Managing mobile ad hoc networks (MANETs) presents new challenges due to the need for a distributed management mechanism that can efficiently adapt to the dynamic nature of these networks. In particular, provisioning and management of Quality of Service (QoS) in such networks remains a challenging task. Previous works in this field have focused largely on the monitoring and data collection aspects of network management; literature on the provisioning of devices and protocol support for MANET configuration is scarce. One approach for QoS provisioning and management in the Internet that has met with considerable interest in the networking community is that of Policy-Based Network Management (PBNM). However, its application has been so far limited mainly to fixed high-bandwidth networks. In this research, we apply the PBNM concept, for the first time, for managing QoS in ad hoc networks. We formulate a framework to understand the various crucial components that should comprise an ad hoc network management system. We propose a taxonomy of policy architectures to classify the various feasible architectures into distinct categories. Based on our assessment using the taxonomy, we identify architectures that seem promising for managing ad hoc networks. We propose a solution suite to address the different challenges in deploying policy-based management in MANETs. These solutions include k-hop clustering, Dynamic Service Redundancy (DynaSeR), inter-domain policy negotiation, and automated service discovery. We propose extensions to the standard Common Open Policy Service (COPS) protocol and suggest methods for cross-layer interaction to implement our solutions. Our methodology focuses on both a prototype implementation and experimental analysis using wired and wireless testbed networks, and modeling and performance evaluation using simulation. The whole exercise of conducting experiments provided valuable insight into the challenges of operating in an actual ad hoc network environment; implementation and testing facilitated assessment of the feasibility of our proposed schemes. Simulation allowed us to evaluate our solutions for different cluster sizes, network densities, and node mobility. The scalability of our solutions was tested with networks of up to 100 nodes. In general, average service availability for the PBNM system improved as the cluster size increased, with decreased COPS connection overhead (the tradeoff is increased unpredictability, longer response time, and resource requirements at intermediate nodes to support larger clusters). We were also able to determine that, for a given cluster size, our proposed delegation scheme resulted in a 10 to 25% improvement in service availability. Using our proposed time-based heuristic, savings on the order of 50 to 400% were obtained in the service discovery overhead for larger cluster sizes. We also validated some of the simulation results against proof-of-concept experiments conducted using the testbed. We presented a working illustration of our PBNM system prototype by demonstrating its application for managing QoS for multimedia and real-time mission critical applications in a multi-domain ad hoc network. The policy-based approach is a promising one for the management of MANETs, but it requires the flexibility to adapt to a constantly changing environment. Through experimental studies and simulation, we were able to determine that using our proposed solution suite and through the addition of a set of extensions to the COPS protocol, we can achieve our objective of a self-organizing, robust, and efficient PBNM system for managing MANETs. / Ph. D.

Meta-synthesis is an approach to synthesize qualitative research results. Originally proposed in the medical field and in education, this approach helps to advance current knowledge by generating a new interpretive synthesis. Since current research practices and knowledge development in emergency management is excessively divergent, there has been a need for a synthesis of knowledge from practice and research. One of the main arguments of this study is that the need is met by this study of a meta-synthesis. In this research, I suggested that many research results dealing with the issue of how to improve the performance of emergency management can be integrated into strategies for network management in emergencies. I used the term strategies in a much more generalized way to capture the idea of managerial/behavioral skills, plans, and insights for emergency management. The meta-synthesis was conducted from a keyword search, surveys, and expert interviews, which identified representative studies in emergency response. The review process of the representative studies is captured in a two-by-two matrix (intervention point axis and planning-improvisation axis) as a way of presenting the meta-synthesis results. This study then, turned to an analysis of reports of the Hurricane Katrina response using the meta-synthesis results. Qualitative content analysis was used as a method for the analysis. Reports from the White House, the House of Representatives, and the Senate are the target documents of the analysis. While conducting the analysis, I argued that the attempt of interpreting the failures of Katrina response into the failures of network management strategies provides clearer understandings regarding what went wrong and what was lacking. Furthermore, I argued that the way of thinking attempted in the analysis is a constructive one in that it provides an instructive action agenda for future disasters by connecting lessons learned to the strategies for emergency management. / Ph. D.

Networks are an increasingly common aspect of administrative life in almost any policy arena. In 1999 the health care industry created the National Quality Forum, a network administrative organization, whose founding mission was to improve American healthcare through endorsement of consensus-based national standards for measurement and public reporting of healthcare performance data that provide meaningful information about whether care is safe, timely, beneficial, patient-centered, equitable and efficient. The NQF is representative of a network administrative organization because it was created to address issues of health care quality in a new way by bringing together organizations from the public and private sectors and providing them with a forum to discuss and debate measures of quality, and ultimately, to effect change. The NQF thus represents a major administrative experiment in addressing health policy issues. In spite of the popularity of networks, little is known about a network manager's or, more appropriately for this dissertation, a network entrepreneur's critical tasks in creating a network administrative organization. The purpose of this dissertation is to present the results of an empirical study of the critical leadership tasks of the NQF's President and CEO during the NQF's formative stages. This dissertation identifies and conceptualizes three critical leadership tasks of the NQF's President and CEO: defining the NQF's mission, building and maintaining the NQF's social base, and creating the NQF's Consensus Development Process. In addition, this dissertation proposes a series of testable hypothesis based on these three critical tasks that can be used for exploring leadership in other NAOs. The findings indicate that leadership is crucial to the formation of a network administrative organization and fills a gap in our understanding of network management by developing the concept of network leadership and exploring the critical tasks a leader undertakes during the formative stages of building an NAO like the NQF. / Ph. D.

