Results for “Capacity allocation”

NASA NTRS1994

Low-Earth-Orbiter resource allocation and capacity planning for the DSN using LEO4CAST

The Deep Space Network provides tracking and communication services for a number of U.S. and international low-Earth-orbiting (LEO) and near-Earth missions. This service is supplied by the 26-m subnet (located at each of the DSN complexes), the 9-m and the 34-m Antenna Research System antennas at Goldstone, and the 11-m antennas (following the orbital VLBI mission). An increasing number of LEO missions are planned for DSN support, which will result in increasingly complex ground resource allocation and mission support trades. To support TDA decision making on mission support and cost-effective ground system evolution for this 26-m subnet, LEO4CAST has been developed. LEO4CAST is a tool that uses statistical approaches to provide useful information for long-term ground system capacity planning and near-term resource allocation (prior to detailed time-of-day scheduling). LEO4CAST is currently beta-test software and is being exercised by both the Office of Telecommunications and Data Acquisition (TDA) and the JPL Systems Division.

Fox, G.↗

NASA NTRS2018

Evaluation of Multiple Flow Constrained Area Capacity Setting Methods for Collaborative Trajectory Options Program

The purpose of this study was to compare flow constrained area (FCA) capacity setting methods for Collaborative Trajectory Options Program (CTOP) as they pertain to the Integrated Demand Management (IDM) concept. IDM uses flow balancing to manage air traffic across multiple FCAs with a common downstream constraint, as well as constraints at the respective FCA locations. FCA capacity rates can be set manually, but generating capacities for multiple, interdependent FCAs could potentially over-burden a user. A new enhancement to CTOP called the FCA Balance Algorithm (FBA) was developed at NASA Ames Research Center to improve the process of allocating capacity across multiple flow constrained segments in the airspace. The FBA evaluates the predicted demand and capacity across multiple FCAs and dynamically generates capacity settings for the FCAs that best meet capacity limits for all identified constraints. In a human-in-the-loop simulation study, both manual and automated capacity setting methods were evaluated in terms of their overall feasibility using measures of system performance, human performance, and qualitative feedback. Subject matter experts were asked to use three different methods to allocate capacity to three FCAs, either (1) by manually setting capacity for every 60-minute time window, (2) by manually setting capacity for every 15-minute time window, or (3) by using the FBA capability to automatically generate capacity settings. Results showed no significant differences in terms of overall system performance, indicated by similar ground delay and airport throughput numbers between methods. However, differences in individual strategies afforded by the manual methods allowed some participants to achieve system-wide delay that was much lower than the average. The FBA was the fastest method of capacity setting, and it received the lowest subjective rating scores on physical task load, mental task load, task difficulty and task complexity out of the three methods. Finally, participants explained through qualitative feedback that there were many benefits to using the FBA, such as ease of use, accuracy, and low risk of human input error. Participants did not experience the same limitations with the FBA that they did with the manual methods, such as reduced accuracy in the 60-minute manual condition, or high complexity in the 15-minute/manual condition. These results suggest that the FBA automation enhancement to CTOP maintains system performance while improving human performance. Therefore, the FBA could be introduced as a way to mitigate operator workload while planning a CTOP.

NextGen↗

NASA NTRS2018

Evaluation of Multiple Flow Constrained Area Capacity Setting Methods for Collaborative Trajectory Options Program

