Saleh Ibrahim, Ph.D.

The development of a new dissolved gas analysis (DGA) method often requires a comparative study to assess the accuracy of the proposed technique. This is faced with the following challenges: (i) the time and effort required to implement and validate the implementation of existing DGA methods, adds to the comparative study cost; (ii) the output states of different DGA methods are not similar, which makes it difficult to put methods side by side in a comparative study; and (iii) the availability of test data is limited. In this study, a user-friendly graphical user interface software package, DGALab, is developed to overcome these challenges. DGALab implements a unified DGA diagnosis framework to map the output states of DGA methods to uniform specifications. DGALab includes a library implementing most common DGA techniques, and includes a repository for input datasets available in the literature and collected directly from laboratories. DGALab simplifies the addition of new DGA techniques written in virtually any programming language. As a result, the process of developing a new DGA technique is greatly simplified using DGALab. To evaluate the software package results, the datasets and methods implemented therein were used to regenerate the results published in earlier research papers.

Underwater Wireless Sensor Networks (UWSN) are revolutionizing our ability to monitor and explore underwater environments. The applications of UWSN span a wide spectrum of scientific, commercial and defense domains, such as oceanographic data collection and tactical surveillance. Due to various physical limitations that face EM waves in water, acoustic communication has emerged as the most practical form of underwater wireless communication. The unique characteristics of underwater acoustic channels confront the design of UWSN with grand challenges, among which are the long propagation delays and the low available bandwidth, which makes communication efficiency of paramount importance. Moreover, nodes in wireless sensor networks are usually powered by batteries, which are difficult to replace or recharge. For long-term applications such as environment monitoring, a node is expected to work continuously for a long time. Thus, energy efficiency becomes one of the most important design considerations.
To deal with these challenges at the architectural level, a layer of radio-capable gateway nodes can be deployed at the surface level. This heterogeneous architecture integrates underwater acoustic communication and aerial radio communication to substantially improve the performance characteristics of underwater sensor networks, provided that gateway nodes are placed in suitable locations. In this work, we study the problem of gateway placement for maximizing the cost-benefit of this UWSN architecture.

Firstly, we develop a mixed integer programming (MIP) gateway deployment optimization (GDO) framework. We investigate the performance advantages of the surface-gateway architecture in the optimal case. We develop various heuristic algorithms for efficiently finding an approximate solution to this NP-hard optimization problem, and compare the complexity and quality of the developed algorithms.

Secondly, after noting the limitations of using a regular mesh of candidate gateway locations, we develop a novel technique for enhancing the problem formulation, by deriving candidate gateway locations from the geometry of the underwater network deployment.

Thirdly, we extend the GDO framework to solve the gateway deployment problem for maximizing network lifetime and present a method for balancing this goal with other performance optimization objectives, such as the minimization of average end-to-end delay.

Lastly, we show how our gateway deployment optimization framework can be practicality extended to a dynamic redeployment scenario. In addition to improving the performance of existing underwater sensor network deployments, the methods developed in this dissertation provide guidance for improving the performance of deployments of autonomous underwater and water-surface robots.