Algorithms for Self-Organizing Wireless Sensor Networks
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The unique characteristics of sensor networks pose numerous challenges that have to be overcome to enable their efficient use. In particular, sensor networks are energy constrained because of their reliance on battery power. They can be composed of a large number of unreliable nodes. These characteristics render node collaboration essential to the accomplishment of the network task and justify the development of new algorithms to provide services such as routing, fault tolerance and naming. This work increases the knowledge on the growing field of sensor network algorithms by contributing a new evaluation tool and two new algorithms. A new sensor network simulator that can be used to evaluate sensor network algorithms is discussed. It incorporates models for the different functional units composing a sensor node and characterizes the energy consumption of each. It is designed in a modular and efficient way favoring the ease of use and extension. It allows the user to choose from different implementations of energy models, accuracy models and types of sensors. The second contribution of this thesis is a distributed algorithm to solve the unique ID assignment problem in sensor networks. Our solution starts by assigning long unique IDs and organizing nodes in a tree structure. This tree structure is used to compute the size of the network. Then, unique IDs are assigned using the minimum length. Globally unique IDs are useful in providing many network functions, e.g. node maintenance and security. Theoretical and simulation analysis of the ID assignment algorithm demonstrate that a high percentage of nodes are assigned unique IDs at the termination of the algorithm when the algorithm parameters are set properly. Furthermore, the algorithm terminates in a short time that scales well with the network size. The third contribution of this thesis is a general fault-tolerant event detection scheme that allows nodes to detect erroneous local decisions based on the local decisions reported by their neighbors. It can handle cases where nodes have different and dynamic accuracy levels. We prove analytically that the derived fault-tolerant estimator is optimal under the maximum a posteriori criterion. An equivalent weighted voting scheme is derived.