The purpose of this study was to compare flow constrained area (FCA) capacity setting methods for Collaborative Trajectory Options Program (CTOP) as they pertain to the Integrated Demand Management (IDM) concept. IDM uses flow balancing to manage air traffic across multiple FCAs with a common downstream constraint, as well as constraints at the respective FCA locations. FCA capacity rates can be set manually, but generating capacities for multiple, interdependent FCAs could potentially over-burden a user. A new enhancement to CTOP called the FCA Balance Algorithm (FBA) was developed at NASA Ames Research Center to improve the process of allocating capacity across multiple flow constrained segments in the airspace. The FBA evaluates the predicted demand and capacity across multiple FCAs and dynamically generates capacity settings for the FCAs that best meet capacity limits for all identified constraints. In a human-in-the-loop simulation study, both manual and automated capacity setting methods were evaluated in terms of their overall feasibility using measures of system performance, human performance, and qualitative feedback. Subject matter experts were asked to use three different methods to allocate capacity to three FCAs, either (1) by manually setting capacity for every 60-minute time window, (2) by manually setting capacity for every 15-minute time window, or (3) by using the FBA capability to automatically generate capacity settings. Results showed no significant differences in terms of overall system performance, indicated by similar ground delay and airport throughput numbers between methods. However, differences in individual strategies afforded by the manual methods allowed some participants to achieve system-wide delay that was much lower than the average. The FBA was the fastest method of capacity setting, and it received the lowest subjective rating scores on physical task load, mental task load, task difficulty and task complexity out of the three methods. Finally, participants explained through qualitative feedback that there were many benefits to using the FBA, such as ease of use, accuracy, and low risk of human input error. Participants did not experience the same limitations with the FBA that they did with the manual methods, such as reduced accuracy in the 60-minute manual condition, or high complexity in the 15-minute/manual condition. These results suggest that the FBA automation enhancement to CTOP maintains system performance while improving human performance. Therefore, the FBA could be introduced as a way to mitigate operator workload while planning a CTOP.

NextGen↗

NASA NTRS2011

Benefits Assessment of the Interaction Between Traffic Flow Management Delay and Airspace Partitions in the Presence of Weather

The concept of re-partitioning the airspace into a new set of sectors for allocating capacity rather than delaying flights to comply with the capacity constraints of a static set of sectors is being explored. The reduction in delay, a benefit, achieved by this concept needs to be greater than the cost of controllers and equipment needed for the additional sectors. Therefore, tradeoff studies are needed for benefits assessment of this concept.

Palopo, Kee↗

NASA NTRS1992

Guaranteeing synchronous message deadlines with the timed token medium access control protocol

We study the problem of guaranteeing synchronous message deadlines in token ring networks where the timed token medium access control protocol is employed. Synchronous capacity, defined as the maximum time for which a node can transmit its synchronous messages every time it receives the token, is a key parameter in the control of synchronous message transmission. To ensure the transmission of synchronous messages before their deadlines, synchronous capacities must be properly allocated to individual nodes. We address the issue of appropriate allocation of the synchronous capacities. Several synchronous capacity allocation schemes are analyzed in terms of their ability to satisfy deadline constraints of synchronous messages. We show that an inappropriate allocation of the synchronous capacities could cause message deadlines to be missed even if the synchronous traffic is extremely low. We propose a scheme called the normalized proportional allocation scheme which can guarantee the synchronous message deadlines for synchronous traffic of up to 33 percent of available utilization. To date, no other synchronous capacity allocation scheme has been reported to achieve such substantial performance. Another major contribution of this paper is an extension to the previous work on the bounded token rotation time. We prove that the time elapsed between any consecutive visits to a particular node is bounded by upsilon TTRT, where TTRT is the target token rotation time set up at system initialization time. The previous result by Johnson and Sevcik is a special case where upsilon = 2. We use this result in the analysis of various synchronous allocation schemes. It can also be applied in other similar studies.

Agrawal, Gopal↗

NASA NTRS2000

Dependence of Photosynthetic Capacity, Photosynthetic Pigment Allocation, and Carbon Storage on Nitrogen Levels in Foliage of Aspen Stands

