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A viewgraph presentation on experiments with sensor webs and service oriented architectures is shown. The topics include: 1) Problem; 2) Basic Service Oriented Architecture Approach; 3) Series of Experiments; and 4) Next Experiments.
This viewgraph presentation reviews the vision of the sensor web enablement via a Service Oriented Architecture (SOA). An generic example is given of a user finding a service through the Web, and initiating a request for the desired observation. The parts that comprise this system and how they interact are reviewed. The advantages of the use of SOA are reviewed.
This viewgraph presentation reviews the development of a Service Oriented Architecture to assist in lowering the cost of new Earth Science products. This architecture will enable rapid and cost effective reconfiguration of new sensors.
This paper describes the work being managed by the NASA Goddard Space Flight Center (GSFC) Information System Division (ISD) under a NASA Earth Science Technology Ofice (ESTO) Advanced Information System Technology (AIST) grant to develop a modular sensor web architecture which enables discovery of sensors and workflows that can create customized science via a high-level service-oriented architecture based on Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) web service standards. These capabilities serve as a prototype to a user-centric architecture for Global Earth Observing System of Systems (GEOSS). This work builds and extends previous sensor web efforts conducted at NASA/GSFC using the Earth Observing 1 (EO-1) satellite and other low-earth orbiting satellites.
The Collaborative Information Portal (CIP) was enterprise software developed jointly by the NASA Ames Research Center and the Jet Propulsion Laboratory (JPL) for NASA's highly successful Mars Exploration Rover (MER) mission. Both MER and CIP have performed far beyond their original expectations. Mission managers and engineers ran CIP inside the mission control room at JPL, and the scientists ran CIP in their laboratories, homes, and offices. All the users connected securely over the Internet. Since the mission ran on Mars time, CIP displayed the current time in various Mars and Earth time zones, and it presented staffing and event schedules with Martian time scales. Users could send and receive broadcast messages, and they could view and download data and image files generated by the rovers' instruments. CIP had a three-tiered, service-oriented architecture (SOA) based on industry standards, including J2EE and web services, and it integrated commercial off-the-shelf software. A user's interactions with the graphical interface of the CIP client application generated web services requests to the CIP middleware. The middleware accessed the back-end data repositories if necessary and returned results for these requests. The client application could make multiple service requests for a single user action and then present a composition of the results. This happened transparently, and many users did not even realize that they were connecting to a server. CIP performed well and was extremely reliable; it attained better than 99% uptime during the course of the mission. In this paper, we present overviews of the MER mission and of CIP. We show how CIP helped to fulfill some of the mission needs and how people used it. We discuss the criteria for choosing its architecture, and we describe how the developers made the software so reliable. CIP's reliability did not come about by chance, but was the result of several key design decisions. We conclude with some of the important lessons we learned form developing, deploying, and supporting the software.
The National Virtual Observatory (NVO) Extensible Secure Scalable Service Infrastructure (NESSSI) is a Web service architecture and software framework that enables Web-based astronomical data publishing and processing on grid computers such as the National Science Foundation's TeraGrid. Characteristics of this architecture include the following: (1) Services are created, managed, and upgraded by their developers, who are trusted users of computing platforms on which the services are deployed. (2) Service jobs can be initiated by means of Java or Python client programs run on a command line or with Web portals. (3) Access is granted within a graduated security scheme in which the size of a job that can be initiated depends on the level of authentication of the user.
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Interoperability and loose coupling requirements are pushing the next generation of distributed applications towards more decentralized and more dynamic interaction schemes, which the classic requestJresponse communication paradigm can hardly accommodate. Hence, sound foundations and mechanisms for the establishment of unmticiptitteb peer-to-peer interactions across organizational boundaries are of significant importance to upcoming middleware platforms. The Executable Choreography Framework (ECF) is a middleware-level framework that targets dynamic and decentralized service compositions. The ECF combines transparent context propagation with aspect-oriented software composition techniques to dynamically refine the default control and data flow of service invocations. The framework provides a ground for experimentation with dynamic and distributed workflows, and a base to assess their safety and applicability when depioyed across organizational boundaries.
This paper presents the lessons learned from six years of experiments with planetary rover prototypes running the Service Oriented Robotic Architecture (SORA) developed by the Intelligent Robotics Group (IRG) at the NASA Ames Research Center. SORA relies on proven software engineering methods and technologies applied to space robotics. Based on a Service Oriented Architecture and robust middleware, SORA encompasses on-board robot control and a full suite of software tools necessary for remotely operated exploration missions. SORA has been eld tested in numerous scenarios of robotic lunar and planetary exploration. The experiments conducted by IRG with SORA exercise a large set of the constraints encountered in space applications: remote robotic assets, ight relevant science instruments, distributed operations, high network latencies and unreliable or intermittent communication links. In this paper, we present the results of these eld tests in regard to the developed architecture, and discuss its bene ts and limitations.
