Accurate modeling and prediction of energy availability in energy harvesting real-time embedded systems

Authors:
Jun Lu;Shaobo Liu;Qing Wu;Qinru Qiu
Affiliations:
Department of Electrical and Computer Engineering, Binghamton University, State University of New York, USA;Department of Electrical and Computer Engineering, Binghamton University, State University of New York, USA;Department of Electrical and Computer Engineering, Binghamton University, State University of New York, USA;Department of Electrical and Computer Engineering, Binghamton University, State University of New York, USA
Venue:
GREENCOMP '10 Proceedings of the International Conference on Green Computing
Year:
2010

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Abstract

Energy availability is the primary subject that drives the research innovations in energy harvesting systems. In this paper, we first propose a novel concept of effective energy dissipation that defines a unique quantity to accurately quantify the energy dissipation of the system by including not only the energy demand by the electronic circuit, but also the energy overhead incurred by energy flows amongst system components. This work also addresses the techniques in run-time prediction of future harvested energy. These two contributions significantly improve the accuracy of energy availability computation for the proposed Model-Accurate Predictive DVFS algorithm, which aims at achieving best system performance under energy harvesting constraints. Experimental results show the improvements achieved by the MAP-DVFS algorithm in deadline miss rate. In addition, we illustrate the trend of system performance variation under different conditions and system design parameters.