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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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7 records

All sources NASA NTRS DOE OSTI

DOE OSTI2019

Orchestrating intercontinental advance reservations with software-defined exchanges

To interconnect research facilities across wide geographic areas, network operators deploy science networks, also referred to as research and education networks. These networks allow experimenters to establish dedicated circuits between research facilities for transferring large amounts of data by using advanced reservation systems. Intercontinental dedicated circuits typically require coordination among multiple administrative domains, which need to reach an agreement on a suitable advance reservation. The success rate of finding an advance reservation decreases as the number of participant domains increases for traditional systems because the circuit is composed over a single path. To improve provisioning of multidomain advance reservations, we have designed and implemented an architecture for end-to-end service orchestration in multidomain science networks that leverages software-defined exchanges for providing multipath, multidomain advance reservations. In conclusion, our orchestration architecture improves the reservation success rate from 50% in single-path systems to 99% when four paths are available.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Software-defined network for end-to-end networked science at the exascale

Domain science applications and workflow processes are currently forced to view the network as an opaque infrastructure into which they inject data and hope that it emerges at the destination with an acceptable Quality of Experience. There is little ability for applications to interact with the network to exchange information, negotiate performance parameters, discover expected performance metrics, or receive status/troubleshooting information in real time. The work presented here is motivated by a vision for a new smart network and smart application ecosystem that will provide a more deterministic and interactive environment for domain science workflows. The Software-Defined Network for End-to-end Networked Science at Exascale (SENSE) system includes a model-based architecture, implementation, and deployment which enables automated end- to-end network service instantiation across administrative domains. An intent based interface allows applications to express their high-level service requirements, an intelligent orchestrator and resource control systems allow for custom tailoring of scalability and real-time responsiveness based on individual application and infrastructure operator requirements. This allows the science applications to manage the network as a first-class schedulable resource as is the current practice for instruments, compute, and storage systems. Deployment and experiments on production networks and testbeds have validated SENSE functions and performance. Emulation based testing verified the scalability needed to support research and education infrastructures. Key contributions of this work include an architecture definition, reference implementation, and deployment. This provides the basis for further innovation of smart network services to accelerate scientific discovery in the era of big data, cloud computing, machine learning and artificial intelligence.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Software-Defined Network for End-to-end Networked Science at the Exascale

Domain science applications and workflow processes are currently forced to view the network as an opaque infrastructure into which they inject data and hope that it emerges at the destination with an acceptable Quality of Experience. There is little ability for applications to interact with the network to exchange information, negotiate performance parameters, discover expected performance metrics, or receive status/troubleshooting information in real time. The work we presen here is motivated by a vision for a new smart network and smart application ecosystem that will provide a more deterministic and interactive environment for domain science workflows. The Software-Defined Network for End-to-end Networked Science at Exascale (SENSE) system includes a model-based architecture, implementation, and deployment which enables automated end-to-end network service instantiation across administrative domains. An intent based interface allows applications to express their high-level service requirements, an intelligent orchestrator and resource control systems allow for custom tailoring of scalability and real-time responsiveness based on individual application and infrastructure operator requirements. This allows the science applications to manage the network as a first-class schedulable resource as is the current practice for instruments, compute, and storage systems. Deployment and experiments on production networks and testbeds have validated SENSE functions and performance. Emulation based testing verified the scalability needed to support research and education infrastructures. Key contributions of this work include an architecture definition, reference implementation, and deployment. This provides the basis for further innovation of smart network services to accelerate scientific discovery in the era of big data, cloud computing, machine learning and artificial intelligence.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Enhancing Security and Resiliency in Operational Technology Environments Through Network Slicing and Federated Learning

