Search NASA⌕ Search

SEARCH · Search NASA

Results for “network scheduling”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

S-band and Ku-band return service interference between TDRSS users

The Tracking Data Relay Satellite System (TDRSS) return service performance can be degraded by interference from another user when two or more spacecraft communicate with the same Tracking Data Relay Satellite (TDRS) at the same time. This paper describes the S-band and Ku-band return service self interference environment expected in the 1996 - 2010 timeframe and shows the self-interference expected for selected TDRSS users based on Communications Link Analysis and Simulation System (CLASS) Automated Conflict Resolution System (ACRS) and Interference Monitor (IM) tools. The results show: which user links are susceptible to interference from other users, the interference statistics, and whether or not interference can be avoided with appropriate interference mitigation techniques such as scheduling, cross-polarization, or Pseudo random Noise (PN) spreading. The analysis results enable Space Network (SN) managers to determine the impacts of self-interference on the TDRSS service availability. They also enable project offices to determine whether they should select return service communications parameters, such as polarization and PN spreading, to minimize the probability of being impacted by self-interference; try to schedule TDRSS support around other user spacecraft communications schedules; or accept communication outages due to self-interference.

Harrell, Linda↗
NASA NTRS2006

Scheduling with Automatic Resolution of Conflicts

DSN Requirement Scheduler is a computer program that automatically schedules, reschedules, and resolves conflicts for allocations of resources of NASA s Deep Space Network (DSN) on the basis of ever-changing project requirements for DSN services. As used here, resources signifies, primarily, DSN antennas, ancillary equipment, and times during which they are available. Examples of project-required DSN services include arraying, segmentation, very-long-baseline interferometry, and multiple spacecraft per aperture. Requirements can include periodic reservations of specific or optional resources during specific time intervals or within ranges specified in terms of starting times and durations. This program is built on the Automated Scheduling and Planning Environment (ASPEN) software system (aspects of which have been described in previous NASA Tech Briefs articles), with customization to reflect requirements and constraints involved in allocation of DSN resources. Unlike prior DSN-resource- scheduling programs that make single passes through the requirements and require human intervention to resolve conflicts, this program makes repeated passes in a continuing search for all possible allocations, provides a best-effort solution at any time, and presents alternative solutions among which users can choose.

Clement, Bradley↗
NASA NTRS1983

NASCOM network ground communications availability report

A performance analysis of NASCOM Network circuits is presented. An objective of 99.80 percent availability has been established for all network circuits and an acceptable level of 99.50. A network narrative summary for the current month includes changes in network configurations, current month's totals for modes of service and trouble category losses, a discussion of trends, and significant losses that affected the performance indexes of individual or groups of circuits. A table and narrative summary of those circuits that failed to meet the objective of 99.80% availability for all network circuits and an acceptable level of 99.50. Lost time and interruption tables showing all circuits affected by outages, by trouble category, with their total time and events, scheduled operating hours, and individual availability indexes also are included. Selected circuits whose availabilities have or continue to affect the overall network availability are also analyzed.

Source record↗
NASA NTRS1992

Second tracking and data relay satellite system (TDRSS) ground terminal - STGT

The STGT will provide high availability command and control and improved services to users of NASA's Space Network in the 1990s and beyond. The Space Network, comprising the TDRSS, will be the primary communications gateway for Space Station Freedom and other user's spacecraft and their ground support elements. The STGT will contain a redundant, distributed computer system providing configuration and control of redundant RF to baseband equipment chains for throughput of user data, for user tracking services and for control and monitoring of the TDR Satellites. An interface with NASA's Network Control Center, located at the Goddard Space Flight Center, provides automated scheduling and control of the STGT. A local TDRSS Operations Control Center for local monitoring and back-up control and an interface with the Domestic Satellite for data distribution will be provided by the STGT. This paper describes the STGT, with emphasis on configuration, control and monitoring of those elements providing TDRSS services to user spacecraft.

