TY - GEN
T1 - A self-adaptive approximate interpolation scheme for dense sensing
AU - Vahabi, Maryam
AU - Tovar, Eduardo
AU - Albano, Michele
PY - 2013/10/17
Y1 - 2013/10/17
N2 - Very dense networks offer a better resolution of the physical world and therefore a better capability of detecting the occurrence of an event; this is of paramount importance for a number of industrial applications. However, the scale of such systems poses huge challenges in terms of interconnectivity and timely data processing. In this paper we will look at efficient scalable data acquisition methods for such densely instrumented cyber-physical systems. Previous research works have proposed approaches for obtaining an interpolation of sensor readings from different sensor nodes. Those approaches are based on dominance protocols, presenting therefore excellent scalability properties for dense instrumented systems. In this paper we propose an important advance to the state-of-the-art. Our novel approach not only incorporates a physical model to enable more accurate approximate interpolations but it also detects and self-adapts to changes in the physical model.
AB - Very dense networks offer a better resolution of the physical world and therefore a better capability of detecting the occurrence of an event; this is of paramount importance for a number of industrial applications. However, the scale of such systems poses huge challenges in terms of interconnectivity and timely data processing. In this paper we will look at efficient scalable data acquisition methods for such densely instrumented cyber-physical systems. Previous research works have proposed approaches for obtaining an interpolation of sensor readings from different sensor nodes. Those approaches are based on dominance protocols, presenting therefore excellent scalability properties for dense instrumented systems. In this paper we propose an important advance to the state-of-the-art. Our novel approach not only incorporates a physical model to enable more accurate approximate interpolations but it also detects and self-adapts to changes in the physical model.
KW - Aggregate quantities
KW - Data acquisition
KW - Dominance-based MAC protocols
KW - Sensor networks
UR - http://www.scopus.com/inward/record.url?scp=84885408169&partnerID=8YFLogxK
U2 - 10.1109/SIES.2013.6601481
DO - 10.1109/SIES.2013.6601481
M3 - Article in proceeding
AN - SCOPUS:84885408169
SN - 9781479906581
T3 - Proceedings of the 8th IEEE International Symposium on Industrial Embedded Systems, SIES 2013
SP - 105
EP - 109
BT - Proceedings of the 8th IEEE International Symposium on Industrial Embedded Systems, SIES 2013
T2 - 8th IEEE International Symposium on Industrial Embedded Systems, SIES 2013
Y2 - 19 June 2013 through 21 June 2013
ER -