Application-driven power management for mobile communication
Wireless Networks
Requester-aware power reduction
ISSS '00 Proceedings of the 13th international symposium on System synthesis
Application Transformations for Energy and Performance-Aware Device Management
Proceedings of the 2002 International Conference on Parallel Architectures and Compilation Techniques
The Case for Higher-Level Power Management
HOTOS '99 Proceedings of the The Seventh Workshop on Hot Topics in Operating Systems
Layered representations for learning and inferring office activity from multiple sensory channels
Computer Vision and Image Understanding - Special issue on event detection in video
Cooperative I/O: a novel I/O semantics for energy-aware applications
OSDI '02 Proceedings of the 5th symposium on Operating systems design and implementationCopyright restrictions prevent ACM from being able to make the PDFs for this conference available for downloading
Human-Computer Interaction (3rd Edition)
Human-Computer Interaction (3rd Edition)
The lumière project: Bayesian user modeling for inferring the goals and needs of software users
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Interaction-aware energy management for wireless network cards
SIGMETRICS '08 Proceedings of the 2008 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Context-aware mechanisms for reducing interactive delays of energy management in disks
ATC'08 USENIX 2008 Annual Technical Conference on Annual Technical Conference
| Hi-index | 0.00 |
In this paper, we present a novel approach for tuning power modes of wireless 802.11 interfaces. We use K-means and simple correlation techniques to analyze user's interaction with applications based on mouse clicks. This provides valuable contextual hints that are used to anticipate future network access patterns and intent of users. Based on those hints, we adapt the power mode of the wireless network interface to optimize both energy usage and bandwidth usage. Evaluation results (based on real data gathered from interaction with a desktop) show significant improvements over earlier power management schemes.