Smart devices with multiple on-board sensors, networked through wired or wireless
links, are distributed in physical systems and environments. Broad applications
of such sensor networks include manufacturing quality control and wireless sensor
systems. In the operation of sensor systems, robust methods for retrieving reliable
information from sensor systems are crucial in the presence of potential sensor failures.
Existence of sensor redundancy is one of the main drivers for the robustness or
fault tolerance capability of a sensor system.
The redundancy degree of sensors plays two important roles pertaining to the robustness
of a sensor network. First, the redundancy degree provides proper parameter
values for robust estimator; second, we can calculate the fault tolerance capability of
a sensor network from the redundancy degree. Given this importance of the redundancy
degree, this dissertation presents efficient algorithms based on matroid theory
to compute the redundancy degree of a clustered sensor network. In the efficient algorithms,
a cluster pattern of a sensor network allows us to decompose a large sensor
network into smaller sub-systems, from which the redundancy degree can be found
more efficiently.
Finally, the robustness analysis as well as its algorithm procedure is illustrated
using examples of a multi-station assembly process and calibration of wireless sensor
networks.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-2527 |
| Date | 15 May 2009 |
| Creators | Cho, Jung Jin |
| Contributors | Ding, Yu |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Dissertation, text |
| Format | electronic, application/pdf, born digital |
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