Designing the user interface (2nd ed.): strategies for effective human-computer interaction
Designing the user interface (2nd ed.): strategies for effective human-computer interaction
Voltage scheduling in the IpARM microprocessor system
ISLPED '00 Proceedings of the 2000 international symposium on Low power electronics and design
The Psychology of Human-Computer Interaction
The Psychology of Human-Computer Interaction
A scheduling model for reduced CPU energy
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
User-perceived latency driven voltage scaling for interactive applications
Proceedings of the 42nd annual Design Automation Conference
Towards a Responsive, Yet Power-ef.cient, Operating System: A Holistic Approach
MASCOTS '05 Proceedings of the 13th IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems
Dynamic Power Optimization Targeting User Delays in Interactive Systems
IEEE Transactions on Mobile Computing
Policies for dynamic clock scheduling
OSDI'00 Proceedings of the 4th conference on Symposium on Operating System Design & Implementation - Volume 4
Scheduling for reduced CPU energy
OSDI '94 Proceedings of the 1st USENIX conference on Operating Systems Design and Implementation
An energy-aware framework for dynamic software management in mobile computing systems
ACM Transactions on Embedded Computing Systems (TECS)
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In an interactive embedded system, special task execution patterns and scheduling constraints exist due to frequent human-computer interactions. This paper proposes a transaction-based dynamic voltage scaling (T-DVS) approach that takes into account the characteristics of interactive transactions. T-DVS scales CPU performance levels to reduce energy consumption, while satisfying the constraints of both human-perceptual threshold and CPU requirement of an interactive transaction. T-DVS considers CPU requirements of both interactive and background tasks during a user interaction. It exploits CPU idle time waiting for user responses to run background task with lower CPU frequency. Experiments demonstrate that T-DVS can reduce energy consumption significantly compared to state-of-the-art approaches, with little sacrifice in user-perceived performance.