A State-Based Programming Model for Wireless Sensor Networks

142 Chapter 8. Related Work
Control-Oriented Systems
Instead of computing outputs data from input data, control-oriented embedded
systems typically control the device they are embedded into. Often controloriented
systems constantly react to their environment by computing output
events from input events (i.e., stimuli from outside of the embedded system).
Such systems are called reactive. Examples of reactive systems are protocol processors
in fax machines as well as mobile phones, control units in automobiles
(such as airbag release and cruise control), and fly-by-wire systems.
A subcategory of reactive systems are interactive systems, which also react to
stimuli from the environment. However, in interactive systems the computer
is the leader of the interaction, stipulating its pace, its allowable input alphabet
and order, etc. Therefore, the design of a purely interactive system is generally
considered easier than the design of an environmentally-driven reactive system.
Many of the recent applications of embedded systems consist of both, controloriented
and data-oriented parts. In general, the reactive part of the system
controls the computationally intense transformative operations. In turn, results
of the such operations are often feed back into the control-oriented part. Thus,
actual embedded systems often expose both characteristics.
Control and Data-oriented Wireless Sensor Networks
Wireless sensor nodes, too, include transformational as well as reactive parts.
For example, transformational parts in sensor nodes compute from streams of
data whether a product has been damaged [106] (acceleration data), the location
where a gun has been fired [86] (audio data), the specific type of animal based on
its call [64, 105, 117, 118] (again, audio data), and so on. The same sensor nodes
also have control-oriented parts, for example, for processing network-level and
application-level protocols (such as the Bluetooth protocol stack used in [106]
and the EnviroTrack group-management application protocol discussed in the
previous chapter). In WSNs, the feedback loop between the reactive and transformative
parts is of particular importance. Due to the constrained nature of
the nodes, resource-intense operations are often controlled by criteria that are
themselves computed by a much less intense processing stage. In [118], for example,
recorded audio samples are first rated how well they match calls of specific
birds using a relatively simple algorithm. Only if there is a high confidence
that a sample represents a desired birdcall, the samples are compressed and sent
to the clusterhead in order to apply beamforming for target localization, which
are very resource-intense operations. Other criteria for controlling the behavior
of sensor nodes may reflect the importance of a detection, the proximity (and
thus expected sensing quality) of a target, the number of other nodes detecting
the same target, and so on. In the extreme case, so called adaptive-fidelity
algorithms allow to dynamically trade the quality of a sensing result against resource
usage by controlling the amount of sampling and processing performed
by a node.