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In the area of artificial intelligence, the development of Evolutionary Algorithms (EAs) has been very active, especially in the last decade. These algorithms started to evolve when scientists from various regions of the world applied the principles of evolution to algorithmic search and problem solving. EAs have been utilised successfully in diverse complex application areas. Their success in tackling hard problems has been the engine of the field of Evolutionary Computation (EC). Nowadays, EAs are considered to be the best solution to use when facing a hard search or optimisation problem. Various improvements are continually being made with the design of new operators, hybrid models, among others. A very important example of such improvements is the use of parallel models of GAs (PGAs). PGAs have received widespread attention from various researchers as they have proved to be more effective than panmictic GAs, especially in terms of efficacy and speedup. This thesis focuses on, and investigates, cellular Genetic Algorithms (cGAs)-a competitive variant of parallel GAs. In a cGA, the tentative solutions evolve in overlapped neighbourhoods, allowing smooth diffusion of the solutions. The benefits derived from using cGAs come not only from flexibility gains and their fitness to the objective target in combination with a robust behaviour but also from their high performance and amenability to implementation using advanced custom silicon chip technologies. Nowadays, cGAs are considered as adaptable concepts for solving problems, especially complex optimisation problems. Due to their structural characteristics, cGAs are able to promote an adequate exploration/exploitation trade-off and thus maintain genetic diversity. Moreover, cGAs are characterised as being massively parallel and easy to implement. The structural characteristics inherited in a cGA provide an active area for investigation. Because of the vital role grid structure plays in determining the effectiveness of the algorithm, cellular dimensionality is the main issue to be investigated here. The implementation of cGAs is commonly carried out on a one- or two-dimensional structure. Studies that investigate higher cellular dimensions are lacking. Accordingly, this research focuses on cGAs that are implemented on a three-dimensional structure. Having a structure with three dimensions, specifically a cubic structure, facilitates faster spreading of solutions due to the shorter radius and denser neighbourhood that result from the vertical expansion of cells. In this thesis, a comparative study of cellular dimensionality is conducted. Simulation results demonstrate higher performance achieved by 3D-cGAs over their 2D-cGAs counterparts. The direct implementation of 3D-cGAs on the new advanced 3D-IC technology will provide added benefits such as higher performance combined with a reduction in interconnection delays, routing length, and power consumption. The maintenance of system reliability and availability is a major concern that must be addressed. A system is likely to fail due to either hard or soft errors. Therefore, detecting a fault before it deteriorates system performance is a crucial issue. Single Event Upsets (SEUs), or soft errors, do not cause permanent damage to system functionality, and can be handled using fault-tolerant techniques. Existing fault-tolerant techniques include hardware or software fault tolerance, or a combination of both. In this thesis, fault-tolerant techniques that mitigate SEUs at the algorithmic level are explored and the inherent abilities of cGAs to deal with these errors are investigated. A fault-tolerant technique and several mitigation techniques are also proposed, and faulty critical data are evaluated critical fault scenarios (stuck at ‘1’ and stuck at ‘0’ faults) are taken into consideration. Chief among several test and real world problems is the problem of determining the attitude of a vehicle using a Global Positioning System (GPS), which is an example of hard real-time application. Results illustrate the ability of cGAs to maintain their functionality and give an adequate performance even with the existence of up to 40% errors in fitness score cells. The final aspect investigated in this thesis is the dynamic characteristic of cGAs. cGAs, and EAs in general, are known to be stochastic search techniques. Hence, adaptive systems are required to continue to perform effectively in a changing environment, particularly when tackling real-world problems. The adaptation in cellular engines is mainly achieved through dynamic balancing between exploration and exploitation. This area has received considerable attention from researchers who focus on improving the algorithmic performance without incurring additional computational effort. The structural properties and the genetic operations provide ways to control selection pressure and, as a result, the exploration/exploitation trade-off. In this thesis, the genetic operations of cGAs, particularly the selection aspect and their influence on the search process, are investigated in order to dynamically control the exploration/exploitation trade-off. Two adaptive-dynamic techniques that use genetic diversity and convergence speeds to guide the search are proposed. Results obtained by evaluating the proposed approaches on a test bench of diverse-characteristic real-world and test problems showed improvement in dynamic cGAs performance over their static counterparts and other dynamic cGAs. For example, the proposed Diversity-Guided 3D-cGA outperformed all the other dynamic cGAs evaluated by obtaining a higher search success rate that reached to 55%.

