In recent years,as an emerging technology,cloud computing has pro-vided us with convenient services,and power consumption on issues have be-come increasingly *** machine live migration technology has be-come an import...
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In recent years,as an emerging technology,cloud computing has pro-vided us with convenient services,and power consumption on issues have be-come increasingly *** machine live migration technology has be-come an important technology to reduce the power consumption of cloud com-puting *** the process of virtual machine migration,the performance of the virtual machine is inevitably degraded,which may violate service level agree-ment(SLA,Service Level Agreement).How to use virtual machine live migra-tion technology to reduce power consumption as much as possible while ensuring a low SLA violation rate becomes a hot *** paper aims to optimize the light loaddetection and virtual machine redistribution in the virtual machine live migration *** at the problem that the existing virtual machine light loaddetection method is easy to cause "over-migration",this paper proposes a threshold-based minimum CPU utilization method for light loaddetection,which effectively avoids excessive virtual machine *** at the problem that the current process of virtual machine re allocation algorithm is relatively simple,and there is a certain power loss space,we present power aware simula-tion annealing algorithm(PASA).The algorithm combines the simulated anneal-ing algorithm based on the power aware best fit decreasing algorithm(PABFD),which largely avoids the disadvantage that the PABFD easily falls into the local optimal solution *** paper uses the CloudSim simulator as simulation *** results show that compared with the best algorithm combination pro-posed by the previous researchers,the power consumption of the new algorithm combination proposed in the paper is reduced by 16.79%,and the SLA violation rate is reduced by 85.37%.Combining the two algorithms together can lead to better energy efficiency,performance and quality of service than using the two algorithms.
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