This paper presents the lessons learned from six years of experiments with planetary rover prototypes running the Service Oriented Robotic Architecture (SORA) developed by the Intelligent Robotics Group (IRG) at NASA Ames Research Center. SORA relies on proven software methods and technologies applied to the robotic world. Based on a Service Oriented Architecture and robust middleware, SORA extends its reach beyond the on-board robot controller and supports the full suite of software tools used during mission scenarios from ground control to remote robotic sites. SORA has been field tested in numerous scenarios of robotic lunar and planetary exploration. The results of these high fidelity experiments are illustrated through concrete examples that have shown the benefits of using SORA as well as its limitations.
Future needs of the National Airspace System require decision support tools to adopt a service-oriented architecture in alignment with the FAA’s vision for an Info-Centric NAS. To achieve this, many existing systems will need to undergo a digital transformation from a monolithic decision support tool to a service-oriented architecture where individual services are exposed through well defined Application Programming Interfaces (APIs). To enable this transformation, NASA has developed the Digital Information Platform as a cloud based foundation for development of aviation services with a special focus towards Artificial Intelligence and Machine Learning (ML) services. This paper describes the work required for the transformation of NASA’s legacy surface management system to a real-time ML based decision support system deployed in the cloud. Details of the Machine Learning Operations (MLOps) infrastructure and best practices are described which enabled the end-toend lifecycle management of ML within an integrated software system. Validation results are provided from an operational field evaluation where performance was benchmarked against the legacy approach.
We are entering a new era in space exploration. Reduced operating budgets require innovative solutions to leverage existing systems to implement the capabilities of future missions. Custom solutions to fulfill mission objectives are no longer viable. Can NASA adopt international standards to reduce costs and increase interoperability with other space agencies? Can legacy systems be leveraged in a service oriented architecture (SOA) to further reduce operations costs? The Operations Technology Facility (OTF) at the Johnson Space Center (JSC) is collaborating with Deutsches Zentrum fur Luft- und Raumfahrt (DLR) to answer these very questions. The Mission Operations and Information Management Services Area (MOIMS) Spacecraft Monitor and Control (SM&C) Working Group within the Consultative Committee for Space Data Systems (CCSDS) is developing the Mission Operations standards to address this problem space. The set of proposed standards presents a service oriented architecture to increase the level of interoperability among space agencies. The OTF and DLR are developing independent implementations of the standards as part of an interoperability prototype. This prototype will address three key components: validation of the SM&C Mission Operations protocol, exploration of the Object Management Group (OMG) Data Distribution Service (DDS), and the incorporation of legacy systems in a SOA. The OTF will implement the service providers described in the SM&C Mission Operation standards to create a portal for interaction with a spacecraft simulator. DLR will implement the service consumers to perform the monitor and control of the spacecraft. The specifications insulate the applications from the underlying transport layer. We will gain experience with a DDS transport layer as we delegate responsibility to the middleware and explore transport bridges to connect disparate middleware products. A SOA facilitates the reuse of software components. The prototype will leverage the capabilities of existing legacy systems. Various custom applications and middleware solutions will be combined into one system providing the illusion of a set of homogenous services. This paper will document our journey as we implement the interoperability prototype. The team consists of software engineers with experience on the current command, telemetry and messaging systems that support the International Space Station (ISS) and Space Shuttle programs. Emphasis will be on the objectives, results and potential cost saving benefits.
The goal of this REASoN applications and technology project is to deliver and use Earth Science Enterprise (ESE) data and tools in support of air quality management. Its scope falls within the domain of air quality management and aims to develop a federated air quality information sharing network that includes data from NASA, EPA, US States and others. Project goals were achieved through a access of satellite and ground observation data, web services information technology, interoperability standards, and air quality community collaboration. In contributing to a network of NASA ESE data in support of particulate air quality management, the project will develop access to distributed data, build Web infrastructure, and create tools for data processing and analysis. The key technologies used in the project include emerging web services for developing self describing and modular data access and processing tools, and service oriented architecture for chaining web services together to assemble customized air quality management applications. The technology and tools required for this project were developed within DataFed.net, a shared infrastructure that supports collaborative atmospheric data sharing and processing web services. Much of the collaboration was facilitated through community interactions through the Federation of Earth Science Information Partners (ESIP) Air Quality Workgroup. The main activities during the project that successfully advanced DataFed, enabled air quality applications and established community-oriented infrastructures were: develop access to distributed data (surface and satellite), build Web infrastructure to support data access, processing and analysis create tools for data processing and analysis foster air quality community collaboration and interoperability.