Berndt, Allen K.↗
NASA NTRS2012

Orbit Transfers for Dawn's Vesta Operations : Navigation and Mission Design Experience

Dawn, a mission belonging to NASA's Discovery Program, was launched on September 27, 2007 to explore main belt asteroids in order to yield insights into important questions about the formation and evolution of the solar system. From July of 2011 to August of 2012, the Dawn spacecraft successfully returned valuable science data, collected during the four planned mapping orbits at its first target asteroid, Vesta. Each mapping orbit was designed to enable a different set of scientific observations. Such a mission would have been impossible without the low thrust ion propulsion system (IPS). Maneuvering a spacecraft using only the IPS for the transfers between the mapping orbits posed many technical challenges to Dawn's flight team at NASA's Jet Propulsion Laboratory. Each transfer needs a robust plan that accounts for uncertainties in maneuver execution, orbit determination, and physical characteristics of Vesta. This paper discusses the mission design and navigational experience during Dawn's Vesta operations. Topics include requirements and constraints from Dawn's science and spacecraft teams, orbit determination and maneuver design and building process for transfers, developing timelines for thrust sequence build cycles, and the process of scheduling very demanding coverage with ground antennae at NASA's Deep Space Network.

low thrust↗
NASA NTRSDate not supplied

New Horizons for a Practical and Performance-Optimized Solar System Internet

The High-rate Delay Tolerant Networking (HDTN) project at the NASA Glenn Research Center (GRC) is developing a performance-optimized Delay Tolerant Networking (DTN) implementation using the Bundle Protocol (BP) both for infusion in modern, distributed spacecraft systems and for foundational network research purposes. While one purpose of networking is to enable a returns-to-scale with communicating assets, it is recognized that neither the protocol nor its implementations may impose a bottleneck on data delivery if expected to be implemented. With this in mind, this paper explores the current status of the HDTN software, including its capabilities and also various performance metrics at the bundle layer, the convergence layers (e.g. performance-optimized Licklider Transmission Protocol, or LTP), and bundle storage and retrieval. This includes goals of software implementations that support multi-gigabit per second communications regardless of payload size. A discussion on the current software architecture and internal scheduling and routing is included. Interoperability with such extant DTN implementations as Interplanetary Overlay Network (ION) and DTN Marshall Enterprise Implementation (DTNME) are included. The research goals of the project are also listed, including Software-Defined Networking (SDN) and the theory of DTNs. A table-based filtration system for the Bundle Protocol (BP), called BP Filter, is also explored: this addition enables table-based policies within the context of a DTN for management purposes. Infusion begins with systems testing in the Johnson Space Center (JSC) Software Development and Integration Laboratory (SDIL), which supports International Space Station (ISS) Flight Software development, integration, and verification. Observations made from the results of testing in the SDIL and in flight testing are also discussed, pointing to a path for infusion into high data return low-earth orbit (LEO) missions. The paper concludes with areas for future work.

Delay Tolerant Networking↗
NASA NTRS2012

HURON (HUman and Robotic Optimization Network) Multi-Agent Temporal Activity Planner/Scheduler

HURON solves the problem of how to optimize a plan and schedule for assigning multiple agents to a temporal sequence of actions (e.g., science tasks). Developed as a generic planning and scheduling tool, HURON has been used to optimize space mission surface operations. The tool has also been used to analyze lunar architectures for a variety of surface operational scenarios in order to maximize return on investment and productivity. These scenarios include numerous science activities performed by a diverse set of agents: humans, teleoperated rovers, and autonomous rovers. Once given a set of agents, activities, resources, resource constraints, temporal constraints, and de pendencies, HURON computes an optimal schedule that meets a specified goal (e.g., maximum productivity or minimum time), subject to the constraints. HURON performs planning and scheduling optimization as a graph search in state-space with forward progression. Each node in the graph contains a state instance. Starting with the initial node, a graph is automatically constructed with new successive nodes of each new state to explore. The optimization uses a set of pre-conditions and post-conditions to create the children states. The Python language was adopted to not only enable more agile development, but to also allow the domain experts to easily define their optimization models. A graphical user interface was also developed to facilitate real-time search information feedback and interaction by the operator in the search optimization process. The HURON package has many potential uses in the fields of Operations Research and Management Science where this technology applies to many commercial domains requiring optimization to reduce costs. For example, optimizing a fleet of transportation truck routes, aircraft flight scheduling, and other route-planning scenarios involving multiple agent task optimization would all benefit by using HURON.

