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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.

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NASA NTRS2017

Archive Management of NASA Earth Observation Data to Support Cloud Analysis

NASA collects, processes and distributes petabytes of Earth Observation (EO) data from satellites, aircraft, in situ instruments and model output, with an order of magnitude increase expected by 2024. Cloud-based web object storage (WOS) of these data can simplify the execution of such an increase. More importantly, it can also facilitate user analysis of those volumes by making the data available to the massively parallel computing power in the cloud. However, storing EO data in cloud WOS has a ripple effect throughout the NASA archive system with unexpected challenges and opportunities. One challenge is modifying data servicing software (such as Web Coverage Service servers) to access and subset data that are no longer on a directly accessible file system, but rather in cloud WOS. Opportunities include refactoring of the archive software to a cloud-native architecture; virtualizing data products by computing on demand; and reorganizing data to be more analysis-friendly. Reviewed by Mark McInerney ESDIS Deputy Project Manager.

Lynnes, Christopher↗

NASA NTRS2004

Swift Gamma-Ray Burst Explorer: Mission Design for Rapid, Accurate Location of Gamma-ray Bursts

The Swift Gamma-ray Burst Explorer is a NASA Mid-sized Explorer (MIDEX) with the primary mission of determining the origins of Gamma-Ray Bursts (GRBs). It will be the first mission to autonomously respond to newly-discovered GRBs and provide immediate follow-up narrow field instruments capable of multi-wavelength (UV, Optical, X-ray) observations. The characteristics of GRBs that are the key mission design drivers, are their non-repeating and brief duration bursts of multi-wavelength photons. In addition, rapid notification of the location and characteristics of the GRBs to ground-and-space- based observatories drive the end-to-end data analysis and distribution requirements. The Swift mission is managed by the GSFC, and includes an international team of contributors that each bring their unique perspective that have proven invaluable to the mission. The spacecraft bus, provided by Spectrum Astro, Inc. was procured through a Rapid Spacecraft Development Office (RSDO) contract by the GSFC. There are three instruments: the Burst Alert Telescope (BAT) provided by the GSFC; the X-Ray Telescope (XRT) provided by a team led by the Pennsylvania State University (PSU); and the Ultra-Violet Optical Telescope (UVOT), again managed by PSU. The Mission Operations Center (MOC) was developed by and is located at PSU. Science archiving and data analysis centers are located at the GSFC, in the UK and in Italy.

Bundas, David J.↗

NASA NTRS1978

NASA and the U.S. climate program - A problem in data management

NASA's contribution to the total data base for the National Climate Plan will be to produce climate data sets from its experimental space observing systems and to maximize the value of these data for climate analysis and prediction. Validated data sets will be provided to NOAA for inclusion into their overall diagnostic data base. NASA data management for the Climate Plan will involve: (1) cataloging and retrieval of large integrated and distributed data sets upon user demand, and (2) the storage equivalent of 100,000 digital data tapes. It will be the largest, most complex data system ever developed by NASA

Quann, J. J.↗

NASA NTRS1991

Network interface unit design options performance analysis

An analysis is presented of three design options for the Space Station Freedom (SSF) onboard Data Management System (DMS) Network Interface Unit (NIU). The NIU provides the interface from the Fiber Distributed Data Interface (FDDI) local area network (LAN) to the DMS processing elements. The FDDI LAN provides the primary means for command and control and low and medium rate telemetry data transfers on board the SSF. The results of this analysis provide the basis for the implementation of the NIU.

Miller, Frank W.↗

NASA NTRS1988

Artificial intelligence approaches in space power systems automation at Marshall Space Flight Center

Various applications of AI to spacecraft electrical power systems are described. Particular attention is given to NICBES (nickel-cadmium battery expert system which is interfaced with the Hubble Space Telescope electrical power system test bed); the SSES; the three cooperating AI systems in the Space Station module power management and distribution system test bed; and I-DARE, the intelligent data reduction expert. It is found that the utilization of AI approaches permits comprehensive fault management and dynamic rescheduling capabilities for the electrical power system.

