Algorithms for Self-Organizing Wireless Sensor Networks

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.Ph.D.Committee Chair: Professor Bonnie Heck Ferri; Committee Chair: Professor George F. Riley; Committee Member: Professor Douglas M. Blough; Committee Member: Professor Henry L. Owen III; Committee Member: Professor Mostafa H. Ammar; Committee Member: Professor Raghupathy Sivakuma

Distributed Fault-Tolerance for Event Detection Using Heterogeneous Wireless Sensor Networks

Distributed event detection using wireless sensor networks has received growing interest in recent years. In such applications, a large number of inexpensive and unreliable sensor nodes are distributed in a geographical region to make firm and accurate local decisions about the presence or absence of specific events based on their sensor readings. However, sensor readings can be unreliable, due to either noise in the sensor readings or hardware failures in the devices, and may cause nodes to make erroneous local decisions. We present a general fault-tolerant event detection scheme that allows nodes to detect erroneous local decisions based on the local decisions reported by their neighbors. This detection scheme does not assume homogeneity of sensor nodes and can handle cases where nodes have different accuracy levels. We prove analytically that the derived fault-tolerant estimator is optimal under the maximum a posteriori (MAP) criterion. An equivalent weighted voting scheme is also derived. Further, we describe two new error models that take into account the neighbor distance and the geographical distributions of the two decision quorums. These models are particularly suitable for detection applications where the event under consideration is highly localized. Our fault-tolerant estimator is simulated using a network of 1024 nodes deployed randomly in a square region and assigned random probability of failures

Distributed Fault-Tolerance for Event Detection Using Heterogeneous Wireless Sensor Networks

Abstract — Distributed event detection using wireless sensor networks has received growing interest in recent years. In such applications, a large number of inexpensive and unreliable sensor nodes are distributed in a geographical region to make firm and accurate local decisions about the presence or absence of specific events based on their sensor readings. However, sensor readings can be unreliable, due to either noise in the sensor readings or hardware failures in the devices, and may cause nodes to make erroneous local decisions. We present a general faulttolerant event detection scheme that allows nodes to detect erroneous local decisions based on the local decisions reported by their neighbors. This detection scheme does not assume homogeneity of sensor nodes and can handle cases where nodes have different accuracy levels. We prove analytically that the derived fault-tolerant estimator is optimal under the maximum a posteriori (MAP) criterion. An equivalent weighted voting scheme is also derived. Further, we describe two new error models that take into account the neighbor distance and the geographical distributions of the two decision quorums. These models are particularly suitable for detection applications where the event under consideration is highly localized. Our fault-tolerant estimator is simulated using a network of 1024 nodes deployed randomly in a square region and assigned random probability of failures. I

Distributed Global Identification for Sensor Networks

A sensor network consists of a set of battery-powered nodes, which collaborate to perform sensing tasks in a given environment. It may contain one or more base stations to collect sensed data and possibly relay it to a central processing and storage system. These networks are characterized by scarcity of resources, in particular the available energy. We present a distributed algorithm to solve the unique ID assignment problem. The proposed 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 number of bytes. Globally unique IDs are useful in providing many network functions, e.g. configuration, monitoring of individual nodes, and various security mechanisms. Theoretical and simulation analysis of the proposed solution have been preformed. The results demonstrate that a high percentage of nodes (more than 99%) are assigned globally unique IDs at the termination of the algorithm when the algorithm parameters are set properly. Furthermore, the algorithm terminates in a relatively short time that scales well with the network size. For example, the algorithm terminates in about 5 minutes for a network of 1,000 nodes