Search NASASearch

SEARCH · Search NASA

Results for “service migration”

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 19 records

An Approach to Reasoning Service Migration in Data and Reasoning Fabric (DRF) Implementation

In this paper we consider service migration problem for Data and Reasoning Fabric (DRF) enabled airspace operations assuming a fixed cloud/edge infrastructure with allocated computing, storage and power resources, where cloud/edge servers, and communication stations are in a wired connected network, while vehicles use a wireless network for communication. The objective is to automatically select the best location for the requested service execution, which achieves minimum cost while satisfying the user quality of service (QoS) and available resources constraints. To this end, estimates of the response time, consumed energy and total cost are defined for each potential compute location. A mixed-integer linear program is then formulated and solved to identify optimal compute locations given QoS constraints, network infrastructure limitations, with worst-case vehicle positioning. The approach is applied to trajectory re-planning use case to avoid a collision with an emergency vehicle in real time.

Air mobility

An Approach to Reasoning Service Migration in Data and Reasoning Fabric (DRF) Implementation

In this paper we consider service placement problem for Data and Reasoning Fabric (DRF) enabled airspace operations assuming a fixed cloud/edge infrastructure with allocated computing, storage and power resources, where cloud/edge servers, and communication stations are in a wired connected network, while vehicles use a wireless network for communication. The objective is to automatically select the best location for the requested service execution, which achieves minimum cost while satisfying the user quality of service (QoS) and available resources constraints. To this end, we estimate for each potential location the response time, consumed energy and total cost; formulate an optimization problem for cost minimization given the users QoS constraints and network infrastructure limitations; and solve it using nonlinear programming tools. The approach is applied to trajectory re-planning use case to handle a no-fly zone contingency in real time.

Vahram Stepanyan

DMFS: A Data Migration File System for NetBSD

I have recently developed dmfs, a Data Migration File System, for NetBSD. This file system is based on the overlay file system, which is discussed in a separate paper, and provides kernel support for the data migration system being developed by my research group here at NASA/Ames. The file system utilizes an underlying file store to provide the file backing, and coordinates user and system access to the files. It stores its internal meta data in a flat file, which resides on a separate file system. Our data migration system provides archiving and file migration services. System utilities scan the dmfs file system for recently modified files, and archive them to two separate tape stores. Once a file has been doubly archived, files larger than a specified size will be truncated to that size, potentially freeing up large amounts of the underlying file store. Some sites will choose to retain none of the file (deleting its contents entirely from the file system) while others may choose to retain a portion, for instance a preamble describing the remainder of the file. The dmfs layer coordinates access to the file, retaining user-perceived access and modification times, file size, and restricting access to partially migrated files to the portion actually resident. When a user process attempts to read from the non-resident portion of a file, it is blocked and the dmfs layer sends a request to a system daemon to restore the file. As more of the file becomes resident, the user process is permitted to begin accessing the now-resident portions of the file. For simplicity, our data migration system divides a file into two portions, a resident portion followed by an optional non-resident portion. Also, a file is in one of three states: fully resident, fully resident and archived, and (partially) non-resident and archived. For a file which is only partially resident, any attempt to write or truncate the file, or to read a non-resident portion, will trigger a file restoration. Truncations and writes are blocked until the file is fully restored so that a restoration which only partially succeed does not leave the file in an indeterminate state with portions existing only on tape and other portions only in the disk file system. We chose layered file system technology as it permits us to focus on the data migration functionality, and permits end system administrators to choose the underlying file store technology. We chose the overlay layered file system instead of the null layer for two reasons: first to permit our layer to better preserve meta data integrity and second to prevent even root processes from accessing migrated files. This is achieved as the underlying file store becomes inaccessible once the dmfs layer is mounted. We are quite pleased with how the layered file system has turned out. Of the 45 vnode operations in NetBSD, 20 (forty-four percent) required no intervention by our file layer - they are passed directly to the underlying file store. Of the twenty five we do intercept, nine (such as vop_create()) are intercepted only to ensure meta data integrity. Most of the functionality was concentrated in five operations: vop_read, vop_write, vop_getattr, vop_setattr, and vop_fcntl. The first four are the core operations for controlling access to migrated files and preserving the user experience. vop_fcntl, a call generated for a certain class of fcntl codes, provides the command channel used by privileged user programs to communicate with the dmfs layer.

Studenmund, William

NASA’s Global Imagery Browse Services and Worldview Migrate to Mapbox Vector Tiles: The Drawbacks and Advantages

NASA’s Global Imagery Browse Services (GIBS) is in the process of migrating their vector data from raster tiles to Mapbox Vector Tiles (MVTs). MVTs are becoming ubiquitous in the world of web mapping. Serving data in place of pixels for each feature presents numerous new visualization opportunities as well as various new challenges to overcome. This presentation will cover some of the hardships these teams encountered, the techniques used to overcome those barriers, and it will give you a glimpse at how the user experience was enhanced.

