Performance Analysis of Data Retrieval in Wireless Sensor Networks
Stochastic Operations Research group
University of Twente
Promoter: Prof. Dr. R.J. Boucherie
Co-promoter: Dr. Ir. M. de Graaf
Co-promoter: Dr. Ir. J. Goseling
Wireless sensor networks are often employed to retrieve information about various attributes of an area of interest, such as atmospheric conditions, geo-physical contexts, or to detect objects/people and track their movement. The reliability of sensor measurements, however, is often affected by factors such as the hardware characteristics of the sensors, the position of the sensors relative to the monitored object/phenomenon, the characteristics of the environment where the sensors are deployed, the availability of energy resources. This thesis consists of several mathematical models employed to analyze the performance of wireless sensor networks under data retrieval time, energy and measurement reliability constraints. To analyze these models, methods such as queueing theory, combinatorial theory, Monte Carlo simulations, Markov Decision Processes, are employed. The mathematical models considered in this thesis aim to provide a formal, theoretical support for the design of wireless sensor network applications related to the retrieval of reliable data, query-based sensing and data caching, with a goal of assisting the implementation of such applications.
About Mihaela Mitici
Mihaela Mitici received her M.Sc. degree in Operations Research from the University of Amsterdam in 2011. For her master thesis on ‘Flexible Air Traffic Scheduling’, Mihaela did a 6-months internship at NLR (National Laboratory of Aeronautics, Amsterdam). Starting 2011, she is a Ph.D. candidate at the Stochastic Operations Research group, University of Twente, where she conducts research about data retrieval and compression in wireless sensor networks, within the RRR project (Realisation of Reliable and Secure Residential Sensor Platforms). Her research interests are in transmission scheduling, energy minimization, energy harvesting for wireless sensor networks. In her work, she focuses on providing analytical results to support the design and implementation of wireless sensor network applications.