Hua, Hook↗
NASA NTRS2011

CCSDS Advanced Orbiting Systems Virtual Channel Access Service for QoS MACHETE Model

To support various communications requirements imposed by different missions, interplanetary communication protocols need to be designed, validated, and evaluated carefully. Multimission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE), described in "Simulator of Space Communication Networks" (NPO-41373), NASA Tech Briefs, Vol. 29, No. 8 (August 2005), p. 44, combines various tools for simulation and performance analysis of space networks. The MACHETE environment supports orbital analysis, link budget analysis, communications network simulations, and hardware-in-the-loop testing. By building abstract behavioral models of network protocols, one can validate performance after identifying the appropriate metrics of interest. The innovators have extended the MACHETE model library to include a generic link-layer Virtual Channel (VC) model supporting quality-of-service (QoS) controls based on IP streams. The main purpose of this generic Virtual Channel model addition was to interface fine-grain flow-based QoS (quality of service) between the network and MAC layers of the QualNet simulator, a commercial component of MACHETE. This software model adds the capability of mapping IP streams, based on header fields, to virtual channel numbers, allowing extended QoS handling at link layer. This feature further refines the QoS v existing at the network layer. QoS at the network layer (e.g. diffserv) supports few QoS classes, so data from one class will be aggregated together; differentiating between flows internal to a class/priority is not supported. By adding QoS classification capability between network and MAC layers through VC, one maps multiple VCs onto the same physical link. Users then specify different VC weights, and different queuing and scheduling policies at the link layer. This VC model supports system performance analysis of various virtual channel link-layer QoS queuing schemes independent of the network-layer QoS systems.

Jennings, Esther H.↗
NASA NTRS1976

TDRSS operations control analysis study

The use of an operational Tracking and Data Relay Satellite System (TDRSS) and the remaining ground stations for the STDN (GSTDN) was investigated. The operational aspects of TDRSS concepts, GSTDN as a 14-site network, and GSTDN as a 7 site-network were compared and operations control concepts for the configurations developed. Man/machine interface, scheduling system, and hardware/software tradeoff analyses were among the factors considered in the analysis.

Source record↗
NASA NTRS1986

EOS: A project to investigate the design and construction of real-time distributed embedded operating systems

The EOS project is investigating the design and construction of a family of real-time distributed embedded operating systems for reliable, distributed aerospace applications. Using the real-time programming techniques developed in co-operation with NASA in earlier research, the project staff is building a kernel for a multiple processor networked system. The first six months of the grant included a study of scheduling in an object-oriented system, the design philosophy of the kernel, and the architectural overview of the operating system. In this report, the operating system and kernel concepts are described. An environment for the experiments has been built and several of the key concepts of the system have been prototyped. The kernel and operating system is intended to support future experimental studies in multiprocessing, load-balancing, routing, software fault-tolerance, distributed data base design, and real-time processing.

Campbell, R. H.↗
NASA NTRS1994

Measurement and interpretation of crustal deformation rates associated with postglacial rebound

This project involves obtaining GPS measurements in Scandinavia and using the measurements to estimate the viscosity profile of the earth's mantle and to correct tide-gauge measurements for the rebound effect. We report on several aspects of this project. The DSGS was not scheduled to be reoccupied with DOSE receivers during the report period. The permanent network set up by Onsala Space Observatory continues to operate, and the data are being evaluated. An important technical advance we intend for this project is to use the full three dimensional site velocity information for inferring geophysical parameters. During the report period, two papers have been been accepted for publication in the Journal of Geophysical Research and will be published in April. Reprints of these papers are contained in the Appendix.

Davis, James L.↗
NASA NTRS2013

Ny-Alesund Geodetic Observatory

In 2012 the 20-m telescope at Ny-Alesund, Svalbard, operated by the Norwegian Mapping Authority (NMA), took part in 163 out of 168 scheduled sessions of the IVS program. Since spring, all data was transferred by network, and the receiver monitoring computer was replaced by a bus-coupler. In autumn, the NMA received building permission for a new observatory from the Governor of Svalbard. The bidding process and first construction work for the infrastructure will start in 2013.