The role of foliar nitrogen (N) in the seasonal dynamics and vertical canopy distribution of photosynthetic pigments, photosynthetic capacity, and carbon (C) storage was investigated in boreal broadleaved species. The study was conducted at two different aged stands (60 y and 15 y) in 1994 and 1996 in Saskatchewan, Canada as part of the Boreal Ecosystem-Atmosphere Study (BOREAS). Foliage in upper and lower strata was examined for aspen (Populus tremuloides Michx.) and its associated hazelnut shrub (Corylus americana Walt.). We determined that C accumulation, expressed as dry mass per unit leaf area (mg C cm (exp -2)), was linearly dependent on N content (approximately 0.3- 3.5 mg N cm (exp -2))(r (exp 2) = 0.93, n=383, P less than 0.001) when eleven foliage groups were defined according to species, site, and developmental stage. C assembly was greatest in the upper aspen strata of both sites (seasonal average, 40.1 plus or minus 0.6 mg C cm (exp -2)), intermediate in the lower aspen strata (32.7 plus or minus 0.6), and considerably lower, and similar, in the hazelnut shrub layers (23.7 plus or minus 0.6) and in expanding aspen leaves (23.8 plus or minus 0.5); the lowest C assembly per unit N occurred in the two youngest, emerging leaf groups (17.1 plus or minus 0.6). Other relationships among physiological and biochemical variables were typically non-linear and were confounded by inclusion of the three groups of young (i.e., emerging or expanding) leaves, unless these were separately identified. Net C uptake, measured as photosynthetic capacity (A (sub max), micromole CO2 m (exp -2) s (exp -1)), was greater in aspen throughout the season, and optimal in mid-summer at a C:N ratio of approximately 18 (approximately 2.3 %N). When young leaves were excluded and logarithms of both variables were used, A (sub max) was approximately linearly dependent on N (mg N cm (exp-2) (r (exp 2) = 0.85, n= 193, P less than 0.001), attributed to incorporation of N into photosynthetic complexes and enzymes. In mature leaves, differences in pigment content vs. N among canopy strata were accentuated when N was expressed per unit leaf area (Mg cm (exp -2)) . However, the simplest log-linear relationship between a pigment variable and N was obtained for a ratio describing the relative allocation of photosynthetic pigment to Chl a (Chl a/[Chl b + carotenoids], microgram cm (exp -2)/ microgram cm-2) vs. %N (r (exp 2) = 0.90, n=343, P less than 0.001). Attainment of comparable A (sub max) Chl a content and relative Chl a allocation per unit N (mg cm (exp -2)) was achieved at different foliar N levels per canopy group: the lowest N requirement was for hazelnut leaves in the lowest, shaded stratum at the older, closed canopy site; the highest N requirement was in aspen leaves of the upper-most stratum at the younger, more open canopy site. These results highlight the differences in physiological responses between young and fully expanded leaves and show that sustaining those foliar constituents and processes important to C balance may require higher foliar N levels in leaves of establishing vs. mature aspen stands. There may be implications for remote-sensing assessments made for carbon balance in springtime, or over a landscape mosaic comprised of different aged stands.

Middleton, Elizabeth M.↗

NASA NTRS1994

A model for analysis of TDA budget allocation

There is an ever-increasing need to achieve greater efficiency in the operation of the Deep Space Network (DSN), i.e., increased productivity at reduced cost. One of the tools used in the course of a planning workshop on this subject was a methodology for budget allocation applicable to long-range planning. This article presents a model for analysis of the TDA budget allocation. For the 1994 through 1999 period, the percentage of the total TDA budget allocated to capacity and capability is being cut in half, whereas the percentage spent on efficiency of delivery will be increasing.

Remer, D. S.↗

NASA NTRS1992

Optimal routing and buffer allocation for a class of finite capacity queueing systems

The problem of routing jobs to K parallel queues with identical exponential servers and unequal finite buffer capacities is considered. Routing decisions are taken by a controller which has buffering space available to it and may delay routing of a customer to a queue. Using ideas from weak majorization, it is shown that the shorter nonfull queue delayed (SNQD) policy minimizes both the total number of customers in the system at any time and the number of customers that are rejected by that time. The SNQD policy always delays routing decisions as long as all servers are busy. Only when all the buffers at the controller are occupied is a customer routed to the queue with the shortest queue length that is not at capacity. Moreover, it is shown that, if a fixed number of buffers is to be distributed among the K queues, then the optimal allocation scheme is the one in which the difference between the maximum and minimum queue capacities is minimized, i.e., becomes either 0 or 1.

