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This thesis outlines the evolution of computer hardware and software architectures which are suitable for the programming and control of modular robots and distributed manipulators. Fundamental aspects of automating manufacturing functions are considered and the use of flexible machines, constructed from components of a family of mechanical modules and associated control system elements, are proposed. Many of the features of these flexible machines can be identified with those of conventional industrial robots. However a broader class of manufacturing machine is represented in as much as the industrial user defines the kinematics and dynamics of the manipulator. Such flexible machines can be referred to as "modular robots" or, where the mechanical modules are arranged in concurrently operating but mechanically decoupled groups, as "distributed manipulators". The main body of the work reported centred on the design of a family of computer control system elements which can serve a range of distributed manipulator and modular robot forms. These control system elements, whose cost is commensurate with the size and complexity of the manipulator's mechanical configuration, necessarily have many of the features found in robot controllers but also require properties of reconfigurability, programmability, and control system performance for the considerable array of manipulator configurations which can be constructed.

We design, analyze, and optimize distributed detection and estimation algorithms in a large, shared-channel, single-hop wireless sensor network (WSN). The fusion center (FC) is allocated a shared transmission channel to collect local decisions/estimates but cannot collect all of them because of limited energy, bandwidth, or time. We propose a strategy called reliability-based splitting algorithm that enables the FC to collect local decisions/estimates in descending order of their reliabilities through a shared collision channel. The algorithm divides the transmission channel into time frames and the sensor nodes into groups based on their observation reliabilities. Only nodes with a specified range of reliabilities compete for the channel using slotted ALOHA within each frame. Nodes with the most reliable decisions/estimates attempt transmission in the first frame; nodes with the next most reliable set of decisions/estimates attempt in the next frame; etc. The reliability-based splitting algorithm is applied in three scenarios: time-constrained distributed detection; sequential distributed detection; and time-constrained estimation. Performance measures of interest - including detection error probability, efficacy, asymptotic relative efficiency, and estimator variance - are derived. In addition, we propose and analyze algorithms that exploit information from the occurrence of collisions to improve the performance of both time-constrained distributed detection and sequential distributed detection.

Monitoring and debugging distributed systems is inherently a difficult problem. Events collected during the execution of distributed systems can enable developers to diagnose and fix faults. Process-time diagrams are normally used to view the relationships between the events and understand the interaction between processes over time. A major difficulty with analyzing these sets of events is that they are usually very large. Therefore, being able to search through the event-data sets can enable users to get to points of interest quickly and find out if patterns in the dataset represent the expected behaviour of the system. A lot of research work has been done to improve the search algorithm for finding event-patterns in large partial-order datasets. In this thesis, we improve on this work by parallelizing the search algorithm. This is useful as many computers these days have more than one core or processor. Therefore, it makes sense to exploit this available computing power as part of an effort to improve the speed of the algorithm. The search problem itself can be modeled as a Constraint Satisfaction Problem (CSP). We develop a simple and efficient way of generating tasks (to be executed by the cores) that guarantees that no two cores will ever repeat the same work-effort during the search. Our approach is generic and can be applied to any CSP consisting of a large domain space. We also implement an efficient dynamic work-stealing strategy that ensures the cores are kept busy throughout the execution of the parallel algorithm. We evaluate the efficiency and scalability of our algorithm through experiments and show that we can achieve efficiencies of up to 80% on a 24-core machine.

This thesis focuses on the development of a distributed pair programming tool that enables two programmers to generate code together in JBuilder editor over the web. First, software development processes are generally reviewed and Extreme Programming, Distributed Extreme Programming, and Distributed Pair Programming issues are examined. The tools that enable Distributed Pair Programming are compared. This thesis also specifies the functional requirements of the newly presented tool and includes information about its design and implementation processes. Finally, an evaluation is given by indicating the positive and negative sides of the tool.

This thesis presents the design, development, and testing of a multi-agent systems laboratory that will enable the experimental investigation of Networked Control Systems. Networked Control Systems (NCS) are integrations of computation, networking, and physical dynamics, in which embedded devices are networked to sense, monitor, execute collaborative tasks, and interact with the physical world. As the potential for applications of NCS has increased, so has the research interest in this area. Possible applications include search and rescue, scientific data collection, and health care monitoring systems. One of the primary challenges in applying NCS is designing distributed algorithms that will enable the networked devices to achieve global objectives. Another challenge is in ensuring that distributed algorithms have the necessary robustness to achieve those global objectives in dynamic and unpredictable environments. A multi-agent systems laboratory provides the researcher with a means to observe the behavior and performance of distributed algorithms as they are executed on a set of networked devices. Through this observation, the researcher may discover robustness issues that were not present in computer simulation. The objective of this research is to design and implement the infrastructure for a multi-agent systems laboratory to observe distributed algorithms implemented on networked devices.

Thesis (M.Sc.)--Acadia University, 1999. / Includes bibliographical references (leaves 88-89). Also available on the Internet via the World Wide Web.