Weeks, David J.↗

NASA NTRS2004

Application of Bayesian Classification to Content-Based Data Management

The high volume of Earth Observing System data has proven to be challenging to manage for data centers and users alike. At the Goddard Earth Sciences Distributed Active Archive Center (GES DAAC), about 1 TB of new data are archived each day. Distribution to users is also about 1 TB/day. A substantial portion of this distribution is MODIS calibrated radiance data, which has a wide variety of uses. However, much of the data is not useful for a particular user's needs: for example, ocean color users typically need oceanic pixels that are free of cloud and sun-glint. The GES DAAC is using a simple Bayesian classification scheme to rapidly classify each pixel in the scene in order to support several experimental content-based data services for near-real-time MODIS calibrated radiance products (from Direct Readout stations). Content-based subsetting would allow distribution of, say, only clear pixels to the user if desired. Content-based subscriptions would distribute data to users only when they fit the user's usability criteria in their area of interest within the scene. Content-based cache management would retain more useful data on disk for easy online access. The classification may even be exploited in an automated quality assessment of the geolocation product. Though initially to be demonstrated at the GES DAAC, these techniques have applicability in other resource-limited environments, such as spaceborne data systems.

Lynnes, Christopher↗

NASA NTRS1993

VIEWCACHE: An incremental pointer-based access method for autonomous interoperable databases

One of the biggest problems facing NASA today is to provide scientists efficient access to a large number of distributed databases. Our pointer-based incremental data base access method, VIEWCACHE, provides such an interface for accessing distributed datasets and directories. VIEWCACHE allows database browsing and search performing inter-database cross-referencing with no actual data movement between database sites. This organization and processing is especially suitable for managing Astrophysics databases which are physically distributed all over the world. Once the search is complete, the set of collected pointers pointing to the desired data are cached. VIEWCACHE includes spatial access methods for accessing image datasets, which provide much easier query formulation by referring directly to the image and very efficient search for objects contained within a two-dimensional window. We will develop and optimize a VIEWCACHE External Gateway Access to database management systems to facilitate database search.

Roussopoulos, N.↗

NASA NTRS1988

A multiprocessing architecture for real-time monitoring

A multitasking architecture for performing real-time monitoring and analysis using knowledge-based problem solving techniques is described. To handle asynchronous inputs and perform in real time, the system consists of three or more distributed processes which run concurrently and communicate via a message passing scheme. The Data Management Process acquires, compresses, and routes the incoming sensor data to other processes. The Inference Process consists of a high performance inference engine that performs a real-time analysis on the state and health of the physical system. The I/O Process receives sensor data from the Data Management Process and status messages and recommendations from the Inference Process, updates its graphical displays in real time, and acts as the interface to the console operator. The distributed architecture has been interfaced to an actual spacecraft (NASA's Hubble Space Telescope) and is able to process the incoming telemetry in real-time (i.e., several hundred data changes per second). The system is being used in two locations for different purposes: (1) in Sunnyville, California at the Space Telescope Test Control Center it is used in the preflight testing of the vehicle; and (2) in Greenbelt, Maryland at NASA/Goddard it is being used on an experimental basis in flight operations for health and safety monitoring.

Schmidt, James L.↗

NASA NTRS1987

Advanced data management design for autonomous telerobotic systems in space using spaceborne symbolic processors

The use of computers in autonomous telerobots is reaching the point where advanced distributed processing concepts and techniques are needed to support the functioning of Space Station era telerobotic systems. Three major issues that have impact on the design of data management functions in a telerobot are covered. It also presents a design concept that incorporates an intelligent systems manager (ISM) running on a spaceborne symbolic processor (SSP), to address these issues. The first issue is the support of a system-wide control architecture or control philosophy. Salient features of two candidates are presented that impose constraints on data management design. The second issue is the role of data management in terms of system integration. This referes to providing shared or coordinated data processing and storage resources to a variety of telerobotic components such as vision, mechanical sensing, real-time coordinated multiple limb and end effector control, and planning and reasoning. The third issue is hardware that supports symbolic processing in conjunction with standard data I/O and numeric processing. A SSP that currently is seen to be technologically feasible and is being developed is described and used as a baseline in the design concept.

