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

A Concept of Operations for Earth Science Data Archive and Distribution in the Cloud

Science data systems can enable more comprehensive Earth system research by evolving to take advantage of advances in commercial computer technology services. Since their inception twenty five years ago, NASA's Earth Observing System Data and Information System (EOSDIS) Distributed Active Archive Centers (DAACs) have periodically evolved to utilize new technology and expand research using the exponential growth and diversity of Earth observations. Recently, with the advent of a maturing commercial compute services industry and upcoming high data volume missions such as the Surface Water and Ocean Topography (SWOT) mission and the NASA-Indian Space Research Organization Synthetic Aperture Radar (NISAR) mission, options were explored and a decision made to utilize commercial compute and storage services. This paper presents an overview of the concept of operations under development for the DAACs in the Cloud. We highlight the goals and expected advantages of utilizing Cloud services. We outline EOSDIS operations tenets and driving principles. A high-level view of EOSDIS system of systems target architecture serves as context for describing principle interactions. Concepts for key DAAC system and EOSDIS enterprise functions characterize automated end-to-end operations but mark nominal check and recovery points. Concepts are presented for managing Cloud resources, including organizational roles and responsibilities of the NASA project and DAAC personnel. Scenarios we use to further distinguish between what the system will do and what configuration and controls operators will have. Examples include interactions with data providers and data consumers with both in-cloud and on-premise facilities

Earth Observing System Data and Information System (EOSDIS) in the Cloud

No abstract availabl

Integrating Thematic Web Portal Capabilities into the NASA Earthdata Web Infrastructure

This poster will present the process of integrating thematic web portal capabilities into the NASA Earth data web infrastructure, with examples from the Sea Level Change Portal. The Sea Level Change Portal will be a source of current NASA research, data and information regarding sea level change. The portal will provide sea level change information through articles, graphics, videos and animations, an interactive tool to view and access sea level change data and a dashboard showing sea level change indicators

Implicit vs explicit treatments of aphasia, a case study

This single subject, multiple baseline intervention compared implicit and explicit treatments to improve verb retrieval. This implicit intervention is based on theoretical models of lexical retrieval that propose that spreading activation of close semantic neighbors is essential for the preparation of lexical items for production. Results were analyzed and revealed an increased number of correct responses following explicit treatment. Implicit treatment decreased the number of response failures and increased the number of semantically related errors suggesting that implicit treatment may have helped the participant overcome reluctance to respond. Results warrant consideration of implicit treatment as an adjunct to standard therapy

Observing the Earth from Afar with NASA's Worldview

NASA's Worldview interactive web map application delivers global, near real-time imagery from NASA's fleet of Earth Observing System (EOS) satellites. Within hours of satellite overpass, discover where the latest wildfires, severe storms, volcanic eruptions, dust and haze, ice shelves calving as well as many other events are occurring around the world. Near real-time imagery is made available in Worldview through the Land, Atmosphere Near real-time Capability for EOS (LANCE) via the Global Imagery Browse Services (GIBS). This poster will explore new near real-time imagery available in Worldview, the current ways in which the imagery is used in research, the news and social media and future improvements to Worldview that will enhance the availability and viewing of NASA EOS imagery

Rapidly Connecting You to the World: Improving NASAs Worldview to Enhance Discovery and Access to Near Real-Time Imagery

The world around us is constantly in motion. Storms swirl, fires rage, volcanoes erupt and icebergs calve. NASAs fleet of Earth Observing System (EOS) satellites are there to capture this. Within hours of satellite overpass, NASAs Worldview (https://worldview.earthdata.nasa.gov) delivers this global, near-real time imagery through an interactive web map application. Provided through NASAs Land Atmosphere Near real-time Capability for EOS (LANCE) (https://earthdata.nasa.gov/lance) via NASAs Global Imagery Browse Services (GIBS) (https://earthdata.nasa.gov/gibs), the near real-time satellite imagery provides a launching point to discover where the latest wildfires, severe storms, volcanic eruptions, and calving ice shelves are happening. This poster will explore the newest near real-time satellite imagery and soon-to-be available imagery in Worldview, including imagery from geostationary satellites - GOES-East/West and Himawari-8. The poster will cover recent and future improvements to Worldview aimed to enhance the discovery and interaction with near real-time imagery and show how it is used by people from researchers, to meteorologists to the science-minded public around the world

DRAMsim: A Memory System Simulator

As memory accesses become slower with respect to the processor and consume more power with increasing memory size, the focus of memory performance and power consumption has become increasingly important. With the trend to develop multi-threaded, multi-core processors, the demands on the memory system will continue to scale. However, determining the optimal memory system configuration is non-trivial. The memory system performance is sensitive to a large number of parameters. Each of these parameters take on a number of values and interact in fashions that make overall trends difficult to discern. A comparison of the memory system architectures becomes even harder when we add the dimensions of power consumption and manufacturing cost. Unfortunately, there is a lack of tools in the public-domain that support such studies. Therefore, we introduce DRAMsim, a detailed and highly configurable C-based memory system simulator to fill this gap. DRAMsim implements detailed timing models for a variety of existing memories, including SDRAM, DDR, DDR2, DRDRAM and FB-DIMM, with the capability to easily vary their parameters. It also models the power consumption of SDRAM and its derivatives. It can be used as a standalone simulator or as part of a more comprehensive system-level model. We have successfully integrated DRAMsim into a variety of simulators including MASE[15], Sim-alpha[14], BOCHS[2] and GEMS[13]. The simulator can be downloaded from www.ece.umd.edu/dramsim

The Performance and Energy Consumption of Embedded Real-Time Operating Systems

This paper presents the modeling of embedded systems with SimBed, an execution-driven simulation testbed that measures the execution behavior and power consumption of embedded applications and RTOSs by executing them on an accurate architectural model of a microcontroller with simulated real-time stimuli. We briefly describe the simulation environment and present a study that compares three RTOSs: μ C/OS-II, a popular public-domain embedded real-time operating system; Echidna, a sophisticated, industrial-strength (commercial) RTOS; and NOS, a bare-bones multi-rate task scheduler reminiscent of typical “roll-your-own” RTOSs found in many commercial embedded systems. The microcontroller simulated in this study is the Motorola M-CORE processor: a low-power, 32-bit CPU core with 16-bit instructions, running at 20MHz. Our simulations show what happens when RTOSs are pushed beyond their limits, and they depict situations in which unexpected interrupts or unaccounted-for task invocations disrupt timing, even when the CPU is lightly loaded. In general, there appears no clear winner in timing accuracy between preemptive systems and cooperative systems. The power-consumption measurements show that RTOS overhead is a factor of two to four higher than it needs to be, compared to the energy consumption of the minimal scheduler. In addition, poorly designed idle loops can cause the system to double its energy consumption—energy that could be saved by a simple hardware sleep mechanism