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Optimal design of mixed-media packet-switching networks - Routing and capacity assignment

This paper considers a mixed-media packet-switched computer communication network which consists of a low-delay terrestrial store-and-forward subnet combined with a low-cost high-bandwidth satellite subnet. We show how to route traffic via ground and/or satellite links by means of static, deterministic procedures and assign capacities to channels subject to a given linear cost such that the network average delay is minimized. Two operational schemes for this network model are investigated: one is a scheme in which the satellite channel is used as a slotted ALOHA channel; the other is a new multiaccess scheme we propose in which whenever a channel collision occurs, retransmission of the involved packets will route through ground links to their destinations. The performance of both schemes is evaluated and compared in terms of cost and average packet delay tradeoffs for some examples. The results offer guidelines for the design and optimal utilization of mixed-media networks.

Huynh, D.

SatNet: A Benchmark for Satellite Scheduling Optimization

Satellites provide essential services such as networking and weather tracking, and the number of near-earth and deep space satellites are expected to grow rapidly in the coming years. Communications with terrestrial ground stations is one of the critical functionalities of any space mission. Satellite scheduling is a problem that has been scientifically investigated since the 1970s. A central aspect of this problem is the need to consider resource contention and satellite visibility constraints as they require line of sight. Due to the combinatorial nature of the problem, prior solutions such as linear programs and evolutionary algorithms require extensive compute capabilities to output a feasible schedule for each scenario. Machine learning based scheduling can provide an alternative solution by training a model with historical data and generating a schedule quickly with model inference. We present SatNet, a benchmark for satellite scheduling optimization based on historical data from the NASA Deep Space Network. We propose formulation of the satellite scheduling problem as a Markov Decision Process and use reinforcement learning (RL) policies to generate schedules. The nature of constraints imposed by SatNet differ from other combinatorial optimization problems such as vehicle routing studied in prior literature. Our initial results indicate that RL is an alternative optimization approach that can generate candidate solutions of comparable quality to existing state-of-the-practice results. However, we also find that RL policies overfit to the training dataset and do not generalize well to new data, thereby necessitating continued research on reusable and generalizable agents.

Wilson, Brian

Objective Assessment Method for RNAV STAR Adherence

Flight crews and air traffic controllers have reported many safety concerns regarding area navigation standard terminal arrival routes (RNAV STARs). Specifically, optimized profile descents (OPDs). However, our information sources to quantify these issues are limited to subjective reporting and time consuming case-by-case investigations. This work is a preliminary study into the objective performance of instrument procedures and provides a framework to track procedural concepts and assess design specifications. We created a tool and analysis methods for gauging aircraft adherence as it relates to RNAV STARs. This information is vital for comprehensive understanding of how our air traffic behaves. In this study, we mined the performance of 24 major US airports over the preceding three years. Overlaying 4D radar track data onto RNAV STAR routes provided a comparison between aircraft flight paths and the waypoint positions and altitude restrictions. NASA Ames Supercomputing resources were utilized to perform the data mining and processing. We assessed STARs by lateral transition path (full-lateral), vertical restrictions (full-lateral/full-vertical), and skipped waypoints (skips). In addition, we graphed frequencies of aircraft altitudes relative to the altitude restrictions. Full-lateral adherence was always greater than Full-lateral/ full- vertical, as it is a subset, but the difference between the rates was not consistent. Full-lateral/full-vertical adherence medians of the 2016 procedures ranged from 0% in KDEN (Denver) to 21% in KMEM (Memphis). Waypoint skips ranged from 0% to nearly 100% for specific waypoints. Altitudes restrictions were sometimes missed by systematic amounts in 1,000 ft. increments from the restriction, creating multi-modal distributions. Other times, altitude misses looked to be more normally distributed around the restriction. This tool may aid in providing acceptability metrics as well as risk assessment information.