Goforth, Andre↗

NASA NTRS2017

Archive Management of NASA Earth Observation Data to Support Cloud Analysis

Lynnes, Christopher↗

NASA NTRS2014

Federated Giovanni: A Distributed Web Service for Analysis and Visualization of Remote Sensing Data

The Geospatial Interactive Online Visualization and Analysis Interface (Giovanni) is a popular tool for users of the Goddard Earth Sciences Data and Information Services Center (GES DISC) and has been in use for over a decade. It provides a wide variety of algorithms and visualizations to explore large remote sensing datasets without having to download the data and without having to write readers and visualizers for it. Giovanni is now being extended to enable its capabilities at other data centers within the Earth Observing System Data and Information System (EOSDIS). This Federated Giovanni will allow four other data centers to add and maintain their data within Giovanni on behalf of their user community. Those data centers are the Physical Oceanography Distributed Active Archive Center (PO.DAAC), MODIS Adaptive Processing System (MODAPS), Ocean Biology Processing Group (OBPG), and Land Processes Distributed Active Archive Center (LP DAAC). Three tiers are supported: Tier 1 (GES DISC-hosted) gives the remote data center a data management interface to add and maintain data, which are provided through the Giovanni instance at the GES DISC. Tier 2 packages Giovanni up as a virtual machine for distribution to and deployment by the other data centers. Data variables are shared among data centers by sharing documents from the Solr database that underpins Giovanni's data management capabilities. However, each data center maintains their own instance of Giovanni, exposing the variables of most interest to their user community. Tier 3 is a Shared Source model, in which the data centers cooperate to extend the infrastructure by contributing source code.

Giovanni↗

NASA NTRS1977

Instrumentation complex for Langley Research Center's National Transonic Facility

The instrumentation discussed in the present paper was developed to ensure reliable operation for a 2.5-meter cryogenic high-Reynolds-number fan-driven transonic wind tunnel. It will incorporate four CPU's and associated analog and digital input/output equipment, necessary for acquiring research data, controlling the tunnel parameters, and monitoring the process conditions. Connected in a multipoint distributed network, the CPU's will support data base management and processing; research measurement data acquisition and display; process monitoring; and communication control. The design will allow essential processes to continue, in the case of major hardware failures, by switching input/output equipment to alternate CPU's and by eliminating nonessential functions. It will also permit software modularization by CPU activity and thereby reduce complexity and development time.

Russell, C. H.↗

NASA NTRS1993

Space Station Freedom ground data system: Design and operations

Over the previous year the Space Station Freedom (SSF) Program (SSFP) ground data distribution system has become independent of a number of data systems that were to have been provided by other National Aeronautics and Space Administration (NASA) programs. Consequently, the SSFP has outlined the basic architecture of a new data system dedicated to supporting SSF requirements. This has been accomplished through a complete redesign of the ground network and a reallocation of selected functions. There are a number of aspects of the new ground data distribution system that are unique among NASA programs. These considerations make SSF ground data distribution one of the most extensive and complex data management challenges encountered in the arena of Space Operations. A description of this system comprises the main focus of the paper.

Dunning, Richard A., Jr.↗

NASA NTRS1993

Data management system performance modeling

This paper discusses analytical techniques that have been used to gain a better understanding of the Space Station Freedom's (SSF's) Data Management System (DMS). The DMS is a complex, distributed, real-time computer system that has been redesigned numerous times. The implications of these redesigns have not been fully analyzed. This paper discusses the advantages and disadvantages for static analytical techniques such as Rate Monotonic Analysis (RMA) and also provides a rationale for dynamic modeling. Factors such as system architecture, processor utilization, bus architecture, queuing, etc. are well suited for analysis with a dynamic model. The significance of performance measures for a real-time system are discussed.

