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A Distributed and Adaptive Signal
Processing Approach to Exploiting Correlation in Sensor Networks
Jim Chou, Dragan Petrovic, Kannan
Ramchandran
Journal of Ad Hoc Networks
Abstract:
We
propose a novel approach to reducing energy consumption
in sensor networks using a distributed adaptive signal processing framework and
efficient algorithm 1. While the topic of
energy-aware routing to alleviate energy consumption in sensor networks has
received attention recently [1,2], in this paper, we propose an orthogonal
approach to complement previous methods. Specifically, we propose a distributed
way of continuously exploiting existing
correlations in sensor data based on adaptive signal processing and distributed
source coding principles. Our approach enables sensor nodes to blindly compress
their readings with respect to one another without
the need for explicit and energy-expensive inter-sensor communication to effect
this compression. Furthermore, the distributed algorithm used by each sensor
node is extremely low in complexity and easy
to implement (i.e., one modulo operation), while an adaptive
filtering framework is used at the data gathering unit to
continuously learn the relevant correlation structures in the sensor
data. Applying the algorithm to testbed data resulted in energy savings of
10%-65% for a multitude of sensor modalities. method
of conserving energy in sensor networks that is mutually exclusive
and complementary to the above approaches, and
can be used in combination with them to increase energy reduction.

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