This paper describes a system level design approach to power awareness in the wearable computers project at Carnegie Mellon University. The paper identifies the major components of power consumption in a mobile computer, evaluates their respective contributions to power consumption, and analyzes various techniques for improving their energy efficiency. The paper describes our research framework and experimental evaluations of techniques for improving energy efficiency of a system, ranging from the communication level down to the physical level of the battery. The work described includes techniques for dynamically varying the CPU clock frequency.
This paper introduces a systematic approach to power awareness in mobile, handheld computers. It describes experimental evaluations of several techniques for improving the energy efficiency of a system, ranging from the network level down to the physical level of the battery. At the network level, a new routing method based upon the power consumed by the network subsystem is shown to improve power consumption by 15% on average and to reduce latency by 75% over methods that consider only the transmitted power. At the boundary between the network and the processor levels, the paper presents the problem of local versus remote processing and derives a figure of merit for determining whether a computation should be completed locally or remotely, one that involves the relative performance of the local and remote system, the transmission bandwidth and power consumption, and the network congestion. At the processor level, the main memory bandwidth is shown to have a significant effect on the relationship between performance and CPU frequency, which in turn determines the energy savings of dynamic CPU speed-setting. The results show that accounting for the main memory bandwidth using Amdahl's law permits the performance speed-up and peak power versus the CPU frequency to be estimated to within 5%. The paper concludes with a technique for mitigating the loss of battery energy capacity with large peak currents, showing an improvement of up to 10% in battery life, albeit at some cost to the size and weight of the system.
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