Automatic memory management is crucial in implementation of runtime systems even though it induces a significant computational overhead. In this thesis I explore the use of statistical properties of the directed graph describing the set of live data to decide between garbage collection and heap expansion in a memory management algorithm combining the dynamic array represented heaps with a mark and sweep garbage collector to enhance its performance. The sampling method predicting the density and the distribution of useful data is implemented as a partial marking algorithm. The algorithm randomly marks the nodes of the directed graph representing the live data at different depths with a variable probability factor p. Using the information gathered by the partial marking algorithm in the current step and the knowledge gathered in the previous iterations, the proposed empirical formula predicts with reasonable accuracy the density of live nodes on the heap, to decide between garbage collection and heap expansion. The resulting heuristics are tested empirically and shown to improve overall execution performance significantly in the context of the Jinni Prolog compiler's runtime system.

The widely used vector model maintains its popularity because of its simplicity, fast speed, and the appeal of using spatial proximity for semantic proximity. However, this model faces a disadvantage that is associated with the vagueness from keywords overlapping. Efforts have been made to improve the vector model. The research on improving document representation has been focused on four areas, namely, statistical co-occurrence of related items, forming term phrases, grouping of related words, and representing the content of documents. In this thesis, we propose the idea-indexing model to improve document representation for the filtering task in IR. The idea-indexing model matches document terms with the ideas they express and indexes the document with these ideas. This indexing scheme represents the document with its semantics instead of sets of independent terms. We show in this thesis that indexing with ideas leads to better performance.

A mobile ad hoc network (MANET) is a collection of mobile platforms or nodes that come together to form a network capable of communicating with each other, without the help of a central controller. To avail the maximum potential of a MANET, it is of great importance to devise a routing scheme, which will optimize upon the performance of a MANET, given the high rate of random mobility of the nodes. In a MANET individual nodes perform the routing functions like route discovery, route maintenance and delivery of packets from one node to the other. Existing routing protocols flood the network with broadcasts of route discovery messages, while attempting to establish a route. This characteristic is instrumental in deteriorating the performance of a MANET, as resource overhead triggered by broadcasts is directly proportional to the size of the network. Bounded-dynamic source routing (B-DSR), is proposed to curb this multitude of superfluous broadcasts, thus enabling to reserve valuable resources like bandwidth and battery power. B-DSR establishes a bounded region in the network, only within which, transmissions of route discovery messages are processed and validated for establishing a route. All route discovery messages reaching outside of this bounded region are dropped, thus …

In order to provide improved service quality to applications, networks need to address the need for reliability of data delivery. Reliability can be improved by incorporating fault tolerance into network routing, wherein a set of multiple routes are used for routing between a given source and destination. This thesis proposes a new fault-tolerant protocol, called the Multipath Fault Tolerant Protocol for Routing (MFTPR), to improve the reliability of network routing services. The protocol is based on a multipath discovery algorithm, the Quasi-Shortest Multipath (QSMP), and is designed to work in conjunction with the routing protocol employed by the network. MFTPR improves upon the QSMP algorithm by finding more routes than QSMP, and also provides for maintenance of these routes in the event of failure of network components. In order to evaluate the resilience of a pair of paths to failure, this thesis proposes metrics that evaluate the non-disjointness of a pair of paths and measure the probability of simultaneous failure of these paths. The performance of MFTPR to find alternate routes based on these metrics is analyzed through simulation.

Effective stewardship of forest ecosystems make it imperative to measure, monitor, and predict the dynamic changes of forest ecology. Measuring and monitoring provides us a picture of a forest's current state and the necessary data to formulate models for prediction. However, societal and natural events alter the course of a forest's development. A simulation environment that takes into account these events will facilitate forest management. In this thesis, we describe an efficient parallel implementation of a land cover use model, Mosaic, and discuss the development efforts to incorporate spatial interaction and succession dynamics into the model. To evaluate the performance of our implementation, an extensive set of simulation experiments was carried out using a dataset representing the H.J. Andrews Forest in the Oregon Cascades. Results indicate that a significant reduction in the simulation execution time of our parallel model can be achieved as compared to uni-processor simulations.

The explosive demand for multimedia and fast transmission of continuous media on wireless networks means the simultaneous existence of traffic requiring different qualities of service (QoS). In this thesis, several efficient algorithms have been developed which offer several QoS to the end-user. We first look at a request TDMA/CDMA protocol for supporting wireless multimedia traffic, where CDMA is laid over TDMA. Then we look at a hybrid push-pull algorithm for wireless networks, and present a generalized performance analysis of the proposed protocol. Some of the QoS factors considered include customer retrial rates due to user impatience and system timeouts and different levels of priority and weights for mobile hosts. We have also looked at how customer impatience and system timeouts affect the QoS provided by several queuing and scheduling schemes such as FIFO, priority, weighted fair queuing, and the application of the stretch-optimal algorithm to scheduling.

With the growing popularity of e-commerce applications that use software agents, the protection of mobile agent data has become imperative. To that end, the performance of four methods that protect the data integrity of mobile agents is evaluated. The methods investigated include existing approaches known as the Partial Result Authentication Codes, Hash Chaining, and Set Authentication Code methods, and a technique of our own design, called the Modified Set Authentication Code method, which addresses the limitations of the Set Authentication Code method. The experiments were run using the DADS agent system (developed at the Network Research Laboratory at UNT), for which a Data Integrity Module was designed. The experimental results show that our Modified Set Authentication Code technique performed comparably to the Set Authentication Code method.

