Energy-Aware Dynamic Load Balancing of Virtual Machines (VMs) in Cloud Data Center with Adaptive Threshold (AT) based Migration

The in compliance between user requests and the specification of physical server in cloud computing led to poor load balancing, poor performance and large power consumption etc. Concentrating at this problem, this paper presents an energy-aware resource scheduling strategy based on dynamic migration of virtual machines. The strategy integrates the virtualization characteristics of cloud computing, presuming maximum and minimum thresholds, and selects those virtual machines on the physical servers that the load is over the upper values or load under the lower threshold values to be migrated, Boosting resource utilization of the cloud data center and reducing their energy consumption. To reduce migration here we integrate minimum migration time policy. Resulting experiments show that the strategy can reduce the migration times and the energy consumption of virtual machine migration, and further achieve load balancing and meet service level agreement (SLA) requirements.