Not available / text

We present tools for a network topology based characterization of heterogeneity in multiagent systems, thereby providing a framework for the analysis and design of heterogeneous multiagent networks from a network structure view-point. In heterogeneous networks, agents with a diverse set of resources coordinate with each other. Coordination among different agents and the structure of the underlying network topology have significant impacts on the overall behavior and functionality of the system. Using constructs from graph theory, a qualitative as well as a quantitative analysis is performed to examine an inter-relationship between the network topology and the distribution of agents with various capabilities in heterogeneous networks. Our goal is to allow agents maximally exploit heterogeneous resources available within the network through local interactions, thus exploring a promise heterogeneous networks hold to accomplish complicated tasks by leveraging upon the assorted capabilities of agents. For a reliable operations of such systems, the issue of security against intrusions and malicious agents is also addressed. We provide a scheme to secure a network against a sequence of intruder attacks through a set of heterogeneous guards. Moreover, robustness of networked systems against noise corruption and structural changes in the underlying network topology is also examined.

Thesis (M.S.)--Ohio University, March, 1982. / Title from PDF t.p.

Thesis (Ph. D.)--University of Texas at Austin, 2004. / Supervisor: Greg Plaxton. Vita. Includes bibliographical references. Also available from UMI.

Thesis (Ph. D.)--Industrial and Systems Engineering, Georgia Institute of Technology, 2006. / Dr. Yih-Long Chang, Committee Member ; Dr. Martin Savelsbergh, Committee Member ; Dr. Leon McGinnis, Committee Co-Chair ; Dr. Gunter Sharp, Committee Chair ; Dr. Doug Bodner, Committee Member ; Dr. Joel Sokol, Committee Member.

M.Ing. / Mobile adhoc networks (MANETs) are multihop wireless topologies that have rapidly changing node structure and limited connectivity. Since MANETs are not deployed on a wide scale, the research community still depends on the simulators such as the network simulator (Ns2) to evaluate MANET protocols. The topic of how to accurately model an indoor environment in the MANET research community is explored in this dissertation. We take an empirical and simulative approach to model our mobility pattern. Our mobility model is based on activity patterns drawn from the transport science. A comparison with the random way point is made in order to understand the weighty discrepancy between the two models. Our contribution in this research is three fold: 1. We argue that mobility modelling should be based on activities other than stochastic process that have got no realistic backing; 2. We model our network using by putting up an algorithm and take an empirical approach to model the radio frequency propagation. To show the difference of the two mobility models, the behaviour of the signal strength on the two mobility models is drawn; and 3. Finally an implementation of our mobility pattern and RF measurements in ns2 is done.

The influx of new data-intensive applications, such as machine learning and artificial intelligence, in high performance computing (HPC) and data centers (DC), has driven the design of efficient interconnection networks to meet the requisite bandwidth of the growing traffic demand. While the exponentially-growing traffic demand is expected to continue into the future, the free scaling of CMOS-based electrical interconnection networks will eventually taper off due to Moore’s Law. These trends suggest that building all-electrical interconnects to meet the increased demand for low latency, high throughput networking will become increasingly impractical going forward. Integrating optical interconnects capable of supporting high bandwidth links and dynamic network topology reconfiguration offer a potential solution to scaling current networks. However, the insertion of photonic interconnection networks offers a massive design space in terms of network topology and control plane that is currently under-explored. The work in this dissertation is centered around the study and development of control plane challenges to aid in the eventual adoption of optically-enabled reconfigurable networks. We begin by exploring Flexspander, a novel reconfigurable network topology that combines the flexible random expander networks construction with topological-reconfigurability using optical circuit switching (OCS). By incorporating random expander graph construction, as opposed to other more symmetric reconfigurable topologies, Flexspander can be built with a broader range of electrical packet switch (EPS) radix, while retaining high throughput and low latency when coupled with multi-path routing. In addition, we propose a topology-routing co-optimization scheme to improve network robustness under traffic uncertainties. Our proposed scheme employs a two-step strategy: First, we optimize the topology and routing strategy by maximizing throughput and average packet hop count for the expected traffic patterns based on historical traffic patterns. Second, we employ a desensitization step on top of the topology and routing solution to lower performance degradation due to traffic variations. We demonstrate the effectiveness of our approach using production traces from Facebook's Altoona data center, and show that even with infrequent reconfigurations, our solution can attain performances within 15\% of an offline optimal oracle. Next, we study the problem of routing scheme design in reconfigurable networks, which is a more under-studied problem compared to routing design for static networks. We first perform theoretical analyses to first identify the key properties an effective routing protocol for reconfigurable networks should possess. Using findings from these theoretical analyses, we propose a lightweight but effective routing scheme that yields high performance for practical HPC and DC workloads when employed with reconfigurable networks. Finally, we explore two fundamental design problems in the optical reconfigurable network design. First, it investigates how different OCS placement in the physical network topology lead to different tradeoffs in terms of power consumption/cost, network performance, and scalability. Second, we investigate how network performance is affected by different reconfiguration periods to understand how frequency of topology reconfiguration affects application performance. Taken together, the work in this dissertation tackles several key challenges related to efficient control plane for reconfigurable network designs, with the goal of facilitating the eventual adoption of optically-enable reconfigurable networks in high performance systems.