Years of success in the aerospace industry has taught Kentucky Space several lessons. This thesis will summarize the accomplishments in an attempt to formulate a well-defined program for designing and testing small spacecraft in an environment with strict financial restraints. The motivation for producing this well-defined platform for testing small spacecraft arose when Kentucky Space became the liaison between NASA and its customers for the NanoRacks and CubeLab module program. Having a solid program for testing small spacecraft will allow future student programs to easily set standards for experiment payloads. Also by discussing obstacles for smaller programs such as restraints on funding, scheduling restrictions, and testing facility procurement, this thesis will provide a basis that other programs can use to start or expand a space research program that may be struggling due to mistakes that programs face in the early years due to the lack of experience and maturity of a veteran program.

Fault tolerant and distributed embedded systems are research areas that have the interest of such entities as NASA, the Department of Defense, and various other government agencies, corporations, and universities. Taking a system and designing it to work in the presence of faults is appealing to these entities as it inherently increases the reliability of the deployed system. There are a few different fault tolerant techniques that can be implemented in a system design to handle faults as they occur. One such technique is the reconfiguration of a portion of the system to a redundant resource. This is a difficult task to manage within a distributed embedded system because of the distributed, directly addressed data producer and consumer dependencies that exist in common network infrastructures. It is the goal of this thesis work to develop a novel message routing layer for the communication management of distributed embedded systems that reduces the complexity of this problem. The resulting product of this thesis provides a robust approach to the design, implementation, integration, and deployment of a distributed embedded system.

Dependable and Fault-tolerant computing is actively being pursued as a research area since the 1980s in various fields involving development of safety-critical applications. The ability of the system to provide reliable functional service as per its design is a key paradigm in dependable computing. For providing reliable service in fault-tolerant systems, dynamic reconfiguration has to be supported to enable recovery from errors (induced by faults) or graceful degradation in case of service failures. Reconfigurable Distributed applications provided a platform to develop fault-tolerant systems and these reconfigurable architectures requires an embedded network that is inherently fault-tolerant and capable of handling movement of tasks between nodes/processors within the system during dynamic reconfiguration. The embedded network should provide mechanisms for deterministic message transfer under faulty environments and support fault detection/isolation mechanisms within the network framework. This thesis describes the design, implementation and validation of an embedded networking layer using Controller Area Network (CAN) to support reconfigurable embedded systems.

This thesis describes the design, implementation and testing of a spacecraft bus implemented on KySat-1, a picosatellite scheduled to launch late 2009 to early 2010. The spacecraft bus is designed to be a robust reusable bus architecture using commercially available off the shelf components and subsystems. The bus designed and implemented for the KySat-1 spacecraft will serve as the basis for a series of future Kentucky Space Consortium missions. The spacecraft bus consists of attitude determination and control subsystem, communications subsystem, command and data handling subsystem, thermal subsystem, power subsystem, and structures and mechanisms. The spacecraft bus design is described and the implementation and testing and experimental results of the integrated spacecraft engineering model. Lessons learned with the integration, implementation, and testing using commercial off the shelf components are also included. This thesis is concluded with future spacecraft bus improvements and launch opportunity of the implemented spacecraft, KySat-1.

