TY - GEN
T1 - Minimum variance energy allocation for a solar-powered sensor system
AU - Noh, Dong Kun
AU - Wang, Lili
AU - Yang, Yong
AU - Le, Hieu Khac
AU - Abdelzaher, Tarek
PY - 2009
Y1 - 2009
N2 - Using solar power in wireless sensor networks (WSNs) requires adaptation to a highly varying energy supply. From an application's perspective, however, it is often preferred to operate at a constant quality level as opposed to changing application behavior frequently. Reconciling the varying supply with the fixed demand requires good tools for predicting supply such that its average is computed and demand is fixed accordingly. In this paper, we describe a probabilistic observation-based model for harvested solar energy, which accounts for both long-term tendencies and temporary environmental conditions. Based on this model, we develop a time-slot-based energy allocation scheme to use the periodically harvested solar energy optimally, while minimizing the variance in energy allocation. Our algorithm is tested on both outdoor and indoor testbeds, demonstrating the efficacy of the approach.
AB - Using solar power in wireless sensor networks (WSNs) requires adaptation to a highly varying energy supply. From an application's perspective, however, it is often preferred to operate at a constant quality level as opposed to changing application behavior frequently. Reconciling the varying supply with the fixed demand requires good tools for predicting supply such that its average is computed and demand is fixed accordingly. In this paper, we describe a probabilistic observation-based model for harvested solar energy, which accounts for both long-term tendencies and temporary environmental conditions. Based on this model, we develop a time-slot-based energy allocation scheme to use the periodically harvested solar energy optimally, while minimizing the variance in energy allocation. Our algorithm is tested on both outdoor and indoor testbeds, demonstrating the efficacy of the approach.
UR - http://www.scopus.com/inward/record.url?scp=68749083989&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=68749083989&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-02085-8_4
DO - 10.1007/978-3-642-02085-8_4
M3 - Conference contribution
AN - SCOPUS:68749083989
SN - 3642020844
SN - 9783642020841
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 44
EP - 57
BT - Distributed Computing in Sensor Systems - 5th IEEE International Conference, DCOSS 2009, Proceedings
T2 - 5th IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2009
Y2 - 8 June 2009 through 10 June 2009
ER -