78. ENERGY MANAGEMENT IN VIRTUALIZED ENVIRONMENTS
Department: Computer Science & Engineering
Research Institute Affiliation: Graduate Program in Computational Science, Mathematics, and Engineering (CSME)
Faculty Advisor(s):
Tajana Simunic-Rosing
Primary Student
Name: Raid Ayoub Ayoub
Email: rayoub@ucsd.edu
Phone: 858-534-9892
Grad Year: 2010
Student Collaborators
Giacomo Marchetti, gmarchet@ucsd.edu | Gaurav Dhiman, gdhiman@ucsd.edu
Abstract
The cost of energy consumption in modern data centers has reached and even surpassed the cost of the physical data center itself. This necessitates research for dynamically reducing the amount of energy used for computing, cooling and maintaining a data center. This is the primary motivation for this work, i.e. to develop data center power management scheme that delivers energy efficiency while minimizing the impact on performance.
Our approach is based on developing policies for power management techniques like dynamic power management (DPM) and dynamic voltage frequency scaling (DVFS) based on online learning for a computing system. Such an approach reduces these problems to one of dynamic workload characterization, where the policies adapt to changes in the workloads. Our experiments with CPU and hard disks confirm the efficiency and adaptability of our online learning based policies. We further propose extensions to adapt this approach in a virtualized environment encompassing multiple virtual and physical machines, which is fairly common in modern data centers. The idea is to perform characterization of virtual machines at the hypervisor level in order to drive both the power management policies and energy aware scheduling. The energy aware scheduler would schedule virtual machines both within and across physical machines for higher energy efficiency.
All Content Copyright 2008 Regents of the University of California. All rights reserved.
Official Web page of the University of California, San Diego.
