TY - GEN
T1 - AdaptSens
T2 - Real-Time Systems Symposium, RTSS 2009
AU - Wang, Lili
AU - Yang, Yong
AU - Noh, Dong Kun
AU - Le, Hieu K.
AU - Liu, Jie
AU - Abdelzaher, Tarek F.
AU - Ward, Michael
PY - 2009
Y1 - 2009
N2 - In this paper, we present AdaptSens: a reliable data collection and storage system for solar-powered sensor networks. Unlike battery-operated devices, solar-powered systems have a less predictable energy supply and their ability to harvest energy depends on past spending, thereby creating incentives for adaptive matching of energy supply and demand. Our storage system is novel in its layered architecture and its incremental layer activation mechanism. AdaptSens provides a set of functions, in separate layers, such as sensory data collection, replication (to prevent failure-induced data loss), and storage balancing (to prevent depletion-induced data loss). The mechanism utilizes surplus energy when available by activating more layers, and resorts to progressively more energy-efficient (partial hibernation) modes when energy is scarce. Best reliability is achieved when all layers are active but meaningful intermediate modes allow different degrees of energy conservation. The efficacy of AdaptSens in trading off reliability for energy is tested on both an outdoor system and an indoor testbed. Evaluation results show that AdaptSens minimizes the sum of all data losses when combining the energy, storage and node failure factors.
AB - In this paper, we present AdaptSens: a reliable data collection and storage system for solar-powered sensor networks. Unlike battery-operated devices, solar-powered systems have a less predictable energy supply and their ability to harvest energy depends on past spending, thereby creating incentives for adaptive matching of energy supply and demand. Our storage system is novel in its layered architecture and its incremental layer activation mechanism. AdaptSens provides a set of functions, in separate layers, such as sensory data collection, replication (to prevent failure-induced data loss), and storage balancing (to prevent depletion-induced data loss). The mechanism utilizes surplus energy when available by activating more layers, and resorts to progressively more energy-efficient (partial hibernation) modes when energy is scarce. Best reliability is achieved when all layers are active but meaningful intermediate modes allow different degrees of energy conservation. The efficacy of AdaptSens in trading off reliability for energy is tested on both an outdoor system and an indoor testbed. Evaluation results show that AdaptSens minimizes the sum of all data losses when combining the energy, storage and node failure factors.
UR - http://www.scopus.com/inward/record.url?scp=77649315108&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77649315108&partnerID=8YFLogxK
U2 - 10.1109/RTSS.2009.8
DO - 10.1109/RTSS.2009.8
M3 - Conference contribution
AN - SCOPUS:77649315108
SN - 9780769538754
T3 - Proceedings - Real-Time Systems Symposium
SP - 303
EP - 312
BT - Proceedings - Real-Time Systems Symposium, RTSS 2009
Y2 - 1 December 2009 through 4 December 2009
ER -