Kiser, Larry M.↗

NASA NTRS2004

New Earth Science Data and Access Methods

NASA's Earth Science Enterprise, working with its domestic and international partners, provides scientific data and analysis to improve life here on Earth. NASA provides science data products that cover a wide range of physical, geophysical, biochemical and other parameters, as well as services for interdisciplinary Earth science studies. Management and distribution of these products is administered through the Earth Observing System Data and Information System (EOSDIS) Distributed Active Archive Centers (DAACs), which all hold data within a different Earth science discipline. This paper will highlight selected EOS datasets and will focus on how these observations contribute to the improvement of essential services such as weather forecasting, climate prediction, air quality, and agricultural efficiency. Emphasis will be placed on new data products derived from instruments on board Terra, Aqua and ICESat as well as new regional data products and field campaigns. A variety of data tools and services are available to the user community. This paper will introduce primary and specialized DAAC-specific methods for finding, ordering and using these data products. Special sections will focus on orienting users unfamiliar with DAAC resources, HDF-EOS formatted data and the use of desktop research and application tools.

Moses, John F.↗

NASA NTRS2019

New Era, New Opportunity, Is GES DISC Ready for Big Data Challenge?

The new era of Big Data has opened doors for many new opportunities, as well as new challenges, for both Earth science research/application and data communities. As one of the twelve NASA data centers - Goddard Earth Sciences Data and Information Services Center (GES DISC), one of our great challenges has been how to help research/application community efficiently (quickly and properly) accessing, visualizing and analyzing the massive and diverse data in natural hazard research, management, or even prediction. GES DISC has archived over 2000 TB data on premises and distributed over 23,000 TB of data since 2010. Our data has been widely used in every phase of natural hazard management and research, i.e. long term risk assessment and reduction, forecasting and predicting, monitoring and detection, early warning, damage assessment and response. The big data challenge is not just about data storage, but also about data discoverability and accessibility, and even more, about data migration/mirroring in the cloud. This paper is going to demonstrate GES DISC’s efforts and approaches of evolving our overall Web services and powerful Giovanni (Geospatial Interactive Online Visualization ANd aNalysis Infrastructure) tool into further improving data discoverability and accessibility. Prototype works will also be presented.

Li, A.↗

NASA NTRS1986

Notes on a storage manager for the Clouds kernel

The Clouds project is research directed towards producing a reliable distributed computing system. The initial goal is to produce a kernel which provides a reliable environment with which a distributed operating system can be built. The Clouds kernal consists of a set of replicated subkernels, each of which runs on a machine in the Clouds system. Each subkernel is responsible for the management of resources on its machine; the subkernal components communicate to provide the cooperation necessary to meld the various machines into one kernel. The implementation of a kernel-level storage manager that supports reliability is documented. The storage manager is a part of each subkernel and maintains the secondary storage residing at each machine in the distributed system. In addition to providing the usual data transfer services, the storage manager ensures that data being stored survives machine and system crashes, and that the secondary storage of a failed machine is recovered (made consistent) automatically when the machine is restarted. Since the storage manager is part of the Clouds kernel, efficiency of operation is also a concern.

Pitts, David V.↗

NASA NTRS1989

Exploiting replication in distributed systems

Techniques are examined for replicating data and execution in directly distributed systems: systems in which multiple processes interact directly with one another while continuously respecting constraints on their joint behavior. Directly distributed systems are often required to solve difficult problems, ranging from management of replicated data to dynamic reconfiguration in response to failures. It is shown that these problems reduce to more primitive, order-based consistency problems, which can be solved using primitives such as the reliable broadcast protocols. Moreover, given a system that implements reliable broadcast primitives, a flexible set of high-level tools can be provided for building a wide variety of directly distributed application programs.

Birman, Kenneth P.↗