The growing convergence of Information Technology (IT) and Operational Technology (OT) within Industry 4.0 environments has introduced new demands on industrial network infrastructure. As cyber-physical systems become increasingly interconnected, ensuring the secure, timely, and efficient exchange of critical data is essential. This thesis explores how network slicing, a method of creating isolated virtual network segments, can be applied within OT environments to address challenges such as latency, security, and resource allocation. The first research question addressed in this thesis is: How can OT networks take advantage of NFV and SDN technology to become cyber resilient? This study examines the operational, security, and architectural implications of introducing network slicing into traditionally static OT infrastructures such as Industrial Control Systems (ICS) and SCADA. Through simulated deployments and case studies, the research demonstrates how slicing enables better isolation between critical and non-critical services, thereby improving response time, throughput, and security in sensitive environments. The second question considers: How to dynamically implement network slicing and take advantage of network resources towards integrating decentralized machine learning? In response, this thesis proposes a framework that combines Software-Defined Networking (SDN), Network Function Virtualization (NFV), and Federated Learning (FL) to enable real-time analytics while maintaining data locality. The proposed approach reduces the burden on centralized infrastructure and minimizes privacy risks by supporting on-site training of models across distributed OT nodes, coordinated through dynamically allocated network slices. The third focus explores: How slicing helps to increase the resiliency of OT networks through the orchestration of a dynamic DMZ? To answer this, the thesis presents a method for creating and managing Dynamic Demilitarized Zones (DMZs) using network slicing. This enables flexible and automated isolation of sensitive subsystems during threat scenarios or high-risk operations. Coupled with intelligent orchestration and containerized security services, the dynamic DMZ significantly enhances the system's ability to respond to cyber incidents without halting production. Ultimately, this thesis contributes a comprehensive architecture that blends network slicing with machine learning, secure segmentation, and automation, paving the way for resilient, adaptive, and intelligent OT environments. Performance evaluations across multiple scenarios show improvements in system reliability, threat response time, model accuracy, and resource utilization, providing a strong foundation for future industrial automation systems.

Rodiles Delgado, Brian G↗

DOE OSTI2019

Future SDN-HPON Control Plane Architecture and Protocol for On-Demand Terabit End-to-End Extreme-Scale Science Applications

The UC Davis team conducted architecture, algorithm and experimental studies for next generation ultra-high-bandwidth optical networks in support of extreme-scale science applications. In particular, over the course of this 3-year project, the UC Davis team achieved the following main accomplishments: Designed a network architecture for automated multi-domain service provisioning: Designed information exchange schemes between autonomous systems (domains) Designed application programming interfaces to orchestrate resource reservation in data centers, high performance computation facilities, and communication networks belonging to different autonomous systems Experimentally assessed the multi-domain network architecture in a distributed field trial set-up connecting premises in three continents Designed a broker-based orchestrated multi-domain optical networking framework supporting observe-analyze-act cycle based cognitive inter-domain service provisioning: Designed an inter-domain operation mechanism, e.g., topology abstraction, for the broker plane and domain managers to collaboratively accomplish inter-domain service provisioning while respecting the autonomy of each administrative domain Designed an alien wavelength monitoring scheme and an artificial neural network based optical signal-to-noise ratio estimator for quality-of-transmission aware inter-domain service provisioning Developed a deep neural network based multi-domain traffic predictor and a cognitive routing and spectrum assignment algorithm to realize knowledge-based autonomous traffic engineering in multi-domain networks Implemented an optical signal-to-noise ratio estimator and traffic predictor with Google’s Tensor flow and assessed their performance using experimental and synthetic data Demonstrated the benefits of the proposed cognitive schemes with experiments ona two-domain elastic optical network testbed and evaluations on a six-domain simulation framework Built a two-domain software-defined networking control plane testbed using the ONOS platform and demonstrated the workflow of broker and domain manager cooperation, including hierarchical performance monitoring, topology abstraction and cognitive resource allocation. Designed self-learning cognitive service provisioning schemes using advanced machine learning technologies: Designed a self-taught anomaly detection framework for optical networks, including an unsupervised data clustering module for pattern recognition, a supervised data regression and classification module for online anomaly detection, and the system operation principle Experimentally validated the effectiveness of the self-taught anomaly detection framework with various failure/anomaly scenarios. Designed a self-learning autonomic routing, modulation and spectrum assignment (RMSA) provisioning framework for elastic optical networks with deep reinforcement learning. Designed effective modeling and training mechanisms for the self-learning RMSA framework Conducted extensive numerical simulations with various traffic patterns and topologies to verify the advantage of the self-learning RMSA framework.

