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Power-Adaptive Computing System Design for Solar-Energy-Powered Embedded Systems

Lookup NU author(s): Dr Terrence Mak, Professor Alex Yakovlev

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Abstract

Through energy harvesting system, new energy sources are made available immediately for many advanced applications based on environmentally embedded systems. However, the harvested power, such as the solar energy, varies significantly under different ambient conditions, which in turn affects the energy conversion efficiency. In this paper, we propose an approach for designing power-adaptive computing systems to maximize the energy utilization under variable solar power supply. Using the geometric programming technique, the proposed approach can generate a customized parallel computing structure effectively. Then, based on the prediction of the solar energy in the future time slots by a multilayer perceptron neural network, a convex model-based adaptation strategy is used to modulate the power behavior of the real-time computing system. The developed power-adaptive computing system is implemented on the hardware and evaluated by a solar harvesting system simulation framework for five applications. The results show that the developed power-adaptive systems can track the variable power supply better. The harvested solar energy utilization efficiency is 2.46 times better than the conventional static designs and the rule-based adaptation approaches. Taken together, the present thorough design approach for self-powered embedded computing systems has a better utilization of ambient energy sources.


Publication metadata

Author(s): Liu Q, Mak T, Zhang T, Niu X, Luk W, Yakovlev A

Publication type: Article

Publication status: Published

Journal: IEEE Transactions on Very Large Scale Integration (VLSI) Systems

Year: 2015

Volume: 23

Issue: 8

Pages: 1402-1414

Print publication date: 01/08/2015

Online publication date: 13/08/2014

Acceptance date: 16/07/2014

ISSN (print): 1063-8210

ISSN (electronic): 1557-9999

Publisher: IEEE

URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6877694&isnumber=7164363

DOI: 10.1109/TVLSI.2014.2342213


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