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At least 73 records · Page 4

Convective Weather Avoidance with Uncertain Weather Forecasts

Convective weather events have a disruptive impact on air traffic both in terminal area and in en-route airspaces. In order to make sure that the national air transportation system is safe and efficient, it is essential to respond to convective weather events effectively. Traffic flow control initiatives in response to convective weather include ground delay, airborne delay, miles-in-trail restrictions as well as tactical and strategic rerouting. The rerouting initiatives can potentially increase traffic density and complexity in regions neighboring the convective weather activity. There is a need to perform rerouting in an intelligent and efficient way such that the disruptive effects of rerouting are minimized. An important area of research is to study the interaction of in-flight rerouting with traffic congestion or complexity and developing methods that quantitatively measure this interaction. Furthermore, it is necessary to find rerouting solutions that account for uncertainties in weather forecasts. These are important steps toward managing complexity during rerouting operations, and the paper is motivated by these research questions. An automated system is developed for rerouting air traffic in order to avoid convective weather regions during the 20- minute - 2-hour time horizon. Such a system is envisioned to work in concert with separation assurance (0 - 20-minute time horizon), and longer term air traffic management (2-hours and beyond) to provide a more comprehensive solution to complexity and safety management. In this study, weather is dynamic and uncertain; it is represented as regions of airspace that pilots are likely to avoid. Algorithms are implemented in an air traffic simulation environment to support the research study. The algorithms used are deterministic but periodically revise reroutes to account for weather forecast updates. In contrast to previous studies, in this study convective weather is represented as regions of airspace that pilots are likely to avoid. The automated system periodically updates forecasts and reassesses rerouting decisions in order to account for changing weather predictions. The main objectives are to reroute flights to avoid convective weather regions and determine the resulting complexity due to rerouting. The eventual goal is to control and reduce complexity while rerouting flights during the 20 minute - 2 hour planning period. A three-hour simulation is conducted using 4800 flights in the national airspace. The study compares several metrics against a baseline scenario using the same traffic and weather but with rerouting disabled. The results show that rerouting can have a negative impact on congestion in some sectors, as expected. The rerouting system provides accurate measurements of the resulting complexity in the congested sectors. Furthermore, although rerouting is performed only in the 20-minute - 2-hour range, it results in a 30% reduction in encounters with nowcast weather polygons (100% being the ideal for perfectly predictable and accurate weather). In the simulations, rerouting was performed for the 20-minute - 2-hour flight time horizon, and for the en-route segment of air traffic. The implementation uses CWAM, a set of polygons that represent probabilities of pilot deviation around weather. The algorithms were implemented in a software-based air traffic simulation system. Initial results of the system's performance and effectiveness were encouraging. Simulation results showed that when flights were rerouted in the 20-minute - 2-hour flight time horizon of air traffic, there were fewer weather encounters in the first 20 minutes than for flights that were not rerouted. Some preliminary results were also obtained that showed that rerouting will also increase complexity. More simulations will be conducted in order to report conclusive results on the effects of rerouting on complexity. Thus, the use of the 20-minute - 2-hour flight time horizon weather avoidance teniques performed in the simulation is expected to provide benefits for short-term weather avoidance.

