Wireless sensor networks (WSN) are event based systems that rely on the collective effort of densely
deployed several microsensor nodes which continuously observe physical phenomenon. The main objective
of the WSN is to reliably detect/estimate event features from the collective information provided by sensor
nodes. Therefore, the energy and hence processing constraints of small wireless sensor nodes are overcome
by this collective sensing notion which is realized via their networked deployment. While the collaborative
nature of the WSN brings significant advantages over traditional sensing, the spatio-temporal correlation
among the sensor observations is another significant and unique characteristic of the WSN which can be
exploited to drastically enhance the overall network performance. The characteristics of the correlation
in the WSN can be summarized as follows:
– Spatial Correlation: Typical WSN applications require spatially dense sensor deployment in order to
achieve satisfactory coverage [1]. As a result, multiple sensors record information about a single event
in the sensor field. Due to high density in the network topology, spatially proximal sensor observations
are highly correlated with the degree of correlation increasing with decreasing internode separation.
– Temporal Correlation: Some of the WSN applications such as event tracking may require sensor nodes
to periodically perform observation and transmission of the sensed event features. The nature of the
energy-radiating physical phenomenon constitutes the temporal correlation between each consecutive
observation of a sensor node [7]. The degree of correlation between consecutive sensor measurements
may vary according to the temporal variation characteristics of the phenomenon.