The GeneLab project is a science initiative to maximize the scientific return of omics data collected from spaceflight and from ground simulations of microgravity and radiation experiments, supported by a data system for a public bioinformatics repository and collaborative analysis tools for these data. The mission of GeneLab is to maximize the utilization of the valuable biological research resources aboard the ISS by collecting genomic, transcriptomic, proteomic and metabolomic (so-called omics) data to enable the exploration of the molecular network responses of terrestrial biology to space environments using a systems biology approach. All GeneLab data are made available to a worldwide network of researchers through its open-access data system. GeneLab is currently being developed by NASA to support Open Science biomedical research in order to enable the human exploration of space and improve life on earth. Open access to Phase 1 of the GeneLab Data Systems (GLDS) was implemented in April 2015. Download volumes have grown steadily, mirroring the growth in curated space biology research data sets (61 as of June 2016), now exceeding 10 TB/month, with over 10,000 file downloads since the start of Phase 1. For the period April 2015 to May 2016, most frequently downloaded were data from studies of Mus musculus (39) followed closely by Arabidopsis thaliana (30), with the remaining downloads roughly equally split across 12 other organisms (each 10 of total downloads). GLDS Phase 2 is focusing on interoperability, supporting data federation, including integrated search capabilities, of GLDS-housed data sets with external data sources, such as gene expression data from NIHNCBIs Gene Expression Omnibus (GEO), proteomic data from EBIs PRIDE system, and metagenomic data from Argonne National Laboratory's MG-RAST. GEO and MG-RAST employ specifications for investigation metadata that are different from those used by the GLDS and PRIDE (e.g., ISA-Tab). The GLDS Phase 2 system will implement a Google-like, full-text search engine using a Service-Oriented Architecture by utilizing publicly available RESTful web services Application Programming Interfaces (e.g., GEO Entrez Programming Utilities) and a Common Metadata Model (CMM) in order to accommodate the different metadata formats between the heterogeneous bioinformatics databases. GLDS Phase 2 completion with fully implemented capabilities will be made available to the general public in September 2017.
Amidst a concerning surge in power consumption during peak hours, coupled with heightened power grid instability, and driven by a growing demand for electricity, aggregations of Distributed Energy Resource are becoming a viable means for providing essential reliability services.Electric utility companies have proactively implemented Demand Response programs for decades. These programs employ Direct Load Control methods to enhance power grid stability, achieved by controlling customers’ Distributed Energy Resource during peak hours to reduce power consumption. However, a notable drawback of Direct Load Control has been high unenrollment rates of DR program participants due to customer discomfort.Therefore, the underlying issue of over-consumption persists. To address these concerns, this paper introduces a Service-Oriented Load Participation approach to providing grid services such as Demand Response. Leveraging a Service-Oriented Architecture, this method offers the advantage of efficient service management and provisioning within the system. The SOLP approach not only aims to reduce power consumption but also to maintain customer satisfaction by ensuring a comfortable grid service experience.
There will always be a new latest and greatest architecture for satellite ground systems. This paper discusses the use of a proven message-oriented middleware (MOM) architecture using publish/subscribe functions and the strengths it brings to these mission critical systems. An even newer approach gaining popularity is Service Oriented Architectures (SOAs). SOAs are generally considered more powerful than the MOM approach and address many mission-critical system challenges. A MOM vs SOA discussion can highlight capabilities supported or enabled by the underlying architecture and can identify benefits of MOMs and SOAs when applied to differing sets of mission requirements or evaluation criteria.
During 2005 through 2008, NASA defined and implemented a major evolutionary change in it Earth Observing system Data and Information System (EOSDIS) to modernize its capabilities. This implementation was based on a vision for 2015 developed during 2005. The EOSDIS 2015 Vision emphasizes increased end-to-end data system efficiency and operability; increased data usability; improved support for end users; and decreased operations costs. One key feature of the Evolution plan was achieving higher operational maturity (ingest, reconciliation, search and order, performance, error handling) for the NASA s Earth Observing System Clearinghouse (ECHO). The ECHO system is an operational metadata registry through which the scientific community can easily discover and exchange NASA's Earth science data and services. ECHO contains metadata for 2,726 data collections comprising over 87 million individual data granules and 34 million browse images, consisting of NASA s EOSDIS Data Centers and the United States Geological Survey's Landsat Project holdings. ECHO is a middleware component based on a Service Oriented Architecture (SOA). The system is comprised of a set of infrastructure services that enable the fundamental SOA functions: publish, discover, and access Earth science resources. It also provides additional services such as user management, data access control, and order management. The ECHO system has a data registry and a services registry. The data registry enables organizations to publish EOS and other Earth-science related data holdings to a common metadata model. These holdings are described through metadata in terms of datasets (types of data) and granules (specific data items of those types). ECHO also supports browse images, which provide a visual representation of the data. The published metadata can be mapped to and from existing standards (e.g., FGDC, ISO 19115). With ECHO, users can find the metadata stored in the data registry and then access the data either directly online or through a brokered order to the data archive organization. ECHO stores metadata from a variety of science disciplines and domains, including Climate Variability and Change, Carbon Cycle and Ecosystems, Earth Surface and Interior, Atmospheric Composition, Weather, and Water and Energy Cycle. ECHO also has a services registry for community-developed search services and data services. ECHO provides a platform for the publication, discovery, understanding and access to NASA s Earth Observation resources (data, service and clients). In their native state, these data, service and client resources are not necessarily targeted for use beyond their original mission. However, with the proper interoperability mechanisms, users of these resources can expand their value, by accessing, combining and applying them in unforeseen ways.