42 ENGINEERING↗

NASA NTRS2016

Future Standardization of Space Telecommunications Radio System with Core Flight System

NASA Glenn Research Center (GRC) is integrating the NASA Space Telecommunications Radio System (STRS) Standard with the Core Flight System (cFS), an avionics software operating environment. The STRS standard provides a common, consistent framework to develop, qualify, operate and maintain complex, reconfigurable and reprogrammable radio systems. The cFS is a flexible, open architecture that features a plugand- play software executive called the Core Flight Executive (cFE), a reusable library of software components for flight and space missions and an integrated tool suite. Together, STRS and cFS create a development environment that allows for STRS compliant applications to reference the STRS application programmer interfaces (APIs) that use the cFS infrastructure. These APIs are used to standardize the communication protocols on NASAs space SDRs. The cFS-STRS Operating Environment (OE) is a portable cFS library, which adds the ability to run STRS applications on existing cFS platforms. The purpose of this paper is to discuss the cFS-STRS OE prototype, preliminary experimental results performed using the Advanced Space Radio Platform (ASRP), the GRC S‑ band Ground Station and the SCaN (Space Communication and Navigation) Testbed currently flying onboard the International Space Station (ISS). Additionally, this paper presents a demonstration of the Consultative Committee for Space Data Systems (CCSDS) Spacecraft Onboard Interface Services (SOIS) using electronic data sheets (EDS) inside cFE. This configuration allows for the data sheets to specify binary formats for data exchange between STRS applications. The integration of STRS with cFS leverages mission-proven platform functions and mitigates barriers to integration with future missions. This reduces flight software development time and the costs of software-defined radio (SDR) platforms. Furthermore, the combined benefits of STRS standardization with the flexibility of cFS provide an effective, reliable and modular framework to minimize software development efforts for spaceflight missions.

space communications↗

NASA NTRS2016

Future Standardization of Space Telecommunications Radio System with Core Flight System

NASA Glenn Research Center (GRC) is integrating the NASA Space Telecommunications Radio System (STRS) Standard with the Core Flight System (cFS). The STRS standard provides a common, consistent framework to develop, qualify, operate and maintain complex, reconfigurable and reprogrammable radio systems. The cFS is a flexible, open architecture that features a plug-and-play software executive called the Core Flight Executive (cFE), a reusable library of software components for flight and space missions and an integrated tool suite. Together, STRS and cFS create a development environment that allows for STRS compliant applications to reference the STRS APIs through the cFS infrastructure. These APis are used to standardize the communication protocols on NASAs space SDRs. The cFE-STRS Operating Environment (OE) is a portable cFS library, which adds the ability to run STRS applications on existing cFS platforms. The purpose of this paper is to discuss the cFE-STRS OE prototype, preliminary experimental results performed using the Advanced Space Radio Platform (ASRP), the GRC Sband Ground Station and the SCaN (Space Communication and Navigation) Testbed currently flying onboard the International Space Station. Additionally, this paper presents a demonstration of the Consultative Committee for Space Data Systems (CCSDS) Spacecraft Onboard Interface Services (SOIS) using electronic data sheets inside cFE. This configuration allows for the data sheets to specify binary formats for data exchange between STRS applications. The integration of STRS with cFS leverages mission-proven platform functions and mitigates barriers to integration with future missions. This reduces flight software development time and the costs of software-defined radio (SDR) platforms. Furthermore, the combined benefits of STRS standardization with the flexibility of cFS provide an effective, reliable and modular framework to minimize software development efforts for spaceflight missions.

space communications↗