Karahan, Sinan↗

Evaluation of an Impedance Threshold Device as a VIIP Countermeasure

Visual Impairment /Intracranial Pressure (VIIP) is a top human spaceflight risk for which NASA does not currently have a proven mitigation strategy. Thigh cuffs (Braslets) and lower body negative pressure (LBNP; Chibis) devices have been or are currently being evaluated as a means to reduce VIIP signs and symptoms, but these methods alone may not provide sufficient relief of cephalic venous congestion and VIIP symptoms. Additionally, current LBNP devices are too large and cumbersome for their systematic use as a countermeasure. Therefore, a novel approach is needed that is easy to implement and provides specific relief of symptoms. This investigation will evaluate an impedance threshold device (ITD) as a VIIP countermeasure. The ITD works by providing up to 7 cm H2O (approximately 5 mmHg) resistance to inspiratory air flow, effectively turning the thorax into a vacuum pump upon each inhalation which lowers the intrathoracic pressure (ITP) and facilitates venous return to the heart. The ITD is FDA-approved and was developed to augment venous return to the central circulation and increase cardiac output during cardiopulmonary resuscitation (CPR) and in patients with hypotension. While the effect of ITD on CPR survival outcomes is controversial, the ITD's ability to lower ITP with a concomitant decrease in intracranial pressure (ICP) is well documented. A similar concept that creates negative ITP during exhalation (intrathoracic pressure regulator; ITPR) decreased ICP in 16 of 20 patients with elevated ICP in a hospital pilot study. ITP and central venous pressure (CVP) have been shown to decrease in microgravity however ITP drops more than CVP, indicating an increased transmural CVP. This could explain the paradoxical distention of jugular veins (JV) in microgravity despite lower absolute CVP and also suggests that JV transmural pressure is not dramatically elevated. Use of an ITD may lower JV pressure enough to remove or relieve cephalic venous congestion. During spaceflight experiments with Braslet thigh cuffs and modified (open-glottis) Mueller maneuvers, Braslets alone reduced cardiac preload but only reduced the internal JV (IJV) cross sectional area by 23%. The addition of Mueller maneuvers resulted in an IJV area reduction of 48%. This project will test if ITD essentially applies a Mueller maneuver with added negative ITP in every respiratory cycle, acting to: 1) reduce venous congestion in the neck and 2) potentially lower ICP. The expected mechanism of action is that in microgravity (or an analog) blood is relocated toward the heart from vasculature in the head and neck. Once validated, the ITD would be an exceptionally easy countermeasure to deploy and test on the ISS. Dosage could be altered though 1) duration of application and 2) inspiratory resistance set point. Effects could be additionally enhanced through co-application with other countermeasures such as thigh cuffs or LBNP.

Ebert, D.↗

Evaluation of an Impedance Threshold Device as a VIIP Countermeasure

Visual Impairment/Intracranial Pressure (VIIP) is a top human spaceflight risk for which NASA does not currently have a proven mitigation strategy. Thigh cuffs (Braslets) and lower body negative pressure (LBNP; Chibis) devices have been or are currently being evaluated as a means to reduce VIIP signs and symptoms, but these methods alone may not provide sufficient relief of cephalic venous congestion and VIIP symptoms. Additionally, current LBNP devices are too large and cumbersome for their systematic use as a countermeasure. Therefore, a novel approach is needed that is easy to implement and provides specific relief of symptoms. This investigation will evaluate an impedance threshold device (ITD) as a VIIP countermeasure. The ITD works by providing up to 7 cm H2O (approximately 5 mmHg) resistance to inspiratory air flow, effectively turning the thorax into a vacuum pump upon each inhalation which lowers the intrathoracic pressure (ITP) and facilitates venous return to the heart. The ITD is FDA-approved and was developed to augment venous return to the central circulation and increase cardiac output during cardiopulmonary resuscitation (CPR) and in patients with hypotension. While the effect of ITD on CPR survival outcomes is controversial, the ITD's ability to lower ITP with a concomitant decrease in intracranial pressure (ICP) is well documented. A similar concept that creates negative ITP during exhalation (intrathoracic pressure regulator; ITPR) decreased ICP in 16 of 20 patients with elevated ICP in a hospital pilot study. ITP and central venous pressure (CVP) have been shown to decrease in microgravity however ITP drops more than CVP, indicating an increased transmural CVP. This could explain the paradoxical distention of jugular veins (JV) in microgravity despite lower absolute CVP and also suggests that JV transmural pressure is not dramatically elevated. Use of an ITD may lower JV pressure enough to remove or relieve cephalic venous congestion. During spaceflight experiments with Braslet thigh cuffs and modified (open-glottis) Mueller maneuvers, Braslets alone reduced cardiac preload but only reduced the internal JV (IJV) cross sectional area by 23%. The addition of Mueller maneuvers resulted in an IJV area reduction of 48%. This project will test if ITD essentially applies a Mueller maneuver with added negative ITP in every respiratory cycle, acting to: 1) reduce venous congestion in the neck and 2) potentially lower ICP. The expected mechanism of action is that in microgravity (or an analog) blood is relocated toward the heart from vasculature in the head and neck. Once validated, the ITD would be an exceptionally easy countermeasure to deploy and test on the ISS. Dosage could be altered though 1) duration of application and 2) inspiratory resistance set point. Effects could be additionally enhanced through co-application with other countermeasures such as thigh cuffs or LBNP.