Sieber, Moritz↗
NASA NTRSDate not supplied

Navigation Performance of the BioSentinel Deep Space CubeSat Mission

The BioSentinel mission was recently launched aboard the SLS launch vehicle (LV) as part of the Artemis- 1 campaign. The BioSentinel navigation team successfully tracked and guided the spacecraft through a lunar gravity assist to its destination Earth-trailing heliocentric orbit. This 6U CubeSat carries live yeast cells to analyze the effects of radiation at large distances from Earth, becoming the first biological payload in Deep Space. Prelaunch activities included mission design updates, orbit determination rehearsals and the development of a tracking schedule in coordination with the Artemis-1 payload office and the Deep Space Network (DSN). An important influence on the trajectories of Artemis I secondaries was the uncertainty associated with deployment from the Interim Cryogenic Propulsion System (ICPS), the upper stage of the SLS LV. The ICPS was rotating at a rate of 1 rpm; there was also an uncertainty in the spin axis attitude, which translated into an unknown clock angle of deployment. The variability in this angle and magnitude of deployment implied the existence of a non-negligible risk of a lunar impact, which was evaluated for various potential launch dates. We present the results of Monte Carlo analyses and compute the pertinent maneuvers to avoid it. In addition, we present a comparison with the actual deployment once the mission launched by reconstructing our trajectory with tracking data. On November 16th 2022 BioSentinel successfully deployed from ICPS and the navigation team started to receive 2-way Doppler and Sequential Ranging data from the DSN. We processed early data to try to obtain a first ephemeris using Initial Orbit Determination (IOD) methods such as the least squares. Soon after deployment, the spacecraft was tumbling and entered safe mode, creating a period where the tracking data were sparse. The mission team recovered the spacecraft and after four tracking passes, we solved for a first ephemeris that was sent to the DSN for better tracking of the spacecraft. After propagating this first ephemeris solution, we determined that we avoided impact with a margin of a few hundred km from the lunar surface. More tracking data over the next few days (from DSN as well as ESA antennas) allowed for a more refined orbit solution predicting a periselene altitude of 406 km and a lunar eclipse lasting 36.5 minutes. Therefore, BioSentinel operators aborted any correction maneuvers. This periselene altitude also gave us the necessary energy to achieve a heliocentric orbit. The next challenge was due to the necessary adjustments in our orbit determination method due to the large energy boost resulting from the lunar flyby. After a series of tracking passes we were able to get a nominal solution that resulted into a stable trajectory. This paper discusses in detail the navigation performance using the X-band IRIS transponder, as well as the challenges and lessons learned prior to and during this deep space, CubeSat mission.

Andres Dono Perez↗
NASA NTRSDate not supplied

BioSentinel Deep Space CubeSat Mission

The BioSentinel mission was recently launched aboard the SLS launch vehicle (LV) as part of the Artemis-1 campaign. This 6U CubeSat carries yeast cells to analyze the effects of radiation at large distances from Earth, becoming the first biological payload in Deep Space. Prelaunch activities included mission design updates, orbit determination rehearsals and the development of a tracking schedule in coordination with the Artemis-1 payload office and the Deep Space Network (DSN). An important influence on the trajectories of Artemis I secondaries was the uncertainty associated with deployment from the Interim Cryogenic Propulsion System (ICPS), the upper stage of the SLS LV. The ICPS was rotating at a rate of 1 rpm; there was also uncertainty in the spin axis attitude, which translated into an unknown clock angle of deployment. The variability in this angle and magnitude of deployment implied the existence of a non-negligible risk of a lunar impact, which was evaluated for various potential launch dates. On November 16 th 2022 BioSentinel successfully deployed from ICPS and the navigation team started to receive tracking data from the DSN and ESA antennas. Soon after deployment, the spacecraft was tumbling and entered safe mode. The mission team recovered the spacecraft and after four tracking passes, we solved for a first ephemeris that was sent to the DSN for better tracking of the spacecraft. After propagating this first ephemeris solution, we determined that we avoided impact with a margin of a few hundred km from the lunar surface. More tracking data over the next few days allowed for a more refined orbit solution predicting a periselene altitude of 406 km and a lunar eclipse lasting 36.5 minutes. Therefore, BioSentinel operators avoided any correction maneuvers on the trajectory and successfully tracked and guide the spacecraft. The spacecraft performed a nominal lunar flyby which provided the pertinent energy to achieve a final Earth-trailing heliocentric orbit. Over the course of two weeks, the mission operators corroborated that the subsystems were functioning as expected after the lunar eclipse and the large ΔV incurred. Science operations started once the mission achieved the nominal orbit in Deep Space. This paper discusses in detail the BioSentinel flight performance, as well as the challenges and lessons learned prior to and during this CubeSat mission.

Andres Dono Perez↗
NASA NTRS2001

Integrating LMINET with TAAM and SIMMOD: A Feasibility Study

LMINET is a queuing network air traffic simulation model implemented at 64 large airports and the entire National Airspace System in the United States. TAAM and SIMMOD are two widely used air traffic event-driven simulation models mostly for airports. Based on our proposed Progressive Augmented window approach, TAAM and SIMMOD are integrated with LMINET though flight schedules. In the integration, the flight schedules are modified through the flight delays reported by the other models. The benefit to the local simulation study is to let TAAM or SIMMOD take the modified schedule from LMINET, which takes into account of the air traffic congestion and flight delays at the national network level. We demonstrate the value of the integrated models by the case studies at Chicago O'Hare International Airport and Washington Dulles International Airport. Details of the integration are reported and future work for a full-blown integration is identified.

Long, Dou↗