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Due to projectedincrea ses in air traffic, there are several research efforts underway to evaluate ways to safely increase the capacity of the National Airspace System (NAS), improve operational efficiency, andre duce aircraft noise. At NASA Langley Research Center (LaRC) in Hampton, Virginia, two parallel research efforts have focusedon terminal area research: one is Airborne Precision Spacing (APS), and the other is the Quiet Aircraft Technologies (QAT) project. The APS objective is to increase terminal-area capacity without adversely affecting safety, whereas the QAT project objective is to develop noise- and fuel-efficient approach trajectories. The APS project developed a cockpit tool, called Airborne Merging and Spacing for Terminal Arrivals (AMSTAR), that issues speedco mmands to aircraft to maintain desired spacing between aircraft pairs. The APS studies showed an ability to increase runway capacity; however, capacity increases may negatively impact noise andemissio n levels in airport areas. The QAT project created efficient Continuous Descent Approaches (CDAs), which showedred uctions in aircraft ground noise and fuel consumption. Previous research has shown that CDA trajectories have adverse effects on runway capacity because aircraft must be spacedf urther apart at long distances from the runway to prevent separation losses at the runway threshold. To date, the APS and CDA concepts have been evaluated independently at LaRC.In this study, three different approaches to combining APS and CDA operations were evaluatedto determine the feasibility and benefits of combining these concepts. These methods combined AMSTAR with 3◦-flight-path-angle-CDA approach routes, 3◦-CDA routes with spoilers, and2 ◦-CDA routes without spoilers. Adding the use of spoilers allowedf aster responses to large speedr eductions issued by AMSTAR. This improvement was contrastedwith the effects of a shallower flight-path angle for greater deceleration capabilities. This research indicated that AMSTAR improved the performance of CDA operations, although full capacity improvements were not achieved. Whereas the 2◦-CDA routes were expectedto show the best results, the 3◦-CDA case with spoilers showed the least variability in thresholdspacing errors. All of the CDA routes were more noise, fuel, and time efficient than traditional step-descent routes that are commonly usedto day.

The Internet is dynamically shared by numerous flows of data traffic. Network congestion occurs when the aggregate flow rate persistently exceeds the network capacity, leading to excessive delivery delay and loss of user data. To control network congestion, a flow needs to adapt the sending rate to its inferred level of congestion, and a packet switch needs to report its local level of congestion. In this framework of Internet congestion control, it is important for flows to react promptly against congestion, and robustly against interfering network events resembling congestion. This is challenging due to the highly dynamic interactions of various network components over a global scale. Prior approaches rely predominantly on empirical observations in experiments for constructing and validating designs. However, without a careful, systematic examination of all viable options, more efficient designs may be overlooked. Moreover, experimental results have limited applicability to scenarios beyond the specific experimental settings. In this thesis, I employ a novel, systematic design approach. I formalize the design process of Internet congestion control from a minimal set of empirical observations. I prove the robustness and optimality of the attained design in general settings, and validate these properties in practical experimental settings. First, I develop a systematic method for enhancing the robustness of flows against interfering events resembling congestion. The class of additive-increase-multiplicative-decrease (AIMD) algorithms in Transmission Control Protocol (TCP) is the set of dominant algorithms governing the flow rate adaptation process. Over the present Internet, packet reordering and non-congestive loss occur frequently and are misinterpreted by TCP AIMD as packet loss due to congestion. This leads to underutilization of network resources. With a complete, formal characterization of the design space of TCP AIMD, I formulate designing wireless TCP AIMD as an optimal control problem over this space. The derived optimal algorithm attains a significant performance improvement over existing enhancements in packet-level simulation. Second, I propose a novel design principle, known as pricing-link-by-time (PLT), that specifies how to set the measure of congestion, or “link price”, at a router to provide prompt feedback to flows. Existing feedback mechanisms require sophisticated parameter tuning, and experience drastic performance degradation with improperly tuned parameters. PLT makes parameter tuning a simple, optional process. It increases the link price as the backlog stays above a threshold value, and resets the price once the backlog goes below the threshold. I prove that such a system exhibits cyclic behavior that is robust against changes in network environment and protocol parameters. Moreover, changing the threshold value can control delay without undermining system performance. I validate these analytical results using packet-level simulation. The incremental deployment of various enhancements have made Internet congestion control highly heterogeneous. The final part of the thesis studies this issue by analyzing the competition among flows with heterogeneous robustness against interfering network events. While rigorous theories have been a major vehicle for understanding system designs, the thesis involves them directly in the design process. This systematic design approach can fully exploit the structural characteristics, and lead to generally applicable, effective solutions. / published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

The current Space Traffic Management (STM) community was not prepared for the exponential increase in the resident space object (RSO) population that has taken place over the last several years. The combination of poor communication infrastructure and long scheduling lead times of the Space Surveillance Network (SSN) prevent any type of reactive sensor tasking, which is required in event of anomaly detection. This dissertation was designed to survey extensions to the classical notions of covariance based sensor tasking strategies and develop a methodology for evaluating these techniques. A suboptimal partially observable Markov decision process (POMDP) was used as the simulation framework to test various reward functions and decision algorithms while enabling autonomous, reactive sensor tasking. The goal of this work was used the developed evaluation methodology to perform statistical analyses to determine which metrics were most reliable and efficient for Space Traffic Management (STM) of the geosynchronous Earth orbit (GEO) resident space object (RSO) catalog. Hypotheses were tested against simulations of 873 resident space object (RSO) in geosynchronous Earth orbit (GEO) being tracked by 18 heterogeneous, geographically disperse ground-based electro-optical (EO) sensors. This dissertation evaluates the ability of various sensor tasking metrics to produce rewards that maximize geosynchronous Earth orbit (GEO) catalog coverage capability of a sensor network under realistic communication restrictions. / Doctor of Philosophy / Space is getting crowded at an increasing rate. Communication issues and rigid scheduling of the Space Surveillance Network (SSN) prevent reactive sensor tasking, which is needed to alleviate this issue. This dissertation was designed to survey different sensor tasking strategies and develop a methodology for evaluating these techniques. A discrete time estimator called a suboptimal partially observable Markov decision process (POMDP) was used as the simulation framework to test various reward functions and decision algorithms while enabling autonomous, reactive sensor tasking. The goal of this work was used the developed evaluation methodology to perform statistical analyses to determine which metrics were most reliable and efficient for Space Traffic Management (STM) of the geosynchronous Earth orbit (GEO) resident space object (RSO) catalog. Multiple simulation scenarios were evaluated, with the first focused on determining the proper metrics in the ideal sensor network distribution case. From there, hypotheses were tested against simulations of a geographically disperse network of ground-based electro-optical (EO) sensors. This dissertation evaluates the ability of various sensor tasking metrics to produce rewards that maximize geosynchronous Earth orbit (GEO) catalog coverage capability of a sensor network under realistic communication restrictions

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