Thesis (M.S.)--West Virginia University, 2008. / Title from document title page. Document formatted into pages; contains ix, 107 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 101-107).

Thesis (Ph. D.)--University of California, Riverside, 2008. / Includes abstract. Title from first page of PDF file (viewed March 10, 2010). Available via ProQuest Digital Dissertations. Includes bibliographical references (p. 93-98). Also issued in print.

Thesis (Ph.D.)--University of Western Sydney, 2009. / A thesis presented to the University of Western Sydney, College of Health and Science, School of Computing and Mathematics, in fulfilment of the requirements for the degree of Doctor of Philosophy. Includes bibliographies.

Thesis (Ph. D.)--University of Washington, 2002. / Vita. Includes bibliographical references (p. 98-104).

A cyber-physical system (CPS) is a system featuring a tight combination of, and coordination between, the system’s computational and physical elements. A large-scale CPS usually consists of several subsystems which are formed by networked sensors and actuators, and deployed in different locations. These subsystems interact with the physical world and execute specific monitoring and control functions. How to organize the sensors and actuators inside each subsystem and interconnect these physically separated subsystems together to achieve secure, reliable and real-time communication is a big challenge. In this thesis, we first present a TDMA-based low-power and secure real-time wireless protocol. This protocol can serve as an ideal communication infrastructure for CPS subsystems which require flexible topology control, secure and reliable communication and adjustable real-time service support. We then describe the network management techniques designed for ensuring the reliable routing and real-time services inside the subsystems and data management techniques for maintaining the quality of the sampled data from the physical world. To evaluate these proposed techniques, we built a prototype system and deployed it in different environments for performance measurement. We also present a light-weighted and scalable solution for interconnecting heterogeneous CPS subsystems together through a slim IP adaptation layer and a constrained application protocol layer. This approach makes the underlying connectivity technologies transparent to the application developers thus enables rapid application development and efficient migration among different CPS platforms. At the end of this thesis, we present a semi-autonomous robotic system called cyberphysical avatar. The cyberphysical avatar is built based on our proposed network infrastructure and data management techniques. By integrating recent advance in body-compliant control in robotics, and neuroevolution in machine learning, the cyberphysical avatar can adjust to an unstructured environment and perform physical tasks subject to critical timing constraints while under human supervision. / text

The Embedded Computer System Support Improvement Program, or ESIP, was begun by the U.S. Air Force in 1983 to find new cost effective ways of integrating, testing and maintaining the computers embedded in military airborne, spaceborne, and ground electronic systems. A major initiative of this program is the Extendable Integration Support Environment (EISE). The EISE project involves design and development of a high speed network-based hardware and software integration and test environment. The ongoing work is being done jointly by U.S. Air Force civilian engineers at McClellan Air Force Base and TRW in Sacramento, California, in support of embedded avionics computers in the A-10 aircraft. The prototype design will be used to test and integrate various other aircraft and space systems. The author was the EISE project lead system engineer from July 1986 through January 1988.

published_or_final_version / abstract / toc / Physics / Doctoral / Doctor of Philosophy

published_or_final_version / Electrical and Electronic Engineering / Master / Master of Philosophy

Date stream mining techniques can be used in tracking user behaviors as they attempt to achieve their goals. Quality metrics over stream-mined models identify potential changes in user goal attainment. When the quality of some data mined models varies significantly from nearby models—as defined by quality metrics—then the user’s behavior is automatically flagged as a potentially significant behavioral change. Decision tree, sequence pattern and Hidden Markov modeling being used in this study. These three types of modeling can expose different aspect of user’s behavior. In case of decision tree modeling, the specific changes in user behavior can automatically characterized by differencing the data-mined decision-tree models. The sequence pattern modeling can shed light on how the user changes his sequence of actions and Hidden Markov modeling can identifies the learning transition points. This research describes how model-quality monitoring and these three types of modeling as a generic framework can aid recognition and diagnoses of behavioral changes in a case study of cognitive rehabilitation via emailing. The date stream mining techniques mentioned are used to monitor patient goals as part of a clinical plan to aid cognitive rehabilitation. In this context, real time data mining aids clinicians in tracking user behaviors as they attempt to achieve their goals. This generic framework can be widely applicable to other real-time data-intensive analysis problems. In order to illustrate this fact, the similar Hidden Markov modeling is being used for analyzing the transactional behavior of a telecommunication company for fraud detection. Fraud similarly can be considered as a potentially significant transaction behavioral change.

Modern telecommunications companies are moving away from conventional circuit-switched architectures to more versatile packet-switched infrastructures. Traditional First-In-FirstOut (FIFO) queues that are currently multiplexing IP traffic are not able to meet the strict Quality-of-Service (QoS) requirements of delay sensitive real-time traffic. Two main solution families exist that separate heterogeneous traffic into appropriate classes. The first is known as Generalized Processor Sharing (GPS), which divides the available bandwidth among the contending classes, proportionally to the throughput guarantee negotiated with each class. GPS and its myriad of packetised variants are relatively easy to analyse, as the service rate of individual classes is directly related to its throughput guarantee. As GPS splits the arriving traffic into separate queues, it is useful for best-effort traffic, supplying each class of traffic with either a maximum or minimum amount of bandwidth that it deserves. The second solution is the Earliest Deadline First (EDF) scheduler, also known as Earliest Due Date (EDD). Each traffic class has a delay deadline, by which the individual packets need to be served in order to meet their heterogeneous QoS requirements. EDF selects packets that are closest to their deadline. It is therefore primarily useful for delay sensitive real-time traffic. Although this is a simple algorithm, it turns out to be surprisingly difficult to analyse. Several papers attempted to analyse EDF. Most of them found either discrete bounds, which lie far away from the mean, or stochastic bounds which tend to capture the delay behaviour of the traffic more accurately. After the introductory first chapter, this thesis simulates a realistic cellular environment, where packets of various classes of service are transmitted across an HSDPA air interface. The aim is to understand the behaviour of EDF and its channel aware Opportunistic EDF scheduler compared to other scheduling families commonly used in HSDPA environments. In particular, Round Robin is simulated as the most simplistic scheduler. Max ell chooses packets solely based on the best channel conditions. Finally, PF -T is a scheme that tries to maximise the overall transmission rate that packets experience, but this metric gets divided by the throughput that each class already achieved. This introduces a form of long-term fairness that prevents the starvation of individual classes. The third chapter contains the main analysis, which uses Large Deviation principles and the Effective Bandwidth theory to approximate the deadline violation probability and the delay density function of EDF in a wired network. A definition for the fairness of EDF is proposed. The analysis is extended to approximate the stochastic fairness distribution. In the fourth chapter of the thesis an opportunistic EDF scheduler is proposed for mobile legs of a network that takes advantage of temporary improvements in the channel conditions. An analytical model is developed that predicts the delay density function of the opportunistic EDF scheduler. The channel propagation gain is assumed to be log-normally distributed, which requires graphical curve fitting, as no closed-form solution exists / Thesis (Ph.D.)-University of KwaZulu-Natal, Durban, 2009.