Multiphase fault tolerance genetic algorithm for vm and task scheduling in datacenter

作者：

Highlights：

• Propose a genetic algorithm (GA) based multiphase fault tolerance (MFTGA) approach.

• MFTGA efficiently maps optimal VMs with users according to the service level agreement (SLA).

• Calculate the local fitness (fl) and global fitness (fg) of multiuser according to the SLA.

• MFTGA improve the reliability, latency, and reduce the failure of the task in the cloud computing environment.

摘要

•Propose a genetic algorithm (GA) based multiphase fault tolerance (MFTGA) approach.•MFTGA efficiently maps optimal VMs with users according to the service level agreement (SLA).•Calculate the local fitness (fl) and global fitness (fg) of multiuser according to the SLA.•MFTGA improve the reliability, latency, and reduce the failure of the task in the cloud computing environment.

论文关键词：Datacenter,Cloud computing,Fault tolerance algorithm,Machine learning,Genetic algorithm,Virtual machines,SLA

论文评审过程：Received 14 April 2021, Revised 22 June 2021, Accepted 28 June 2021, Available online 15 July 2021, Version of Record 15 July 2021.

论文官网地址：https://doi.org/10.1016/j.ipm.2021.102676