Ebert, Douglas↗

Cyber-Threat Assessment for the Air Traffic Management System: A Network Controls Approach

Air transportation networks are being disrupted with increasing frequency by failures in their cyber- (computing, communication, control) systems. Whether these cyber- failures arise due to deliberate attacks or incidental errors, they can have far-reaching impact on the performance of the air traffic control and management systems. For instance, a computer failure in the Washington DC Air Route Traffic Control Center (ZDC) on August 15, 2015, caused nearly complete closure of the Centers airspace for several hours. This closure had a propagative impact across the United States National Airspace System, causing changed congestion patterns and requiring placement of a suite of traffic management initiatives to address the capacity reduction and congestion. A snapshot of traffic on that day clearly shows the closure of the ZDC airspace and the resulting congestion at its boundary, which required augmented traffic management at multiple locations. Cyber- events also have important ramifications for private stakeholders, particularly the airlines. During the last few months, computer-system issues have caused several airlines fleets to be grounded for significant periods of time: these include United Airlines (twice), LOT Polish Airlines, and American Airlines. Delays and regional stoppages due to cyber- events are even more common, and may have myriad causes (e.g., failure of the Department of Homeland Security systems needed for security check of passengers, see [3]). The growing frequency of cyber- disruptions in the air transportation system reflects a much broader trend in the modern society: cyber- failures and threats are becoming increasingly pervasive, varied, and impactful. In consequence, an intense effort is underway to develop secure and resilient cyber- systems that can protect against, detect, and remove threats, see e.g. and its many citations. The outcomes of this wide effort on cyber- security are applicable to the air transportation infrastructure, and indeed security solutions are being implemented in the current system. While these security solutions are important, they only provide a piecemeal solution. Particular computers or communication channels are protected from particular attacks, without a holistic view of the air transportation infrastructure. On the other hand, the above-listed incidents highlight that a holistic approach is needed, for several reasons. First, the air transportation infrastructure is a large scale cyber-physical system with multiple stakeholders and diverse legacy assets. It is impractical to protect every cyber- asset from known and unknown disruptions, and instead a strategic view of security is needed. Second, disruptions to the cyber- system can incur complex propagative impacts across the air transportation network, including its physical and human assets. Also, these implications of cyber- events are exacerbated or modulated by other disruptions and operational specifics, e.g. severe weather, operator fatigue or error, etc. These characteristics motivate a holistic and strategic perspective on protecting the air transportation infrastructure from cyber- events. The analysis of cyber- threats to the air traffic system is also inextricably tied to the integration of new autonomy into the airspace. The replacement of human operators with cyber functions leaves the network open to new cyber threats, which must be modeled and managed. Paradoxically, the mitigation of cyber events in the airspace will also likely require additional autonomy, given the fast time scale and myriad pathways of cyber-attacks which must be managed. The assessment of new vulnerabilities upon integration of new autonomy is also a key motivation for a holistic perspective on cyber threats.

Complex Networks↗

Achieving Equilibrium for Dense, Integrated, Vehicle Navigation

Drone usage has proliferated in recent years with many applications that have market-changing potential. Applications that include parcel delivery, wildlife protection, precision farming, law enforcement, and industrial inspection, just to name a few. In this paper, the term drone is used to mean both Unmanned Aerial Vehicle and small Unmanned Aircraft System vehicles. Flight infrastructure can currently only support a few thousand aircraft flying over the United States National Airspace System (NAS) at any given time. A delay atone airport sends ripple effects through the system, causing more delays and missed connections. Once regulations and safety policies are put in place to allow for the widespread use of unmanned drones, the number of aircraft in the NAS is expected to skyrocket to millions, potentially congesting the airspace resulting in possible separation violations. In air traffic control, separation is the concept of keeping an “ownship” aircraft outside a minimum distance from “intruder” aircraft to reduce the risk of the aircraft colliding, as well as preventing accidents due to secondary factors, such as wake turbulence. Maintaining proper separation is a safety critical property for drones in the airspace. This paper addresses separation in time and in distance for high volume corridors (en-route) and lanes(on ground). The requirements and necessary conditions for maintaining proper separation and reaching maximum throughput for a given corridor/lane are addressed assuming unidirectional corridors/lanes where an aircraft arrives from one side and departs from the opposite side. Simulation results are presented that show the presented solution guarantees a set of drones to reach the equilibrium state by adjusting their speed based on their distance to the aircraft in front of them. The equilibrium state is defined as a state when a set of n aircraft moving at a relatively constant speed and uniform spacing from each other in a congested system. A congested system is defined as a state when the aircraft cannot move at their maximum allowed speed. Unlike existing centralized and pre-planned approaches, the proposed solution is fully distributed and enables autonomous aircraft to decide to adjust their speed and distance with respect to the preceding aircraft, dynamically. Simulation results are presented that assess the feasibility of the approach using a large number of drones and evaluate the scalability of the proposed solution.

