QoS Routing Protocols and Privacy in Wireless Sensor Networks

Full network level privacy has often been categorized into four sub-categories: Identity, Route, Location and Data privacy. Achieving full network level privacy is a challenging problem due to the conditions imposed by the sensor nodes (e.g., energy, memory and computation power), sensor networks (e.g., mobility and topology) and QoS issues (e.g., packet reach-ability and timeliness). This proposed paper consists of two algorithms IRL algorithm and data privacy mechanism that addresses this problem. The proposed system provides additional trustworthiness, less computation power, less storage space and more reliability. Also, we proved that our proposed solutions provide protection against various privacy disclosure attacks, such as eavesdropping and hop-by-hop trace back attacks

Ressourcenarme und dezentrale Lokalisierung autonomer Sensorknoten in Sensornetzwerken

Diese Dissertation behandelt Distanz- und Lokalisierungsverfahren in ressourcenarmen Sensornetzwerken. Den Kern der Arbeit bildet die ressourcenarme Lokalisierung von Sensorknoten. In Sensornetzwerken mit geringen Genauigkeitsanforderungen kann die einfache Schwerpunktbestimmung (CL) als Lokalisierungsverfahren eingesetzt werden. In den Randgebieten eines Netzwerkes erreicht der CL-Algorithmus jedoch nur eine sehr geringe Genauigkeit. Das neu vorgestellte Verfahren Centroid Localization with Edge Correction (CLwEC) reduziert diesen Lokalisierungsfehler bei geringfügig höherem Ressourcenaufwand deutlich. Eine weitere Verbesserung der Lokalisierung wird durch ein gewichtete Schwerpunktverfahren (WCL) erreicht.This thesis describes algorithms to determine distances and positions in resource-constrained sensor networks. In sensor networks with low accuracy requirements, node’s positions can be calculated by the centroid localization algorithm (CL) provided that all reference nodes can be configured optimal regarding the presented method. In borderlands of a sensor network, the accuracy of the centroid localization decreases enormously. The new presented algorithm centroid localization with edge correction (CLwEC) reduces this positioning error significantly and requires, in comparison the CL, only slightly increased resources. A further improvement of the positioning error was achieved by the new introduced weighted centroid localization algorithm (WCL)