The Publish/Subscribe (pub/sub) model has been widely applied in a variety of application scenarios which demand loose-coupling and asynchronous communication between a large number of information sources and sinks. In this model, clients are granted the flexibility to specify their interests at a high level and rely on the pub/sub middleware for delivery of their publications of interest. This increased flexibility and ease of use on the client side results in substantial complexity on part of the pub/sub middleware implementation. Furthermore, for several reasons including improved scalability, availability and avoiding a single point of failure, the pub/sub middleware is commonly composed of a set of collaborating message routers, a.k.a. brokers. The distributed nature of this design further introduces new challenges in ensuring end-to-end reliability as well as efficiency of operation. These challenges are largely unique to the pub/sub model and hence absent in both point-to-point or multicast protocols. This thesis develops solutions that ensure the dependable operation of the pub/sub system by exploiting the notion of overlay neighborhoods in a formal manner. More specifically, brokers maintain information about their neighbors within a configurable distance in the pub/sub overlay and exploit this knowledge to construct alternative forwarding paths or make smart forwarding decisions that improves efficiency, bandwidth utilization and delivery delay, all at the same time. Furthermore, in the face of failures overlay neighborhoods enable fast reconstruction of forwarding paths in the system without compromising its reliability and availability. Finally, as an added benefit of overlay neighborhoods, this thesis develops large-scale algorithms that bring the advantages of the pub/sub model to the domain of file sharing and bulk content dissemination applications. Experimental evaluation results with deployments as large as 1000 nodes illustrate that the pub/sub system scales well and outperforms the traditional BitTorrent protocol in terms of content dissemination delay.

Intelligent Transportation Systems (ITS) are gaining momentum among researchers. ITS encompasses several technologies, including wireless communications, sensor networks, data and voice communication, real-time driving assistant systems, etc. These states of the art technologies are expected to pave the way for a plethora of vehicular network applications. In fact, recently we have witnessed a growing interest in Vehicular Networks from both the research community and industry. Several potential applications of Vehicular Networks are envisioned such as road safety and security, traffic monitoring and driving comfort, just to mention a few. It is critical that the existence of convenience or driving comfort services do not negatively affect the performance of safety services. In essence, the dissemination of safety services or the discovery of convenience applications requires the communication among service providers and service requesters through constrained bandwidth resources. Therefore, service discovery techniques for vehicular networks must efficiently use the available common resources. In this thesis, we focus on the design of bandwidth-efficient and scalable service discovery protocols for Vehicular Networks. Three types of service discovery architectures are introduced: infrastructure-less, infrastructure-based, and hybrid architectures. Our proposed algorithms are network layer based where service discovery messages are integrated into the routing messages for a lightweight discovery. Moreover, our protocols use the channel diversity for efficient service discovery. We describe our algorithms and discuss their implementation. Finally, we present the main results of the extensive set of simulation experiments that have been used in order to evaluate their performance.

Fault analysis attacks represent a serious threat to a wide range of cryptosystems including those based on elliptic curves. With the variety and demonstrated practicality of these attacks, it is essential for cryptographic implementations to handle different types of errors properly and securely. In this work, we address some aspects of error detection and recovery in elliptic curve cryptosystems. In particular, we discuss the problem of wasteful computations performed between the occurrence of an error and its detection and propose solutions based on frequent validation to reduce that waste. We begin by presenting ways to select the validation frequency in order to minimize various performance criteria including the average and worst-case costs and the reliability threshold. We also provide solutions to reduce the sensitivity of the validation frequency to variations in the statistical error model and its parameters. Then, we present and discuss adaptive error recovery and illustrate its advantages in terms of low sensitivity to the error model and reduced variance of the resulting overhead especially in the presence of burst errors. Moreover, we use statistical inference to evaluate and fine-tune the selection of the adaptive policy. We also address the issue of validation testing cost and present a collection of coherency-based, cost-effective tests. We evaluate variations of these tests in terms of cost and error detection effectiveness and provide infective and reduced-cost, repeated-validation variants. Moreover, we use coherency-based tests to construct a combined-curve countermeasure that avoids the weaknesses of earlier related proposals and provides a flexible trade-off between cost and effectiveness.

Thesis (Ph. D.)--University of Texas at Austin, 2007. / Vita. Includes bibliographical references.