Affiliation:
1. Department of Information Engineering, Liuzhou City Vocational College, Liuzhou, 545002 Guangxi, China
Abstract
When deploying infrastructure as a service (IaaS) cloud virtual machines using the existing algorithms, the deployment process cannot be simplified, and the algorithm is difficult to be applied. This leads to the problems of high energy consumption, high number of migrations, and high average service-level agreement (SLA) violation rate. In order to solve the above problems, an adaptive deployment algorithm for IaaS cloud virtual machines based on
learning mechanism is proposed in this research. Based on the deployment principle, the deployment characteristics of the IaaS cloud virtual machines are analyzed. The virtual machine scheduling problem is replaced with the Markov process. The multistep
learning algorithm is used to schedule the virtual machines based on the
learning mechanism to complete the adaptive deployment of the IaaS cloud virtual machines. Experimental results show that the proposed algorithm has low energy consumption, small number of migrations, and low average SLA violation rate.
Subject
Electrical and Electronic Engineering,Instrumentation,Control and Systems Engineering
Reference23 articles.
1. Hybrid seismic-electrical data acquisition station based on cloud technology and green IoT;S. Qiao;IEEE Access,2020
2. Cloud technology is the foundation for designing efficient application;M. K. Bouza;Artificial Intelligence,2019
3. An efficient energy-aware method for virtual machine placement in cloud data centers using the cultural algorithm
4. Virtual machine deployment and migration optimization mechanism for cloud data center;Z. Lei;Computer Engineering and Design,2019
5. Research on preemptible virtual machine instance configuration and scheduling methods that meet the execution time limit of workflow;J. Liao;Computer Engineering and Science,2020