Mahyar R. Malekpour↗

Quantum-Accelerated Distributed Algorithms for Approximate Steiner Trees and Directed Minimum Spanning Trees

We present two algorithms in the Quantum CONGEST-CLIQUE model of distributed computation that succeed with high probability; One for producing an approximately optimal Steiner Tree, and one for producing an exact Minimum Directed Spanning tree. These use O(n1/4) rounds of communication and O(n9/4) messages, leading to a quantum speedup in round and message complexity compared to any known algorithms in the classical CONGEST-CLIQUE model (vs O(n1/3) and O(n7/3)). At a high level, we achieve these results by combining classical algorithms with fast quantum subroutines. Further, these problems can not be sped up in the CONGEST (non-clique) setting, and we characterize the constants involved.

Phillip Kerger↗

A Strategic Approach for Dense, Integrated, Vehicle Navigation

Drone usage has been on the rise in recent years with applications that include parcel delivery, wildlife protection, precision farming, law enforcement, and industrial inspection, just to name a few. Once regulations and safety policies are put in place to allow for the widespread use of unmanned drones, the number of aircraft in the National Airspace System (NAS) is expected to skyrocket to millions, potentially congesting the airspace which increases the likelihood of separation violations and possibly incidents. Currently, flight infrastructure can only support a few thousand aircraft flying over the United States National Airspace System (NAS) at any given time. A delay at one airport can send ripple effects throughout the system, causing more delays and missed connections. In air traffic control, separation is the concept of keeping an “ownship” aircraft outside a minimum distance from “intruder” aircraft to reduce the risk of the aircraft colliding, as well as preventing accidents due to secondary factors, such as wake turbulence. Maintaining proper separation is often a safety critical property for fixed-wing drones in the airspace. This paper addresses drone separation in time and distance for high volume corridors (en route) and lanes (on ground), merging as well as crossing intersections of multiple corridors/lanes. In this paper, the term drone is applied to both Unmanned Aerial Vehicle (UAV) and small Unmanned Aircraft System (UAS) vehicles operating autonomously. There exists a gamut of approaches to the merging and crossing problems. At one end of the extreme are the conservative yet low cost and verifiable solutions of today that deal with two drones at a time. At the other end are complex Machine Learning-based solutions with high computing requirements for fully autonomous drones of the future that are expected to handle all contentions. This paper presents a feasible and verifiable strategic approach to these problems that is based on distributed cooperation between the drones and the infrastructure. Three phases of the strategic approach (Prepare, Adjust, Commit) are presented. Simulation results are presented that show the proposed approach is stable and resilient to induced perturbations and guarantees a set of fixed-wing drones to merge and cross intersections by adjusting their speed based on their distance to the aircraft in front of them while remaining in the equilibrium state. The equilibrium state is defined as the state when a set of n aircraft move at a relatively constant speed and uniform spacing from each other in a congested system. A congested system is defined as the state when at least one aircraft cannot move at its maximum allowed speed. Unlike existing centralized and pre-planned approaches, the proposed solution is fully distributed and enables autonomous aircraft to decide to adjust their speed and distance with respect to the preceding aircraft, dynamically. Simulation results are presented that assess the feasibility of the approach.

