Exploring Generative AI for Service-Oriented Software
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Generating Service-Oriented Software using Large Language Models
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Generative AI↗
A Reliable Service-Oriented Architecture for NASA's Mars Exploration Rover Mission
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.
Mak, Ronald↗
Using Open and Interoperable Ways to Publish and Access LANCE AIRS Near-Real Time Data
The Atmospheric Infrared Sounder (AIRS) Near-Real Time (NRT) data from the Land Atmosphere Near real-time Capability for EOS (LANCE) element at the Goddard Earth Sciences Data and Information Services Center (GES DISC) provides information on the global and regional atmospheric state, with very low temporal latency, to support climate research and improve weather forecasting. An open and interoperable platform is useful to facilitate access to, and integration of, LANCE AIRS NRT data. As Web services technology has matured in recent years, a new scalable Service-Oriented Architecture (SOA) is emerging as the basic platform for distributed computing and large networks of interoperable applications. Following the provide-register-discover-consume SOA paradigm, this presentation discusses how to use open-source geospatial software components to build Web services for publishing and accessing AIRS NRT data, explore the metadata relevant to registering and discovering data and services in the catalogue systems, and implement a Web portal to facilitate users' consumption of the data and services.
Zhao, Peisheng↗
Safeguard: Progress and Test Results for a Reliable Independent On-Board Safety Net for UAS
As demands increase to use unmanned aircraft systems (UAS) for a broad spectrum of commercial applications, regulatory authorities are examining how to safely integrate them without compromising safety or disrupting traditional airspace operations. For small UAS, several operational rules have been established; e.g., do not operate beyond visual line-of-sight, do not fly within five miles of a commercial airport, do not fly above 400 feet above ground level. Enforcing these rules is challenging for UAS, as evidenced by the number of incident reports received by the Federal Aviation Administration (FAA). This paper reviews the development of an onboard system - Safeguard - designed to monitor and enforce conformance to a set of operational rules defined prior to flight (e.g., geospatial stay-out or stay-in regions, speed limits, and altitude constraints). Unlike typical geofencing or geo-limitation functions, Safeguard operates independently of the off-the-shelf UAS autopilot and is designed in a way that can be realized by a small set of verifiable functions to simplify compliance with existing standards for safety-critical systems (e.g. for spacecraft and manned commercial transportation aircraft systems). A framework is described that decouples the system from any other devices on the UAS as well as introduces complementary positioning source(s) for applications that require integrity and availability beyond what can be provided by the Global Positioning System (GPS). This paper summarizes the progress and test results for Safeguard research and development since presentation of the design concept at the 35th Digital Avionics Systems Conference (DASC '16). Significant accomplishments include completion of software verification and validation in accordance with NASA standards for spacecraft systems (to Class B), development of improved hardware prototypes, development of a simulation platform that allows for hardware-in-the-loop testing and fast-time Monte Carlo evaluations, and flight testing on multiple air vehicles. Integration testing with NASA's UAS Traffic Management (UTM) service-oriented architecture was also demonstrated.
Young, Steven D.↗
An Executable Choreography Framework for Dynamic Service-Oriented Architectures
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.
Akkawi, Faisal↗
Service-Oriented Architecture for NVO and TeraGrid Computing
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.
Jacob, Joseph↗
Machine Learning Airport Surface Model
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.
Jeremy Coupe↗