Thèse de doctorat en Technologies de l’information et des systèmes
Soutenue en 2012
à Compiègne .
Pas de résumé disponible.
Wireless sensor networks for critical systems supervision
Recent advances in wireless communications and Micro-Electro-Mechanical systems have enabled the development of wireless sensor networks (WSN) which are expected to be one of the most promising technologies in the near future. These networks introduced an innovative way of monitoring and enabled a plethora of applications in the field of critical systems supervision such as battlefield surveillance, radiation detection, healthcare supervision and critical infrastructure protection. Wireless sensor networks for critical applications have their own characteristics which distinguish them from conventional WSN which create new challenges at different layers. These challenges include reliability, fault tolerance, security, QoS and scalability. This thesis contributes to overcome the challenges of WSN for critical systems monitoring and makes contributions at the MAC layer, the network layer and the application layer. In what follows, we consider the healthcare supervision application and particularly rehabilitation supervision application. We start by studying wireless sensor networks for rehabilitation supervision with a focus on scientific and technical challenges in order to identify the open issues. Then, we propose a reliable communication protocol that meets the clinical requirements of high-fidelity rehabilitation supervision in terms of data quality and data rate. Then, we study the state of the art of multi-path routing protocols through reviewing the different techniques developed for paths construction, data forwarding and paths maintenance. Based on this study, we propose a scalable multi-path routing protocol that constructs a large number of paths compared to existing protocols without inducing extra overhead. Thereafter, we propose a distributed architecture for secure and scalable storage of medical data in wireless sensor networks. Finally, we design and implement a wireless sensor network prototype for high-fidelity rehabilitation supervision and propose mobile and web applications for patients and doctors. Without loss of generality, our proposed solutions for WSN-based rehabilitation supervision are also viable for any other critical application that face the same considered challenges.