Power-aware scheduling of virtual machines in DVFS-enabled clusters

Abstract

Abstract-With the advent of Cloud computing, large-scale virtualized compute and data centers are becoming common in the computing industry. These distributed systems leverage commodity server hardware in mass quantity, similar in theory to many of the fastest Supercomputers in existence today. However these systems can consume a cities worth of power just to run idle, and require equally massive cooling systems to keep the servers within normal operating temperatures. This produces CO2 emissions and significantly contributes to the growing environmental issue of Global Warming. Green computing, a new trend for high-end computing, attempts to alleviate this problem by delivering both high performance and reduced power consumption, effectively maximizing total system efficiency. This paper focuses on scheduling virtual machines in a compute cluster to reduce power consumption via the technique of Dynamic Voltage Frequency Scaling (DVFS). Specifically, we present the design and implementation of an efficient scheduling algorithm to allocate virtual machines in a DVFS-enabled cluster by dynamically scaling the supplied voltages. The algorithm is studied via simulation and implementation in a multi-core cluster. Test results and performance discussion justify the design and implementation of the scheduling algorithm.

Towards Energy Aware Scheduling for Precedence Constrained Parallel Tasks in a Cluster with DVFS

“…• In addition to parallel applications, virtual machine scheduling can also use DVFS [1]. Our research in this paper falls into the first category: scheduling DAGs on multiple processors in a cluster with DVFS techniques.…”

“…By lowering processor clock frequency and supply voltage during some time slots, for example, idle or communication phases, large reductions in power consumption can be achieved with only modest performance losses. A DVFS-enabled cluster [1] is a compute cluster where compute nodes can run at multiple power/performance operating points. The DVFS techniques have been applied in the high performance computing fields, for example, in large data centers, to reduce power consumption and achieve high reliability and availability [12], [13], [14].…”

“…Nowadays, high end computing facilities can consume a very large amount of power albeit they provide high performance computing solutions for scientific and engineering applications [1]. For example, operating a middle-sized data center (i.e., a university data center) demands 80000kW power [2].…”

An energy management system for cluster infrastructures

“…Examples of BQS are Torque/PBS 1 , SLURM 2 , Son of GE 3 . Examples of CMS are OpenNebula 4 , OpenStack 5 or CloudStack 6 .…”

“…New technologies, such as Solid State Drives (SSD), are also being adopted for disks in order to reduce the energy consumed by mechanical parts, which accounts for up to 65% of the total amount of energy consumed by a computer [5]. Dynamic Voltage and Frequency Scaling (DVFS) is an efficient technology to control the processor power consumption [6].…”