While government contracting out its work continues to proliferate and studies about this phenomenon have increased during the past two decades, still little is known about how effective government sponsored networks are at managing broad and complex networks of primarily non-governmental entities. This dissertation reports the results of one such investigation, which examined a U.S. federal agency's contracting experiences in evidence-based health care. The Agency for Healthcare Research and Quality (AHRQ) is a unit of the U.S. Department of Health and Human Services (HHS). Among other tasks, AHRQ supports the development and dissemination of evidence about current best practices in health services delivery through its Evidence-based Practice Center (EPC) programs that contract out its work and operate in broad and complex network. The purpose of this study was to examine the extent to which AHRQ's EPC Program I was effective in supporting the translation of evidence reports and disseminating the products to the public by contracting with public and non-profit entities to do the work. This dissertation also sought to examine the extent to which the evidence reports and derivative products were publicly accessible by operationalizing the objectives articulated in AHRQ's authorizing legislation in a manner consistent with theories of representative democracy and exploring Program I's effectiveness using William T. Gormley's ideas (1989; Gormley & Balla 2003) of bureaucratic control. The results from this dissertation suggest that a decentralized network was related to overall higher translation and dissemination network effectiveness. Specifically, the findings from this study suggest that a decentralized network was related to overall higher translation and dissemination network effectiveness. Also, weak ties among the network actors when transferring complex knowledge was associated with higher translation and dissemination network effectiveness on the whole. The findings from this dissertation also contribute to network theory by extending Gormley's bureaucratic control typology (1989; Gormley & Balla 2003) to the network level, and also to the type of control that was available to the Agency over the network. Finally, the results contribute to better understanding of the dynamics that can be associated with the effectiveness of similar programs. / Ph. D.

As resident space object populations grow, and satellite propulsion capabilities improve, it will become increasingly challenging for space-reliant nations to maintain space situational awareness using current human-in-the-loop methods. This dissertation develops several real-time adaptive approaches to autonomous sensor network management for tracking multiple maneuvering and non-maneuvering satellites with a diversely populated Space Object Surveillance and Identification network. The proposed methods integrate suboptimal Partially Observed Markov Decision Processes (POMDPs) with covariance inflation or multiple model adaptive estimation techniques to task sensors and maintain viable orbit estimates for all targets. The POMDPs developed in this dissertation use information-based and system-based metrics to determine the rewards and costs associated with tasking a specific sensor to track a particular satellite. Like in real-world situations, the population of target satellites vastly outnumbers the available set of sensors. Robust and adaptable tasking algorithms are needed in this scenario to determine how and when sensors should be tasked. The strategies developed in this dissertation successfully track 207 non-maneuvering and maneuvering spacecraft using only 24 ground and space-based sensors. The results show that multiple model adaptive estimation coupled with a multi-metric, suboptimal POMDP can effectively and efficiently task a diverse network of sensors to track multiple maneuvering spacecraft, while simultaneously monitoring a large number of non-maneuvering objects. Overall, this dissertation demonstrates the potential for autonomous and adaptable sensor network command and control for real-world space situational awareness. / Ph. D. / As the number of spacecraft in orbit increase, and satellite propulsion capabilities improve, it will become increasingly difficult for space-reliant nations to keep track of every object orbiting earth using human-in-the-loop methods. Already, the population of target satellites vastly outnumbers the available set of sensors. At any given time, a given network of sensors cannot observe every satellite in orbit, and must manage the available sensors effectively to keep track of every object of interest. The ability to maintain actionable knowledge of every orbiting object of interest is known as space situational awareness. Conventional tracking processes have generally not changed for decades, and were designed when there were far fewer satellites in orbit with little or no ability to maneuver. These methods involve large numbers of operators and engineers who schedule a network of sensors under the assumption that the satellites will not unexpectedly change their orbits for long periods of time. In the near future, traditional space surveillance approaches will become insufficient at maintaining space situational awareness, particularly if more satellites conduct unanticipated maneuvers. This dissertation develops several real-time approaches for controlling a diverse network of ground and space-based sensors that remove the need for human intervention. These fully computer-based command and control processes adapt to dynamic situations and automatically task sensors to rapidly track multiple maneuvering and non-maneuvering satellites. The decision processes used to determine which sensors should be tasked to observe a particular spacecraft compare the amount of information that can be collected in a single observation and the workload a sensor must execute to collect the observation. The command and control strategies developed in this dissertation successfully track 207 non-maneuvering and maneuvering spacecraft using only 24 ground and space-based sensors. The results show that adaptive, fully autonomous sensor network control processes can effectively and efficiently task a diverse set of sensors to track multiple maneuvering spacecraft, while simultaneously monitoring a large number of non-maneuvering objects. Overall, this dissertation demonstrates the potential for adaptive, computer-based sensor network command and control for real-world space situational awareness. This research was supported by the Virginia Tech New Horizons Graduate Scholar Program, the Ted and Karyn Hume Center for National Security and Technology, the DARPA Hallmark program, and the U.S. Joint Warfare Analysis Center.

