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Appears in Collections:Computing Science and Mathematics eTheses
Title: Handling Emergent Conflicts in Adaptable Rule-based Sensor Networks
Author(s): Blum, Jesse Michael
Supervisor(s): Magill, Evan
Kolberg, Mario
Keywords: computing science
rule-based networks
conflict analysis
Issue Date: Oct-2012
Publisher: University of Stirling
Abstract: This thesis presents a study into conflicts that emerge amongst sensor device rules when such devices are formed into networks. It describes conflicting patterns of communication and computation that can disturb the monitoring of subjects, and lower the quality of service. Such conflicts can negatively affect the lifetimes of the devices and cause incorrect information to be reported. A novel approach to detecting and resolving conflicts is presented. The approach is considered within the context of home-based psychiatric Ambulatory Assessment (AA). Rules are considered that can be used to control the behaviours of devices in a sensor network for AA. The research provides examples of rule conflict that can be found for AA sensor networks. Sensor networks and AA are active areas of research and many questions remain open regarding collaboration amongst collections of heterogeneous devices to collect data, process information in-network, and report personalised findings. This thesis presents an investigation into reliable rule-based service provisioning for a variety of stakeholders, including care providers, patients and technicians. It contributes a collection of rules for controlling AA sensor networks. This research makes a number of contributions to the field of rule-based sensor networks, including areas of knowledge representation, heterogeneous device support, system personalisation, and in particular, system reliability. This thesis provides evidence to support the conclusion that conflicts can be detected and resolved in adaptable rule-based sensor networks.
Type: Thesis or Dissertation
Affiliation: School of Natural Sciences
Computing Science and Mathematics

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