Workload Classification & Software Energy Measurement for Efficient Scheduling on Private Cloud Platforms

At present there are a number of barriers to creating an energy efficient workload scheduler for a Private Cloud based data center. Firstly, the relationship between different workloads and power consumption must be investigated. Secondly, current hardware-based solutions to providing energy usage statistics are unsuitable in warehouse scale data centers where low cost and scalability are desirable properties. In this paper we discuss the effect of different workloads on server power consumption in a Private Cloud platform. We display a noticeable difference in energy consumption when servers are given tasks that dominate various resources (CPU, Memory, Hard Disk and Network). We then use this insight to develop CloudMonitor, a software utility that is capable of >95% accurate power predictions from monitoring resource consumption of workloads, after a "training phase" in which a dynamic power model is developed.

[1]  Feng Zhao,et al.  Virtual machine power metering and provisioning , 2010, SoCC '10.

[2]  Amin Vahdat,et al.  ECOSystem: managing energy as a first class operating system resource , 2002, ASPLOS X.

[3]  Lizy Kurian John,et al.  Complete System Power Estimation: A Trickle-Down Approach Based on Performance Events , 2007, 2007 IEEE International Symposium on Performance Analysis of Systems & Software.

[4]  Frank Bellosa,et al.  Energy Management for Hypervisor-Based Virtual Machines , 2007, USENIX Annual Technical Conference.

[5]  Ricardo Bianchini,et al.  Mercury and freon: temperature emulation and management for server systems , 2006, ASPLOS XII.

[6]  Richard E. Brown,et al.  Report to Congress on Server and Data Center Energy Efficiency: Public Law 109-431 , 2008 .

[7]  Ian Sommerville,et al.  The Cloud Adoption Toolkit: supporting cloud adoption decisions in the enterprise , 2010, Softw. Pract. Exp..

[8]  Vipin Chaudhary,et al.  VMeter: Power modelling for virtualized clouds , 2010, 2010 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum (IPDPSW).

[9]  Yi Yu,et al.  Energy Measurement for the Cloud , 2010, International Symposium on Parallel and Distributed Processing with Applications.

[10]  David C. Snowdon,et al.  Koala: a platform for OS-level power management , 2009, EuroSys '09.

[11]  William Stallings,et al.  SNMP and SNMPv2: the infrastructure for network management , 1998, IEEE Commun. Mag..