Benjamin King

A Programmable SDN+NFV Architecture for UAV Telemetry Monitoring

With the explosive growth in UAV numbers forecast worldwide, a core concern is how to manage the ad-hoc network configuration required for mobility management. As UAVs migrate among ground control stations, associated network services, routing and operational control must also rapidly migrate to ensure a seamless transition. In this paper, we present a novel, lightweight and modular architecture which supports high mobility, resilience and flexibility through the application of SDN and NFV principles on top of the UAV infrastructure. By combining SDN programmability and Network Function Virtualization we can achieve resilient infrastructure migration of network services, such as network monitoring and anomaly detection, coupled with migrating UAVs to enable high mobility management. Our container-based monitoring and anomaly detection Network Functions (NFs) can be tuned to specific UAV models providing operators better insight during live, high-mobility deployments. We evaluate our architecture against telemetry from over 80flights from a scientific research UAV infrastructure.

Resilience

GENESIS: GPS Environmental and Earth Science Information System

This presentation reviews the GPS ENvironmental and Earth Science Information System (GENESIS). The objectives of GENESIS are outlined (1) Data Archiving, searching and distribution for science data products derived from Space borne TurboRogue Space Receivers for GPS science and other ground based GPS receivers, (2) Data browsing using integrated visualization tools, (3) Interactive web/java-based data search and retrieval, (4) Data subscription service, (5) Data migration from existing GPS archived data, (6) On-line help and documentation, and (7) participation in the WP-ESIP federation. The presentation reviews the products and services of Genesis, and the technology behind the system.

Hajj, George

Using OPeNDAP In The Cloud to Connect NASA Data Centers and Support Open Data Access

NASA DAACs (Distributed Active Archive Centers), including the Goddard Earth Sciences Data Information and Services Center (GES DISC), are currently transitioning from on-premises servers to a shared Earthdata Cloud in order to build more interoperability, cross-collaboration, and streamlined services between their data centers. Migrating its on-premises OPeNDAP service to the cloud is a critical component of making this interconnectedness between NASA DAACs possible. To improve their cloud services, GES DISC is leveraging open-source platforms like Github to collect user feedback, create use cases, and develop resources to enable real-time learning for users about OPeNDAP in the cloud. This presentation gives an overview of the OPeNDAP in the cloud, resources developed to access this service, and considerations for improved user guidance and experience to further support NASA's commitment to the Open-Source Science Initiative (OSSI).

Christopher Battisto

Hydrological Data at the NASA GES DISC: Current Capabilities and New Opportunities

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is one of twelve NASA Earth science data centers that document, process, archive and distribute data from Earth observation missions and projects. GES DISC maintains an archive of several hydrology datasets, including the Land Data Assimilation Systems (LDAS) and the Gravity Recovery and Climate Experiment (GRACE) Data Assimilation for Drought Monitoring (GRACE-DA-DM) data products. These datasets include model output of heat fluxes, rain, snow, soil temperature, soil moisture, and runoff; and observational forcing data, including surface pressure, temperature, precipitation, downward shortwave and longwave radiation, humidity, and wind. The temporal resolution of the hydrology data at GES DISC ranges from hourly to monthly, and spatial resolutions range from 0.1° to 1.0°. The GES DISC provides services which enable users to aggregate, temporally and spatially subset, regrid, and visualize archived data including the GES DISC Subsetter, Hydrology Data Rods, and the Geospatial Interactive Online Visualization and Analysis Infrastructure (GIOVANNI). The Hydrology Data Rods service optimally reorganizes large hydrological data sets as extended time series, providing more efficient access for the hydrological community. The time series data (aka “data rods”) were integrated into hydrology community tools, such as the Data Rods Explorer on HydroShare. Furthermore, the GES DISC is in the process of migrating its data and services to the cloud. Hydrological data available at the GES DISC are now available in the Amazon Web Services (AWS) cloud (us-west-2 region) providing users Direct S3 data access and the capability for cloud computing operations. In this presentation, the hydrology data products and services currently available at the GES DISC will be summarized. Also discussed are the migration to the cloud, user support through this transition, and the status of migrating the data rods service to the cloud.

Ashley Heath

KNBD: A Remote Kernel Block Server for Linux

I am developing a prototype of a Linux remote disk block server whose purpose is to serve as a lower level component of a parallel file system. Parallel file systems are an important component of high performance supercomputers and clusters. Although supercomputer vendors such as SGI and IBM have their own custom solutions, there has been a void and hence a demand for such a system on Beowulf-type PC Clusters. Recently, the Parallel Virtual File System (PVFS) project at Clemson University has begun to address this need (1). Although their system provides much of the functionality of (and indeed was inspired by) the equivalent file systems in the commercial supercomputer market, their system is all in user-space. Migrating their 10 services to the kernel could provide a performance boost, by obviating the need for expensive system calls. Thanks to Pavel Machek, the Linux kernel has provided the network block device (2) with kernels 2.1.101 and later. You can configure this block device to redirect reads and writes to a remote machine's disk. This can be used as a building block for constructing a striped file system across several nodes.

