TOWARD ENERGY-EFFICIENT SCHEDULING USING WEIGHTED ROUND-ROBIN AND VM REUSE

Author

Abdulaziz Mohammed Alnowiser, Southern Illinois University CarbondaleFollow

Date of Award

12-1-2013

Degree Name

Master of Science

Department

Computer Science

First Advisor

Zhu, Dr. Michelle

Abstract

AN ABSTRACT OF THE THESIS OF Abdulaziz M. AlNowiser, for the Master of Science degree in Computer Science, presented on November 1, 2013, at Southern Illinois University Carbondale. TITLE: TOWARD ENERGY-EFFICIENT SCHEDULING USING WEIGHTED ROUND- ROBIN AND VM REUSE MAJOR PROFESSOR: Dr. Michelle M. Zhu In recent years, the rapid evolving Cloud Computing technologies multiply challenges such as minimizing power consumption and meeting Quality-of-Services (QoS) requirements in the presence of heavy workloads from a large number of users using shared computing resources. Powering a middle-sized data center normally consumes 80,000kW power every year and computer servers consume around .5% of the global power [1]. Statistics for 5000 production servers over a six-month period show that only 10-50% of the total capacity has been effectively used, and a large portion of the resources is actually wasted. In order to address the skyrocket energy cost from the high level resource management aspect, we propose an energy efficient job scheduling approach based on a modified version of Weighted Round Robin scheduler that incorporates VMs reuse and live VM migration without compromising the Service Level Agreement (SLA). The Weighted Round Robin scheduler can monitor the running VMs status for possible VM sharing for job consolidation or migration. In addition, the VMs utilization rate is observed to start live migration from the over-utilizing Processing Element (PE) to under-utilized PEs or to the hibernated PEs by sending WOL (Wake-On-LAN) signal to activate them. The simulation experiments are conducted under the CloudReports environment based on open source CloudSim simulator. The comparisons with other similar scheduling algorithms demonstrate that our enhanced Weighted Round Robin algorithm (EWRR) can achieve considerable better performance in terms of energy consumption and resource utilization rate.