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Enabling Resource-Awareness for In-Network Data Processing in Wireless Sensor Networks
Roehm, U., Gaber, M.M., Tse and Quincy
The next-generation of wireless sensor platforms allows
for more advanced in-network data processing.
The central challenge remains energy and communication
efficiency. This paper presents a resource awareness
framework for wireless sensor networks
that allows in-network data processing to adapt to
changing resource levels such as battery power or
available memory. We have implemented the proposed
framework as part of a query processing system
for the Sun SPOT sensor network platform. As
a case study, we have applied the framework to the
query processor's on-line data clustering algorithm,
making it resource-aware. In an experimental study,
we demonstrate how communication costs can be significantly reduced by de-coupling clustering and data
communication. The results also show the effectiveness
of the resource-aware clustering algorithm: It can
keep a constant memory footprint for only a marginal
acceptable error in result accuracy. |
Cite as: Roehm, U., Gaber, M.M., Tse and Quincy (2008). Enabling Resource-Awareness for In-Network Data Processing in Wireless Sensor Networks. In Proc. Nineteenth Australasian Database Conference (ADC 2008), Wollongong, NSW, Australia. CRPIT, 75. Fekete, A. and Lin, X., Eds. ACS. 95-102. |
(from crpit.com)
(local if available)
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