Coordinated management of power usage and runtime performance

With the continued growth of computing power and reduction in physical size of enterprise servers, the need for actively managing electrical power usage in large datacenters is becoming ever more pressing. By far the greatest savings in electrical power can be effected by dynamically consolidating workload onto the minimum number of servers needed at a given time and powering off the remainder. However, simple schemes for achieving this goal fail to cope with the complexities of realistic usage scenarios. In this paper we present a combined power-and performance-management system that builds on a state-of-the-art performance manager to achieve significant power savings without unacceptable loss of performance. In our system, the degree to which performance may be traded off against power is itself adjustable using a small number of easily-understood parameters, permitting administrators in different facilities to select the optimal tradeoff for their needs. We characterize the power saved, the effects of the tradeoff between power and performance, and the changes in behavior as the tradeoff parameters are adjusted, both in simulation and in a sample deployment of the real system.

[1]  Asser N. Tantawi,et al.  Performance management for cluster-based web services , 2005, IEEE Journal on Selected Areas in Communications.

[2]  Asser N. Tantawi,et al.  Performance management for cluster based Web services , 2003 .

[3]  E. N. Elnozahy,et al.  Energy Conservation Policies for Web Servers , 2003, USENIX Symposium on Internet Technologies and Systems.

[4]  Kang G. Shin,et al.  Online Web Cluster Capacity Estimation and Its Application to Energy Conservation , 2007, IEEE Transactions on Parallel and Distributed Systems.

[5]  Wolf-Dietrich Weber,et al.  Power provisioning for a warehouse-sized computer , 2007, ISCA '07.

[6]  Andrzej Kochut,et al.  Dynamic Placement of Virtual Machines for Managing SLA Violations , 2007, 2007 10th IFIP/IEEE International Symposium on Integrated Network Management.

[7]  Michael Kistler,et al.  The case for power management in web servers , 2002 .

[8]  Rajarshi Das,et al.  Coordinating Multiple Autonomic Managers to Achieve Specified Power-Performance Tradeoffs , 2007, Fourth International Conference on Autonomic Computing (ICAC'07).

[9]  G. Pacifici,et al.  Managing the Response Time for Multi-tiered Web Applications , 2005 .

[10]  Asser N. Tantawi,et al.  Dynamic estimation of CPU demand of web traffic , 2006, valuetools '06.

[11]  Malgorzata Steinder,et al.  A scalable application placement controller for enterprise data centers , 2007, WWW '07.

[12]  Nagarajan Kandasamy,et al.  Adaptive Performance Control of Computing Systems via Distributed Cooperative Control: Application to Power Management in Computing Clusters , 2006, 2006 IEEE International Conference on Autonomic Computing.

[13]  Anand Sivasubramaniam,et al.  Managing server energy and operational costs in hosting centers , 2005, SIGMETRICS '05.

[14]  Asser N. Tantawi,et al.  Dynamic placement for clustered web applications , 2006, WWW '06.

[15]  E. N. Elnozahy,et al.  Energy-Efficient Server Clusters , 2002, PACS.

[16]  Amin Vahdat,et al.  Managing energy and server resources in hosting centers , 2001, SOSP.

[17]  Kang G. Shin,et al.  Real-time dynamic voltage scaling for low-power embedded operating systems , 2001, SOSP.