visual sensor network (VSN) consists of a large
amount of camera nodes which are able to process the captured
image data locally and to extract the relevant information. The
tight resource limitations in these networks of embedded sensors
and processors represent a major challenge for the application
development. In this paper we focus on finding optimal VSN
configurations which are basically given by (i) the selection of
cameras to sufficiently monitor the area of interest, (ii) the setting
of the cameras’ frame rate and resolution to fulfill the quality of
service (QoS) requirements, and (iii) the assignment of processing
tasks to cameras to achieve all required monitoring activities.
We formally specify this configuration problem and describe an
efficient approximation method based on an evolutionary algorithm.
We analyze our approximation method on three different
scenarios and compare the predicted results with measurements
on real implementations on a VSN platform. We finally combine
our approximation method with an expectation-maximization
algorithm for optimizing the coverage and resource allocation
in VSN with pan-tilt-zoom (PTZ) camera nodes
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