de Máquinas Virtuais Cloudsim Plus Computação Em Nuvem Qualidade de Serviço Service Level Agreement Simulação