Hierarchical VM scheduling to improve energy and performance efficiency in IaaS Cloud data centers

Efficient energy use has become a critical issue for resource management in Cloud data centers. Virtualization is a key technology for reducing energy cost and improving resource utilization in data centers. One of the challenges faced by virtualized data centers is to decide how to pack VMs on the least number of hosts. This paper presents a decentralized scheduling policy for dynamic consolidation of VMs equipped with ARIMA model to improve resource allocation by predicting resource usage of VMs in the near future so as to minimize Service Level Agreement (SLA) violations and energy consumption in Cloud data centers.