There are two main approaches for intrusion detection: signature-based and anomaly-based. Signature-based detection employs pattern matching to match attack signatures with observed data making it ideal for detecting known attacks. However, it cannot detect unknown attacks for which there is no signature available. Anomaly-based detection builds a profile of normal system behavior to detect known and unknown attacks as behavioral deviations. However, it has a drawback of a high false alarm rate. In this thesis, we describe our anomaly-based IDS designed for detecting intrusions in cryptographic and application-level protocols. Our system has several unique characteristics, such as the ability to monitor cryptographic protocols and application-level protocols embedded in encrypted sessions, a very lightweight monitoring process, and the ability to react to protocol misuse by modifying protocol response directly.

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.

Geometric packing problems are NP-complete problems that arise in VLSI design. In this thesis, we present two novel algorithms using dynamic programming to compute exactly the maximum number of k x k squares of unit size that can be packed without overlap into a given n x m grid. The first algorithm was implemented and ran successfully on problems of large input up to 1,000,000 nodes for different values. A heuristic based on the second algorithm is implemented. This heuristic is fast in practice, but may not always be giving optimal times in theory. However, over a wide range of random data this version of the algorithm is giving very good solutions very fast and runs on problems of up to 100,000,000 nodes in a grid and different ranges for the variables. It is also shown that this version of algorithm is clearly superior to the first algorithm and has shown to be very efficient in practice.

Guiding navigation in virtual environments (VEs) is a challenging task. A key issue in the navigation of a virtual environment is to be able to strike a balance between the user's need to explore the environment freely and the designer's need to ensure that the user experiences all the important events in the VE. This thesis reports on a study aimed at comparing the effectiveness of various navigation cues that are used to motivate users towards a specific target location. The results of this study indicate some significant differences in how users responded to the various cues.

Many of the contemporary routing algorithms use simple mechanisms such as flooding or broadcasting to disseminate the routing information available to them. Such routing algorithms cause significant network resource overhead due to the large number of messages generated at each host/router throughout the route update process. Many of these messages are wasteful since they do not contribute to the route discovery process. Reducing the resource overhead may allow for several algorithms to be deployed in a wide range of networks (wireless and ad-hoc) which require a simple routing protocol due to limited availability of resources (memory and bandwidth). Motivated by the need to reduce the resource overhead associated with routing algorithms a new implementation of distance vector routing algorithm using an agent-based paradigm known as Agent-based Distance Vector Routing (ADVR) has been proposed. In ADVR, the ability of route discovery and message passing shifts from the nodes to individual agents that traverse the network, co-ordinate with each other and successively update the routing tables of the nodes they visit.

Wireless ad hoc networks are expected to play an important role in civilian and military settings where wireless access to wired backbone is either ineffective or impossible. Wireless sensor networks are effective in remote data acquisition. Congestion control and power consumption in wireless ad hoc networks have received a lot of attention in recent research. Several algorithms have been proposed to reduce congestion and power consumption in wireless ad hoc and sensor networks. In this thesis, we focus upon two schemes, which deal with congestion control and power consumption issues. This thesis consists of two parts. In the first part, we describe a randomization scheme for congestion control in dynamic source routing protocol, which we refer to as RDSR. We also study a randomization scheme for GDSR protocol, a GPS optimized variant of DSR. We discuss RDSR and RGDSR implementations and present extensive simulation experiments to study their performance. Our results indicate that both RGDSR and RDSR protocols outperform their non-randomized counterparts by decreasing the number of route query packets. Furthermore, a probabilistic congestion control scheme based on local tuning of routing protocol parameters is shown to be feasible. In the second part we present a simulation based performance study …

Peer-to-Peer (P2P) networks have seen tremendous growth in development and usage in recent times. This attention has brought many developments as well as new challenges to these networks. We will show that agent extensions to P2P networks offer solutions to many problems faced by P2P networks. In this research, an attempt is made to bring together JXTA P2P infrastructure and Jinni, a Prolog based agent engine to form an agent based P2P network. On top of the JXTA, we define simple Java API providing P2P services for agent programming constructs. Jinni is deployed on this JXTA network using an automated code update mechanism. Experiments are conducted on this Jinni/JXTA platform to implement a simple agent communication and data exchange protocol.

Agent-oriented software engineering (AOSE) covers issues on developing systems with software agents. There are many techniques, mostly agent-oriented and object-oriented, ready to be chosen as building blocks to create agent-based systems. There have been several AOSE methodologies proposed intending to show engineers guidelines on how these elements are constituted in having agents achieve the overall system goals. Although these solutions are promising, most of them are designed in ad-hoc manner without truly obeying software developing life-cycle fully, as well as lacking of examinations on agent-oriented features. To address these issues, we investigated state-of-the-art techniques and AOSE methodologies. By examining them in different respects, we commented on the strength and weakness of them. Toward a formal study, a comparison framework has been set up regarding four aspects, including concepts and properties, notations and modeling techniques, process, and pragmatics. Under these criteria, we conducted the comparison in both overview and detailed level. The comparison helped us with empirical and analytical study, to inspect the issues on how an ideal agent-based system will be formed.

The resources (memory, power and bandwidth) are limited in wireless and mobile networks. Previous research has shown that the quality of service (QoS) of the mobile client can be improved through efficient resources management. This thesis contains two areas of research that are strongly interrelated. In the first area of research, we extended the MoSync Algorithm, a network application layer media synchronization algorithm, to allow play-out of multimedia packets by the base station upon the mobile client in a First-In-First-Out (FIFO), Highest-Priority-First (PQ), Weighted Fair-Queuing (WFQ) and Round-Robin (RR) order. In the second area of research, we make modifications to the DSR and TORA routing algorithms to make them energy aware routing protocols. Our research shows that the QoS of the mobile client can be drastically improved through effective resource allocation.