Stewart, Michael

AIRNOISE: A Tool for Preliminary Noise-Abatement Terminal Approach Route Design

Noise from aircraft in the airport vicinity is one of the leading aviation-induced environmental issues. The FAA developed the Integrated Noise Model (INM) and its replacement Aviation Environmental Design Tool (AEDT) software to assess noise impact resulting from all aviation activities. However, a software tool is needed that is simple to use for terminal route modification, quick and reasonably accurate for preliminary noise impact evaluation and flexible to be used for iterative design of optimal noise-abatement terminal routes. In this paper, we extend our previous work on developing a noise-abatement terminal approach route design tool, named AIRNOISE, to satisfy this criterion. First, software efficiency has been significantly increased by over tenfold using the C programming language instead of MATLAB. Moreover, a state-of-the-art high performance GPU-accelerated computing module is implemented that was tested to be hundreds time faster than the C implementation. Secondly, a Graphical User Interface (GUI) was developed allowing users to import current terminal approach routes and modify the routes interactively to design new terminal approach routes. The corresponding noise impacts are then calculated and displayed in the GUI in seconds. Finally, AIRNOISE was applied to Baltimore-Washington International Airport terminal approach route to demonstrate its usage.

aircraft noise

Analysis of the Capacity Potential of Current Day and Novel Configurations for New York's John F. Kennedy Airport

In 2015, a series of systems analysis studies were conducted on John F. Kennedy Airport in New York (NY) in a collaborative effort between NASA and the Port Authority of New York and New Jersey (PANYNJ). This work was performed to build a deeper understanding of NY airspace and operations to determine the improvements possible through operational changes with tools currently available, and where new technology is required for additional improvement. The analysis was conducted using tool-based mathematical analyses, video inspection and evaluation using recorded arrival/departure/surface traffic captured by the Aerobahn tool (used by Kennedy Airport for surface metering), and aural data archives available publically through the web to inform the video segments. A discussion of impacts of trajectory and operational choices on capacity is presented, including runway configuration and usage (parallel, converging, crossing, shared, independent, staggered), arrival and departure route characteristics (fix sharing, merges, splits), and how compression of traffic is staged. The authorization in March of 2015 for New York to use reduced spacing under the Federal Aviation Administration (FAA) Wake Turbulence Recategorization (RECAT) also offers significant capacity benefit for New York airports when fully transitioned to the new spacing requirements, and the impact of these changes for New York is discussed. Arrival and departure capacity results are presented for each of the current day Kennedy Airport configurations. While the tools allow many variations of user-selected conditions, the analysis for these studies used arrival-priority, no-winds, additional safety buffer of 5% to the required minimum spacing, and a mix of traffic typical for Kennedy. Two additional "novel" configurations were evaluated. These configurations are of interest to Port Authority and to their airline customers, and are believed to offer near-term capacity benefit with minimal operational and equipage changes. One of these is the addition of an Optimized Profile Descent (OPD) route to runways 22L and 22R, and the other is the simultaneous use of 4 runways, which is not currently done at Kennedy. The background and configuration for each of these is described, and the capacity results are presented along with a discussion of drawbacks and enablers for each.

Glaab, Patricia

NextGen Far-Term Concept Exploration for Integrated Gate-to-Gate Trajectory-Based Operations

NASA is currently conducting concept exploration studies toward the definition of a far-term, gate-to-gate concept for Trajectory-Based Operations. This paper presents a basic architectural framework for the far-term concept and discusses some observations about implementation of trajectory-based operations in the National Airspace System. Within the concept, operators and service providers collaboratively negotiate aircraft trajectories, providing agile, optimized, aircraft-specific routing to meet service provider gate-to-gate flow-management constraints and increasing capacity by smoothly and effectively combining flight-deck-based and ground-based metering, merging, and spacing in a mixed-equipage environment. The far-term TBO concept is intended to influence the direction of mid-term TBO research and to inform the definition of stable requirements and standards for TBO communications infrastructure and user equipage.

Johnson, Sally C.

Masked Proportional Routing

Masked proportional routing is an improved procedure for choosing links between adjacent nodes of a network for the purpose of transporting an entity from a source node ("A") to a destination node ("B"). The entity could be, for example, a physical object to be shipped, in which case the nodes would represent waypoints and the links would represent roads or other paths between waypoints. For another example, the entity could be a message or packet of data to be transmitted from A to B, in which case the nodes could be computer-controlled switching stations and the links could be communication channels between the stations. In yet another example, an entity could represent a workpiece while links and nodes could represent, respectively, manufacturing processes and stages in the progress of the workpiece towards a finished product. More generally, the nodes could represent states of an entity and the links could represent allowed transitions of the entity. The purpose of masked proportional routing and of related prior routing procedures is to schedule transitions of entities from their initial states ("A") to their final states ("B") in such a manner as to minimize a cost or to attain some other measure of optimality or efficiency. Masked proportional routing follows a distributed (in the sense of decentralized) approach to probabilistically or deterministically choosing the links. It was developed to satisfy a need for a routing procedure that 1. Does not always choose the same link(s), even for two instances characterized by identical estimated values of associated cost functions; 2. Enables a graceful transition from one set of links to another set of links as the circumstances of operation of the network change over time; 3. Is preferably amenable to separate optimization of different portions of the network; 4. Is preferably usable in a network in which some of the routing decisions are made by one or more other procedure(s); 5. Preferably does not cause an entity to visit the same node twice; and 6. Preferably can be modified so that separate entities moving from A to B do not arrive out of order.