Rockfall from rock slopes adjacent to roadways is a major hazard and poses a problem for transportation agencies across the country. The state of Tennessee has implemented the Tennessee Rockfall Management System (RMS) as a means of reducing the liabilities associated with rockfall hazard. It utilizes digital data acquisition via PDAs coupled with distribution via an expandable web-based GIS database. The Tennessee Rockfall Hazard Rating System (RHRS) is part of the Tennessee RMS and assigns a numeric hazard rating according relative hazard for all slopes identified as having a high potential for delivering rock blocks onto Tennessee Department of Transportation maintained roadways. The Tennessee RHRS uses standard rock slope failure mechanisms (planar failure, wedge failure, topple failure, differential weathering, and raveling) along with the site and roadway geometry to assess the rockfall hazard of an individual slope. This study suggests methods that will expedite fieldwork, including an informational guide on how to properly identify individual failure mechanisms in the field. Also, the study examines the current method of scoring abundance and suggests an alternative, multiplicative approach. The alternative of using a multiplicative abundance is considered and its results summarized. / Master of Science

Policy based network management is a promising approach for provisioning and management of quality of service in mobile ad hoc networks. In this thesis, we focus on performance evaluation of this approach in context of the amount of service received by certain nodes called policy execution points (PEPs) or policy clients from certain specialized nodes called the policy decision points (PDPs) or policy servers. We develop analytical models for the study of the system behavior under two scenarios; a simple Markovian scenario where we assume that the random variables associated with system processes follow an exponential distribution and a more complex non-Markovian scenario where we model the system processes according to general distribution functions as observed through simulation. We illustrate that the simplified Markovian model provides a reasonable indication of the trend of the service availability seen by policy clients and highlight the need for an exact analysis of the system without relying on Poisson assumptions for system processes. In the case of the more exact non-Markovian analysis, we show that our model gives a close approximation to the values obtained via empirical methods. Stochastic Petri Nets are used as performance evaluation tools in development and analysis of these system models. / Master of Science

Yes / This paper proposes a novel method for planning active distribution networks (ADNs) with the integration of an active network management (ANM) scheme using coordinated voltage control (CVC) through on-load tap changer (OLTC) transformers. The method was formulated as a security-constrained optimal power flow (SCOPF) problem to minimize total operational costs, which maximizes the utilization of renewable distributed generators (DGs) over a planning horizon. The ANM scheme was applied using OLTC to ensure safe operation and reduce voltage violations in the network. To analyse the impact of ANM, the planning problem was examined both with and without the ANM scheme. Moreover, SCOPF, considering the N-1 line contingency analysis and multi-DG configuration, was implemented to analyse the feasibility of the proposed method and the advantages of ANM under contingency situations. The method was validated on a weakly-meshed 16-bus UK generic distribution system (UKGDS). The results showed that ANM can lower operational costs and maintain network voltage for operation in feasible conditions even in the case of a contingency. Moreover, the ANM scheme mitigated the voltage rise effect caused by DGs and maximized their utilization.

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Approved for public release, distribution is unlimited / The performance of network management tools for SONET/SDH networks subject to the load conditions is studied and discussed in this thesis. Specifically, a SONET network which consists of four CISCO ONS 15454s, managed by a CISCO Transport Manager, is set up in the Advanced Network Laboratory of the Naval Postgraduate School. To simulate a realistic data transfer environment for the analysis, Smartbits Avalanche software is deployed to simulate multiple client-server scenarios in the SONET network. Traffic from the management channel is then captured using a packet sniffer. Queuing analysis on the captured data is performed with particular emphasis on properties of self-similarity. In particular, the Hurst parameter which determines the captured traffic's degree of self-similarity is estimated using the Variance-Index plot technique. Link utilization is also derived from the computation of first-order statistics of the captured traffic distribution. The study shows that less management data was exchanged when the SONET network was fully loaded. In addition, it is recommended that CTM 4.6 be used to manage not more than 1552 NEs for safe operation. The results presented in this thesis will aid network planners to optimize the management of their SONET/SDH networks. / Civilian, Ministry of Defense, Singapore