FairCPU: Uma Arquitetura para Provisionamento de MÃquinas Virtuais Utilizando CaracterÃsticas de Processamento / FairCPU: An Architecture for Provisioning Virtual Machines Using Processing Features

AUTOR(ES)
FONTE

IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia

DATA DE PUBLICAÇÃO

02/03/2012

RESUMO

Resource scheduling is a key process for cloud computing platform, which generally uses virtual machines (VMs) as scheduling units. The use of virtualization techniques provides great flexibility with the ability to instantiate multiple VMs on one physical machine (PM), migrate them between the PMs and dynamically scale VMâs resources. The techniques of consolidation and dynamic allocation of VMs have addressed the impact of its use as an independent measure of location. It is generally accepted that the performance of a VM will be the same regardless of which PM it is allocated. This assumption is reasonable for a homogeneous environment where the PMs are identical and the VMs are running the same operating system and applications. Nevertheless, in a cloud computing environment, we expect that a set of heterogeneous resources will be shared, where PMs will face changes both in terms of their resource capacities and as also in data affinities. The main objective of this work is to propose an architecture to standardize the representation of the processing power by using processing units (PUs). Adding to that, the limitation of CPU usage is used to provide performance isolation and maintain the VMâs processing power at the same level regardless the underlying PM. The proposed solution considers the PMs heterogeneity present in the cloud infrastructure and provides scheduling policies based on PUs. The proposed architecture is called FairCPU and was implemented to work with KVM and Xen hypervisors. As study case, it was incorporated into a private cloud, built with the middleware OpenNebula, where several experiments were conducted. The results prove the efficiency of FairCPU architecture to use PUs to reduce VMsâ performance variability, as well as to provide a new way to represent and manage the processing power of the infrastructureâs physical and virtual machines.

ASSUNTO(S)

kvm xen opennebula computaÃÃo em nuvem processamento eletrÃnico de dados - processamento distribuido mÃquinas leitoras (processamento de dados) performance variability ciencia da computacao provisionamento de mÃquinas virtuais ambiente heterogÃneo limitaÃÃo do uso da cpu computaÃÃo em nuvem virtualizaÃÃo escalonamento unidade de processamento variabilidade de desempenho kvm xen opennebula virtual machines provisioning heterogeneous environment limit cpu usage cloud computing virtualization: scheduling processing unit

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