A predictive system shutdown method for energy saving of event-driven computation
ICCAD '97 Proceedings of the 1997 IEEE/ACM international conference on Computer-aided design
A survey of design techniques for system-level dynamic power management
IEEE Transactions on Very Large Scale Integration (VLSI) Systems - Special section on low-power electronics and design
Dynamic Power Management for Nonstationary Service Requests
IEEE Transactions on Computers
Measurement and modelling of the effective sleep time interval for dynamic power management of PCS
PDCN'07 Proceedings of the 25th conference on Proceedings of the 25th IASTED International Multi-Conference: parallel and distributed computing and networks
Performance and power consumption of computers using batch service with event and time counter
PDCN'07 Proceedings of the 25th conference on Proceedings of the 25th IASTED International Multi-Conference: parallel and distributed computing and networks
Policy optimization for dynamic power management
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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Low power consumption is an important factor in designing a PC system. Dynamic power management (DPM) can be an effective approach to the reduction of power consumption without significantly degrading performance. A system shuts down devices when they are not needed and wakes them up when necessary. When a system shuts down or wakes up, it requires more power consumption. In this paper we measure and model the power consumption during the state transition which causes the transition penalty. In our experiment results we measure the transition penalty with respect to the parameters of the systems. As a result of a great deal of measurement and observation the transition penalty can be represented by a mathematics model or a transition model. According to our model the transition penalty and the effective sleep time can be predicted for different PCs. With our transition model, the user can use the dynamic power management of a PC with respect to its parameters and the user's habits to reduce the power consumption.