Distributed↗

A Strategic Approach for Dense, Integrated, Vehicle Navigation

Drone usage has been on the rise in recent years with applications that include parcel delivery, wildlife protection, precision farming, law enforcement, and industrial inspection, just to name a few. Once regulations and safety policies are put in place to allow for the widespread use of unmanned drones, the number of aircraft in the National Airspace System (NAS) is expected to skyrocket to millions, potentially congesting the airspace which increases the likelihood of separation violations and possibly incidents. Currently, flight infrastructure can only support a few thousand aircraft flying over the United States National Airspace System (NAS) at any given time. A delay at one airport can send ripple effects throughout the system, causing more delays and missed connections. In air traffic control, separation is the concept of keeping an “ownship” aircraft outside a minimum distance from “intruder” aircraft to reduce the risk of the aircraft colliding, as well as preventing accidents due to secondary factors, such as wake turbulence. Maintaining proper separation is often a safety critical property for fixed-wing drones in the airspace. This paper addresses drone separation in time and distance for high volume corridors (en route) and lanes (on ground), merging as well as crossing intersections of multiple corridors/lanes. In this paper, the term drone is applied to both Unmanned Aerial Vehicle (UAV) and small Unmanned Aircraft System (UAS) vehicles operating autonomously. There exists a gamut of approaches to the merging and crossing problems. At one end of the extreme are the conservative yet low cost and verifiable solutions of today that deal with two drones at a time. At the other end are complex Machine Learning-based solutions with high computing requirements for fully autonomous drones of the future that are expected to handle all contentions. This paper presents a feasible and verifiable strategic approach to these problems that is based on distributed cooperation between the drones and the infrastructure. Three phases of the strategic approach (Prepare, Adjust, Commit) are presented. Simulation results are presented that show the proposed approach is stable and resilient to induced perturbations and guarantees a set of fixed-wing drones to merge and cross intersections by adjusting their speed based on their distance to the aircraft in front of them while remaining in the equilibrium state. The equilibrium state is defined as the state when a set of n aircraft move at a relatively constant speed and uniform spacing from each other in a congested system. A congested system is defined as the state when at least one aircraft cannot move at its maximum allowed speed. Unlike existing centralized and pre-planned approaches, the proposed solution is fully distributed and enables autonomous aircraft to decide to adjust their speed and distance with respect to the preceding aircraft, dynamically. Simulation results are presented that assess the feasibility of the approach.

Distributed↗

Quantum Distributed Algorithms for Approximate Steiner Trees and Directed Minimum Spanning Trees

We present two algorithms in the Quantum CONGEST- CLIQUE model of distributed computation that succeed with high probability; one for producing an approximately optimal Steiner Tree, and one for producing an exact directed minimum spanning tree, each of which uses O ̃(n1/4) rounds of communication and O ̃(n9/4) messages, achieving a lower asymptotic round and message complexity than any known algorithms in the classical CONGEST-CLIQUE model. At a high level, we achieve these results by combining classical algorithms with fast quantum subroutines. Additionally, we characterize the constants and logarithmic factors involved in our algorithms, as well as related classical algorithms, revealing that advances are needed to render both practical.

quantum computing↗

Quantum Distributed Algorithms for Approximate Steiner Trees and Directed Minimum Spanning Trees​

We present two algorithms in the Quantum CONGEST- CLIQUE model of distributed computation that succeed with high probability; one for producing an approximately optimal Steiner Tree, and one for producing an exact directed minimum spanning tree, each of which uses O ̃(n 1/4 ) rounds of communication and O ̃(n 9/4 ) messages, achieving a lower asymptotic round and message complexity than any known algorithms in the classical CONGEST-CLIQUE model. At a high level, we achieve these results by combining classical algorithms with fast quantum subroutines. Additionally, we characterize the constants and logarithmic factors involved in our algorithms, as well as related classical algorithms, revealing that advances are needed to render both practical.

quantum computing↗

Civil Aviation Research and Development /CARD/ Policy Study.

The results of the study lead to a number of conclusions regarding priority areas for R and D. It was found that aircraft noise abatement deserves highest priority because of widespread concern for the environment and because the success of the noise-abatement program will affect the solutions to other problems. Congestion is next on the list of priority problems. Its solution will involve an organized effort directed at the combination of air traffic control, runway capacity, ground control of aircraft, terminal processing, access and egress, parking, and airport location, acquisition, and development. A new short-haul system could help relieve congestion at existing airports. Constant improvements in technology for long-haul vehicles and their propulsion systems are essential to continued U.S. leadership.

Syvertson, C. A.↗

Energy impact of short-haul STOL systems

An analysis has been made to evaluate the impact on fuel requirements of a segregated short-haul system. A comparison has been made between two alternate scenarios: one with STOL, and the other without STOL. For the New York to Washington, D.C. city pair the results show: (1) the modal efficiency approach, while indicating the with STOL scenario requires more fuel than the without STOL scenario, is of questionable validity because it does not account for various effects which exist in realistic scenarios; (2) evaluation of fuel requirements based on more detailed modeling indicates that while a STOL scenario requires more fuel than without STOL when an idealized CTOL system is postulated, the STOL scenario requires less fuel than without STOL when the CTOL system has even moderate delays. These results are due to a combination of effects: the closer and more convenient locations of STOL ports to the traveler, congestion at the CTOL airports, and the impact of the through passenger traffic. Sensitivity of results to STOL aircraft block fuel and to CTOL congestion delays are considered.

