Abstract
In recent years, the rapid evolving Cloud Computing technologies multiply challenges including minimum power consumption and Quality-of-Services (QoS) requirements in the presence of heavy workloads from a large number of users. Powering a middle-sized data center normally consumes 80,000kW power every year. In order to address the skyrocketed energy cost from the resource management aspect, we proposed an energy efficient job scheduling approach based on a modified Weighted Round Robin scheduler that incorporates VMs reuse and live VM migration without compromising the Service Level Agreement (SLA). Enhanced Weighted Round Robin (EWRR) algorithm enhanced scheduler monitors and evaluates the running VMs status for possible task consolidation or VM Migration. In addition, VM Manager observes the VMs utilization rate to start live migration from the over-utilized Processing Element (PE) to under-utilized PEs or to the hibernated PEs by sending WOL (Wake-On-LAN) signal to guarantee performance. Moreover, we integrated a Dynamic Voltage and Frequency Scaling (DVFS) algorithm to specify the minimum VM frequency for each task depending on the task complexity and the execution deadline.