Paper Info
Title
Getting more out of energy-harvesting systems: energy management under time-varying utility with P re A ct
Abstract
Careful energy management is a prerequisite for long-term, unattended operation of solar-harvesting sensing systems. We observe that in many applications the utility of sensed data varies over time, but current energy-management algorithms do not exploit prior knowledge of these variations for making better decisions. This paper presents PreAct, the first energy-management algorithm that exploits time-varying utility to optimize application performance. PreAct's design combines strategic long-term planning of future energy utilization with feedback control to compensate for deviations from the expected conditions. We implement PreAct on a low-power microcontroller and compare it against the state of the art on multiple years of real-world data. Our results demonstrate that PreAct is up to 53 % more effective in utilizing harvested solar energy and significantly more robust to uncertainties and inefficiencies of practical systems. These gains translate into an improvement of 28% in the end-to-end performance of a real-world application we investigate when using PreAct.
Year
DOI
Venue
2019
10.1145/3302506.3310393
Proceedings of the 18th International Conference on Information Processing in Sensor Networks
Keywords
DocType
ISBN
dynamic power management, energy allocation, energy harvesting, energy management, energy prediction, solar power
Conference
978-1-4503-6284-9
Citations 
PageRank 
References 
5
0.45
0
Authors
4
Name
Order
Citations
PageRank
Kai Geissdoerfer1112.70
R. Jurdak2567.60
Brano Kusy3608.48
Marco Zimmerling465444.15