Summary The adoption of infrastructure as a Service (IaaS) is a reality for academic, industrial, and governmental institutions. Cloud tenants request dynamically provisioned virtual infrastructures (VIs) tailored to their application requirements, detailing not only the virtual compute/storage resources but also the network components, topology, and services. The creation of a large number of cloud providers came along with the widespread use of VIs. The selection of an appropriate provider is a challenging task due to the diversity of the IaaS market and formally is a multicriteria analysis (NP‐hard). Notwithstanding the provider selection complexity, the mobility of VI‐hosted applications is limited due to the optimization anchors introduced by providers. Although the existing IaaS cloud brokers can indicate a hosting provider, they lack on conceptual and technical skills to migrate a VI and all its internal components between providers. This work enhances the state‐of‐the‐art on IaaS cloud brokerage by proposing virtual infrastructure multicriteria allocation and migration–based broker (VIMAM), which performs a multicriteria analysis of providers and VI migration. VIMAM is driven by an analytic hierarchy process (AHP) to select an IaaS provider, offering a set of predefined weighting schemas to represent distinct tenant perspectives. Moreover, to migrate a VI, VIMAM takes into account the virtual machines, containers, switches, and other topology elements. In addition to discussing the AHP ranking weights and frequency of providers selection, the experimental analysis details the implementation of an OpenStack and Docker–based prototype for VI migration.

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A utilização de contêineres passou a ser recentemente adotada como suporte para o provisionamento rápido de sistemas distribuídos. Microsserviços, processamento de fluxos de dados, computação nas bordas e outros sistemas complexos podem ser concretizados sob forma de contêineres. Entretanto, devido a heterogeneidade de configuração das requisições e a dimensionalidade dos Data Centers (DC) hospedeiros, o escalonamento de contêineres é um problema NP-Difícil. Ou seja, o advento do provisionamento facilitado sofre o impacto do tempo de resposta do escalonador. Um caminho eficiente para amenizar a complexidade do escalonamento é a utilização do processamento paralelo de alto desempenho. Neste contexto, o presente trabalho apresenta o EMULAG: um escalonador multicritério acelerado por GPU. A função objetivo do escalonador representa a perspectiva do provedor, buscando a consolidação do DC. Uma análise experimental revelou que a solução é escalável, apresentando resultados superiores aos encontrados na literatura, mas com baixo tempo de processamento.

Network management on multi-tenant containerbased data center has critical impact on performance. Tenants encapsulate applications in containers abstracting away details on hosting infrastructures, and entrust data center management framework with the provisioning of network Quality-of-Service requirements. In this paper, we propose a network-aware multicriteria container scheduler to jointly process containers and network requirements. We introduce a new Mixed Integer Linear Programming formulation for network-aware scheduling encompassing both tenants and providers metrics. We describe two GPU-accelerated modules to address the complexity barrier of the problem and efficiently process scheduling requests. Our experiments show that our scheduling approach accounting for both network and containers outperforms traditional algorithms used by containers orchestrators.