Fine-grained energy profiling for power-aware application design
ACM SIGMETRICS Performance Evaluation Review
Resource aware programming in the Pixie OS
Proceedings of the 6th ACM conference on Embedded network sensor systems
Aggressive dynamic voltage scaling for energy-aware video playback based on decoding time estimation
EMSOFT '09 Proceedings of the seventh ACM international conference on Embedded software
How lock contention affects energy use in a CMP server
Proceedings of the 24th ACM SIGPLAN conference companion on Object oriented programming systems languages and applications
Mercury: a wearable sensor network platform for high-fidelity motion analysis
Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems
Achieving viewing time scalability in mobile video streaming using scalable video coding
MMSys '10 Proceedings of the first annual ACM SIGMM conference on Multimedia systems
Semantic-less coordination of power management and application performance
ACM SIGOPS Operating Systems Review
eShare: a capacitor-driven energy storage and sharing network for long-term operation
Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems
Rank based dynamic voltage and frequency scaling fortiled graphics processors
CODES/ISSS '10 Proceedings of the eighth IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis
MobiCon: a mobile context-monitoring platform
Communications of the ACM
Proceedings of the International Conference on Computer-Aided Design
System-level application-aware dynamic power management in adaptive pipelined MPSoCs for multimedia
Proceedings of the International Conference on Computer-Aided Design
Journal of Systems and Software
A hierarchical distributed control for power and performances optimization of embedded systems
ARCS'10 Proceedings of the 23rd international conference on Architecture of Computing Systems
Energy-aware resource sharing with mobile devices
Computer Networks: The International Journal of Computer and Telecommunications Networking
An efficient renewable energy management and sharing system for sustainable embedded devices
Journal of Electrical and Computer Engineering
Adaptive power management of on-chip video memory for multiview video coding
Proceedings of the 49th Annual Design Automation Conference
Achieving long-term operation with a capacitor-driven energy storage and sharing network
ACM Transactions on Sensor Networks (TOSN)
Accurate characterization of the variability in power consumption in modern mobile processors
HotPower'12 Proceedings of the 2012 USENIX conference on Power-Aware Computing and Systems
Application modes: a narrow interface for end-user power management in mobile devices
Proceedings of the 14th Workshop on Mobile Computing Systems and Applications
Self-adaptive hybrid dynamic power management for many-core systems
Proceedings of the Conference on Design, Automation and Test in Europe
Agent-based distributed power management for kilo-core processors
Proceedings of the International Conference on Computer-Aided Design
Energy analysis and prediction for applications on smartphones
Journal of Systems Architecture: the EUROMICRO Journal
Hi-index | 0.02 |
In this paper, we present Chameleon an application-level power management approach for reducing energy consumption in mobile processors. By using application domain knowledge, as opposed to OS-level or hardware-level inferred knowledge, Chameleon can substantially reduce CPU energy consumption. By exporting the energy management to user-space, designers can design more flexible and easily portable algorithms and systems, and use multiple energy management policies simultaneously. Specifically, we propose a minimal operating system interface that applications use to obtain global knowledge from the kernel in order to make local decisions. We consider three classes of applications soft real-time, interactive and batch and design userlevel power management strategies for representative applications such as a movie player, a word processor, a web browser, and a batch compiler. Our experiments show that, compared to the traditional system-wide CPU voltage scaling approaches, Chameleon can achieve up to 32-50% energy savings while delivering comparable or better performance to applications. Similarly, Chameleon extracts 9-41% more energy when compared to GraceOS, which uses some application knowledge but operates within the kernel. Further, Chameleon imposes minimal overhead and is effective at scheduling concurrent applications with diverse energy needs.