Stewart, E. C.↗

Measures to increase airfield capacity by changing aircraft runway occupancy characteristics

Airfield capacity and aircraft runway occupancy characteristics were studied. Factors that caused runway congestion and airfield crowding were identified. Several innovations designed to alleviate the congestion are discussed. Integrated landing management, the concept that the operation of the final approach and runway should be considered in concert, was identified as underlying all of the innovations.

Gosling, G. D.↗

Probabilistic computer model of optimal runway turnoffs

Landing delays are currently a problem at major air carrier airports and many forecasters agree that airport congestion will get worse by the end of the century. It is anticipated that some types of delays can be reduced by an efficient optimal runway exist system allowing increased approach volumes necessary at congested airports. A computerized Probabilistic Runway Turnoff Model which locates exits and defines path geometry for a selected maximum occupancy time appropriate for each TERPS aircraft category is defined. The model includes an algorithm for lateral ride comfort limits.

Schoen, M. L.↗

Civil Applications For New V/STOL and STOL Aircraft

New designs offer benefits in congested urban areas and remote regions. Report explores potential uses in civil aviation of advanced rotorcraft, vertical/short-takeoff-and-landing (V/STOL) aircraft, and short-takeoff-and-landing (STOL) aircraft. Future opportunities overcome formidable geographic barriers and lack of major airport facilities, bringing fast, flexible transportation to remote areas. Aircraft relieves congestion at airports in densely populated areas by utilizing pads and short runways without interfering with large-air-carrier traffic.

Albers, James A.↗

Real-time adaptive aircraft scheduling

One of the most important functions of any air traffic management system is the assignment of ground-holding times to flights, i.e., the determination of whether and by how much the take-off of a particular aircraft headed for a congested part of the air traffic control (ATC) system should be postponed in order to reduce the likelihood and extent of airborne delays. An analysis is presented for the fundamental case in which flights from many destinations must be scheduled for arrival at a single congested airport; the formulation is also useful in scheduling the landing of airborne flights within the extended terminal area. A set of approaches is described for addressing a deterministic and a probabilistic version of this problem. For the deterministic case, where airport capacities are known and fixed, several models were developed with associated low-order polynomial-time algorithms. For general delay cost functions, these algorithms find an optimal solution. Under a particular natural assumption regarding the delay cost function, an extremely fast (O(n ln n)) algorithm was developed. For the probabilistic case, using an estimated probability distribution of airport capacities, a model was developed with an associated low-order polynomial-time heuristic algorithm with useful properties.

Kolitz, Stephan E.↗

Civil tiltrotor missions and applications. Phase 2: The commercial passenger market

The commercial passenger market for the civil tiltrotor was examined in phase 2. A market responsive commercial tiltrotor was found to be technically feasible, and a significant worldwide market potential was found to exist for such an aircraft, especially for relieving congestion in urban area-to-urban area service and for providing cost effective hub airport feeder service. Potential technical obstacles of community noise, vertiport area navigation, surveillance, and control, and the pilot/aircraft interface were determined to be surmountable. Nontechnical obstacles relating to national commitment and leadership and development of ground and air infrastructure were determined to be more difficult to resolve; an innovative public/private partnership is suggested to allow coordinated development of an initial commercial tiltrotor network to relieve congestion in the crowded US Northeast corridor by the year 2000.

Thompson, P.↗

Predictive onboard flow control for packet switching satellites

We outline two alternate approaches to predicting the onset of congestion in a packet switching satellite, and argue that predictive, rather than reactive, flow control is necessary for the efficient operation of such a system. The first method discussed is based on standard, statistical techniques which are used to periodically calculate a probability of near-term congestion based on arrival rate statistics. If this probability exceeds a present threshold, the satellite would transmit a rate-reduction signal to all active ground stations. The second method discussed would utilize a neural network to periodically predict the occurrence of buffer overflow based on input data which would include, in addition to arrival rates, the distributions of packet lengths, source addresses, and destination addresses.

Bobinsky, Eric A.↗