An Intelligent Residual Resource Monitoring Scheme in Cloud Computing Environments
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초록
Recently, computational intelligence has received a lot of attention from researchers due to its potentialapplications to artificial intelligence. In computer science, computational intelligence refers to a machine’sability to learn how to compete various tasks, such as making observations or carrying out experiments. Weadopted a computational intelligence solution to monitoring residual resources in cloud computing environments. The proposed residual resource monitoring scheme periodically monitors the cloud-based host machines, sothat the post migration performance of a virtual machine is as consistent with the pre-migration performanceas possible. To this end, we use a novel similarity measure to find the best target host to migrate a virtualmachine to. The design of the proposed residual resource monitoring scheme helps maintain the quality ofservice and service level agreement during the migration. We carried out a number of experimental evaluationsto demonstrate the effectiveness of the proposed residual resource monitoring scheme. Our results show thatthe proposed scheme intelligently measures the similarities between virtual machines in cloud computingenvironments without causing performance degradation, whilst preserving the quality of service and servicelevel agreement.
Abstract
Recently, computational intelligence has received a lot of attention from researchers due to its potentialapplications to artificial intelligence. In computer science, computational intelligence refers to a machine’sability to learn how to compete various tasks, such as making observations or carrying out experiments. Weadopted a computational intelligence solution to monitoring residual resources in cloud computing environments. The proposed residual resource monitoring scheme periodically monitors the cloud-based host machines, sothat the post migration performance of a virtual machine is as consistent with the pre-migration performanceas possible. To this end, we use a novel similarity measure to find the best target host to migrate a virtualmachine to. The design of the proposed residual resource monitoring scheme helps maintain the quality ofservice and service level agreement during the migration. We carried out a number of experimental evaluationsto demonstrate the effectiveness of the proposed residual resource monitoring scheme. Our results show thatthe proposed scheme intelligently measures the similarities between virtual machines in cloud computingenvironments without causing performance degradation, whilst preserving the quality of service and servicelevel agreement.
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