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Distributed Event Detection and Event Localization in Wireless Sensor Networks

Betreuer: Markus Waelchli, Prof. Dr. Torsten Braun

Distributed event detection and event localization are inherent tasks of many wireless sensor network applications. The inaccuracy of the sensed data and the difficulty to determine event properties such as location, area diameter, etc. make event detection and event localization challenging problems. In current approaches, uncertainty is only barely considered and the detection and localization of events has not yet been done in a fully distributed manner. In contrast, all data generated in the neighborhood of an event is sent to a gateway and the localization of the event is calculated there.

In this master thesis an efficient and fully distributed event detection and event localization algorithm that avoids the drawback of increased data traffic between the sensed area and a sink node shall be considered. Thereby, all sensors in the neighborhood of an event derive a weight that determines the relevance with which they sensed the event. In order to derive these weights, uncertainty will have to be modeled. Therefore, a syntax for describing fuzzy rule sets and an appropriate inference method will be proposed. Based on that information, a distributed election algorithm is used that determines the relevant subset of sensors which are responsible for handling the event further. The described approach as well as a simple centralized approach will have to be implemented and evaluated in a simulation environment (Omnet++ or JIST).

Start of Master's thesis: asap

Required skills: C/C++, basic knowledge in computer networks

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