Short-Term Prediction of Cloud Computing Virtual Resource Load Based on Openstack


  • Mingchao Wang College of Mechanical Electronic and Information Engineering,Wuxi Vocational Institute of Arts & Technology, Yixing 214206, China


The allocation of the cloud computing virtual resource load is vulnerable to cloud computing network transmission channel load ambiguity resulting in the poor configuration of this load. In order to improve the efficiency of load allocation, a link robustness prediction algorithm for cloud computing virtual resource load allocation based on OpenStack is proposed. The link routing node channel model of wireless sensor network is constructed, the spread spectrum processing of the data forwarding channel is carried out by wireless random sequence scheduling technology, the modulation component of link robustness prediction is calculated, and the channel transmission delay and multi-grained adaptive weighting value are obtained by the link routing node adaptive modulation method. The simulation results show that the short-term prediction of link robustness using this method
for load allocation in the cloud has high accuracy, strong anti-interference, low energy consumption and enhanced node activity.

Keywords: OpenStack, Cloud Computing, Virtual Resources, Load, Short-term Forecast.

Cite As

M. Wang, "Short-Term Prediction of Cloud Computing Virtual Resource Load Based on
Openstack", Engineering Intelligent Systems, vol. 29 no. 6, pp. 419-429, 2021.