TY - GEN
T1 - Lucid dreaming
T2 - IPSN 2007: 6th International Symposium on Information Processing in Sensor Networks
AU - Jevtic, Sasha
AU - Kotowsky, Mathew
AU - Dick, Robert P.
AU - Dinda, Peter A
AU - Dowding, Charles
PY - 2007
Y1 - 2007
N2 - Existing sensor network architectures are based on the assumption that data will be polled. Therefore, they are not adequate for long-term battery-powered use in applications that must sense or react to events that occur at unpredictable times. In response, and motivated by a structural autonomous crack monitoring (ACM) application from civil engineering that requires bursts of high resolution sampling in response to aperiodic vibrations in buildings and bridges, we have designed, implemented, and evaluated lucid dreaming, a hardware - software technique to dramatically decrease sensor node power consumption in this and other event-driven sensing applications. This work makes the following main contributions: (1) we have identified the key mismatches between existing, polling-based, sensor network architectures and event-driven applications; (2) we have proposed a hardware - software technique to permit the power-efficient use of sensor networks in event-driven applications; (3) we have analytically characterized the situations in which the proposed technique is appropriate; and (4) we have designed, implemented, and tested a hardware-software solution for standard Crossbow motes that embodies the proposed technique. In the building and bridge structural integrity monitoring application, the proposed technique achieves 1/245 the power consumption of existing sensor network architectures, thereby dramatically increasing battery lifespan or permitting operation based on energy scavenging. We believe that the proposed technique will yield similar benefits in a wide range of applications. Printed circuit board specification files permitting reproduction of the current implementation are available for free use in research and education.
AB - Existing sensor network architectures are based on the assumption that data will be polled. Therefore, they are not adequate for long-term battery-powered use in applications that must sense or react to events that occur at unpredictable times. In response, and motivated by a structural autonomous crack monitoring (ACM) application from civil engineering that requires bursts of high resolution sampling in response to aperiodic vibrations in buildings and bridges, we have designed, implemented, and evaluated lucid dreaming, a hardware - software technique to dramatically decrease sensor node power consumption in this and other event-driven sensing applications. This work makes the following main contributions: (1) we have identified the key mismatches between existing, polling-based, sensor network architectures and event-driven applications; (2) we have proposed a hardware - software technique to permit the power-efficient use of sensor networks in event-driven applications; (3) we have analytically characterized the situations in which the proposed technique is appropriate; and (4) we have designed, implemented, and tested a hardware-software solution for standard Crossbow motes that embodies the proposed technique. In the building and bridge structural integrity monitoring application, the proposed technique achieves 1/245 the power consumption of existing sensor network architectures, thereby dramatically increasing battery lifespan or permitting operation based on energy scavenging. We believe that the proposed technique will yield similar benefits in a wide range of applications. Printed circuit board specification files permitting reproduction of the current implementation are available for free use in research and education.
KW - Event detection
KW - Power consumption
KW - Sensing
KW - Sensor networks
UR - http://www.scopus.com/inward/record.url?scp=35348836695&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=35348836695&partnerID=8YFLogxK
U2 - 10.1145/1236360.1236405
DO - 10.1145/1236360.1236405
M3 - Conference contribution
AN - SCOPUS:35348836695
SN - 1595936386
SN - 9781595936387
T3 - IPSN 2007: Proceedings of the Sixth International Symposium on Information Processing in Sensor Networks
SP - 350
EP - 359
BT - IPSN 2007
Y2 - 25 April 2007 through 27 April 2007
ER -