Event-driven power management
Simunic, T.; Benini, L.; Glynn, P.; De Micheli, G.
Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on
Volume 20, Issue 7, Jul 2001 Page(s):840 - 857
Digital Object Identifier 10.1109/43.931003
Summary:Energy consumption of electronic devices has become a serious
concern in recent years. Power management (PM) algorithms aim at
reducing energy consumption at the system-level by selectively placing
components into low-power states. Formerly, two classes of heuristic
algorithms have been proposed for PM: timeout and predictive. Later, a
category of algorithms based on stochastic control was proposed for PM.
These algorithms guarantee optimal results as long as the system that is
power managed can be modeled well with exponential distributions. We
show that there is a large mismatch between measurements and simulation
results if the exponential distribution is used to model all user
request arrivals. We develop two new approaches that better model system
behavior for general user request distributions. Our approaches are
event-driven and give optimal results verified by measurements. The
first approach we present is based on renewal theory. This model assumes
that the decision to transition to low-power state can be made in only
one state. Another method we developed is based on the time-indexed
semi-Markov decision process (TISMDP) model. This model has wider
applicability because it assumes that a decision to transition into a
lower-power state can be made upon each event occurrence from any number
of states. This model allows for transitions into low-power states from
any state, but it is also more complex than our other approach. It is
important to note that the results obtained by renewal model are
guaranteed to match results obtained by TISMDP model, as both approaches
give globally optimal solutions. We implemented our PM algorithms on two
different classes of devices: two different hard disks and client-server
wireless local area network systems such as the SmartBadge or a laptop.
The measurement results show power savings ranging from a factor of 1.7
up to 5.0 with insignificant variation in performance
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