Becker, Jeff

The Future of NASA Earth Science in the Commercial Cloud: Challenges and Opportunities

NASA produces a large volume and variety of data products that are used every day to support research, decision making, and education. The widespread use of NASA’s Earth Science data is enabled by NASA’s Earth Science Data System (ESDS) program, which oversees the archiving and distribution of these data and invests in the development of new data systems and tools. However, NASA’s current approach to Earth Science data distribution — based on distributed institutional archives with individual on-premises high-performance computing capabilities — faces some significant challenges, including massive increases in data volume from upcoming missions, a greater need for transdisciplinary science that synthesizes many different kinds of observations, and a push to make science more open, inclusive, and accessible. To address these challenges, NASA is aggressively migrating its Earth Science data and related tools and services into the commercial cloud. Migration of data into the commercial cloud can significantly improve NASA’s existing data system capabilities by (1) providing more flexible options for storage and compute (including rapid, as-needed access to state-of-the-art capabilities); (2) by centralizing and standardizing data access, which gives all of NASA’s institutional data centers access to all of each other’s datasets; and (3) by facilitating “analysis-in-place”, whereby users can bring their own computational workflows and tools to the data rather than having to maintain their own copies of NASA datasets. However, migration to the commercial cloud also poses some significant challenges, including (1) managing costs under a “pay-as-you-go” model; (2) incompatibility with existing tools and data formats with object-based storage and network access; (3) vendor lock-in; (4) challenges with data access for workflows that mix on-premise and cloud computing; and (5) standardization for highly diverse data as is present in NASA’s data archive. I conclude with two examples of recent NASA activities showcasing capabilities enabled by the commercial cloud: An interactive analysis and development platform for analyzing airborne imaging spectroscopy data, and a new collection of tools and services for data discovery, analysis, publication, and data-driven storytelling (Visualization, Exploration, and Data Analysis, VEDA).

Alexey N Shiklomanov

LAADS DAAC Migrates to the Cloud: Lessons Learned from Communicating About Earth Science Data on the Cloud

The Level-1 and Atmosphere Archive Distribution System (LAADS) Distributed Active Archive Center (DAAC) is migrating data to the cloud. As one of twelve DAACS supported by NASA’s Earth Science Data and Information System (ESDIS), LAADS is using moving away from on premise data storage facilities to migrating to Amazon Web Services, where the massive archive of data from the Moderate Imaging Spectroradiometer (MODIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) will be available for download and post-processing transformations online. The migration is happening in three phases and LAADS is concluding its beta testing period. This poster shows the lessons learned from communicating with a select group of users about how to effectively educate data users on using data in the cloud.

Tassia Owen

New Metadata Capabilities within NASA's Common Metadata Repository (CMR)

This talk will convey the new capabilities and features of the UMM-Variables and the UMM-Services metadata model within the Common Metadata Repository (CMR) and how community engagement through the ESDIS Standards Office (ESO) review shaped the new versions of the models. The Unified Metadata Model (UMM) provides a common metadata model to unify legacy systems (i.e. GCMD (Global Change Master Directory), ECHO (Earth Observing System (EOS) Clearinghouse)) with new systems (i.e. CMR). The rationale and migration process of the Service Entry Resource Format (SERF) to the UMM-S will also be conveyed. The talk will conclude with discussing issues and lessons learned from the review process and how future reviews will be conducted to ensure a more targeted, meaningful review with a faster turn-around time for triage and implementation.

Earth Observing System

Trade Study: Storing NASA HDF5/netCDF-4 Data in the Amazon Cloud and Retrieving Data via Hyrax Server / THREDDS Data Server

As part of the overall effort to understand implications of migrating ESDIS data and services to the cloud we are testing several common OPeNDAP and HDF use cases against three architectures for general performance and cost characteristics. The architectures include retrieving entire files, retrieving datasets using HTTP range gets, and retrieving elements of datasets (chunks) with HTTP range gets. We will describe these architectures and discuss our approach to estimating cost.

HDF

WGISS-46 ACCESS Section: IDN Report

The objective of this presentation is to provide IDN updates on features and activities to the Committee on Earth Observation Satellites (CEOS) Working Group on Information Systems and Services (WGISS) and provider community. The following topics will be will be discussed during the presentation: Overview of NASA's Vision of Services (UMM-S), Migration of IDN SERFs to UMM-S, Metadata Management Tool (MMT): Successor to DocBuilder, DocBuilder-10: Create/Update Dataset Records, Transition of DIF-9 to DIF-10, Schedule for UMM-C and GCMD/IDN Keywords, IDN's WGISS/WGCV Joint Session: Collaborative Actions.

