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- Temporally Correct Algorithms for Transaction Concurrency Control in Distributed Databases
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Many activities are comprised of temporally dependent events that must be executed in a specific chronological order. Supportive software applications must preserve these temporal dependencies. Whenever the processing of this type of an application includes transactions submitted to a database that is shared with other such applications, the transaction concurrency control mechanisms within the database must also preserve the temporal dependencies. A basis for preserving temporal dependencies is established by using (within the applications and databases) real-time timestamps to identify and order events and transactions. The use of optimistic approaches to transaction concurrency control can be undesirable in such situations, as they allow incorrect results for database read operations. Although the incorrectness is detected prior to transaction committal and the corresponding transaction(s) restarted, the impact on the application or entity that submitted the transaction can be too costly. Three transaction concurrency control algorithms are proposed in this dissertation. These algorithms are based on timestamp ordering, and are designed to preserve temporal dependencies existing among data-dependent transactions. The algorithms produce execution schedules that are equivalent to temporally ordered serial schedules, where the temporal order is established by the transactions' start times. The algorithms provide this equivalence while supporting currency to the extent out-of-order commits and reads. With respect to the stated concern with optimistic approaches, two of the proposed algorithms are risk-free and return to read operations only committed data-item values. Risk with the third algorithm is greatly reduced by its conservative bias. All three algorithms avoid deadlock while providing risk-free or reduced-risk operation. The performance of the algorithms is determined analytically and with experimentation. Experiments are performed using functional database management system models that implement the proposed algorithms and the well-known Conservative Multiversion Timestamp Ordering algorithm.
- A Theoretical Network Model and the Incremental Hypercube-Based Networks
- The study of multicomputer interconnection networks is an important area of research in parallel processing. We introduce vertex-symmetric Hamming-group graphs as a model to design a wide variety of network topologies including the hypercube network.
- A Timescale Estimating Model for Rule-Based Systems
- The purpose of this study was to explore the subject of timescale estimating for rule-based systems. A model for estimating the timescale necessary to build rule-based systems was built and then tested in a controlled environment.
- A Top-Down Structured Programming Technique for Mini-Computers
- This paper reviews numerous theoretical results on control structures and demonstrates their practical examples. This study deals with the design of run-time support routines by using top-down structured programming technique. A number of examples are given as illustration of this method. In conclusion, structured programming has proved to be an important methodology for systematic program design and development.
- A Unifying Version Model for Objects and Schema in Object-Oriented Database System
- There have been a number of different versioning models proposed. The research in this area can be divided into two categories: object versioning and schema versioning. In this dissertation, both problem domains are considered as a single unit. This dissertation describes a unifying version model (UVM) for maintaining changes to both objects and schema. UVM handles schema versioning operations by using object versioning techniques. The result is that the UVM allows the OODBMS to be much smaller than previous systems. Also, programmers need know only one set of versioning operations; thus, reducing the learning time by half. This dissertation shows that UVM is a simple but semantically sound and powerful version model for both objects and schema.
- Using Normal Deduction Graphs in Common Sense Reasoning
- This investigation proposes a powerful formalization of common sense knowledge based on function-free normal deduction graphs (NDGs) which form a powerful tool for deriving Horn and non-Horn clauses without functions. Such formalization allows common sense reasoning since it has the ability to handle not only negative but also incomplete information.
- Visualization of Surfaces and 3D Vector Fields
- Visualization of trivariate functions and vector fields with three components in scientific computation is still a hard problem in compute graphic area. People build their own visualization packages for their special purposes. And there exist some general-purpose packages (MatLab, Vis5D), but they all require extensive user experience on setting all the parameters in order to generate images. We present a simple package to produce simplified but productive images of 3-D vector fields. We used this method to render the magnetic field and current as solutions of the Ginzburg-Landau equations on a 3-D domain.
- XML-Based Agent Scripts and Inference Mechanisms
- Natural language understanding has been a persistent challenge to researchers in various computer science fields, in a number of applications ranging from user support systems to entertainment and online teaching. A long term goal of the Artificial Intelligence field is to implement mechanisms that enable computers to emulate human dialogue. The recently developed ALICEbots, virtual agents with underlying AIML scripts, by A.L.I.C.E. foundation, use AIML scripts - a subset of XML - as the underlying pattern database for question answering. Their goal is to enable pattern-based, stimulus-response knowledge content to be served, received and processed over the Web, or offline, in the manner similar to HTML and XML. In this thesis, we describe a system that converts the AIML scripts to Prolog clauses and reuses them as part of a knowledge processor. The inference mechanism developed in this thesis is able to successfully match the input pattern with our clauses database even if words are missing. We also emulate the pattern deduction algorithm of the original logic deduction mechanism. Our rules, compatible with Semantic Web standards, bring structure to the meaningful content of Web pages and support interactive content retrieval using natural language.