Towsley, Don↗

NASA NTRS1987

Concurrent communication among multi-transceiver stations over shared media

In order to increase a local-area network's throughput beyond a single bus data rate without using dedicated switching nodes, multiple buses and multitransceiver stations are required. The design space of single-hop interconnections is explored among such stations. Interconnections are presented whose throughput can grow quadratically with the number of transmitters and receivers per station. These are referred to as selective broadcast interconnections (SBIs). The performance of various SBIs are studied. A spread-spectrum channel can accommodate several current successful transmission, and a single-transceiver node can thus utilize only a small fraction of the channel capacity. In order to allocate the appropriate fraction of capacity to a busy node, it is proposed to equip it with several transmitters and receivers, thereby turning it into a supernode. Several architectures and operation policies for supernodes are suggested and compared. It is shown that a supernode can significantly outperform a collection of independent conventional nodes with the same total numbers of transmitters and receivers. Packet-radio networks with half-duplex nodes, as well as networks with full-duplex nodes, are considered.

Birk, Yitzhak↗

NASA NTRS2006

Steps Toward Optimal Competitive Scheduling

This paper is concerned with the problem of allocating a unit capacity resource to multiple users within a pre-defined time period. The resource is indivisible, so that at most one user can use it at each time instance. However, different users may use it at different times. The users have independent, se@sh preferences for when and for how long they are allocated this resource. Thus, they value different resource access durations differently, and they value different time slots differently. We seek an optimal allocation schedule for this resource. This problem arises in many institutional settings where, e.g., different departments, agencies, or personal, compete for a single resource. We are particularly motivated by the problem of scheduling NASA's Deep Space Satellite Network (DSN) among different users within NASA. Access to DSN is needed for transmitting data from various space missions to Earth. Each mission has different needs for DSN time, depending on satellite and planetary orbits. Typically, the DSN is over-subscribed, in that not all missions will be allocated as much time as they want. This leads to various inefficiencies - missions spend much time and resource lobbying for their time, often exaggerating their needs. NASA, on the other hand, would like to make optimal use of this resource, ensuring that the good for NASA is maximized. This raises the thorny problem of how to measure the utility to NASA of each allocation. In the typical case, it is difficult for the central agency, NASA in our case, to assess the value of each interval to each user - this is really only known to the users who understand their needs. Thus, our problem is more precisely formulated as follows: find an allocation schedule for the resource that maximizes the sum of users preferences, when the preference values are private information of the users. We bypass this problem by making the assumptions that one can assign money to customers. This assumption is reasonable; a committee is usually in charge of deciding the priority of each mission competing for access to the DSN within a time period while scheduling. Instead, we can assume that the committee assigns a budget to each mission.This paper is concerned with the problem of allocating a unit capacity resource to multiple users within a pre-defined time period. The resource is indivisible, so that at most one user can use it at each time instance. However, different users may use it at different times. The users have independent, se@sh preferences for when and for how long they are allocated this resource. Thus, they value different resource access durations differently, and they value different time slots differently. We seek an optimal allocation schedule for this resource. This problem arises in many institutional settings where, e.g., different departments, agencies, or personal, compete for a single resource. We are particularly motivated by the problem of scheduling NASA's Deep Space Satellite Network (DSN) among different users within NASA. Access to DSN is needed for transmitting data from various space missions to Earth. Each mission has different needs for DSN time, depending on satellite and planetary orbits. Typically, the DSN is over-subscribed, in that not all missions will be allocated as much time as they want. This leads to various inefficiencies - missions spend much time and resource lobbying for their time, often exaggerating their needs. NASA, on the other hand, would like to make optimal use of this resource, ensuring that the good for NASA is maximized. This raises the thorny problem of how to measure the utility to NASA of each allocation. In the typical case, it is difficult for the central agency, NASA in our case, to assess the value of each interval to each user - this is really only known to the users who understand their needs. Thus, our problem is more precisely formulated as follows: find an allocation schedule for the resource that maximizes the sum ofsers preferences, when the preference values are private information of the users. We bypass this problem by making the assumptions that one can assign money to customers. This assumption is reasonable; a committee is usually in charge of deciding the priority of each mission competing for access to the DSN within a time period while scheduling. Instead, we can assume that the committee assigns a budget to each mission.

