Title :
Energy-aware scheduling for infrastructure clouds
Author :
Knauth, Thomas ; Fetzer, Christof
Abstract :
More and more data centers are built, consuming ever more kilo watts of energy. Over the years, energy has become a dominant cost factor for data center operators. Utilizing low-power idle modes is an immediate remedy to reduce data center power consumption. We use simulation to quantify the difference in energy consumption caused exclusively by virtual machine schedulers. Besides demonstrating the inefficiency of wide-spread default schedulers, we present our own optimized scheduler. Using a range of realistic simulation scenarios, our customized scheduler OptSched reduces cumulative machine uptime by up to 60.1%. We evaluate the effect of data center composition, run time distribution, virtual machine sizes, and batch requests on cumulative machine uptime. IaaS administrators can use our results to quickly assess possible reductions in machine uptime and, hence, untapped energy saving potential.
Keywords :
cloud computing; computer centres; computer power supplies; energy conservation; energy consumption; optimisation; processor scheduling; virtual machines; IaaS; cumulative machine; customized scheduling; data center composition; data center operator; default scheduling; energy aware scheduling; energy consumption; energy saving; infrastructure cloud; optimized scheduling; run time distribution; virtual machine scheduling; Cloud computing; Indexes; Random access memory; Round robin; Scheduling; Servers; Virtual machining;
Conference_Titel :
Cloud Computing Technology and Science (CloudCom), 2012 IEEE 4th International Conference on
Conference_Location :
Taipei
Print_ISBN :
978-1-4673-4511-8
Electronic_ISBN :
978-1-4673-4509-5
DOI :
10.1109/CloudCom.2012.6427569