Title :
Lightweight energy prediction framework for solar-powered wireless sensor networks
Author :
Merkel, Cory E. ; Kudithipudi, Dhireesha ; Kwasinski, Andres
Author_Institution :
Dept. of Comput. Eng., Rochester Inst. of Technol., Rochester, NY, USA
Abstract :
This research studies lightweight energy prediction filters for solar-powered wireless sensor networks. A generalized prediction filter is developed from the empirical analysis of several solar intensity datasets. The Array of Beta Coefficients (ABC) energy prediction filter is proposed. A comparison metric is also proposed to evaluate different filters based on their accuracy, storage requirements, and calculation complexity. Simulation results show that the ABC filter has up to 8-fold accuracy improvement over other published filters.
Keywords :
solar power; wireless sensor networks; 8-fold accuracy; ABC filter; array of beta coefficients; energy prediction filter; generalized prediction filter; lightweight energy prediction filters; lightweight energy prediction framework; solar intensity datasets; solar-powered wireless sensor networks; Accuracy; Arrays; Energy harvesting; Measurement; Solar energy; Wireless communication; Wireless sensor networks;
Conference_Titel :
SOC Conference (SOCC), 2012 IEEE International
Conference_Location :
Niagara Falls, NY
Print_ISBN :
978-1-4673-1294-3
DOI :
10.1109/SOCC.2012.6398397