System-level power optimization: techniques and tools
ACM Transactions on Design Automation of Electronic Systems (TODAES)
A predictive system shutdown method for energy saving of event-driven computation
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Dynamic power management of complex systems using generalized stochastic Petri nets
Proceedings of the 37th Annual Design Automation Conference
Dynamic power management for portable systems
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
Run-time power estimation in high performance microprocessors
ISLPED '01 Proceedings of the 2001 international symposium on Low power electronics and design
Managing energy and server resources in hosting centers
SOSP '01 Proceedings of the eighteenth ACM symposium on Operating systems principles
ECOSystem: managing energy as a first class operating system resource
Proceedings of the 10th international conference on Architectural support for programming languages and operating systems
Comparing System-Level Power Management Policies
IEEE Design & Test
Dynamic Power Management for Nonstationary Service Requests
IEEE Transactions on Computers
Adaptive Disk Spin-down Policies for Mobile Computers
MLICS '95 Proceedings of the 2nd Symposium on Mobile and Location-Independent Computing
The Case for Higher-Level Power Management
HOTOS '99 Proceedings of the The Seventh Workshop on Hot Topics in Operating Systems
Policy optimization for dynamic power management
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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A significant volume of research has concentrated on operating-system directed power management (OSPM). The primary focus of previous research has been the development of OSPM policies. Under different conditions, one policy may outperform another and vice versa. In this paper, we explain how to select the best policies at run-time without user or administrator intervention. We present a hardware-neutral architecture portable across different platforms running Linux. Our experiments reveal that changing policies at run-time can adapt to workloads more quickly than using any of the policies individually.