Resource monitoring method of the expandable cloud platform based on micro-service architecture Online publication date: Wed, 18-May-2022
by Dong He; Hongbing Huang; Yiyang Yao; Weiqiang Qi; Hong Li; Dong Mao
International Journal of Autonomous and Adaptive Communications Systems (IJAACS), Vol. 15, No. 1, 2022
Abstract: In order to improve the ability of resource monitoring and adaptive forwarding control of the scalable cloud platform, this paper proposes an esource monitoring method based on the microservice architecture. Built the optimised microservice architecture of the scalable cloud platform, and used the distributed cloud composite storage method to design the modular storage structure. Fuzzy correlation detection method was used to detect the characteristics of scalable cloud platform resources and to process information fusion. The microservice platform system was built on the scalable cloud platform for adaptive clustering. Mining association rule set of scalable cloud platform resources in cluster center, based on microservice architecture. Simulation results show that when the SNR is - 2 dB, the output bit error rate of the proposed method is 0. The results show that this method has good information scheduling ability in scalable cloud platform resource monitoring, and can provide a stable resource output balance.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Autonomous and Adaptive Communications Systems (IJAACS):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com