Some of the early, pioneering energy-management schemes simply turned selected areas of a system on and off. These schemes were based on rudimentary utilization algorithms. It's now understood that an energy-waste cost is associated with turning off and on a section of an electronic device. Depending on how frequently a block is turned off and on, this cost may exceed the benefit of powering it off in the first place.
In addition, designers now know that smoothing the discharge profile over time—rather than having dramatic discharge-rate changes—results in longer times between battery recharging. A meaningful run-time-behavior analysis has to consider many aspects, including block workloads, energy-consumption rates, the usage environment, and requested services. Based on a block-workload analysis, adaptive-predictive shutdown techniques can put inactive system areas in power- or shut-down mode. This step occurs as a result of previous usage patterns.
Among the examples of energy-consumption-based power-management techniques are communication-based power management (CBPM) and heat management with passive cooling. CBPM exercises dynamic and proactive control over system components. It delays components that are executing less performance-critical operations even if they're not idle. By dynamically blocking the execution of certain components, CBPM can regulate the system's power profile. In contrast, heat management with passive-cooling procedures monitors the system's temperature. It limits the power consumption of certain sections and even disables services if necessary.
Based on the usage environment, some of the system parameters are adjusted. Such adjustments include compulsory system shutdown. The usage environment could be, for example, the strength of the received RF signal, the intensity of the ambient light, or the remaining battery charge. To reduce battery discharging, some services also may be disabled. Even if the user requests those services, they won't be performed.
As mentioned previously, implementing a comprehensive energy-management strategy imposes new system-level requirements with both hardware and software implications. The software component of such a strategy contributes to its flexibility and adaptability. The hardware aspect includes additional functions and blocks like timers, sensors, and power and clock controllers. It also incorporates very specific transistor-level features, which enable battery-life optimization.
In addition, designers now know that smoothing the discharge profile over time—rather than having dramatic discharge-rate changes—results in longer times between battery recharging. A meaningful run-time-behavior analysis has to consider many aspects, including block workloads, energy-consumption rates, the usage environment, and requested services. Based on a block-workload analysis, adaptive-predictive shutdown techniques can put inactive system areas in power- or shut-down mode. This step occurs as a result of previous usage patterns.
Among the examples of energy-consumption-based power-management techniques are communication-based power management (CBPM) and heat management with passive cooling. CBPM exercises dynamic and proactive control over system components. It delays components that are executing less performance-critical operations even if they're not idle. By dynamically blocking the execution of certain components, CBPM can regulate the system's power profile. In contrast, heat management with passive-cooling procedures monitors the system's temperature. It limits the power consumption of certain sections and even disables services if necessary.
Based on the usage environment, some of the system parameters are adjusted. Such adjustments include compulsory system shutdown. The usage environment could be, for example, the strength of the received RF signal, the intensity of the ambient light, or the remaining battery charge. To reduce battery discharging, some services also may be disabled. Even if the user requests those services, they won't be performed.
As mentioned previously, implementing a comprehensive energy-management strategy imposes new system-level requirements with both hardware and software implications. The software component of such a strategy contributes to its flexibility and adaptability. The hardware aspect includes additional functions and blocks like timers, sensors, and power and clock controllers. It also incorporates very specific transistor-level features, which enable battery-life optimization.
posted by wirefly | 9:03 PM
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