Basic PWM dc-to-dc converter structure is examined wherein a basic substructure of converters, known as a converter cell, is identified. Converter cells can be used in generation and classification of basic PWM dc-to-dc converters. A large number of new converters are generated. Converter analysis, whereby the nonlinear response of the system to perturbations in the control or the input, is determined by two different methods. A classical approach to nonlinear systems analysis is first used wherein the system is represented by a Volterra functional series. The alternative approach presented concentrates on deriving circuit models for the PWM switch. The PWM switch represents the static nonlinear substructure of the vast majority of converter cells. Analysis of converters then proceeds in an analogous fashion to ordinary transistor circuit analysis whereby the nonlinear device is replaced by its circuit model. Topological considerations of single-phase dc-to-ac inverters are discussed. A number of zero-current switching quasi-resonant inverter topologies are derived. Schemes that permit these topologies to handle reactive loads are identified. / Ph. D.

Wireless sensor networks (WSNs) are characterized by limited amount of energy supply at sensor nodes. Hence, energy efficiency is an important issue in system design and operation of WSNs. In this work we focus on solving the energy efficiency problems of data gathering processes in WSNs. We first address this problem on a macroscopic level by investigating the efficiency of data gathering trees when data sent by different sensors are correlated. Such correlation aware data gathering strategies typically shift the aggregation structure from a default shortest-path tree (SPT) to a steiner minimum tree (SMT) in order to achieve the required efficiency. We study the energy efficiency of correlation aware data aggregation trees under various sensor network conditions and the tradeoffs involved in using them. Comprehensive simulation results as well as inferences and theoretical analysis of those results are presented in the thesis. Based on the insights gained through the investigation, we propose a simple, scalable and distributed correlation aware aggregation structure that achieves good energy performance across a wide range of sensor network configurations, and at the same time addresses the practical challenges of establishing a correlation aware data aggregation structure in resource-constrained WSNs. On a microscopic level, we propose a novel communication strategy called Communication through Silence (CtS) to achieve energy-efficient data gathering without significant degradation on overall throughput in WSNs. The proposed scheme primarily uses time, along with a minimal amount of energy to deliver information among sensors. CtS can be used to replace the conventional energy-based transmissions between each pair of sensor nodes during a data gathering process. We analyze in detail the primary energy-throughput tradeoff inherent in this approach as well as other challenges related to the realization of the proposed communication strategy. Finally, we propose a practical realization of CtS strategy that includes radio technology, MAC layer, and higher layer solutions. Performance evaluation results prove that this solution effectively realizes the CtS strategy in a WSN setting, at the same time achieves considerable energy savings compared to conventional communication strategies.

Critical infrastructure systems are essential for the continuous functionality of modern global societies. Some examples of these systems include electric energy, potable water, oil and gas, telecommunications, and the internet. Different topologies underline the structure of these networked systems. Each topology (i.e., physical layout) conditions the way in which networks transmit and distribute their flow. Also, their ability to absorb unforeseen natural or intentional disruptions depends on complex relations between network topology and optimal flow patterns. Most of the current research on large networks is focused on understanding their properties using statistical physics, or on developing advanced models to capture network dynamics. Despite these important research efforts, almost all studies concentrate on specific networks. This network-specific approach rules out a fundamental phenomenon that may jeopardize the performance predictions of current sophisticated models: network response is in general interdependent, and its performance is conditioned on the performance of additional interacting networks. Although there are recent conceptual advances in network interdependencies, current studies address the problem from a high-level point of view. For instance, they discuss the problem at the macro-level of interacting industries, or utilize economic input-output models to capture entire infrastructure interactions. This study approaches the problem of network interdependence from a more fundamental level. It focuses on network topology, flow patterns within the networks, and optimal interdependent system performance. This approach also allows for probabilistic response characterization of interdependent networked systems when subjected to disturbances of internal nature (e.g., aging, malfunctioning) or disruptions of external nature (e.g., coordinated attacks, seismic hazards). The methods proposed in this study can identify the role that each network element has in maintaining interdependent network connectivity and optimal flow. This information is used in the selection of effective pre-disaster mitigation and post-disaster recovery actions. Results of this research also provide guides for growth of interacting infrastructure networks and reveal new areas for research on interdependent dynamics. Finally, the algorithmic structure of the proposed methods suggests straightforward implementation of interdependent analysis in advanced computer software applications for multi-hazard loss estimation.