Graduation Semester and Year

2005

Language

English

Document Type

Thesis

Degree Name

Master of Science in Electrical Engineering

Department

Electrical Engineering

First Advisor

Dan Popa

Abstract

The spatiotemporally varying network topology of mobile sensor networks makes it very suitable for applications such as reconstruction of environmental fields through sampling at locations that maximally reduce the largest uncertainty in the field estimate. Mobile sensor networks comprise of multiple heterogeneous resources and a deadlock-free resource scheduling in the presence of shared and routing resources becomes necessary to schedule the most efficient (cost / energy / time) resource for a task. Location information is imperative in sensor networks for most applications for localized sensing where localizing the network adaptively with no additional hardware is important. Adaptive sampling approaches for spatially distributed static linear and Gaussian fields with mobile robotic sensors are formulated and experimentally validated. Resource scheduling algorithms for dispatching resources in a deadlock-free manner in systems with shared and routing resources are mathematically formulated and experimentally validated. Simultaneous and Adaptive localization algorithms for sensor network localization through simple geometric constraints are validated through simulations.

Disciplines

Electrical and Computer Engineering | Engineering

Comments

Degree granted by The University of Texas at Arlington

Download

Share

COinS