Date of Award

11-2018

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Computer Engineering and Sciences

First Advisor

Carlos E. Otero

Second Advisor

Samuel Kozaitis

Third Advisor

William Allen

Fourth Advisor

Munevver Subasi

Abstract

Researchers are actively investigating wireless sensor networks (WSNs) with respect to node design, architecture, networking protocols, and processing algorithms. However, few researchers consider the impact of deployments on the performance of a system. As a result, an appropriate deployment simulator that estimates the performance of WSNs concerning several deployment variables is needed. This research presents a holistic deployment framework that assists decision makers in making optimum WSN deployment choices by considering the terrain of their region of interest and type of deployment. This framework employs empirical propagation models to predict the performance of the deployment in terms of connectivity, coverage, lifetime, and throughput for stochastic and deterministic deployments in dense tree, tall grass, and short grass environments. For each type of environment, this study investigates the effects of node orientation on the performance metrics. The outlined framework can serve as a useful prototype for creating deployment simulators that optimize WSN deployments by considering terrain factors and type of deployment. Furthermore, mathematical prediction models that optimize the decision-making process are presented. Rather than executing the simulation, the mathematical prediction models are used to predict the performance of the system which provides real time results.

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