Frank, Jeremy↗

NASA NTRS2000

Consequences of Slot Transactions on Airport Congestion and Environmental Protection

Recent trends in the liberalization of market access by many commercial airlines have opened the skies to virtually unlimited flights between many countries. However, this liberalization is stultified by the lack of airport capacity to accommodate the many flights that are generated by demand for capacity. Accordingly, the allocation of slots for open skies airlines remain dependent on the expansion and effective management of airport capacity. This article examines the ramifications of slot allocation on traffic peaking at airports and environmental concerns, which may emerge with this activity.

Abeyratne, Ruwantissa I.R.↗

NASA NTRS2005

Playing Games with Optimal Competitive Scheduling

This paper is concerned with the problem of allocating a unit capacity resource to multiple users within a pre-defined time period. The resource is indivisible, so that at most one user can use it at each time instance. However, different users may use it at different times. The users have independent, selfish preferences for when and for how long they are allocated this resource. Thus, they value different resource access durations differently, and they value different time slots differently. We seek an optimal allocation schedule for this resource.

Frank, Jeremy↗

NASA NTRSDate not supplied

Development of an Airspace Simulation and Modeling Tool for Enhanced Spectrum Management

The emergence of new aerial vehicles into the National Airspace System creates an increased demand for aeronautical communications to support aviation operations. However, the issue of spectrum scarcity remains an ever-present concern, and the growing demand cannot be supported using existing spectrum allocation strategies. As a result, a new spectrum management approach is required, and the National Aeronautics and Space Administration (NASA) is investigating advanced concepts to modernize the management and use of aviation spectrum by leveraging the latest advancements in wireless communications, big data and machine learning. This research proposes an autonomous spectrum allocation concept, which allocates communications resources, such as spectrum and power, based on the predicted communications and air traffic demands throughout the airspace, as opposed to the use of fixed allocations as is done today. This approach will result in improved spectrum utilization efficiency and enhanced airspace capacity. The autonomous spectrum allocation concept decomposes into three research areas: demand prediction, resource allocation, and use case evaluation. As part of the use case evaluation effort, a modeling and simulation capability is currently under development. This simulation capability includes the implementation of various features, including visualization of both live or virtually-generated airspace traffic, simulation scenario development, simulation management with data collection, and flight plan creation with corresponding trajectory generation. This modeling and simulation capability will continue to evolve as new and advanced airspace applications are introduced into existing and emerging operational environments.

Eric J. Knoblock↗

NASA NTRS2004

An Integrated Decision-Making Model for Categorizing Weather Products and Decision Aids

The National Airspace System s capacity will experience considerable growth in the next few decades. Weather adversely affects safe air travel. The FAA and NASA are working to develop new technologies that display weather information to support situation awareness and optimize pilot decision-making in avoiding hazardous weather. Understanding situation awareness and naturalistic decision-making is an important step in achieving this goal. Information representation and situation time stress greatly influence attentional resource allocation and working memory capacity, potentially obstructing accurate situation awareness assessments. Three naturalistic decision-making theories were integrated to provide an understanding of the levels of decision making incorporated in three operational situations and two conditions. The task characteristics associated with each phase of flight govern the level of situation awareness attained and the decision making processes utilized. Weather product s attributes and situation task characteristics combine to classify weather products according to the decision-making processes best supported. In addition, a graphical interface is described that affords intuitive selection of the appropriate weather product relative to the pilot s current flight situation.

Elgin, Peter D.↗

NASA NTRS1979

Pricing of NASA Space Shuttle transportation system cargo

A two-part pricing policy is investigated as the most feasible method of pricing the transportation services to be provided by NASA's SSTS. Engineering cost estimates and a deterministic operating cost model generate a data base and develop a procedure for pricing the services of the SSTS. It is expected that the SSTS will have a monopoly on space material processing in areas of crystal growth, glass processing, metallurgical space applications, and biomedical processes using electrophoresis which will require efficient pricing. Pricing problems, the SSTS operating costs based on orbit elevation, number of launch sites, and number of flights, capital costs of the SSTS, research and development costs, allocation of joint transportation costs of the SSTS to a particular space processing activity, and rates for the SSTS are discussed. It is concluded that joint costs for commercial cargoes carried in the SSTS can be most usefully handled by making cost allocations based on proportionate capacity utilization.