Wolpert, David

Optimal Integration of Departure and Arrivals in Terminal Airspace

Coordination of operations with spatially and temporally shared resources such as route segments, fixes, and runways improves the efficiency of terminal airspace management. Problems in this category include scheduling and routing, thus they are normally difficult to solve compared with pure scheduling problems. In order to reduce the computational time, a fast time algorithm formulation using a non-dominated sorting genetic algorithm (NSGA) was introduced in this work and applied to a test case based on existing literature. The experiment showed that new method can solve the whole problem in fast time instead of solving sub-problems sequentially with a window technique. The results showed a 60% or 406 second delay reduction was achieved by sharing departure fixes (more details on the comparison with MILP results will be presented in the final paper). Furthermore, the NSGA algorithm was applied to a problem in LAX terminal airspace, where interactions between 28% of LAX arrivals and 10% of LAX departures are resolved by spatial segregation, which may introduce unnecessary delays. In this work, spatial segregation, temporal segregation, and hybrid segregation were formulated using the new algorithm. Results showed that spatial and temporal segregation approaches achieved similar delay. Hybrid segregation introduced much less delay than the other two approaches. For a total of 9 interacting departures and arrivals, delay reduction varied from 4 minutes to 6.4 minutes corresponding flight time uncertainty from 0 to 60 seconds. Considering the amount of flights that could be affected, total annual savings with hybrid segregation would be significant.

high density terminal

Avoiding Braess' Paradox Through Collective Intelligence

In an Ideal Shortest Path Algorithm (ISPA), at each moment each router in a network sends all of its traffic down the path that will incur the lowest cost to that traffic. In the limit of an infinitesimally small amount of traffic for a particular router, its routing that traffic via an ISPA is optimal, as far as cost incurred by that traffic is concerned. We demonstrate though that in many cases, due to the side-effects of one router's actions on another routers performance, having routers use ISPA's is suboptimal as far as global aggregate cost is concerned, even when only used to route infinitesimally small amounts of traffic. As a particular example of this we present an instance of Braess' paradox for ISPA'S, in which adding new links to a network decreases overall throughput. We also demonstrate that load-balancing, in which the routing decisions are made to optimize the global cost incurred by all traffic currently being routed, is suboptimal as far as global cost averaged across time is concerned. This is also due to "side-effects", in this case of current routing decision on future traffic. The theory of COllective INtelligence (COIN) is concerned precisely with the issue of avoiding such deleterious side-effects. We present key concepts from that theory and use them to derive an idealized algorithm whose performance is better than that of the ISPA, even in the infinitesimal limit. We present experiments verifying this, and also showing that a machine-learning-based version of this COIN algorithm in which costs are only imprecisely estimated (a version potentially applicable in the real world) also outperforms the ISPA, despite having access to less information than does the ISPA. In particular, this COIN algorithm avoids Braess' paradox.

Wolpert , David H.

Contact Graph Routing

Contact Graph Routing (CGR) is a dynamic routing system that computes routes through a time-varying topology of scheduled communication contacts in a network based on the DTN (Delay-Tolerant Networking) architecture. It is designed to enable dynamic selection of data transmission routes in a space network based on DTN. This dynamic responsiveness in route computation should be significantly more effective and less expensive than static routing, increasing total data return while at the same time reducing mission operations cost and risk. The basic strategy of CGR is to take advantage of the fact that, since flight mission communication operations are planned in detail, the communication routes between any pair of bundle agents in a population of nodes that have all been informed of one another's plans can be inferred from those plans rather than discovered via dialogue (which is impractical over long one-way-light-time space links). Messages that convey this planning information are used to construct contact graphs (time-varying models of network connectivity) from which CGR automatically computes efficient routes for bundles. Automatic route selection increases the flexibility and resilience of the space network, simplifying cross-support and reducing mission management costs. Note that there are no routing tables in Contact Graph Routing. The best route for a bundle destined for a given node may routinely be different from the best route for a different bundle destined for the same node, depending on bundle priority, bundle expiration time, and changes in the current lengths of transmission queues for neighboring nodes; routes must be computed individually for each bundle, from the Bundle Protocol agent's current network connectivity model for the bundle s destination node (the contact graph). Clearly this places a premium on optimizing the implementation of the route computation algorithm. The scalability of CGR to very large networks remains a research topic. The information carried by CGR contact plan messages is useful not only for dynamic route computation, but also for the implementation of rate control, congestion forecasting, transmission episode initiation and termination, timeout interval computation, and retransmission timer suspension and resumption.

