Prediction method of physical host resource status in iaas cloud environment

Abstract

The present invention discloses a physical host resource state forecasting method under an IaaS cloud environment. The method comprises the following steps of: Step A: determining an IaaS cloud resource demand forecasting process as a Hidden Markov Process (HMP); Step B: determining an observation state set and a hidden state set of physical host resources; Step C: constructing an HMP model for forecasting of IaaS cloud platform resources; and Step D: scheduling resources according to the forecasting state of the HMP Model forecast according to IaaS cloud platform resources. According to the physical host resource state forecasting method under an IaaS cloud environment, the migration timing selection problem of a virtual machine is well solved, the violation rate of SLA is decreased, and the energy consumption is reduced. According to the physical host resource state forecasting method under an IaaS cloud environment, determining the IaaS cloud resource demand forecasting process as the HM, is correct and effective. The controllability of resource demands and the green energy-conserving goal can be well realized according to the forecasting process.

Description

technical field [0001] The invention relates to the technical field of cloud platform applications, in particular to a method for predicting the resource state of a physical host in an IaaS cloud environment. Background technique [0002] In a cloud environment, improving resource utilization is an important means that must be considered for energy consumption perception and load balancing, and resource utilization is reflected by changing the resource status of physical hosts through virtual machine migration operations. Therefore, virtual machine migration is an important method for IaaS cloud resource scheduling. particularly important key technologies. [0003] At present, in the research on IaaS cloud resource scheduling strategy, violation of SLA or overload of physical host is the triggering factor of virtual machine migration, which will inevitably lead to system performance degradation and additional energy consumption costs, which are the consequences of post-proce...

AI Technical Summary

Problems solved by technology

Overload and underload of the server are the two operating states of the physical host. Overload will cause the possibility of violating the SLA, while underload will cause the resource utilization of the physical host to be low, resulting in additional waste of energy consumption.

[0005] It can be seen that there is currently no method to reduce the SLA violation rate of the IaaS cloud platform based on the relationship between the energy consumption cost of virtual machine migration and the power income of the physical host and the shutdown of the physical host, and further improvement is urgently needed

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