2001
DOI: 10.1109/43.931003
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Event-driven power management

Abstract: 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 power management: timeout and predictive. Later, a category of algorithms based on stochastic control was proposed for power management. These algorithms guarantee optimal results as long as the system that is powe… Show more

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Cited by 160 publications
(99 citation statements)
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References 31 publications
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“…In addition, policies can be stationary (the same policy applies at any point in time) or non stationary (the policy changes over time). All stochastic approaches except for the discrete adaptive approach presented in [22] are stationary. Approaches based on discrete time setting require policy evaluation even in the low power state [21], [22]thus wasting energy.…”
Section: Related Workmentioning
confidence: 99%
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“…In addition, policies can be stationary (the same policy applies at any point in time) or non stationary (the policy changes over time). All stochastic approaches except for the discrete adaptive approach presented in [22] are stationary. Approaches based on discrete time setting require policy evaluation even in the low power state [21], [22]thus wasting energy.…”
Section: Related Workmentioning
confidence: 99%
“…All stochastic approaches except for the discrete adaptive approach presented in [22] are stationary. Approaches based on discrete time setting require policy evaluation even in the low power state [21], [22]thus wasting energy. On the other hand, event driven models based on exponential distributions [25] show little or no power savings when implemented in real systems since the exponential model does not describe well the request interarrival times [23], [24].…”
Section: Related Workmentioning
confidence: 99%
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“…A general distribution is assumed for the inter-arrival times because an exponential distribution would underestimate the occurrence probability for long request inter-arrival times and so it does not adequately model the request arrival time in the idle periods [14]. The service time behavior is captured by a given service time distribution for the functional module when it is in the active mode.…”
Section: Modeling a Ftq-based Systemmentioning
confidence: 99%
“…Previous studies on battery-powered electronics point out that the display subsystem dominates the energy consumption of the whole system. In the SmartBadge system, for instance, the display consumes 29%, 29%, and 50% of the total power in the active, idle, and standby modes, respectively [1]. Direct-view LCDs can largely be categorized into reflective and transmissive displays which utilize ambient light and light from an artificial light source (e.g., fluorescent backlight tube) respectively.…”
Section: Introductionmentioning
confidence: 99%