Imperial College London


Faculty of EngineeringDepartment of Computing

Professor of Computer Engineering



+44 (0)20 7594 8313w.luk Website




434Huxley BuildingSouth Kensington Campus






BibTex format

author = {Liu, Q and Mak, T and Zhang, T and Niu, X and Luk, W and Yakovlev, AV},
doi = {10.1109/TVLSI.2014.2342213},
journal = {IEEE Transactions on Very Large Scale Integration (VLSI) Systems},
pages = {1402--1414},
title = {Power-Adaptive Computing System Design for Solar-Energy-Powered Embedded Systems},
url = {},
volume = {23},
year = {2014}

RIS format (EndNote, RefMan)

AB - 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.
AU - Liu,Q
AU - Mak,T
AU - Zhang,T
AU - Niu,X
AU - Luk,W
AU - Yakovlev,AV
DO - 10.1109/TVLSI.2014.2342213
EP - 1414
PY - 2014///
SN - 1557-9999
SP - 1402
TI - Power-Adaptive Computing System Design for Solar-Energy-Powered Embedded Systems
T2 - IEEE Transactions on Very Large Scale Integration (VLSI) Systems
UR -
UR -
UR -
VL - 23
ER -