Burleigh, Scott C.

Noise Impact Analysis for Urban Air Mobility in Dallas-Fort Worth Metroplex

This study supports re-design of airspace and procedures for management of Urban Air Mobility (UAM) fleet operations in a given metropolitan area. A goal of UAM is to maintain geographic separation of UAM flight tracks from densely populated areas in order to reduce the potential negative community impact of UAM and manage flight trajectory in anticipation of allowable noise levels and current land use. A UAM route inventory and a demographic-data-optimized topographic map are developed for the Dallas-Fort Worth metroplex to identify routes or baseline route segments for reduction of noise impact. Noise contours are computed for baseline route and alternative route design given the desired UAM demand level. The impact of UAM fleet noise is predicted based on predicted number of people and noise-sensitive facilities located inside the noise contours.

Urban Air Mobility

Noise Impact Analysis for Urban Air Mobility in Dallas-Fort Worth Metroplex

This study supports re-design of airspace and procedures for management of Urban Air Mobility (UAM) fleet operations in a given metropolitan area. A goal of UAM is to maintain geographic separation of UAM flight tracks from densely populated areas in order to reduce the potential negative community impact of UAM and manage flight trajectory in anticipation of allowable noise levels and current land use. A UAM route inventory and a demographic-data-optimized topographic map are developed for the Dallas-Fort Worth metroplex to identify routes or baseline route segments for reduction of noise impact. Noise contours are computed for baseline route and alternative route design given the desired UAM demand level. The impact of UAM fleet noise is predicted based on predicted number of people and noise-sensitive facilities located inside the noise contours.

Urban Air Mobility

Application of Aviation Turbulence Information to Air-Traffic Management (ATM): Chapter - 24

Unexpected turbulence especially in the upper troposphere and lower stratosphere where cabin crews and passengers in cruising aircraft are likely to unbuckle causes in-flight injuries, structural damage, and flight delay. Therefore, turbulence information can be used to improve safety while pursuing efficiency in Air-Traffic Management (ATM). In this chapter, simple modeling of aircraft trajectories combined with wind and turbulence predictions can suggest the optimal solution of flight plans that minimizes both total flight time (e.g., fuel consumption) and potential encounters of turbulence from departure to arrival airports. Also, probabilistic ensemble turbulence forecasts are applied to suggest an optimal strategic and tactical ATM route planning in a given weather and turbulence condition in the United States which are evaluated against in situ Eddy Dissipation Rate observations from commercial aircraft. Finally, variations of long-haul trans-Oceanic flight routes and their turbulence potentials are investigated using a global reanalysis data to understand how the upper-level large-scale flow patterns can affect the long-term ATM planning through the changes of winds and turbulence conditions.

Wind Optimal

Design of a cooperative problem-solving system for en-route flight planning: An empirical evaluation

Both optimization techniques and expert systems technologies are popular approaches for developing tools to assist in complex problem-solving tasks. Because of the underlying complexity of many such tasks, however, the models of the world implicitly or explicitly embedded in such tools are often incomplete and the problem-solving methods fallible. The result can be 'brittleness' in situations that were not anticipated by the system designers. To deal with this weakness, it has been suggested that 'cooperative' rather than 'automated' problem-solving systems be designed. Such cooperative systems are proposed to explicitly enhance the collaboration of the person (or a group of people) and the computer system. This study evaluates the impact of alternative design concepts on the performance of 30 airline pilots interacting with such a cooperative system designed to support en-route flight planning. The results clearly demonstrate that different system design concepts can strongly influence the cognitive processes and resultant performances of users. Based on think-aloud protocols, cognitive models are proposed to account for how features of the computer system interacted with specific types of scenarios to influence exploration and decision making by the pilots. The results are then used to develop recommendations for guiding the design of cooperative systems.