Committee on Earth Observation Satellites

"Sensor Web Evolution - Webs of Webs for NASA Science - Focus on small Uninhabited Aerial Systems (sUAS)"

This paper will describe the evolution of information collection, derivation and delivery mechanisms in webs of NASA sensor webs, with a focus on recent advancements in small Uninhabited Aerial Systems (sUAS). I will discuss the movement to "Fog Computing", also known as Edge Computing. Fog Computing facilitates the distribution of common operations and networking between edge devices and cloud computing facilities, optimizing the production of actionable intelligence. Initially, sUASs utilized onboard data collection as standard, with minimal data downloaded directly. Information products were derived in conventional computational environments, generally desk top computers, and information products made available to the Science Community in weeks or months. With the increased availability, and increasingly lower costs, of beyond line of sight (BLOS) satellite based communication, transmission rates and data volumes increased, and processing migrated to Cloud based services. Contemporary sUASs are moving some of that information product derivation to on vehicle services, and are creating a distributed Cloud/Fog environment. I will describe the technological advances that have made this possible, including low power multi-core Central Processing Units (CPU), and, more recently, the availability of high end Graphical Processing Units (GPU) that consume only a few watts. Intelligent system software, leveraging these hardware advances, finally allows for information product generation on-board, rather than simple data collection. Additionally, intelligent flight control systems now support mutual vehicle to vehicle collaboration, allowing sUASs to create ad-hoc sensor webs on demand, as required. Also discussed will be the lessons learned by the Authors' development of data systems for NASA's large High Altitude Long Endurance (HALE) UASs like Predator and Global Hawk, and how those lessons are being applied to sUAS development. This paper will focus on application, rather a deep dive into the technology, and will highlight improving data management through these new technologies.

Sensor Web

UASs in the VOG/Edge/FOG Sensor Web Environment

This paper will describe the evolution of information collection, derivation and delivery mechanisms in sensor webs utilizing Uninhabited Aerial Systems (UAS).We will discuss the movement to "Fog Computing", also known as Edge Computing. Fog Computing facilitates the distribution of common operations and networking between edge devices and cloud computing facilities, optimizing the production of actionable intelligence. Initially, UASs utilized onboard data collection as standard, with minimal data downloaded directly. Information products were derived in conventional computational environments, generally desk top computers, and information products made available to the Science Community in weeks or months. With the increased availability, and increasingly lower costs, of beyond line of sight (BLOS) satellite based communication, transmission rates and data volumes increased, and processing migrated to Cloud based services. Contemporary UASs are moving some of that information product derivation to on vehicle services, and are creating a distributed Cloud/Fog environment. The Author will describe the technological advances that have made this possible, including low power multi-core Central Processing Units (CPU), and, more recently, the availability of high end Graphical Processing Units (GPU) that consume only a few watts. Intelligent system software, leveraging these hardware advances, finally allows for information product generation on-board, rather than simple data collection. Additionally, intelligent flight control systems now support mutual vehicle to vehicle collaboration, allowing UASs to create ad-hoc sensor webs on demand, as required. Also discussed will be the lessons learned by the Authors' development of data systems for NASA's large High Altitude Long Endurance (HALE) UASs like Predator and Global Hawk, and how those lessons are being applied to other UAS development This paper will focus on applications, rather a deep dive into the technology, and will highlight improving data management through these new technologies.

UAS

Technical Challenges and Lessons from the Migration of the GLOBE Data and Information System to Utilize Cloud Computing Service

The Global Learning and Observation to Benefit the Environment (GLOBE) Data and Information System supports an international science and education program with capabilities to accept local environment observations, archive, display and visualize them along with global satellite observations. Since its inception twenty years ago, the Web and database system has been upgraded periodically to accommodate the changes in technology and the steady growth of GLOBEs education community and collection of observations. Recently, near the end-of-life of the system hardware, new commercial computer platform options were explored and a decision made to utilize Cloud services. Now the GLOBE DIS has been fully deployed and maintained using Amazon Cloud services for over two years now. This paper reviews the early risks, actual challenges, and some unexpected findings as a result of the GLOBE DIS migration. We describe the plans, cost drivers and estimates, highlight adjustments that were made and suggest improvements. We present the trade studies for provisioning, for load balancing, networks, processing, storage, as well as production, staging and backup systems. We outline the migration teams skills and required level of effort for transition, and resulting changes in the overall maintenance and operations activities. Examples include incremental adjustments to processing capacity and frequency of backups, and efforts previously expended on hardware maintenance that were refocused onto application-specific enhancements.

GLOBE