Hale, C. W.↗

NASA NTRS1999

Modeling and Simulation Reliable Spacecraft On-Board Computing

The proposed project will investigate modeling and simulation-driven testing and fault tolerance schemes for Spacecraft On-Board Computing, thereby achieving reliable spacecraft telecommunication. A spacecraft communication system has inherent capabilities of providing multipoint and broadcast transmission, connectivity between any two distant nodes within a wide-area coverage, quick network configuration /reconfiguration, rapid allocation of space segment capacity, and distance-insensitive cost. To realize the capabilities above mentioned, both the size and cost of the ground-station terminals have to be reduced by using reliable, high-throughput, fast and cost-effective on-board computing system which has been known to be a critical contributor to the overall performance of space mission deployment. Controlled vulnerability of mission data (measured in sensitivity), improved performance (measured in throughput and delay) and fault tolerance (measured in reliability) are some of the most important features of these systems. The system should be thoroughly tested and diagnosed before employing a fault tolerance into the system. Testing and fault tolerance strategies should be driven by accurate performance models (i.e. throughput, delay, reliability and sensitivity) to find an optimal solution in terms of reliability and cost. The modeling and simulation tools will be integrated with a system architecture module, a testing module and a module for fault tolerance all of which interacting through a centered graphical user interface.

Park, Nohpill↗

NASA NTRSDate not supplied

Dynamic Channel Assignments for Efficient Use of Aviation Spectrum Allocations

The demand for voice and data communications continues to rise with the emergence of new aerial vehicles into the airspace and the continued growth of aviation operations throughout the National Airspace System (NAS). Recent studies have shown that the anticipated growing demand for spectrum resources will exceed the capacity of existing aviation spectrum allocations. Further, airspace configurations, via assignment of fixed channel allocations within standard service volumes, do not allow for the dynamic and efficient distribution of spectrum resources based on airspace demand; as a result, a new approach to aviation spectrum management is needed to support the forecasted needs of new airspace users. The National Aeronautics and Space Administration (NASA) is investigating applications of artificial intelligence (AI), machine learning (ML), and other advanced concepts to solve a dynamic constraint satisfaction problem which is analogous to the frequency assignment problem faced by aviation. Procedures and strategies for dynamic channel allocation can be borrowed from other large-scale mobile services (i.e., 4G/5G applications) and can provide a novel spectrum management approach that allows for the intelligent utilization of aviation spectrum throughout the airspace while maintaining the strict quality of service prescribed by aeronautical standards.

Communications↗

NASA NTRSDate not supplied

Dynamic Channel Assignments for Efficient Use of Aviation Spectrum Allocations

The demand for voice and data communications continues to rise with the emergence of new aerial vehicles into the airspace and the continued growth of aviation operations throughout the National Airspace System (NAS). Recent studies have shown that the anticipated growing demand for spectrum resources will exceed the capacity of existing aviation spectrum allocations. Further, airspace configurations, via assignment of fixed channel allocations within standard service volumes, do not allow for the dynamic and efficient distribution of spectrum resources based on airspace demand; as a result, a new approach to aviation spectrum management is needed to support the forecasted needs of new airspace users. The National Aeronautics and Space Administration (NASA) is investigating applications of artificial intelligence (AI), machine learning (ML), and other advanced concepts to solve a dynamic constraint satisfaction problem which is analogous to the frequency assignment problem faced by aviation. Procedures and strategies for dynamic channel allocation can be borrowed from other large-scale mobile services (i.e., 4G/5G applications) and can provide a novel spectrum management approach that allows for the intelligent utilization of aviation spectrum throughout the airspace while maintaining the strict quality of service prescribed by aeronautical standards.

communications↗