Layton, Charles

Design of a cooperative problem-solving system for en-route flight planning: An empirical evaluation

Both optimization techniques and expert systems technologies are popular approaches for developing tools to assist in complex problem-solving tasks. Because of the underlying complexity of many such tasks, however, the models of the world implicitly or explicitly embedded in such tools are often incomplete and the problem-solving methods fallible. The result can be 'brittleness' in situations that were not anticipated by the system designers. To deal with this weakness, it has been suggested that 'cooperative' rather than 'automated' problem-solving systems be designed. Such cooperative systems are proposed to explicitly enhance the collaboration of the person (or a group of people) and the computer system. This study evaluates the impact of alternative design concepts on the performance of 30 airline pilots interacting with such a cooperative system designed to support enroute flight planning. The results clearly demonstrate that different system design concepts can strongly influence the cognitive processes and resultant performances of users. Based on think-aloud protocols, cognitive models are proposed to account for how features of the computer system interacted with specific types of scenarios to influence exploration and decision making by the pilots. The results are then used to develop recommendations for guiding the design of cooperative systems.

Layton, Charles

Integration of Weather Data into Airspace and Traffic Operations Simulation (ATOS) for Trajectory- Based Operations Research

Explicit integration of aviation weather forecasts with the National Airspace System (NAS) structure is needed to improve the development and execution of operationally effective weather impact mitigation plans and has become increasingly important due to NAS congestion and associated increases in delay. This article considers several contemporary weather-air traffic management (ATM) integration applications: the use of probabilistic forecasts of visibility at San Francisco, the Route Availability Planning Tool to facilitate departures from the New York airports during thunderstorms, the estimation of en route capacity in convective weather, and the application of mixed-integer optimization techniques to air traffic management when the en route and terminal capacities are varying with time because of convective weather impacts. Our operational experience at San Francisco and New York coupled with very promising initial results of traffic flow optimizations suggests that weather-ATM integrated systems warrant significant research and development investment. However, they will need to be refined through rapid prototyping at facilities with supportive operational users We have discussed key elements of an emerging aviation weather research area: the explicit integration of aviation weather forecasts with NAS structure to improve the effectiveness and timeliness of weather impact mitigation plans. Our insights are based on operational experiences with Lincoln Laboratory-developed integrated weather sensing and processing systems, and derivative early prototypes of explicit ATM decision support tools such as the RAPT in New York City. The technical components of this effort involve improving meteorological forecast skill, tailoring the forecast outputs to the problem of estimating airspace impacts, developing models to quantify airspace impacts, and prototyping automated tools that assist in the development of objective broad-area ATM strategies, given probabilistic weather forecasts. Lincoln Laboratory studies and prototype demonstrations in this area are helping to define the weather-assimilated decision-making system that is envisioned as a key capability for the multi-agency Next Generation Air Transportation System [1]. The Laboratory's work in this area has involved continuing, operations-based evolution of both weather forecasts and models for weather impacts on the NAS. Our experience has been that the development of usable ATM technologies that address weather impacts must proceed via rapid prototyping at facilities whose users are highly motivated to participate in system evolution.

Peters, Mark

An Application of the Phosphorus Consistent Rule for Environmentally Acceptable Cost-Efficient Management of Broiler Litter in Crop Production

We calculated the profitability of using broiler litter as a source of plant nutrients using the phosphorus consistent litter application rule. The cost saving by using litter is 37% over the use of chemical fertilizer-only option to meet the nutrient needs of major crops grown in Alabama. In the optimal solution, only a few routes of all the possible routes developed were used for inter- and intra- county litter hauling. If litter is not adopted as the sole source of crop nutrients, the best environmental policy may be to pair the phosphorus consistent rule with taxes, marketable permits, and subsidies.flaws

Paudel, Krishna P.

802.11s Wireless Mesh Network Visualization Application

Results of past experimentation at NASA Johnson Space Center showed that the IEEE 802.11s standard has better performance than the widely implemented alternative protocol B.A.T.M.A.N (Better Approach to Mobile Ad hoc Networking). 802.11s is now formally incorporated into the Wi- Fi 802.11-2012 standard, which specifies a hybrid wireless mesh networking protocol (HWMP). In order to quickly analyze changes to the routing algorithm and to support optimizing the mesh network behavior for our intended application a visualization tool was developed by modifying and integrating open source tools.

Mauldin, James Alexander