Power optimization

Abstract: This paper describes PowerBooter, an automated power model construction technique that uses built-in battery voltage sensors and knowledge of battery discharge behavior to monitor power consumption while explicitly controlling the power management and activity states of individual components. It requires no external measurement equipment. We also describe PowerTutor, a component power management and activity state introspection based tool that uses the model generated by PowerBooter for online power estimation. PowerBooter is intended to make it quick and easy for application developers and end users to generate power models for new smartphone variants, which each have different power consumption properties and therefore require different power models. PowerTutor is intended to ease the design and selection of power efficient software for embedded systems. Combined, PowerBooter and PowerTutor have the goal of opening power modeling and analysis for more smartphone variants and their users.

Abstract: Off-state leakage is static power, current that leaks through transistors even when they are turned off. The other source of power dissipation in today's microprocessors, dynamic power, arises from the repeated capacitance charge and discharge on the output of the hundreds of millions of gates in today's chips. Until recently, only dynamic power has been a significant source of power consumption, and Moore's law helped control it. However, power consumption has now become a primary microprocessor design constraint; one that researchers in both industry and academia will struggle to overcome in the next few years. Microprocessor design has traditionally focused on dynamic power consumption as a limiting factor in system integration. As feature sizes shrink below 0.1 micron, static power is posing new low-power design challenges.

Abstract: Embedded computer systems are characterized by the presence of a dedicated processor and the software that runs on it Power constraints are increasingly becoming the critical component of the design specification of these systems At present, however, power analysis tools can only be applied at the lower levels of the design-the circuit or gate level It is either impractical or impossible to use the lower level tools to estimate the power cost of the software component of the system This paper describes the first systematic attempt to model this power cost A power analysis technique is developed that has been applied to two commercial microprocessors-Intel 486DX2 and Fujitsu SPARClite 934 This technique can be employed to evaluate the power cost of embedded software This can help in verifying if a design meets its specified power constraints Further, it can also be used to search the design space in software power optimization Examples with power reduction of up to 40%, obtained by rewriting code using the information provided by the instruction level power model, illustrate the potential of this idea >

Abstract: Relayed transmission is a way to attain broader coverage by splitting the communication link from the source to the destination into several shorter links/hops One of the main advantages of this communication technique is that it distributes the use of power throughout the hops This implies longer battery life and lower interference introduced to the rest of the network In this context, this paper investigates the optimal allocation of power over these links/hops for a given power budget All hops are assumed to be subject to independent Rayleigh fading Outage probability which is the probability that the link quality from source to destination falls below a certain threshold is used as the optimization criterion Numerical results show that optimizing the allocation of power enhances the system performance, especially if the links are highly unbalanced in terms of their average fading power or if the number of hops is large Interestingly, they also show that nonregenerative systems with optimum power allocation can outperform regenerative systems with no power optimization