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

Authors

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

Abstract

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.








Downloads

Published

2021-11-01

Issue

Vol. 29 No. 6 (2021): International Journal of Engineering Intelligent Systems

Section

General Submission

License

The submission of a paper implies that, if accepted for publication, it will not be published elsewhere in the same form, in any language, without the prior consent of the publisher. Before publication, authors are requested to assign copyright to CRL Publishing Ltd. This allows CRL to sanction photocopying, and to authorize the reprinting of issues or volumes according to demand. Authors' traditional rights will not be jeopardized by assigning Copyright in this way, as they retain the right to reuse the material following publication, and to veto third-party publication.